an aging world...cent of all people aged 65 or tor u.s. labor force covered by older. corresponding...

U.S. Department of CommerceEconomics and Statistics Administration

U.S. CENSUS BUREAU

An Aging World: 2001P95/01-1

International Population Reports

Demographic Programs

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Issued November 2001

By Kevin Kinsellaand Victoria A. Velkoff

U.S. Department of Health and Human ServicesNational Institutes of Health

NATIONAL INSTITUTE ON AGING

ACKNOWLEDGMENTS This report was prepared by and activities of the Census Bureau (asKevin Kinsella and Victoria A. well as to many other agencies in theVelkoff under the general direction of United States and worldwide) for the bet-Peter O. Way, Chief, International ter part of two decades.Programs Center (IPC), Population

Within the IPC Aging Studies Branch,Division, Census Bureau. Research for

Valerie Lawson was instrumental toand production of this report were sup-

the completion of myriad tasks involvingported under an interagency agreement

data compilation, verification, table andwith the Behavioral and Social Research

graph production, and general reportProgram, National Institute on Aging,

preparation. Branch members Wan HeAgreement No. Y1-AG-9414-01.

and Jennifer Zanini also contributed toFor their review of and/or suggestions this report. regarding this report, the authors are

Frances Scott, Janet Sweeney,grateful to Emily M. Agree, Department

Barbara Adams, and Arlene C. Butlerof Population Dynamics, Johns Hopkins

of the Administrative and CustomerUniversity; Nikolai Botev, Population

Services Division, Walter C. Odom,Activities Unit, Economic Commission for

Chief, provided publication and printingEurope; Richard V. Burkhauser,

management, graphics design, and com-Department of Policy Analysis and

position and editorial review for printManagement, Cornell University;

and electronic media. General directionJames C. Gibbs, Assistant Center Chief,

and production management were pro-IPC; Albert I. Hermalin, Institute for

vided by Michael G. Garland, AssistantSocial Research, University of Michigan;

Chief, and Gary J. Lauffer, Chief,Linda Hooper, Aging Studies Branch,

Publications Services Branch.IPC; Rose Maria Li, Behavioral andSocial Research Program, National Thanks also are due to Lorraine WrightInstitute on Aging; Jean-Marie Robine, of the Bureau’s Information andEquipe INSERM Demographie et Sante, Resources Services Branch, who cheer-Montpellier; Beth J. Soldo, Population fully and efficiently handled the acquisi-Studies Center, University of tion of a multitude of necessary sourcesPennsylvania; Richard M. Suzman, and references.Behavioral and Social Research Program,

Finally, we would like to thank thoseNational Institute on Aging; Peter O.international organizations and associa-Way, Chief, IPC, Loraine A. West,tions engaged in the collection, tabula-Eurasia Branch, IPC; and tion, analysis and dissemination of dataRichard Woodbury, National Bureau relevant to the aging of the world’s pop-of Economic Research. We also thankulation. In particular, we would like toDavid Rajnes, Housing and Householdacknowledge the efforts of the EconomicEconomic Statistics Division, U.S. CensusCommission for Europe, the InternationalBureau, who provided useful data andLabour Office, the International Networkother information regarding retirementon Healthy Life Expectancy, theand pensions. International Social Security

A very special debt of gratitude is owed Administration, the Organization forto George C. Myers, former director of Economic Co-Operation andthe Center for Demographic Studies at Development, the Statistical Office of theDuke University, who passed away in European Union, the United Nations2000. Not only did Dr. Myers offer Population Division, the United Nationsinstructive comments on this report, but Statistical Office, and the World Healthhe also provided invaluable advice and Organization.guidance to the aging-related products

An Aging World: 2001P95/01-1

Issued November 2001

U.S. Department of CommerceDonald L. Evans,

Secretary

Economics and Statistics AdministrationKathleen B. Cooper,

Under Secretary for Economic Affairs

U.S. CENSUS BUREAUWilliam G. Barron, Jr.,

Acting Director

Suggested Citation

Kinsella, Kevin and Victoria A. Velkoff, U.S. Census Bureau, Series P95/01-1,

An Aging World: 2001, U.S. Government Printing Office,

Washington, DC, 2001.

ECONOMICS

AND STATISTICS

ADMINISTRATION

Economics and StatisticsAdministration

Kathleen B. Cooper,Under Secretary for Economic Affairs

U.S. CENSUS BUREAU

William G. Barron, Jr.,Acting Director

William G. Barron, Jr.,Deputy Director

John H. Thompson,Principal Associate Director for Programs

Nancy M. Gordon,Associate Director for Demographic Programs

John F. Long,Chief, Population Division

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Internet: bookstore.gpo.gov Phone: toll free 866-512-1800; DC area 202-512-1800

Fax: 202-512-2250 Mail: Stop SSOP, Washington, DC 20402-0001

U.S. Census Bureau An Aging World: 2001 iii

20 Questions About Global Aging (to test your knowledge of global population aging at the turn of the century)

Answers appear on next page.

1. True or false? In the year 2000, children under the 11. True or false? Today in some countries life expectancyage of 15 still outnumbered elderly people (aged 65 at birth is less than 40 years.and over) in almost all nations of the world.

12. What are the leading killers of elderly women inEurope and North America?2. The world’s elderly population is increasing by approx-

imately how many people each month? a. Cancers b. Circulatory diseasesc. Respiratory diseases d. Accidentsa. 50,000 b. 300,000 c. 500,000 d. 800,000

13. True or false? Elderly women outnumber elderly men3. Which of the world’s developing regions has thein all developing countries.highest aggregate percent elderly?

a. Africa b. Latin America 14. There are more older widows than widowers in virtu-c. The Caribbean d. Asia (excluding Japan) ally all countries because:

a. Women live longer than men4. China has the world’s largest total population (moreb. Women typically marry men older than themselvesthan 1.2 billion people). Which country has thec. Men are more likely than women to remarry afterworld’s largest elderly (65+) population?

divorce or the death of a spousea. Japan b. Germany c. China d. Nigeria d. All of the above

5. True or false? More than half of the world’s elderly 15. In developed countries, recent declines in labor forcetoday live in the industrialized nations of participation rates of older (55 and over) workers areEurope, North America, and Japan. due almost entirely to changing work patterns of

a. Men b. Women c. Men and women6. Of the world’s major countries, which had the highest

percentage of elderly people in the year 2000? 16. What proportion of the world’s countries have a publica. Sweden b. Turkey c. Italy d. France old-age security program?

a. All b. Three-fourths c. One-half d. One-fourth7. True or false? Current demographic projections sug-

gest that 35 percent of all people in the United States 17. Approximately what percent of the private sectorwill be at least 65 years of age by the year 2050. labor force in the United States is covered by a private

pension plan (as opposed to, or in addition to, public8. True or false? The number of the world’s “oldest old” Social Security)?

(people aged 80 and over) is growing more rapidlya. 10 percent b. 25 percent than that of the elderly as a whole.c. 33 percent d. 60 percent

9. More than one-third of the world’s oldest old live in 18. In which country are elderly people least likely to livewhich three countries? alone?a. Germany, the United States, and the a. The Philippines b. Hungary c. Canada d. Denmark

United Kingdomb. India, China, and the United States 19. True or false? In developing countries, older men arec. Japan, China, and Brazil more likely than older women to be illiterate.d. Russia, India, and Indonesia

20. True or false? In most nations, large cities have10. Japan has the highest life expectancy at birth among younger populations (i.e., a lower percent elderly) than

the major countries of the world. How many years the country as a whole.can the average Japanese baby born in 2000 expectto live?

a. 70 years b. 75 years c. 81 years d. 85 years

iv An Aging World: 2001 U.S. Census Bureau

Answers1. True. Although the world’s world’s growth rate for the 80+ But because older men work in

population is aging, children still population from 1999 to 2000 much greater numbers than dooutnumber the elderly in all was 3.5 percent, while that of older women, increases inmajor nations except six: the world’s elderly (65+) popula- female participation were moreBulgaria, Germany, Greece, Italy, tion as a whole was 2.3 percent than offset by falling male partic-Japan, and Spain. (compared with 1.3 percent for ipation.

the total (all ages) population).2. d. The estimated change in the 16. b. Of the 227 countries/areas

total size of the world’s elderly 9. b. India has roughly 6.2 million of the world with populations ofpopulation between July 1999 people aged 80 and over, China at least 5,000, 167 (74 percent)and July 2000 was more than has 11.5 million, and the United reported having some form of 9.5 million people, an average of States 9.2 million. Taken togeth- an old age/disability/survivors795,000 each month. er, these people constitute nearly program circa 1999.

38 percent of the world’s oldest3. c. The Caribbean, with 7.2 per- 17. d. The share of the private sec-old.

cent of all people aged 65 or tor U.S. labor force covered byolder. Corresponding figures for 10. c. 81 years, up from about 52 private pension plans was aboutother regions are: Asia (exclud- in 1947. 60 percent in the mid-1990s.ing Japan), 5.5 percent; Latin However, not all employees who

11. True. In some African countriesAmerica, 5.3 percent; and Africa, are covered by such plans actu-(e.g., Malawi, Swaziland, Zambia,3.1 percent. ally participate in them.and Zimbabwe) where the

4. c. China also has the largest HIV/AIDS epidemic is particularly 18. a. The Philippines. The percentelderly population, numbering devastating, average life of elderly people living alone innearly 88 million in 2000. expectancy at birth may be as developing countries is usually

much as 25 years lower than it much lower than that in devel-5. False. Although industrialized otherwise would be in the oped countries; levels in the lat-

nations have higher percentages absence of HIV/AIDS. ter may exceed 40 percent.of elderly people than do mostdeveloping countries, 59 percent 12. b. Circulatory diseases (especial- 19. False. Older women are lessof the world’s elderly now live in ly heart disease and stroke) typi- likely to be literate. In China inthe developing countries of cally are the leading cause of 1990, for example, only 11 per-Africa, Asia, Latin America, the death as reported by the World cent of women aged 60 andCaribbean, and Oceania. Health Organization. In Canada over could read and write, com-

in 1995, for example, 44 percent pared with half of men aged 606. c. Italy, with 18.1 percent of all of all deaths occurring to women and over.

people aged 65 or over. Monaco, at age 65 or above were attrib-a small principality of about 20. We do not know. Data foruted to circulatory disease. The32,000 people located on the selected cities/countries are pre-percentage was virtually theMediterranean, has more than sented in Chapter 5. Some liter-same for elderly men.22 percent of its residents aged ature from developed countries65 and over. 13. False. Although there are more suggests that the statement is

elderly women than elderly men false; evidence from certain7. False. Although the United in the vast majority of the developing countries suggests

States will age rapidly when the world’s countries, there are that it is true. Both the CensusBaby Boomers (people born exceptions such as India, Iran, Bureau’s International Programsbetween 1946 and 1964) begin and Bangladesh. Center and the National Instituteto reach age 65 after the year on Aging’s Behavioral and Social2010, the percent of population 14. d. All of the above. Research Program would beaged 65 and over in the year

15. a. From the late 1960s until most interested in empirical2050 is projected to be slightly

very recently, labor force partici- input from interested parties.above 20 percent (compared

pation rates of older men in Understanding global aging is awith about 13 percent today).

developed countries were declin- dialectical process.8. True. The oldest old are the ing virtually everywhere, where-

fastest-growing component of as those for women were oftenmany national populations. The holding steady or increasing.

U.S. Census Bureau An Aging World: 2001 v

Contents

20 Questions About Global Aging . . . . . . . . . . . . . .iii 3. Average Annual Growth Rate and Percent Change Over Time for Older Age Groups:

Chapter 2000 to 2015 and 2015 to 2030 . . . . . . . . . .130

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . .1 4. Median Population Age:

2. The Demographics of Aging . . . . . . . . . . . . . . . .7 2000, 2015, and 2030 . . . . . . . . . . . . . . . . . .132

3. Life Expectancy and Changing Mortality . . . . . .23 5. Total and Elderly Urban Population by Sex: Available Data From 1970 to the Present . . . .133

4. Health and Disability . . . . . . . . . . . . . . . . . . . .376. Sex Ratio for Population 25 Years and

5. Urban and Rural Dimensions . . . . . . . . . . . . . .49 Over by Age: 2000 and 2030 . . . . . . . . . . . . .136

6. Sex Ratios and Marital Status . . . . . . . . . . . . . .57 7. Marital Status of Older Persons by Sex: Selected Years 1970 to 1995 . . . . . . . . . . . . .1377. Living Arrangements . . . . . . . . . . . . . . . . . . . .65

8. Support Ratios: 2000, 2015, and 2030 . . . . . .1548. Family and Social Support of Older People . . . .73

9. Parent Support Ratios: 1950, 9. Educational Attainment and Literacy . . . . . . . . .852000, and 2030 . . . . . . . . . . . . . . . . . . . . . .155

10. Labor Force Participation and Retirement . . . . .9310. Labor Force Participation Rates by Age and

11. Pensions and Income Security . . . . . . . . . . . .115 Sex: Selected Years, 1970 to 1999 . . . . . . . . .156

Appendix A. Appendix B.Detailed Tables . . . . . . . . . . . . . . . . . . . . . . .125 Sources and Limitations of the Data . . . . . .163

Table Appendix C.International Comparison of

1. Total Population, Percent Elderly, and Percent Urban and Rural Definitions . . . . . . . . . . . . .167Oldest Old: 1975, 2000, 2015, and 2030 . . . .126

Appendix D.2. Population by Age: 2000 and 2030 . . . . . . . . .128 References . . . . . . . . . . . . . . . . . . . . . . . . . . .169

U.S. Census Bureau An Aging World: 2001 1

CHAPTER 1.

Introduction

The United Nations designated 1999as "The Year of the Older Person,”thereby recognizing and reaffirmingwhat demographers and many othershave known for decades: our globalpopulation is aging, and aging at anunprecedented rate. Fertility declineand urbanization arguably have beenthe dominant global demographictrends during the second half of thetwentieth century, much as rapidimprovements in life expectancycharacterized the early 1900s. As webegin the twenty-first century, popu-lation aging is poised to emerge as apreeminent worldwide phenomenon.The confluence of lowered fertilityand improved health and longevityhas generated growing numbers andproportions of older populationthroughout most of the world. Aseducation and income levels rise,increasing numbers of individualsreach "old age” with markedly differ-ent life expectancies and personalexpectations than their forebears.

Population aging represents, in onesense, a human success story; soci-eties now have the luxury of aging.However, the steady, sustainedgrowth of elderly1 populations also

1 There is a growing awareness that theterm “elderly” is an inadequate generalizationthat conceals the diversity of a broad agegroup, spanning more than 40 years of life. Forcross-national comparative purposes, however,some chronological demarcation of age cate-gories is required. This report uses the follow-ing terms for component age groups: the elder-ly (65 and over); the young old (65 to 74years); and the oldest old (80 years and over).In some contexts (e.g., older people in the laborforce), it may be most useful or necessary (dueto data restrictions) to refer to the “older popu-lation,” those 55 years and older. The term“frail elderly” refers to people 65 years or olderwith significant physical and cognitive healthproblems. This term is used to emphasize thefact that a majority of the elderly, especially theyoung old, do not have serious health prob-lems.

poses myriad challenges to policy-makers in many societies. After theyear 2010, the numbers and propor-tions of elderly, especially the oldestold, will rise rapidly in most devel-oped and many developing coun-tries.2 The projected increase is pri-marily the result of high fertility afterWorld War II. It is secondarily, butincreasingly, the result of reduceddeath rates at all ages; in mostnations of the world, there have beenmajor reductions in the prevalence ofinfectious and parasitic diseases,declines in infant and maternal mor-tality, and improved nutrition duringthe 1900s. One focus of this reportis a look at the numbers, propor-tions, and growth rates (past, cur-rent, and projected) of the elderlypopulation.

Most people, for good reason, asso-ciate the growth of elderly popula-tions with the developed, industrial-ized countries of Europe and NorthAmerica. Most developed nationsare in fact the demographically old-est in the world today, and somemay have more grandparents thanchildren before the middle of thetwenty-first century. In the early1990s, developed nations as a wholehad about as many children under15 years of age as people aged 55and over (approximately 22 percent

2 The “developed” and “developing” countrycategories used in this report correspond direct-ly to the “more developed” and “less developed”classification employed by the United Nations.Developed countries comprise all nations inEurope (including some nations that formerlywere part of the Soviet Union) and NorthAmerica, plus Japan, Australia, and NewZealand. The remaining nations of the worldare classified as developing countries. Whilethese categories commonly are used for com-parative purposes, it is increasingly evident thatthey no longer accurately reflect developmentaldifferences between nations.

of the total population in each cate-gory). The developing world, bycontrast, still had a high proportionof children (35 percent of all peopleunder age 15) and a relatively lowproportion of older people (10 per-cent aged 55 and over).

What is less widely appreciated isthat absolute numbers of elderly indeveloping nations often are largeand everywhere are increasing.Well over half of the world’s elderly(people aged 65 and over) now livein developing nations (59 percent,or 249 million people, in 2000). By2030, this proportion is projectedto increase to 71 percent (686 mil-lion).3 Many developing countrieshave had or are now experiencing asignificant downturn in their rate ofnatural population increase (birthsminus deaths) similar to what previ-ously occurred in most industrial-ized nations. As this process accel-erates, age structures will change.The elderly will be an ever-largerproportion of each nation’s total

3 Throughout this report, projections of pop-ulation size and composition come from theInternational Programs Center, PopulationDivision, U.S. Census Bureau, unless otherwiseindicated. As discussed further in Appendix B,these projections are based on empirical analy-ses of individual national population age andsex structures, components of populationchange (rates of fertility, mortality, and netmigration), and assumptions about the futuretrajectories of fertility, mortality, and migrationfor each country.

Projections, strictly speaking, are neitherforecasts nor predictions. Projections are “cor-rect” in the sense that they are actual results ofmathematical calculations based on specifiedassumptions. Forecasts are projections thatanalysts judge to be the most probable endresults. There can be alternative projections,but it would be contradictory to make alterna-tive forecasts. It may, however, be appropriateto develop numerical ranges for forecast values.Predictions have no formal statistical meaning;they are related more to forecasts than to pro-jections.

population. Elderly populationsalso have grown because of world-wide improvements in health servic-es, educational status, and econom-ic development. The characteristicsof the elderly are likely to beincreasingly heterogeneous withinnations. Thus, a second focus ofAn Aging World: 2001 is to summa-rize socioeconomic statistics forboth developed and developingnations. This report shows suchdata for 52 nations when availableand reasonably comparable. In2000, these 52 nations (listed inAppendix A, Table 1) contained 77 percent of the world’s total pop-ulation, and are referred to as“study countries” at various pointsin the text.4

This report focuses primarily onpeople aged 65 years old and over.As is true of younger age groups,people aged 65 and over have verydifferent economic resources, healthstatuses, living arrangements, andlevels of integration into social life.An Aging World: 2001 acknowl-edges this diversity by disaggregat-ing statistics into narrower agegroups where possible. Such exam-ination may reveal important demo-graphic, social, and economic differ-ences that have direct bearing onsocial policy now and in the future.For example, the fastest growingportion of the elderly population inmany nations are those aged 80and over, referred to as the oldestold. Rapidly expanding numbers ofvery old people represent a socialphenomenon without historicalprecedent, and one that is bound toalter previously held stereotypes ofolder people. The growth of theoldest old is salient to public policybecause individual needs and social

2 An Aging World: 2001 U.S. Census Bureau

4 In some parts of the text, data from addi-tional countries have been included.

responsibilities change considerably the IPC and is funded in part by thewith increased age. Behavioral and Social Research

Program of the U.S. NationalAn Aging World: 2001 is the sev-

Institute on Aging. IDB contents areenth major cross-national report in

readily available from the Censusa Census Bureau series on the

Bureau’s Web site; the direct accessworld’s elderly/older populations.

address is www.census.gov/ipc/The first two reports, An Aging

www/idbnew.htmlWorld (1987) and Aging in theThird World (1988), used data pri- Appendix B provides more informa-marily from the 1970 and 1980 tion about the sources, limitations,rounds of worldwide censuses and availability of IDB files and(those taken from 1965 to 1974 report data in general. There areand 1975 to 1984, respectively), vast differences in both the quantityas well as demographic projections and quality of statistics reported byproduced by the United Nations various countries. The UnitedPopulation Division from its 1984 Nations has provided internationalassessment of global population. recommendations for the standardi-Subsequent reports — Population zation of concepts and definitionsand Health Transitions (1992); of data collected in censuses andAging in Eastern Europe and the surveys. Nevertheless, there areFormer Soviet Union (1993); An still wide discrepancies in data col-Aging World II (1993); Older lection and tabulation practicesWorkers, Retirement and Pensions because of legitimate differences in(1995); and the current report — the resources and informationinclude historical data from the needs among countries. As aearlier reports, available data from result, any attempt to compile stan-the 1990 and 2000 rounds of cen- dard data across countries requiressuses, information from national consideration of whether and howsample surveys and administrative the reported data should be ana-records, historical and projected lyzed to achieve comparability.data from the United Nations, and

The demographic data in this reportdata from component population

have been judged by Census Bureauprojections prepared by the

analysts to be as representative asInternational Programs Center

possible of the situation in a given(IPC), Population Division, U.S.

country. The data are internally con-Census Bureau. Differences among

sistent and congruent with otherreports in projected data may

facts known about the nations.reflect either a change in the

These demographic data also havesource of the projections or, more

been checked for external consisten-importantly, revised demographic

cy, that is, compared with informa-insights based on the most recent

tion on other countries in the sameinformation.

region or subregion and with thoseMany of the data included in this elsewhere at approximately thereport are from the Census Bureau’s same level of socioeconomic devel-International Data Base (IDB). The opment. The socioeconomic data,tabular statistics provided in by contrast, typically are as reportedAppendix A represent only a small by the countries themselves.portion of the total IDB files. The Although Census Bureau analystsIDB is maintained and updated by have not directly evaluated these

data, analysts have attempted to proportion of the world’s population increasingly, biologic and genetic.resolve discrepancies in reported fig- that is elderly (Figure 1-2). The The IDB and this report are an effortures and to eliminate international coming growth, especially of the to contribute to a consistent, sys-inconsistencies; data with obvious oldest old, will be stunning. As tematic, quantitative comparison ofincongruities are not included. their numbers grow, there is a older populations in various coun-

heightened need to understand the tries. Information is the first stepWe are all part of an increasingly

characteristics of older populations, toward a better understanding ofinterdependent and aging world

their strengths, and their require- the effects of population aging with-(Figure 1-1). Current growth of eld-

ments. The effects will be felt not in and across national boundaries.erly populations is steady in some

just within individual nations but As individuals, as nations, and as ancountries and explosive in others.

throughout the global economy. international community, we faceAs the World War II baby-boom

Understanding the dynamics of the challenge of anticipating thecohorts, common to many coun-

aging requires accurate descriptions changing needs and desires of antries, begin to reach their elder

of the elderly from interrelated per- aging world in a new millennium.years after 2010, there will be a

spectives including demographic,significant jump by 2030 in the

social, economic, medical, and


Source: U.S. Census Bureau, 2000a.

Figure 1-1.

Percent Aged 65 and Over: 2000

Less than 3.03.0 to 7.98.0 to 12.913.0 or more

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Figure 1-2.

Percent Aged 65 and Over: 2030

Less than 3.03.0 to 7.98.0 to 12.913.0 or more

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CHAPTER 2.

The Demographics of Aging

The current level and pace of popula- Projections of older populations developed countries during andtion aging vary widely by geographic may be more accurate than projec- after World War I. A second, lessregion, and usually within regions as tions of total population, which severe, decline in the rate ofwell. But virtually all nations are now must incorporate assumptions growth began in the mid-1990sexperiencing growth in their num- about the future course of human and will be most noticeable in thebers of elderly residents. Developed fertility. Short-term and early 2000s. This decline corre-nations have relatively high propor- medium-term projections of tomor- sponds to lowered fertility duringtions of people aged 65 and over, but row’s elderly are not contingent the Great Depression and Worldthe most rapid increases in elderly upon fertility, because anyone who War II. These drops in growth ratepopulation are in the developing will be aged 65 or over in 2030 has highlight the important influenceworld. Even in nations where the already been born. When projecting that past fertility trends have onelderly percentage of total population the size and composition of the current and projected changes inremains small, absolute numbers world’s future elderly population, the size of elderly populations.may be rising steeply. Everywhere, human mortality is the key demo-

The current aggregate growth ratethe growth of elderly populations graphic component. As discussed

of the elderly population in devel-poses challenges to social institutions in the next chapter, current and

oping countries is more than doublethat must adapt to changing age future uncertainties about changing

that in developed countries, andstructures. mortality may produce widely diver-

also double that of the total worldgent projections of the size of

WORLD’S ELDERLY population. The rate in developingtomorrow’s elderly population.

POPULATION INCREASING countries began to rise in the early795,000 EACH MONTH ELDERLY POPULATION 1960s, and has generally continued

GROWING FASTEST IN to increase until recent years. AfterThe world’s elderly population hasDEVELOPING COUNTRIES a brief downturn — again related tobeen growing for centuries. What is

lower wartime fertility — the elderlynew is the rapid pace of aging. The Population aging has become agrowth rate in developing countriesglobal population aged 65 and over well-publicized phenomenon in theis expected to rise beyond andwas estimated to be 420 million industrialized nations of Europeremain above 3.5 percent annuallypeople as of midyear 2000, an and North America. What is notfrom 2015 through 2030 beforeincrease of 9.5 million since widely appreciated is the fact thatdeclining in subsequent decades.midyear 1999. The net balance of developing countries are aging as

the world’s elderly population grew well, often at a much faster rateEUROPE STILL THE “OLDEST”

by more than 795,000 people each than in the developed world. WORLD REGION, AFRICA THEmonth during the year. Projections Seventy-seven percent of the “YOUNGEST”to the year 2010 suggest that the world’s net gain of elderly individu-

Europe has had the highest propor-net monthly gain will then be on als from July 1999 to July 2000 —

tion of population aged 65 and overthe order of 847,000 people. In 615,000 people monthly —

among major world regions for1990, 26 nations had elderly popu- occurred in developing countries.

many decades and should remainlations of at least 2 million, and by Figure 2-2 shows the different pat-

the global leader well into the2000, 31 countries had reached the terns of growth in developed ver-

twenty-first century (Table 2-1).2-million mark. Projections to the sus developing countries. Most

Until recently, this region also hadyear 2030 indicate that more than notable in developed countries is

the highest proportions of popula-60 countries will have 2 million or the steep plunge in growth in the

tion in the most advanced age cate-more people aged 65 and over early 1980s. The slowing of the

gories. But in 2000, the percentage(Figure 2-1). growth rate was the result of low

of population aged 80 and over inbirth rates that prevailed in many


Figure 2-1.

Countries With 2 Million or More Elderly People: 2000 and 2030

20002030

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North America was equal to that ofEurope as a whole, probably as aresult of small European birthcohorts around the time of WorldWar I. By 2015, however, these per-centages are again expected to behighest in Europe; in 2030, nearly12 percent of all Europeans are pro-jected to be over the age of 74 and7 percent are projected to be overthe age of 79.

North America and Oceania alsohave relatively high aggregate per-centages of elderly, and these areprojected to increase substantiallybetween 2000 and 2030. Levels for2000 in Asia and LatinAmerica/Caribbean are expected tomore than double by 2030, whileaggregate proportions of elderlypopulation in Sub-Saharan Africawill grow rather modestly as aresult of continued high fertility inmany nations.

Two important factors bear mentionwhen considering aggregate elderlyproportions of regional populations.The first is that regional averagesoften hide great diversity.Bangladesh and Thailand may beclose geographically, but thesecountries have divergent paths ofexpected population aging.Likewise, many Caribbean nationshave high proportions of elderlypopulation (the Caribbean is the“oldest” of all developing worldregions) in relation to their CentralAmerican neighbors. Secondly andmore importantly, percentages bythemselves may not give a sense ofpopulation momentum. Althoughthe change in percent elderly inSub-Saharan Africa from 2000 to2015 is barely perceptible, the sizeof the elderly population is expect-ed to jump by 50 percent, from19.3 million to 28.9 million people.

Figure 2-2.

Average Annual Percent Growth of Elderly Population in Developed and Developing Countries

Source: United Nations, 1999.

0

1

2

3

4

5

20502040203020202010200019901980197019601950

Total world, all ages

Percent growth

Developed countries, 65 years and over

Developing countries, 65 years and over

Table 2-1.Percent Elderly by Age: 2000 to 2030

Region Year65 yearsand over

75 yearsand over

80 yearsand over

Europe . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

North America . . . . . . . . . . . . . . . . . . . . . .

Oceania . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Asia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Latin America/Caribbean . . . . . . . . . . . . .

Near East/North Africa . . . . . . . . . . . . . . .

Sub-Saharan Africa. . . . . . . . . . . . . . . . . .

200020152030

200020152030

200020152030

200020152030

200020152030

200020152030

200020152030

15.518.724.3

12.614.920.3

10.212.416.3

6.07.8

12.0

5.57.5

11.6

4.35.38.1

2.93.23.7

6.68.8

11.8

6.06.49.4

4.45.27.5

1.92.84.6

1.92.84.6

1.41.92.8

0.81.01.3

3.35.27.1

3.33.95.4

2.33.14.4

0.81.42.2

0.91.52.4

0.60.91.3

0.30.40.6



ITALY NOW THE WORLD’S“OLDEST” MAJOR COUNTRY

The percent of population aged 65and over ranged from 12 to 16 per-cent in 2000 in most developedcountries. For many years Swedenhad the highest such proportion,but recently Italy became the demo-graphically oldest of the world’smajor1 nations. Over 18 percent ofall Italians are aged 65 or over, withlevels approaching or exceeding 17 percent in Greece, Sweden,Japan, Spain, and Belgium. Withthe exception of Japan, the world’s25 oldest countries are all in Europe(Figure 2-3). The United States,with an elderly proportion of lessthan 13 percent in 2000, is ratheryoung by developed-country stan-dards, and its proportion elderlywill increase only slightly during thenext decade. However, as the largebirth cohorts of the baby boom(people born from 1946 through1964) begin to reach age 65 after2010, the percent elderly in theUnited States will rise markedly,likely reaching 20 percent by theyear 2030. Still, this figure will belower than in most countries ofWestern Europe.

1 Some small areas/jurisdictions have veryhigh proportions of elderly population. In2000, three of the world’s seven highest esti-mated percentages of elders were in theEuropean principality of Monaco (more than 22percent), Guernsey (17 percent) and the Isle ofMan (more than 17 percent).

Figure 2-3.

The World's 25 Oldest Countries: 2000


(Percent of population 65 years and over)

Czech Republic

Ukraine

Luxembourg

Slovenia

Estonia

Hungary

Serbia

Denmark

Finland

Latvia

Croatia

Switzerland

Norway

Austria

Portugal

United Kingdom

France

Germany

Bulgaria

Belgium

Spain

Japan

Sweden

Greece

Italy

13.9

18.1

17.3

17.3

17.0

16.9

16.8

16.5

16.2

16.0

15.7

15.4

15.4

15.2

15.1

15.0

15.0

14.9

14.9

14.8

14.6

14.1

14.0

13.9

14.5


SOME ELDERLY POPULATIONSTO MORE THAN TRIPLE BY 2030

During the period 2000-2030, theprojected increase in elderly popu-lation in the 52 study countriesranges from 14 percent in Bulgariato 372 percent in Singapore (Figure2-4). Today’s “older” nations willexperience relatively little changecompared with many developingnations; in countries as diverse asMalaysia and Colombia, elderlypopulations are expected toexpand to more than three timestheir size in 2000.

Figure 2-4.

Percent Increase in Elderly Population: 2000 to 2030


BulgariaUkraine

HungaryMalawiGreece

ItalyZimbabwe

SwedenUruguay

RussiaBelgium

JapanUnited Kingdom

FranceNorway

GermanyCzech Republic

DenmarkAustriaPoland

ArgentinaLuxembourgNew ZealandUnited States

IsraelAustralia

KenyaCanadaJamaicaPakistan

LiberiaChina

TunisiaIndia

TurkeySri Lanka

ChileBrazil

MoroccoGuatemala

ThailandPeru

BangladeshEgypt

South KoreaMexico

IndonesiaPhilippinesCosta RicaColombiaMalaysia

Singapore

Developed countriesDeveloping countries

372277

258250

240240

227216

210207206

197196193192

183

178177174171170

160153

134126

117108102102

9287

8175

67646363

62565554

5048484545

43434137

2114


THE LEGACY OF FERTILITY DECLINE

The most prominent historical fac-tor in population aging has beenfertility decline. The generally sus-tained decrease in total fertilityrates (TFRs) in industrialized nationssince at least 1900 has resulted incurrent levels below the populationreplacement rate of 2.1 live birthsper woman in most such nations(Figure 2-5). Persistent low fertilitysince the late 1970s has led to adecline in the size of successivebirth cohorts and a correspondingincrease in the proportion of olderrelative to younger population.

Fertility change in the developingworld has been more recent andmore rapid, with most regions hav-ing achieved major reductions infertility rates over the last 30 years.Although the aggregate TFRremains in excess of 4.5 childrenper woman in Africa and manycountries of the Near East, overalllevels in Asia and Latin Americadecreased by about 50 percent(from 6 to 3 children per woman)during the period 1965 to 1995.Total fertility in many developingcountries — notably China, SouthKorea, Thailand, and at least adozen Caribbean nations — is nowat or below replacement level.

Figure 2-5.

Total Fertility Rate: 2000


ZimbabweTunisia

MoroccoMalawiLiberiaKenyaEgypt

UruguayPeru

MexicoJamaica

GuatemalaCosta RicaColombia

ChileBrazil

Argentina

TurkeyThailandSri Lanka

South KoreaSingapore

PhilippinesPakistanMalaysia

IsraelIndonesia

IndiaChina

Bangladesh

United StatesNew Zealand

JapanCanada

Australia

UkraineRussiaPoland

HungaryCzech Republic

Bulgaria

United KingdomSwedenNorway

LuxembourgItaly

GreeceGermany

FranceDenmarkBelgiumAustria

(Births per woman)

Western Europe

3.3

1.41.61.71.8

1.41.3

1.21.71.8

1.51.7

1.11.21.31.4

1.31.3

1.81.6

1.41.8

2.1

2.91.8

3.12.62.6

3.34.6

3.51.2

1.72.0

1.92.2

2.52.12.2

2.72.5

4.72.1

2.73.0

2.4

3.23.7

6.45.3

3.12.0

Eastern Europe

Other Developed

Asia

Latin America/Caribbean

Africa


EAST AND SOUTHEAST ASIA Southeast Asia (South Korea,AGING THE FASTEST Taiwan, and Thailand), fueled by

dramatic drops in fertility levels.In only one-quarter of a century —The rapidity of change in thisfrom 1970 to 1996 — the percentregion stands in stark contrast toof population aged 65 and over insome European countries, whereJapan increased from 7 to 14 per-the comparable change occurredcent (Figure 2-6). Similarly swiftover a period of up to 115 years.increases are expected in China,Such rapidly aging societies arebeginning around the turn of thesoon likely to face the often-century, and elsewhere in East and

fractious debates over health carecosts, social security, and intergen-erational equity that have emergedin Europe and North America.

AN AGING INDEX

An easily understood indicator ofage structure is the aging index,defined here as the number of peo-ple aged 65 and over per 100youths under age 15. Among the52 study countries in 2000, 5 coun-tries (Germany, Greece, Italy,Bulgaria, and Japan) had more elder-ly than youth aged 0 to 14. By2030, however, all developed coun-tries in Figure 2-7 have a projectedaging index of at least 100, andseveral European countries andJapan are in excess of 200. Today’saging index typically is much lowerin developing countries than in thedeveloped world, and the pattern offuture change is likely to be morevaried. If future fertility ratesremain relatively high, the absolutechange in the aging index will besmall. Generally, however, the pro-portional rise in the aging index indeveloping countries is expected tobe greater than in developedcountries.

The aging index also is useful inexamining within-country differ-ences in the level of populationaging. As noted in Chapter 5, therecan be significant differences in theextent of aging between urban andrural areas. There may also be

Figure 2-6.

Speed of Population Aging

Sources: Kinsella and Gist, 1995; U.S. Census Bureau, 2000a.

(Number of years required or expected for percent of population aged 65 and over to rise from 7 percent to 14 percent)

Colombia (2017-2037)

Brazil (2011-2032)

Thailand (2003-2025)

Tunisia (2009-2032)

Sri Lanka (2004-2027)

Jamaica (2009-2033)

Chile (2000-2025)

Singapore (2001-2028)

China (2000-2027)

Azerbaijan (2000-2041)

Japan (1970-1996)

Spain (1947-1992)

United Kingdom (1930-1975)

Poland (1966-2013)

Hungary (1941-1994)

Canada (1944-2009)

United States (1944-2013)

Australia (1938-2011)

Sweden (1890-1975)

France (1865-1980)

20

115

85

73

69

6553

47

45

45

26

41

27

27

25

24

23

22

21

23

Developed countries

Developing countries


Figure 2-7.

Aging Index: 2000 and 2030


United States

New Zealand

Japan

Canada

Australia

Ukraine

Russia

Poland

Hungary

Czech Republic

Bulgaria

United Kingdom

Sweden

Norway

Luxembourg

Italy

Greece

Germany

France

Denmark

Belgium

Austria92

18696

172

80143

85155

103187

114206

261127

74117

76131

94169

82152

106

24484

21687

64179

160

70141

78133

60126

66148

115231

51103

59102

(People aged 65 and over per 100 people aged 0-14)

Western Europe

Eastern Europe

Other Developed Countries

DEVELOPED COUNTRIES

20002030

Zimbabwe

Tunisia

Morocco

Malawi

Liberia

Kenya

Egypt

Uruguay

Peru

Mexico

Jamaica

Guatemala

Costa Rica

Colombia

Chile

Brazil

Argentina

Turkey

Thailand

Sri Lanka

South Korea

Singapore

Philippines

Pakistan

Malaysia

Israel

Indonesia

India

China

Bangladesh

Asia


Africa

DEVELOPING COUNTRIES

9

27

14

15

36

12

10

10

38

32

25

27

21

32

91

38

52

73

36

25

30

96

125

85

96

71

39

18

26

14

16

9

22

13

13

53

74

69

90

50

64

18

67

45

43

73

11

6

8

6

13

20

9

34

19

11

10

40

71

23


Amazonas Para

Amapa

Mato Grosso

Acre

Roraima

Rondonia

Parana

Rio Grandedo Sul

Mato Grossodo Sul

SantaCatarina

Sao Paulo

Minas Gerais

Rio deJaneiro

EspiritoSanto

Bahia

Goias

Tocantins

Maranhao

Piaui

Ceara

Sergipe

Alagoas

Pernambuco

Paraiba

Rio Grandedo Norte

Figure 2-8.

Aging Index in Brazil by State: 1991

Source: 1991 Census of Brazil.

5.4 to 8.99.0 to 11.912.0 to 13.914.0 to 21.0

Aging index

(Population aged 65 and over per 100 population aged 0-14)


broader regional differences, espe-cially in large nations such as Brazil(Figure 2-8). Based on 1991 censusdata, the overall aging index inBrazil was 14. However, this meas-ure ranged from less than 6 in sev-eral northern states of the countryto 21 in the state of Rio de Janeiro.

MEDIAN AGE TO RISE IN ALL COUNTRIES

Population aging refers most simplyto increasing proportions of olderpeople within an overall populationage structure. Another way to thinkof population aging is to consider asociety’s median age, the age thatdivides a population into numerical-ly equal parts of younger and olderpeople. For example, the 2000median age in the United States was36 years, indicating that the num-ber of people under age 36 equalsthe number who have already cele-brated their 36th birthday.

The 2000 median ages of the 52study countries ranged from 17 inMalawi to 41 in Japan. Developedcountries are all above the 32-yearlevel, while a majority of develop-ing nations have median ages under25. During the next three decades,the median age will increase in all52 countries, though at very differ-ent rates. By 2030, Italy is project-ed to have the highest median age,with half its population aged 52 orover (Figure 2-9), reflecting in largepart the extremely low level of fer-tility now occurring. By way of con-trast, persistently high birth ratesare likely to preclude a large changein median age in some developingcountries (e.g., Liberia and Malawi).

Figure 2-9.

Median Age in 12 Countries: 2000, 2015, and 2030


2000 2015 2030

Thailand

Pakistan

Mexico

Malawi

Liberia

China

Brazil

United States

Italy

Japan

Germany

Canada

Developed countries


37

40

41

40

36

41

45

45

46

38

44

47

50

52

39

26

30

18

17

23

19

29

31

36

18

20

28

24

35

37

41

20

23

34

29

40

(In years)

THE DYNAMICS OFPOPULATION AGING

The process of population aging is,as noted earlier, primarily deter-mined by fertility (birth) rates andsecondarily by mortality (death)rates, so that populations with highfertility tend to have low propor-tions of older people and viceversa. Demographers use the term“demographic transition” to refer toa gradual process2 wherein a socie-ty moves from a situation of highrates of fertility and mortality toone of low rates of fertility andmortality. This transition is charac-terized first by declines in infantand childhood mortality as infec-tious and parasitic diseases arereduced. The resulting improve-ment in life expectancy at birthoccurs while fertility tends toremain high, thereby producinglarge birth cohorts and an expand-ing proportion of children relativeto adults. Other things being equal,this initial decline in mortality gen-erates a younger population agestructure (Lee, 1994).

Generally, populations begin to agewhen fertility declines and adultmortality rates improve. Successivebirth cohorts may eventuallybecome smaller and smaller,although countries may experiencea “baby boom echo” as women ofprior large birth cohorts reach child-bearing age. International migrationusually does not play a major rolein the aging process, but can beimportant in smaller populations.Certain Caribbean nations, forexample, have experienced a com-bination of emigration of working-age adults, immigration of elderly


2 The concept of demographic transitionadmittedly is a broad one, and some wouldargue that it has many permutations or thatthere is more than one form of demographictransition; see, for example, the discussion inCoale and Watkins (1986).

retirees from other countries, and aged 25 to 44, and younger cohortsreturn migration of former emi- were becoming successively small-grants who are above the average er. If fertility rates continue as pro-population age; all three factors jected through 2030, the aggregatecontribute to population aging. pyramid will start to invert, withSome demographers expect interna- more weight on the top than on thetional migration to assume a more bottom. The size of the oldest-oldprominent role in the aging process, population (especially women) willparticularly in graying countries increase, and people aged 80 andwhere persistently low fertility has over may eventually outnumber anyled to stable or even declining total younger 5-year group. Althoughpopulation size (see Box 2-1). the effect of fertility decline usuallyEventual shortages of workers may has been the driving force in chang-generate demands for immigrant ing population age structures, cur-labor (Peterson, 1999) and may rent and future changes in mortalityforce nations to choose between will assume much greater weight,relaxed immigration policies and particularly in relatively “aged”pronatalist strategies to raise birth countries (Caselli and Vallin, 1990),rates (Kojima, 1996). and are discussed further in the

next chapter.Figure 2-10 illustrates the historicaland projected aggregate population ELDERLY POPULATIONSage structure transition in develop- THEMSELVES OFTEN ARE AGINGing and developed countries. At

An increasingly important feature ofone time, most if not all countries

societal aging is the progressivehad a youthful age structure similar

aging of the elderly populationto that of developing countries as a

itself. Over time, a nation’s elderlywhole in 1950, with a large percent-

population may grow older on aver-age of the entire population under

age as a larger proportion survivesthe age of 15. Given the relatively

to 80 years and beyond. In manyhigh rates of fertility that prevailed

countries, the “oldest old” (peoplein most developing countries from

aged 80 and over) are now the1950 through the early 1970s, the

fastest growing portion of the totaloverall pyramid shape had not

population. In the mid-1990s, thechanged greatly by 1990. However,

global growth rate of the oldest oldthe effects of fertility and mortality

was somewhat lower than that ofdecline can be seen in the projected

the world’s elderly, a result of lowpyramid for 2030, which loses its

fertility that prevailed in manystrictly triangular shape as the size

countries around the time of Worldof younger 5-year cohorts stabilizes

War I. In other words, people whoand the elderly portion of the total

were reaching age 80 in 1996, forpopulation increases.

example, were part of a relatively

The picture in developed countries small birth cohort. The growth rate

has been and will be quite different. of the world’s oldest-old population

In 1950, there was relatively little from 1996 to 1997 was only

variation in the size of 5-year 1.3 percent. Just a few years later,

groups between the ages of 5 and however, the fertility effects of

24. The beginnings of the post- World War I had dissipated; from

World War II baby boom can be 1999 to 2000, the growth rate of

seen in the 0-4 age group. By the world’s 80-and-over population

1990, the baby-boom cohorts were had jumped to 3.5 percent,


Box 2-1.

Population Aging in the Context of Overall Population Decline

European demographers have sounded warning bells means to affect fertility, including direct financialfor at least the last 30 years with regard to the pos- incentives for additional births; indirect pension (i.e.,sibility of declining population size in industrialized early retirement) or in-kind benefits such as preferen-nations. Until very recently, however, this idea had tial access for mothers with many children to subsi-not permeated public discourse. Societies were dized housing; or measures to reduce the opportunityaware that they were aging, but the equation of costs of additional childbearing. These policies haveaging with population decline was uncommon. In had modest impacts in authoritarian states, but onlythe last 2 years, the visibility of likely population minimal impacts in liberal democracies such as Francedecline has increased dramatically, in large part due and Sweden (Teitelbaum, 2000). Industrial societiesto United Nations (2000a; 2000b) reports suggesting already provide various rewards, but using them tothat populations in most of Europe and Japan will deliberately manipulate fertility is a sensitive issue,decrease in size over the next 50 years, and to pub- potentially involving substantial economic transfers.licity accorded to actual declines in Spain, Italy,

The United Nations (2000a) undertook an examinationRussia, and other nations.

of the likely impact of migration as a counterbalanceThis trend raises several contentious issues: Is per- to aging, building on earlier work by Lesthaeghe,sistent below-replacement fertility a threat to Page, and Surkyn (1988), the Organization forEuropean and other societies, and if so, can it be Economic Co-Operation and Development (1991), andaltered? To what extent, if any, should so-called others. The conclusion was that inflows of migrants“replacement migration” be encouraged as a mecha- will not be able to prevent European populationnism to offset population aging? Are there important declines in the future, nor rejuvenate national popula-macroeconomic (e.g., transnational capital flows; tions, unless the migration flows are of very largechanges in national savings rates) and national securi- magnitude (i.e., millions annually). On the heels ofty issues that should be considered? this report, the United Nations convened an Expert

Group Meeting on Policy Responses to PopulationThere are no hard and fast answers to these ques-

Aging and Population Decline in October 2000. Thetions. One study (Bongaarts and Bulatao, 2000) exam-

consensus of the experts was that replacement migra-ined the experience of the diverse set of countries

tion was not a viable “solution” in and of itself, butthat have made the transition to low fertility. In very

could buffer the likely impact of future aging if usedfew of these countries has fertility stabilized at rates

by governments in conjunction with other policiesabove two children per woman. Such an occurrence

(e.g., increased labor force participation, especiallywould be dependent on substantial proportions of

among women; fertility inducements as noted above).higher-order births, but higher-order births are largely

With regard to global financial and security issues, lit-“anachronistic” in industrial-country settings. The ten-

tle systematic work has been done on overalltative conclusion was that fertility is unlikely to

impacts, though researchers are beginning to explorerebound significantly, but it has been noted that few

and model various scenarios (see, e.g., CSIS anddemographers anticipated the post-World War II baby

Watson Wyatt, 2000; Eberstadt, 2000; MacKellar andboom that will soon have a major impact on popula-

Ermolieva, 2001; Mason et al., 2001).tion aging. Governments have employed various

Figure 2-10.

Population by Age and Sex: 1950, 1990, and 2030

Sources: United Nations, 1999 and U.S. Census Bureau, 2000a.

Developing countriesDeveloped countries

1950

Millions

400 300 200 100

0- 4 5- 9

10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79

80+

0 100 200 300 400

1990

400 300 200 100

0- 4 5- 9

10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79

80+

0 100 200 300 400

2030

400 300 200 100

0- 4 5- 9

10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79

80+

0 100 200 300 400

Male FemaleAge



considerably higher than that of theworld’s elderly as a whole (2.3 per-cent). In the future, we expect tosee sustained high growth of theoldest old. In the first decade of thetwenty-first century, the projectedaverage annual growth rate of the80-and-over population is 3.9 per-cent (versus 2.0 percent for the 65-and-over population), and isexpected to remain above 3 percentduring the period 2010-2020.

The oldest old constituted 17 per-cent of the world’s elderly in 2000:22 percent in developed countriesand 13 percent in developing coun-tries. More than half (53 percent) ofthe world’s oldest old in 2000 livedin just six countries: China, theUnited States, India, Japan,Germany, and Russia (Figure 2-11).About an additional one-fifth (22percent) lived elsewhere in Europe,while 7 percent lived in LatinAmerica/Caribbean and about 6percent lived in Africa/Near Eastregions, and another 9 percent inAsian countries other than China,India, and Japan.

Among the 52 study countries, thepercentage of oldest old in the totalpopulation in 2000 was less thanhalf a percent in several developingcountries (e.g., Egypt, Guatemala,Indonesia, Kenya, and Malawi). Incontrast, the oldest old constituted5 percent of the total population of

Sweden, and 4 percent or more of countries (e.g., Barbados, Cuba,the total in several other European Puerto Rico, and Uruguay) havecountries (Denmark, Italy, Norway, higher levels than many Easternand the United Kingdom). In gener- European nations. al, Western European nations are

Countries vary considerably in theabove 3 percent, while other

projected age components of elder-developed countries are between 2

ly populations. In the United States,and 3 percent. In most developing

the oldest old were 26 percent of allnations, less than 1 percent of the

elderly in 2000, and are expectedpopulation is aged 80 and over,

to continue to be 26 percent inalthough some developing

Figure 2-11.

Percent Distribution of World Population Aged 80 and Over: 2000

Note: Data represent the share of the world's total oldest old in each country or region. Individual countries with more than 2.0 percent of the total are shown separately. Source: U.S. Census Bureau, 2000a.

All remaining countries

Africa/Near East


Other Europe

Spain

France

Italy

United Kingdom

Germany

Russia

Other Asia

Japan

India

China

United States 13.1

16.3

8.7

6.6

8.9

4.2

4.1

3.4

3.3

3.1

2.1

10.5

6.9

5.8

3.1


2030 (Figure 2-12). Some European Stability in the proportion of oldestnations will experience a sustained old in the elderly population shouldrise in this ratio, while others will not deflect attention from burgeon-see an increase during the next two ing absolute numbers. In thedecades and then a subsequent United States, the oldest olddecline. The most striking global increased from 374 thousand inincrease is likely to occur in Japan; 1900 to more than 9 million today.by 2030, nearly 40 percent of all The small percentage decline forelderly Japanese are expected to be the United States in Figure 2-12at least 80 years old. Most masks a projected absolute increasedeveloping countries should experi- of over 9 million oldest-old people.ence modest long-term increases in Four-generation families are becom-this ratio. ing increasingly common (Soldo,

1996), and the aging of the baby

boom may produce a great-grand-parent boom in many countries.The numerical growth and increas-ing heterogeneity of the oldest oldcompel social planners to seek fur-ther health and socioeconomicinformation about this group,because the oldest old consumedisproportionate amounts of healthand long-term care services(Suzman, Willis, and Manton, 1992).Past population projections oftenhave underestimated the improve-ment in mortality rates among theoldest old, and as the next chapterpoints out, actual numbers oftomorrow’s oldest old could bemuch higher than presently antici-pated. Because of the sustainedincreases in longevity in manynations, greater age detail is neededfor the oldest old. In the past, com-parable population projections forthe world’s countries often groupedeveryone aged 80 and over into asingle, open-ended component.Today, for the first time, agencies(e.g., the United Nations PopulationDivision; the U.S. Census Bureau’sInternational Programs Center) areproducing sets of international pop-ulation projections that expand therange of older age groups up to anopen-ended category of age 100and over.

Figure 2-12.

Oldest Old as a Percent of All Elderly: 2000 and 2030


United States

Russia

Pakistan

Japan

Bulgaria

Argentina

(People aged 80 and over as a percent of people aged 65 and over)

20002030

26.4

21.7

13.2

21.7

13.3

15.9

26.5

27.3

27.8

39.3

14.4

20.0


Box 2-2.

The Growth of Centenarians

As average length of life increases, the concept of There are several problems with obtaining accurate“oldest old” will change. While people of extreme old age data on very old people (Kestenbaum, 1992; Eloage constitute a tiny portion of total population in et al., 1996), and estimates of centenarians from cen-most of the world, their numbers are of growing suses and other data sources should be scrutinizedimportance, especially in more-developed nations. carefully. For example, the 1990 United States censusThanks to improvements in nutrition, health, and recorded some 37,000 centenarians, although due tohealth care, we now have for the first time in history age misreporting, the actual figure is thought to bethe opportunity to consider significant numeric closer to 28,000, (Krach and Velkoff, 1999). Still, thisgrowth of the population aged 100 and over. represents a doubling of the population aged 100 andAccording to researchers in Europe, the number of over from 1980 to 1990, similar to estimates forcentenarians has doubled each decade since 1950 in European nations. The potentially spectacularindustrialized countries. Using reliable statistics from increase in numbers of centenarians is illustrated byten Western European countries and Japan, Vaupel and data and projections for France. Dinh (1995) has esti-Jeune (1995) estimated that some 8,800 centenarians mated that there were about 200 centenarians inlived in these countries as of 1990, and that the num- France in 1950, and that by the year 2000 the num-ber of centenarians grew at an average annual rate of ber would be 8,500. His 50-year projections suggestapproximately 7 percent between the early 1950s and 41,000 people aged 100 and over by 2025, increas-the late 1980s. They also estimate that, over the ing to 150,000 in 2050. If these projections are real-course of human history, the odds of living from birth ized, the number of centenarians in France will haveto age 100 may have risen from 1 in 20 million to 1 multiplied by a factor of 750 in one century.in 50 for females in low-mortality nations such asJapan and Sweden.


CHAPTER 3.

Life Expectancy and Changing Mortality

The spectacular increases in human European nations, the normal the world have been fairly uniform.life expectancy that began in the lifetime in many African countries Practically all nations have shownmid-1800s and continued during spans fewer than 45 years. On continued improvement, with somethe following century are often average, an individual born in a exceptions in Latin America andascribed primarily to improvements more-developed country can now more recently in Africa, the latterin medicine. However, the major expect to outlive his/her counter- due to the impact of the HIV/AIDSimpact of improvements both in part in the less-developed world by epidemic. The most dramatic gainsmedicine and sanitation did not 13 years. in the developing world have beenoccur until the late nineteenth cen- in East Asia, where life expectancy

TWENTIETH CENTURY LIFEtury. Earlier and more important at birth increased from less than EXPECTANCY HAS DOUBLED INfactors in lowering mortality were 45 years in 1950 to more than SOME DEVELOPED COUNTRIES

innovations in industrial and agri- 72 years today.cultural production and distribution, Table 3-1 shows the enormous

TREND IN RISING LIFEwhich improved nutrition for large strides that countries have made inEXPECTANCY MAY BEnumbers of people (Thomlinson, extending life expectancy sinceCHALLENGED

1976). A growing research consen- 1900. In developed countries, the

sus attributes the gain in human average national gain in life While global gains in life expectancy

longevity since the early 1800s to a expectancy at birth was 66 percent at birth have been the norm,

complex interplay of advancements for males and 71 percent for unforeseen changes and epidemics

in medicine and sanitation coupled females during the period 1900-90. may reverse the usual historical pat-

with new modes of familial, social, In Italy, life expectancy at birth for tern. Beginning in the 1950s, the

economic, and political organization women increased from 43 years in typical sustained increase in life

(Moore, 1993). 1900 to over 82 years in 2000. In expectancy at birth in developedsome cases, life expectancy has countries began to take different

LIFE EXPECTANCY AT BIRTH more than doubled during the cen- paths. While female life expectancyEXCEEDS 78 YEARS IN 28 tury (e.g., Spain). continued to rise virtually every-COUNTRIES where, male gains slowed signifi-

Increases in life expectancy wereLife expectancy at birth in Japan cantly and in some cases leveled

more rapid in the first half than inand Singapore has reached off. From the early 1950s to the

the second half of the century.80 years, the highest level of all the early 1970s, for example, male life

Expansion of public health servicesworld’s major countries, and has expectancy changed little in

and facilities and disease eradica-reached 79 years in several other Australia, the Netherlands, Norway,

tion programs greatly reduceddeveloped nations (e.g., Australia, and the United States. After this

death rates, particularly amongCanada, Italy, Iceland, Sweden, and period of stagnation, male life

infants and children. From 1900 toSwitzerland). Levels for the United expectancy again began to rise.

1950, people in many WesternStates and most other developed

nations were able to add 20 years In Eastern Europe and the formercountries fall in the 76-78 year

or more to their life expectancies. Soviet Union, the pace of improve-range (Figure 3-1). Throughout the

ment in the 1950s and early 1960sdeveloping world, there are Reliable estimates of life expectancy

was extraordinary. Advances inextreme variations in life expectan- for many developing countries prior

living conditions and public healthcy at birth (Figure 3-2). While the to 1950 are unavailable. Since

policies combined to produce largelevels in some developing nations World War II, changes in life

declines in mortality by reducingmatch or exceed those in many expectancy in developing regions of

some major causes of death

(e.g., tuberculosis) to minimal lev-els (Vishnevsky, Shkolnikov, andVassin, 1991). Resultant gains inlife expectancy in excess of 5 years per decade were common.By the mid-1960s, however, therate of increase had deceleratedsharply. In the 1970s and 1980s,changes in female life expectancyat birth were erratic, while malelife expectancy fell throughout theregion (Bobadilla and Costello,1997). Following the demise ofthe former Soviet Union, thedecline has continued into the1990s in some countries. Thedecline has been particularlysevere for Russian men; between1987 and 1994, male lifeexpectancy at birth plummeted 7.3 years to a level of 57.6, beforebeginning to rise again in recentyears (Figure 3-3). The largeincreases in adult male mortalityusually are attributed to a combi-nation of factors includingincreased homicide and accidentrates, excessive alcohol consump-tion, poor diet, and environmen-tal/workplace degradation(Virganskaya and Dmitriev, 1992;Murray and Bobadilla, 1997),although most researchers takepains to point out that clear causalmechanisms remain poorlyunderstood.


Figure 3-1.

Life Expectancy at Birth: 2000


MalawiZimbabwe

KenyaLiberiaEgypt

MoroccoTunisia

BrazilGuatemala

PeruColombia

MexicoArgentina

JamaicaUruguay

ChileCosta Rica

BangladeshPakistan

IndiaPhilippinesIndonesiaThailandMalaysia

TurkeyChina

Sri LankaSouth Korea

IsraelSingapore

New ZealandCanada

AustraliaJapan

UkraineRussia

BulgariaHungary

PolandCzech Republic

DenmarkLuxembourg

GermanyUnited Kingdom

AustriaBelgiumGreece

NorwayFrance

ItalySweden

United States

Developed countriesDeveloping countries(In years)

37.6

77.1

79.679.078.878.778.477.877.777.777.477.176.5

74.573.2

71.470.9

67.266.0

80.779.879.4

77.8

80.178.6

74.471.871.471.070.8

68.668.067.5

62.561.160.2

75.875.775.275.275.1

71.570.370.0

66.262.9

73.769.1

63.351.0

48.037.8

Western Europe

Eastern Europe

Other Developed

Asia


Africa

U.S. C

ensu

s Bureau

An

Agin

g W

orld

: 20

01

25


Figure 3-2.

Life Expectancy at Birth: 2000

Under 50 years50 to 64 years65 to 74 years75 years and over


Table 3-1.Life Expectancy at Birth in 34 Countries:(In years)

1900 to 2000

Region/countryCirca 1900 Circa 1950 2000

Male Female Male Female Male Female

DEVELOPED COUNTRIES

Western EuropeAustria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Belgium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Denmark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .France . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1Germany . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Norway . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Sweden . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .United Kingdom . . . . . . . . . . . . . . . . . . . . . . . . . . .

Southern and Eastern EuropeCzech Republic1 . . . . . . . . . . . . . . . . . . . . . . . . . .Greece. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Hungary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Italy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Spain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

OtherAustralia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Japan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .United States . . . . . . . . . . . . . . . . . . . . . . . . . . . . .


AfricaEgypt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Ghana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Mali. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .South Africa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Uganda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Congo (Brazzaville) . . . . . . . . . . . . . . . . . . . . . . . .

AsiaChina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Kazakhstan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .South Korea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Syria. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Thailand. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Latin AmericaArgentina. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Brazil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Costa Rica . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Chile. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Venezuela . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

37.845.451.645.343.852.352.846.4

38.938.136.642.933.9

53.242.848.3

39.948.954.848.746.655.855.350.1

41.739.738.243.235.7

56.844.351.1

62.062.168.963.764.670.369.966.2

60.963.459.363.759.8

66.759.666.0

67.067.471.569.468.573.872.671.1

65.566.763.467.264.3

71.863.171.7

74.574.574.074.974.375.777.075.0

71.075.967.075.975.3

76.977.574.2

81.081.379.382.980.881.882.480.5

78.281.276.182.482.5

82.784.179.9

Circa 1950 2000

Male Female Male Female

41.240.431.144.038.537.5

39.339.451.646.044.845.0

60.449.356.057.849.253.8

43.643.634.046.041.640.6

42.338.061.949.047.249.1

65.152.858.661.352.456.6

61.356.145.550.442.244.5

69.661.957.770.867.465.3

71.758.573.372.468.570.1

65.558.847.951.843.750.5

73.363.168.978.569.672.0

78.667.678.579.274.776.3

1Figures for Germany and Czech Republic prior to 1999 refer to the former West Germany and Czechoslovakia, respectively.

Note: Reliable estimates for 1900 for most developing countries are not available.

Source: UNDIESA 1988; Siampos 1990; and U.S. Census Bureau, 2000a.

Elsewhere, the HIV/AIDS epidemichas had a devastating impact on lifeexpectancy, particularly in parts ofAfrica. The effect of the epidemicon life expectancy at birth may beconsiderable, given that AIDSdeaths often are concentrated in thechildhood and middle adult (30 to45) ages. Projections to the year2010 suggest that AIDS may reducelife expectancy at birth by morethan 30 years from otherwise-expected levels in countries such asBotswana, Namibia, South Africa,and Zimbabwe. And while the com-mon perception of AIDS mortalityusually associates AIDS deaths withchildren and younger adults, theepidemic may have a direct andgrowing effect on older popula-tions. In the United States in 1992,nearly three times as many peopleaged 60 and over died of AIDS asdid people under age 20. Between1987 and 1992, the annual numberof U.S. children who died of AIDSremained relatively stable, whereasthe number of deaths to peopleaged 60 and over nearly doubled(Hobbs and Damon, 1996).


Figure 3-3.

Life Expectancy at Birth in Four Countries: 1950 to 1998

Sources: United Nations, 1999; U.S. Census Bureau, 2000a; and country sources.

0

10

20

30

40

50

60

70

80

90

199819901980197019601950

South Korea

Life expectancy in years

United States

Russia

United States

Male

0

10

20

30

40

50

60

70

80

90

199819901980197019601950

Life expectancy in yearsFemale

Zimbabwe

RussiaSouth Korea

Zimbabwe

FEMALE ADVANTAGE IN LIFEEXPECTANCY NEARLYUNIVERSAL

The widening of the sex differentialin life expectancy has been a centralfeature of mortality trends in devel-oped countries in the twentieth cen-tury. In 1900, in Europe and NorthAmerica, women typically outlivedmen by 2 or 3 years. Today, theaverage gap between the sexes isroughly 7 years, but exceeds 12 years in parts of the formerSoviet Union as a result of theunusually high levels of male mor-tality discussed above (Figure 3-4).This differential reflects the fact thatin most nations females have lowermortality than males in every agegroup and for most causes of death.Female life expectancy now exceeds80 years in over 30 countries and isapproaching this level in many othernations. The gender differentialusually is smaller in developingcountries, commonly in the 3-6 yearrange, and even is reversed in someSouth Asian and Middle East soci-eties where cultural factors (such aslow female social status and prefer-ence for male rather than female off-spring) are thought to contribute tohigher male than female lifeexpectancy at birth.

MALE MORTALITYSUBSTANTIALLY HIGHER THANFEMALE MORTALITY ATOLDER AGES

The data in Figure 3-5 illustrate theusual gender pattern of mortality atolder ages, wherein male rates areseen to be consistently higher thanfemale rates. In Canada andGermany, for instance, male mortali-ty rates for ages 65 to 74 areroughly twice as great as correspon-ding female rates. Among coun-tries, though, age-specific mortalityrates can differ widely even whereoverall mortality appears similar.


Figure 3-4.

Female Advantage in Life Expectancy at Birth: 2000


Chile

China

Egypt

Mexico

Syria

Bangladesh

Spain

United States

Russia

Hungary

Japan

France

Belarus

(Difference in years between females and males)Developed countriesDeveloping countries

6.8

12.7

8.06.5

9.1

10.75.7

7.2-0.5

2.3

6.24.2

3.7

Figure 3-5.

Mortality Rates at Older Ages: 2000

Source: Estimated by the U.S. Census Bureau based on individual country sources.

80+

75-79

70-74

65-69

80+

75-79

70-74

65-69

80+

75-79

70-74

65-69

(Per 1,000 population in age/sex group)

MaleFemale

116

Canada

23

36

57

117

30

46

68

138

26

40

65

147

12

19

32

87

16

25

45

108

12

21

38

Uruguay

Germany

For example, total life expectancy cited as a source of higher maleat birth in 1995 was about the mortality rates (Statistics Canada,same in Cuba (75.4 years) and 1997), suggesting that the gap inPortugal (74.7 years). However, life expectancy might decrease ifWorld Health Organization data for women increased their use of1995 show that the female mortali- tobacco and alcohol and their par-ty rate for ages 55 to 64 was ticipation in the labor force.30 percent lower in Portugal than in However, data from industrializedCuba, and the female mortality rate countries still show no clear patternat ages 65 to 74 was about 20 per- of change in the gender gap; thecent lower. For older men, on the gap is widening in most of Easternother hand, rates were 15 percent Europe and the former Soviet Unionhigher in each age group in and tends to be narrowing in otherPortugal than in Cuba. developed countries. In the United

States, for instance, life expectancyWILL THE GENDER GAP IN LIFE at birth increased 3.0 years for menEXPECTANCY NARROW? and 1.6 years for women betweenPrecise explanations of the gender 1980 and 1996. But in somedifference in life expectancy still nations with very high overall lifeelude scientists because of the expectancy (e.g., France, Germany,apparent complex interplay of bio- Japan), gains in female longevitylogical, social, and behavioral condi- continue to outpace those of males.tions. Greater exposure to risk fac-

Given the small average gender gaptors such as tobacco and alcohol

in life expectancy in developinguse and occupational hazards is

countries relative to developed

nations, most demographers expectto see a widening of thefemale/male difference in upcomingdecades, along the lines of the his-torical trend in industrializednations. Evidence suggests thatmany developing countries areexperiencing increases in alcoholand tobacco consumption andvehicular as well as industrial acci-dents, all of which tend, at least ini-tially, to adversely affect men morethan women. Another factor thatmay promote a widening gendergap is education, which is positivelyrelated to survival. As women“catch up” to men in terms of edu-cational attainment, female survivaland health status may improve (Liu,Hermalin, and Chuang, 1998).

OLD-AGE MORTALITY RATESDECLINING OVER TIME

In countries where infant mortalityrates are still relatively high butdeclining, most of the improvementin life expectancy at birth resultsfrom helping infants survive thehigh-risk initial years of life. Butwhen a nation’s infant and child-hood mortality reach low levels,longevity gains in older segmentsof the population begin to assumegreater weight (Caselli and Vallin,1990; Gjonca, Brockmann, andMaier, 1999). Most countries areexperiencing a rise in life expectan-cy at age 65, as exemplified byJapanese and U.S. data in Figure 3-6.The average Japanese womanreaching age 65 in 1998 couldexpect to live an additional 22 years, and the average manmore than 17 years. Overall (i.e.,both sexes combined) Japanese lifeexpectancy at age 65 increased 40 percent from 1970 to 1998,compared with an overall increasein life expectancy at birth of 9 per-cent. Comparative figures for theUnited States are 17 and 8 percent,


Figure 3-6.

Life Expectancy at Age 65 in Japan and the United States: 1970, 1980, and 1998


1998

1980

1970

1998

1980

1970

1998

1980

1970

1998

1980

1970

(Years of life remaining for those who reach age 65)

19.2

12.5

14.6

17.1

15.3

17.7

22.0

13.1

14.1

16.0

17.0

18.3

Japan, Male

Japan, Female

United States, Male

United States, Female

respectively. Although greater rela-tive improvement in life expectancyat older ages may not yet be wide-spread in developing regions of theworld, the proportional increase inlife expectancy at older ages isapproaching or has surpassed therelative increase in life expectancyat birth in some developing coun-tries, notably in Latin America andthe Caribbean (Kinsella, 1994).

The rise in life expectancy at age 65that is characteristic of most soci-eties means that the chances ofdying for particular older agegroups are declining. Figure 3-7shows across-the-board declines inmortality in two older age groups(with the exception of women aged80 to 84 in Mauritius) during a fair-ly recent 10-year period. In gener-al, mortality improvements forpeople aged 70 to 74 have beengreater than for people aged 80 to84, reflecting the growing robust-ness of younger elderly cohorts.

MORTALITY RATE INCREASEAPPEARS TO LESSEN AT VERYOLD AGES

As long ago as the early 1800s,research demonstrated that thehuman death rate increases withage in an exponential manner, atleast to the upper ranges of the agedistribution. Recently, researchershave documented that, at very oldages, the rate of increase in themortality rate tends to slow down.In a study of 28 countries with rea-sonably-reliable data for the period1950-90, Kannisto (1994) noted notonly a decline in mortality rates atages 80 and over, but a tendencytoward greater decline in more-recent time periods. Other workhas confirmed this tendency (e.g.,Wilmoth et al., 2000), and a recentstudy in the United States suggeststhat the age at which mortality

deceleration occurs is rising (Lynch may slow down at very old ages,and Brown, 2001). and/or that certain genes that are

detrimental to survival may be sup-Findings such as these have gener-

pressed (see Horiuchi and Wilmoth,ated at least two potential explana-

1998, for a discussion and examina-tions. The “heterogeneity” hypothe-

tion of these hypotheses). Thesis, an extension of the notion of

observed deceleration in mortality,“survival of the fittest,” posits that

combined with the fact that humanthe deceleration in old-age mortality

mortality at older ages has declinedis a result of frailer elderly dying at

substantially, has led to the ques-younger ages, thus creating a very

tioning of many of the theoreticalold population with exceptionally

tenets of aging (Vaupel et al., 1998).healthy attributes resulting from

Important insights are being gar-genetic endowment and/or lifestyle.

nered from “biodemographic”A second, “individual-risk” hypothe-

research which attempts to sis, suggests that the rate of aging


Figure 3-7.

Percent Change in Death Rates for Two Older Age Groups: Circa 1985 to Circa 1995

Source: United Nations, various issues of the annual Demographic Yearbook.

Austria

Japan

Israel

Chile

United States

Mauritius

Netherlands

France

Male

Austria

Japan

Israel

Chile

United States

Mauritius

Netherlands

France

(Based on 3-year average of mortality rates centered on 1985 and 1995)

70-74 years 80-84 years

Female

-20

-6

-7

-27

-6

-24

-20

-27

-23

-20

-8

9

-8

-10

-16

-28

-22

-3

-13

-16

-14

-20

-16

-16

-19

-14

-3

-12

-10

-3

-13

-17

cross-fertilize the biologic and England and Wales is about demographic perspectives of aging 50 percent higher today than inand senescence. While a clearer pic- 1950. Consequently, the number ofture of the causes of mortality decel- female octogenarians is about 50eration at very old ages awaits fur- percent higher than it would havether investigation (and will benefit been had oldest-old mortalityfrom the study of evolutionary biol- remained at 1950 levels; in absoluteogy and aging in nonhuman terms, this means that there arespecies; see Olshansky, 1998; more than one-half million oldest-oldWachter and Finch, 1997; Le Bourg, British women alive today who oth-2001), its recognition at a time erwise would have been dead in thewhen numbers of the very old are absence of mortality improvement.growing rapidly has important poli-

An example from the United Statescy implications.

illustrates the range of future uncer-

PACE OF MORTALITY CHANGE tainty about the size of tomorrow’s

DIFFICULT TO PROJECT oldest-old population. The U.S.Census Bureau estimated the num-

The pace at which death rates atber of people aged 85 and over in

advanced ages decline will play athe United States to be about

major role in determining future3.6 million in 1995 and has made

numbers of elderly and especially ofseveral projections of the future

very old population. Vaupel (1997)size of this age group (Day, 1996;

has noted that the remaining lifeU.S. Census Bureau, 2000b). The

expectancy of 80-year-old women inCensus Bureau’s middle-mortality

series projection suggests thatthere will be 14.3 million peopleaged 85 and over in the year 2040,while the low-mortality (i.e., highlife expectancy) series implies 16.8 million. As those who will be85 years old and over in the year2040 are already at least 40 yearsold, the differences in these projec-tions result almost exclusively fromassumptions about adult mortalityrates and are not affected by futurebirth or infant mortality rates. Inthe middle-mortality series, theCensus Bureau assumes that lifeexpectancy at birth will reach 84.0 years in 2050, while in thelow-mortality series life expectancyis assumed to reach 86.1 years in2050 (Hollmann, Mulder, andKallen, 2000).

Alternative projections (Figure 3-8),using assumptions of lower deathrates and higher life expectancies,have produced even larger esti-mates of the future population ofthe United States aged 85 and over.Simply assuming that death rateswill continue falling at about therecent 2 percent rate results in aprojection of 23.5 million aged 85and over in 2040 (Guralnik,Yanagishita, and Schneider, 1988).Even more optimistic forecasts offuture reductions in death rateshave been made from mathematicalsimulations of potential reductionsin known risk factors for chronicdisease, morbidity, and mortality.Manton, Stallard, and Liu (1993)used such a method to generate anextreme “upper bound” projectionfor the United States of 54 millionpeople aged 85 and over in 2040.While such projections are not nec-essarily the most likely, they doillustrate the potential impact ofchanges in adult mortality on thefuture size of the extremely oldpopulation.


Figure 3-8.

Projections of the United States Population Aged 85 and Over

Note: U.S. Census Bureau projections for 2040 do not reflect the results of the 2000 census.Sources: Guralnik, Yanagishita, and Schneider, 1988; Manton, Stallard, and Liu, 1993; and U.S. Census Bureau, 1983, 1992, and 2000b.

(In millions)

0.9 1.5 2.2 3.1 4.2

14.316.8

23.5

53.9

20001990198019701960

1960-2000 Actual2040 Census Bureau middle mortality2040 Census Bureau low mortality2040 Guralnik et al.2040 Manton et al.

2040

As noted earlier, researchers areincreasingly concerned with overallpatterns of mortality decline inaddition to studying the pace ofdecline. One recent study ofmortality in the G71 countries dur-ing the second half of the twentiethcentury reached a provocative con-clusion: mortality at each age hasdeclined exponentially at a fairlyconstant rate in each country(Tuljapurkar, Li, and Boe, 2000).The possibility of a “universal pat-tern” of mortality decline raisesimportant questions about the rela-tionship between social expendi-tures on health and their effect ondeath rates, and about the likeli-hood that the mortality decline willbe sustained in the future.

THE IMPORTANCE OFCARDIOVASCULAR DISEASE

A major disadvantage of summarymortality indexes such as lifeexpectancy is that they maskchanges in mortality by age and/orcause of death. While one canexamine life expectancy at differentages, it may be more useful to con-sider cause-specific changes in mor-tality, particularly if the intention isto devise medical or nutritionalinterventions to affect overalllongevity and the quality of yearslived at older ages. Worldwide,data on cause-specific mortality arefar from ideal for policy making in amajority of countries (See Box 3-1).Many developed countries, howev-er, have had reasonably good cause-specific mortality data since at least1950.

Death rates due to cardiovascular dis-eases — a broad category thatincludes heart, cerebrovascular(stroke) and hypertensive diseases —


1 The G7 countries include Canada, France,Germany, Italy, Japan, the United Kingdom, andthe United States.

increase with age but in recent years cardiovascular disease is not just athese rates have declined at older developed-country phenomenon; aages in many developed countries. recent U.S. Institute of Medicine studyNevertheless, cardiovascular disease (Howson et al., 1998) identifies car-remains the primary killer among eld- diovascular disease as the primaryerly populations, more so than for noncommunicable health problemadults in general. For example, more throughout the developing world.than two-thirds of all deaths to elderly

In the United States, the heart-people in Bulgaria and nearly half of

disease component of cardiovascularall deaths to elderly people in

mortality is the leading cause ofArgentina are attributed to cardiovas-

death within the elderly population.cular disease, and in most countries

Among people aged 65 to 74, heartthe proportion increases with age

disease and cancers were equally(Figure 3-9). One comprehensive

likely to be reported as the majoranalysis of developed nations

cause of death in 1997, each(Murray and Lopez, 1996) attributes

accounting for about one-third of allnearly 60 percent of all deaths to

deaths in that age group. But as agewomen aged 60 and over in the early

advances, heart disease claims an1990s to cardiovascular disease; the

increasing share, about 49 percentcorresponding figure for older men

of deaths to people aged 75 andwas 50 percent. Cancer deaths at

over (versus 18 percent for cancers).older ages usually rank a distant sec-

This pattern also occurs in other (butond, but may be more worrisome in

not all) developed countries.the public eye; in the 1995 CanadianWomen’s Health Test, most women LUNG CANCER RAMPANTbelieved breast cancer to be the num- SINCE THE 1950sber one killer of women (all ages).

Although deaths from cardiovascularOnly 16 percent of those surveyed

disease are expected to remain mostcorrectly stated that heart disease is

prominent in the future, a majorthe number one killer (Wiesenberg,

concern of health practitioners in1996). The prominence of

Box 3-1.Data on Causes of Death

Statistics on causes of death are prone to many biases and errors in allcountries. Underreporting of deaths, lack of precise causal informa-tion, inaccurate diagnoses, and cultural differences complicate bothnational and international studies of mortality. Also, by attributingdeath to one specific cause, comorbidities and underlying conditionssuch as anemia and nutritional deficiencies are often masked.Nevertheless, World Health Organization efforts to revise and extendcoverage of the International Classification of Diseases produce ongo-ing improvements in the quality and comparability of data such asthose referred to in this report. Although mortality data are imperfect,they can be used to illuminate general patterns and orders of magni-tude, and to focus the attention of research, planning, and practice.While decisionmaking should be skeptical of small differences betweengroups, major differences are likely to indicate underlying disparitiesand trends.

the industrialized world is the rise in cancer has been declining steadilylung cancer among older women as since the 1930s, a decline clearlya result of increased tobacco use attributed to nutritional change, i.e.,since World War II. With regard to a reduction in salt content of food,cancers in general, overall age- especially preserved food (Lopez,standardized death rates for cancer 1990).rose 30-50 percent among men dur-

On the other hand, prevalence ofing the period 1950-85, and fell by

lung cancer has increased sinceabout 10 percent among women.

World War II, initially among menHowever, such broad trends often

but now increasingly amongare the net result of quite different

women. Estimates for the earlychanges in mortality for the leading

1990s (Murray and Lopez, 1996)sites of disease. In the United

suggest that lung cancer isStates and Western Europe, stomach

responsible for 30 percent of allcancer deaths to males in devel-oped countries, and 12 percent ofall cancer deaths to females.Proportions for the 60-and-overpopulation are virtually identical.Male death rates from lung cancerappear to have peaked and are nowfalling in some countries and stabi-lizing in many others, perhaps por-tending future declines.Conversely, female death rates fromlung cancer are rising rapidly, inproportion to the large increases incigarette consumption which beganseveral decades ago (Bonita, 1996).Cigarette smoking has been labeledas the single most important pre-ventable cause of premature deathin women aged 35 to 69 in boththe United States and the UnitedKingdom (Amos, 1996). Still, breastcancer remains the principal neo-plasm site among females, andmortality rates from this sourcehave increased or remained con-stant in most countries since thepost-war period. The rise has beenmost pronounced in Southern andEastern Europe, which is consistentwith the hypothesis that a diet highin saturated fat is a leading risk fac-tor for breast cancer.

SUICIDE RATES MUCH HIGHERAMONG ELDERLY MEN THANWOMEN

Suicide rates in 21 countries withrelatively reliable data (Table 3-2)are consistently higher among menthan women in all age groups,including the elderly. This is a uni-versal trend even in societies as dis-parate as Singapore, the UnitedStates, Israel, and Bulgaria. Suiciderates generally increase with ageamong men, and are highest atages 75 and over. Suicide rates forwomen also tend to rise with age,although the peak rate for womenoccurs before age 75 in about one


Figure 3-9.

Percent of All Deaths From Cardiovascular Diseases and Malignant Neoplasms at Older Ages in Four Countries

Sources: World Health Organization, various issues of World Health Statistics Annual, and www-nt.who.int/whosis/statistics/whsa/whsa_table4.cfm?path=statistics,whsa,whsa_table4&language=english

75 years and over

Female, 65 to 74 years

75 years and over

Male, 65 to 74 years

75 years and over


75 years and over


75 years and over


75 years and over


75 years and over


75 years and over


Cardiovascular diseases Malignant neoplasms

Bulgaria, 1998

Argentina, 1996

France, 1996

United States, 1997

66

74

71

79

16

8

15

6

43

47

41

52

28

37

27

42

40

46

36

52

24

17

27

13

42

24

40

15

33

21

35

15

third of the countries in Table 3-2. their elderly male populations, elderly suicide rates in the world’sThe fact that the average woman while Japan, Switzerland, and more developed countries. Fewoutlives her spouse — coupled Russia have comparatively high nations have experienced the verywith studies that show that married rates among elderly women. Levels gradual rise seen in France until theelders are happier than nonmarried for elderly men in the United States mid-1980s, or the downward ten-elders — might lead one to predict are average when compared with dency observed in England andthat older women would have other countries, whereas the U.S. Wales (Figure 3-10). More often,higher rates of suicide than older rate for women aged 65 and over is national rates have fluctuated withmen, but this is clearly not the case. relatively low. Although some of no perceptible pattern.

these differentials may be artificialAmong the 23 countries examined, There was a downward trend in eld-

due to differences in the reportingHungary and Russia had the highest erly suicide in the United States for

and/or diagnosis of suicide, theirsuicide rates for elderly men, and nearly half a century prior to 1980.

sheer magnitude suggests that realHungary and Bulgaria had the high- From 1981 to 1988, however, the

international differences do existest rates for elderly women. The suicide rate of older Americans rose

and deserve closer study.reported Hungarian rate for men about 25 percent before beginningaged 75 and over is five to seven NO CLEAR TIME TREND IN to decline in the 1990s. Such antimes higher than similar rates in ELDERLY SUICIDE WORLDWIDE increase raised questions at a timeIreland, the United Kingdom, and when older people were living

Data from the World HealthNorway. Belgium and France have longer and were supposedly healthi-

Organization for the past 30 yearscomparatively high rates among er and more financially secure

do not show any clear trend in


Table 3-2.Suicide Rates for Selected Age Groups in 23 Countries:(Rate per 100,000 population in each age group)

Circa 1997

Country

Male Female

15 to 24years

45 to 54years

65 to 74years

75 yearsand over

15 to 24years

45 to 54 65 to 74years years

75 yearsand over

EuropeBelgium, 1994. . . . . . . . . . . . . . . . . . . . .Bulgaria, 1998. . . . . . . . . . . . . . . . . . . . .Denmark, 1996 . . . . . . . . . . . . . . . . . . . .Finland, 1996 . . . . . . . . . . . . . . . . . . . . .France, 1996. . . . . . . . . . . . . . . . . . . . . .Germany, 1997 . . . . . . . . . . . . . . . . . . . .Hungary, 1998 . . . . . . . . . . . . . . . . . . . .Ireland, 1996 . . . . . . . . . . . . . . . . . . . . . .Italy, 1995 . . . . . . . . . . . . . . . . . . . . . . . .Netherlands, 1997 . . . . . . . . . . . . . . . . .Norway, 1995 . . . . . . . . . . . . . . . . . . . . .Poland, 1996. . . . . . . . . . . . . . . . . . . . . .Portugal, 1998 . . . . . . . . . . . . . . . . . . . .Russia, 1997 . . . . . . . . . . . . . . . . . . . . . .Switzerland, 1996. . . . . . . . . . . . . . . . . .United Kingdom, 1997. . . . . . . . . . . . . .

North AmericaCanada, 1997 . . . . . . . . . . . . . . . . . . . . .United States, 1997 . . . . . . . . . . . . . . . .

OtherAustralia, 1995 . . . . . . . . . . . . . . . . . . . .Chile, 1994 . . . . . . . . . . . . . . . . . . . . . . .Israel, 1996 . . . . . . . . . . . . . . . . . . . . . . .Japan, 1997 . . . . . . . . . . . . . . . . . . . . . .Singapore, 1997 . . . . . . . . . . . . . . . . . . .

23151334131318257

112317

4532510

2219

23119

119

372731553830931914162442

7100

3714

2723

2214

94018

434835504132801223163231209747

9

2126

1920183530

9811671488771

131224334243139978017

2745

2727415374

4627434524631962

54

62269

179

1718161020

658

1083

1516

4

97

824

149

17201614151324

179

1077

2017

4

55

524

1914

205020

7202150

28

12569

3324

4

45

51

153333

Sources: World Health Organization, various issues of World Health Statistics Annual, andwww-nt.who.int/whosis/statistics/whsa/whsa_table4.cfm?path=statistics,whsa,whsa_table4&language=english

(Robinson 1990). Likewise in Japan,a 30-year decline in elderly suicideappeared to level off in the 1980s,though more recent data show asignificant decline in the 1990s.However, social scientists remainpuzzled by the relatively high ratesof suicide among elderly Japanesewomen. The unpredictability of sui-cide trends is perhaps best illustrat-ed by the case of the Netherlands.Dutch society is widely recognizedas being more tolerant of voluntaryeuthanasia than are other Westernsocieties, and one might think itwould also have higher rates ofrecorded suicide. However, thecountry’s rates are lower than theindustrialized-country average formost age groups, including the eld-erly, and have not changed greatlyduring the past 30 years.


Figure 3-10.

Suicide Rates by Age in England and Wales and in France: 1965 to 1995

Source: World Health Organization, various issues of World Health Statistics Annual.

Rate per 100,000 population in each age groupEngland and Wales

Rate per 100,000 population in each age groupFrance

0

20

40

60

80

100

120

140

1995199019851980197519701965

0

20

40

60

80

100

120

140

1995199019851980197519701965

Male 75+Male 65-74Female 65-74Female 75+

Male 75+

Female 75+

Male 65-74

Female 65-74


CHAPTER 4.

Health and Disability

Many societies worldwide haveexperienced a change from condi-tions of high fertility and high mor-tality to low fertility and low mortal-ity, a process commonly dubbed the“demographic transition.” Relatedto this trend is the “epidemiologictransition,” a phrase first used inthe early 1970s (Omran, 1971) torefer to a long-term change in lead-ing causes of death, from infectiousand acute to chronic and degenera-tive. In the classic demographictransition, initial mortality declinesresult primarily from the control ofinfectious and parasitic diseases atvery young ages. As children sur-vive and grow, they are increasinglyexposed to risk factors associatedwith chronic diseases and acci-dents. As fertility declines and pop-ulations begin to age, the preemi-nent causes of death shift fromthose associated with childhoodmortality to those associated witholder age (Kalache, 1996).Eventually, growing numbers ofadults shift national morbidity pro-files toward a greater incidence ofchronic and degenerative diseases(Frenk et al., 1989).

EPIDEMIOLOGIC TRANSITIONSHIFTS SURVIVAL CURVE

Figure 4-1, which shows survivalcurves for U.S. females in 1901 and1998, illustrates a general patternseen in developed countries. Thecurve for 1901 represents the earlystages of the epidemiologic transi-tion in which the level of infantmortality was high, there was con-siderable mortality through the mid-dle years, and a gradual increase atthe later ages. Female life

expectancy at birth was approxi- DEVELOPING-COUNTRYmately 50 years, and the median TRANSITION APPEARS

GREATEST IN LATIN AMERICAage at death (the age to which 50 percent of females subject to Developing countries are in variousthe mortality risks of 1901 could stages of epidemiologic transition.expect to survive) was about Change is most evident in Latin60 years. By 1998, the survivorship America and the Caribbean, wherecurve had shifted dramatically. cardiovascular diseases were theFemale life expectancy had risen to leading cause of death in 29 of 3379 years, and the median age at countries examined in 1990 (PAHO,death was above 80 years. The 1994). Most deaths from chronicproportion surviving is now quite and degenerative ailments occur athigh at all ages up to age 50, and relatively old ages. Comparativethe survival curve at older ages is data from the mid-1990s (Figure 4-2)approaching a much more rectangu- show that half or more of all deathslar shape as a result of relatively in numerous nations of the Westernmore chronic-disease mortality at Hemisphere now occur at ages 65older ages. and over.

Figure 4-1.

Survival Curve for U.S. Females: 1901 and 1998

Note: Data for 1901 refer to White females. Sources: U.S. Census Bureau, 1936; U.S. Centers for Disease Control, 2001.

0

10

20

30

40

50

60

70

80

90

100

1009080706050403020100

1901

Percent surviving

1998

Age

The pace of epidemiologic changein East and Southeast Asian nationsis now especially rapid. In the caseof Singapore, where life expectancyat birth rose 30 years in little over ageneration (from 40 years in 1948to 70 years in the late-1970s), theshare of cardiovascular deaths rosefrom 5 to 32 percent of all deaths,while deaths due to infectious dis-eases declined from 40 to 12 per-cent. Data from Taiwan (Table 4-1)exemplify the typical shift in causesof death; the infectious and para-sitic diseases that dominatedTaiwanese mortality in the mid-1950s have given way to chronicand degenerative diseases. By1976, cerebrovascular disease andcancers had become the leadingcauses of death. The situation inthe 1996 was similar to that in1976, except that the relativeimportance of diabetes had risensubstantially while tuberculosis wasno longer a major killer. Althoughreliable data for much of theremainder of Asia and for Africa arelacking, scattered evidence sug-gests the increasing importance ofchronic disease patterns in adultpopulations.

DOES LONGER LIFE EQUAL BETTER LIFE?

Chapter 3 pointed out that continu-al increases in life expectancy, espe-cially at older ages, have been thenorm in most countries worldwide.As individuals live longer, the quali-ty of that longer life becomes a cen-tral issue for both personal andsocial well-being. Are we livinghealthier� as well as longer lives, or


1 “Health” is a relative and continually devel-oping concept which “reflects on the one handthe progress made within the health sciencesand on the other hand the meanings, valuesand prejudices related to health in differentsociocultural contexts.” (Heikkinen 1998; seethis source for a useful discussion of the differ-ent orientations toward health that have beenadopted in the health sciences).

are we spending an increasing profound impact on national health,portion of our older years with dis- retirement, and family systems, andabilities, mental disorders, and in ill particularly on the demand for health? In aging societies, the long-term care. In the future, healthanswer to this question will have a expectancy will come to be as

Figure 4-2.

Proportion of All Deaths Occurring at Ages 65 and Above in 20 Countries: Circa 1995

Source: Pan American Health Organization, 1998.

Nicaragua

Guyana

Venezuela

Colombia

Bahamas

Ecuador

Brazil

Suriname

Mexico

Paraguay

Costa Rica

Trinidad & Tobago

Saint Lucia

Chile

Argentina

Puerto Rico

Cuba

United States

Canada

Barbados

(Percent)

34

75

75

73

67

62

62

61

5957

56

49

45

45

4343

42

42

41

37

Table 4-1.Rank Order of the Ten Leading Causes of Death in Taiwan:1956, 1976, and 1996

Order 1956 1976 1996

1 . . . . . . .2 . . . . . . .3 . . . . . . .4 . . . . . . .5 . . . . . . .6 . . . . . . .7 . . . . . . .8 . . . . . . .9 . . . . . . .10 . . . . . .

GDEC1

PneumoniaTuberculosisPerinatal conditionsVascular lesions of CNS2

Heart diseaseMalignant neoplasmsNephritis/nephrosisBronchitisStomach/duodenum ulcer

Cerebrovascular diseaseMalignant neoplasmsAccidentsHeart diseasePneumoniaTuberculosisCirrhosis of the liverBronchitis3

Hypertensive diseaseNephritis/nephrosis ulcer

Malignant neoplasmsCerebrovascular diseaseAccidentsHeart diseaseDiabetes mellitusCirrhosis/chronic liver diseaseNephritis/nephrosisPneumoniaHypertensive diseaseBronchitis3

1Includes gastritis, duodenitis, enteritis, and colitis (except diarrhoea of newborns).2CNS refers to the central nervous system.3Includes emphysema and asthma.

Source: Taiwan Department of Health, 1997.

important a measure as lifeexpectancy is today.

Research into patterns of change inmortality, sickness, and disabilityhas suggested that these three fac-tors do not necessarily evolve in asimilar fashion. A four-countrystudy (Riley, 1990) notes that inJapan, the United States, and Britain,mortality decreased and sickness(morbidity) increased, while inHungary, mortality increased andsickness decreased.2 Discrepanciesbetween the trends in mortality,morbidity, and disability have


2 The author’s broader review of historicaldata concludes that the relationship betweenfalling sick and dying from sickness has shiftedover time, and that the link between death andhealth risks has been unstable rather than sta-ble across time. The risk of being sick hasincreased as a result of various obvious andnon-obvious factors — among them earlier andbetter detection of sickness, declining mortality,and rising real income — which themselvesconstitute valuable human achievements. Theimplication is that protracted sickness is abyproduct of such achievements.

generated competing theories ofhealth change, several of which maybe characterized as: a pandemic ofchronic disease and disability(Gruenberg, 1977; Kramer, 1980); acompression of morbidity (Fries,1990); dynamic equilibrium(Manton, 1982); and the postpone-ment of all morbid events to olderages (Strehler, 1975). The WorldHealth Organization has proposed ageneral model of health transitionthat distinguishes between total sur-vival, disability-free survival, andsurvival without disabling chronicdisease. In other words, it is desir-able to quantitatively disaggregatelife expectancy into different healthstates to better understand the rela-tive health of populations. Thus, ageneral survival curve such as thatin Figure 4-1 can be partitioned intodifferent categories that indicateoverall survival, survival without dis-ability, and survival without disease.

An application of this model to datafrom France (Robine, Mormiche, andCambois, 1996) shows that theincrease in total survival between1981 and 1991 was generally con-sistent with the increase in disability-free life expectancy, whereas sur-vival without chronic diseaseshowed little change (Figure 4-3).In this case, the differing trajecto-ries of disability and morbidity maybe interpreted as support for thetheory of dynamic equilibrium,which says that increases in overalllife expectancy are driven in part bya reduction in the rate of progres-sion of chronic diseases.

HEALTHY LIFE EXPECTANCY

Since the early 1970s, research hasbeen moving toward the develop-ment of health indexes that takeinto account not only mortality butalso various gradations of ill health.As of 1998, 49 nations had esti-mates of healthy life expectancy,3

an indicator that attempts to inte-grate into a single index the mortal-ity and morbidity conditions of apopulation. Most estimates ofhealthy life expectancy are derivedfrom calculations of disability-freelife expectancy using a methodolo-gy pioneered by Sullivan (1971),which employs cross-sectionalprevalence data but may produceresults that underestimate temporaltrends in a given population.Recognizing that these earlier com-putational approaches could notcapture the full dynamic nature ofdisability, multistate models havebeen developed to incorporateprocesses such as recovery and

3 The concept of healthy life expectancy astypically used refers to expectancy without limi-tations of function that may be the conse-quence of one or more chronic disease condi-tions. The concept is sometimes called “activelife expectancy” or “disability-free life expectan-cy,” to avoid the implication that “healthy”means “absence of disease.”

Figure 4-3.

Survival Without Disease and Survival Without Disability for French Females: 1981 and 1991

Source: Robine, Mormiche, and Cambois, 1996.

0

10

20

30

40

50

60

70

80

90

100

1009080706050403020100

Percent

Total survival in 1981 Total survival in 1991Survival without disability in 1981Survival without disability in 1991Survival without disease in 1981Survival without disease in 1991

Age

rehabilitation into the calculations(see, e.g., Manton and Stallard,1988; Rogers, Rogers, and Belanger,1990). These latter models, howev-er, require longitudinal data whichcurrently are unavailable in mostnations. To date, chronologicalseries are available only for somedeveloped nations.

In recent years, researchers havebeen working toward developingintegrated, comparable measuresof healthy life expectancy(Verbrugge, 1997). Presently, how-ever, it remains impossible tostrictly compare estimates amongnations, due both to different com-putational methods and, moreimportantly, to differences in con-cepts and definitions that definethe basic data. There are impor-tant but not-widely-appreciateddistinctions between impairments,disabilities, and handicaps that canlead to different measures ofhealth status (Chamie, 1989).Because “disability” is defined inmany ways, national estimates ofdisability vary enormously. Forexample, a compilation by theUnited Nations (1990a) showednational crude disability rates forthe total population ranging fromless than half a percent in severaldeveloping countries (Peru, Egypt,Pakistan, Sri Lanka) to nearly 21 percent in Austria. Perhaps themost commonly-used measure-ment tools are scales which assessthe ability of individuals to per-form activities of daily living(ADLs) such as eating, toiletting,and ambulation, as well as instru-mental activities of daily living(IADLs) such as shopping andusing transportation. These meas-ures originated in industrializedsocieties where debate has cen-tered on long-term care systems


and individuals’ ability to functionin everyday life.4

4 ADL measures vary along several dimen-sions, including the number of activities consid-ered and the degree of independence in per-forming physical activities. ADLs do not coverall aspects of disability, however, and are notsufficient by themselves to estimate the needfor long-term care. Some older people havecognitive impairments not measured by ADLlimitations, which may or may not be capturedby IADL measures. And, of course, there aremany questions regarding the validity andapplicability of such measures in different cul-tural settings.

FEMALE ADVANTAGE IN LIFEEXPECTANCY PARTIALLYOFFSET BY DISABILITY

In spite of cross-national compara-bility problems, several generalobservations seem warranted. Forindividuals reaching age 65, healthexpectancy varies more thanremaining life expectancy. Oneexamination (Kinsella and Taeuber,1993) of REVES data (See Box 4-1)showed that the range of lifeexpectancy at age 65 varied byabout 12 percent among developed

Box 4-1.Network on Health Expectancy

To facilitate and promote analyses of health expectancy, an internationalnetwork (REVES, the French acronym for Network on Health Expectancyand Disability Process) was formed in 1989 to bring together researchersconcerned with the measurement of changes and inequalities in healthstatus, not only within but among nations. REVES has produced numer-ous documents and bibliographies of relevant materials, including a sta-tistical yearbook that includes existing estimates of health expectancy invarious countries. Further information may be obtained from Jean-MarieRobine, Network Coordinator, INSERM Equipe Demographie et Sante,Centre Val d’Aurelle, 34298 Montpellier Cedex 5, France.

Figure 4-4.

Portion of Old Age Lived Without Severe Disability: Data From the Early 1990s

Note: Figures refer to the percent of a person's life, after reaching age 65, that she or he might expect to live without needing significant help (personal care) with at least one major activity of daily living. Source: Jacobzone, 1999.

United Kingdom

Japan

France

Canada

Australia

(Percent) Male Female

93

85

85

94

92

94

79

78

90

87

countries for both men and women. spend a slightly greater proportionHowever, the percent of this time of their remaining years in a severe-spent in “good health” (free of prob- ly disabled state relative to elderlylems with personal and instrumen- men, thus negating some of thetal activities of daily living) had a potential benefit of their higher lifemuch wider range, from 45 to more expectancy (Figure 4-4). Otherthan 80 for males, and from 37 to studies of gender differences in the76 for females (these figures incidence of disabling conditions atexclude apparent outlier estimates older ages support this contentionwhich would widen the ranges even (Heikkinen, Jokela, and Jylha, 1996;further). For men in developing Dunlop, Hughes, and Manheim,countries, the estimated range of 1997; Robine and Romieu, 1998). remaining life expectancy at age 65

DEVELOPED-COUNTRYwas 12 to 15 years. However, theDISABILITY RATES AT OLDERestimated percent of remainingAGE SEEN TO BE DECLINING

years spent in relative health variedfrom less than 60 to 88 percent. In nations where time series esti-

For elderly women, the variation in mates of health expectancy are

life expectancy was 28 percent, available (e.g., Canada, the United

while the range of healthy remain- States, Australia, England/Wales),

ing life was 50 to 87 percent. the general view in the 1980s wasone of uncertainty regarding the

Available but geographically limited relationship between rising lifedata from the early 1990s suggest a expectancies and trends in healthfurther tentative statement: women expectancies. One comprehensivereaching age 65 can expect to review of data in the United States

(Freedman and Soldo, 1994) founddeclines in less-severe disability(i.e., in IADLs) during the 1980s.Data from Australia, on the otherhand, revealed that the increase inyears of disability between 1981and 1988 was greater than theoverall increase in life expectancy.Data for Canada and Finland sug-gest that changes in disability-freelife expectancy have been andremain stagnant (Robine andRomieu, 1998). Researchers positeda number of potential factors —other than actual increases inchronic disease incidence and meas-urement error — which might havecontributed to stagnation ordeclines in healthy life expectancy,including increased survival ofchronically ill individuals due toimprovements in medical care, earli-er diagnosis or treatment of chronicdiseases, greater social awarenessof disease and disability, earlieradjustment to chronic conditionsdue to improved pension and healthcare/delivery systems, and risingexpectations of what constitutesgood health or normal functioning(Mathers, 1991; Verbrugge, 1989).

More recent data and rigorousanalyses, however, now stronglysuggest that rates of disability in anumber of developed countries aredeclining. In the United States,researchers (Manton, Corder, andStallard, 1997) used data from the1982, 1984, 1989 and 1994rounds of the U.S. National LongTerm Care Survey to demonstratethat the disability rate among peo-ple aged 65 and over declined overthe 12-year period, such that therewere 1.2 million fewer disabledolder people in 1994 than wouldhave been the case if the 1982rate had not changed (Figure 4-5).Five other U.S. surveys, while vary-ing in content and nature


Figure 4-5.

Number of Chronically Disabled People Aged 65 and Over in the United States: 1982 to 1996

Source: Manton, Corder, and Stallard, 1997.

0

2

4

6

8

10

1996199419891982

Millions

Based on declines in chronic disabilityrate occurring since 1982

If disability rate did not changesince 1982

(e.g., both longitudinal and cross-sectional), have yielded findingsthat support a temporal decline.Likewise, a U.S. study of changesbetween 1982 and 1993 in self-reported ability to work found sig-nificant improvement among bothmen and women who were in theirsixties (Crimmins, Reynolds, andSaito, 1999). Another U.S. study(Freedman and Martin, 1998) ofthe effect of changes in living envi-ronments, device use, and surveydesign on functional ability amongnoninstitutionalized people aged50 and over concludes that thesechanges alone could not accountcompletely for improved function-ing, and that there has indeedbeen some improvement in under-lying physiological capability.Increased levels of education havebeen identified as a potentiallypowerful factor influencing disabil-ity decline in the United States.

A review of trend data from nineother developed countries plusTaiwan concludes that, with a fewexceptions by gender, disability isdeclining among the elderly else-where as well (Waidmann andManton, 1998), as indicated by theFrench data in Figure 4-3.Researchers increasingly have dis-aggregated disability into more-severe versus less-severe cate-gories, and the current consensusin developed countries is that theoverall decline in disability is prima-rily the result of decreases in themore-severe forms (Robine andRomieu, 1998). Freedman, Aykan,and Martin (2001), for example,have recently demonstrated adecline between 1993 and 1998 insevere cognitive impairment amongthe noninstitutionalized populationaged 80 and over in the UnitedStates. Such trends, if sustained,

obviously have substantial implica-tions for public and private healthprograms and expenditures, andpossibly for the conceptualizationand definition of disability itself.5

Many countries with aging popula-tions now recognize the need forlongitudinal surveys as a means ofunderstanding adult health pat-terns, transitions to and from differ-ent health statuses, and how to dif-ferentiate between morbidity andaging per se (Svanborg, 1996).While such survey efforts involvesubstantial economic investment,the potential cost savings in policydesign and implementation wouldseem to dwarf the initial expense.And as various national longitudinalanalyses expand, both geographi-cally and in terms of specific dis-abling conditions, all health sys-tems stand to benefit from morecomprehensive comparisons andthe resultant implications for pro-gram priorities.

DEVELOPING-COUNTRYDISABILITY BURDEN LIKELY TOINCREASE AS POPULATIONSAGE

Two decades ago, the World HealthOrganization noted a distinction inprominent causes of disabilitybetween developed and developingcountries. In the latter, disabilitywas said to stem primarily frommalnutrition, communicable dis-eases, accidents, and congenitalconditions. In industrialized coun-tries disability resulted largelyfrom the chronic diseases dis-cussed earlier — cardiovasculardisease, arthritis, mental illness,and metabolic disorders, as well as


5 For a description of changes and paradigmshifts in disability policy in certain developedcountries, see Kalisch, Aman, and Buchele,1998.

accidents and the consequences ofdrug and alcohol abuse. Aseconomies in developing countriesexpand and the demographic andepidemiologic pictures change, wemight expect to see relatedchanges in the nature and preva-lence of various disabilities.

Numbers of disabled people arealmost certain to increase as a cor-relate of sheer population growth.Figure 4-6 illustrates the applica-tion of empirical gross disabilityrates to the projected populationof the Philippines. This simplisticexample assumes that disabilityrates for men and women as meas-ured in 1980 will remain constantin the future. Even with no provi-sion for higher rates of disabilityas the population ages, the project-ed absolute increases are alarmingin terms of future service and carerequirements.

ESTIMATING THE BURDEN OF DISEASE

A major ongoing effort to under-stand and predict the effect of epi-demiologic change is the GlobalBurden of Disease Project under-taken jointly by the World HealthOrganization, Harvard University,and the World Bank. Using a com-putational (and controversial; see,e.g., Black and McLarty, 1996;Cohen, 2000) concept known asDisability-Adjusted Life Years(DALYs), this study attempts tomeasure global, regional, andcountry-specific disease burdens ina baseline year, and to project suchburdens into the future. Figure 4-7highlights the change in the esti-mated (1990) and projected (2020)rank order of disease burden forthe ten leading disease categorieson a global basis. In addition tounderscoring the expected shift

from communicable to non-communicable disease patterns(largely driven by the changing sit-uation in developing countries;Murray and Lopez, 1997), thisstudy raises specific warning flagsfor many countries in terms of alikely increase in disease burdendue to neuro-psychiatric conditionsand accidents. Among the manyresults, several stand out: (1) theprojected prominence of tobaccouse vis-a-vis mortality (as men-tioned in Chapter 3) and throughvarious disease vectors, with theexpectation that tobacco will killmore people than any single dis-ease by 2020; (2) the concentra-tion of disease burden in certaindeveloping regions. For example,the inhabitants of India and Sub-Saharan Africa were estimated tobear more than 40 percent of theworld’s disease burden in 1990,while constituting only one-fourthof the world’s population. Thestudy also points out the fallacythat noncommunicable diseasesare necessarily related to affluence;the likelihood of dying from a non-communicable disease amongadults under age 70 in both Indiaand Sub-Saharan Africa is greaterthan in Western Europe; and (3) thevastly underestimated importanceof mental illnesses as major andincreasing sources of disease bur-den, which implies significantlong-term care challenges in agingsocieties (Murray and Lopez,1996).


Figure 4-6.

Projected Numbers of Disabled Males in the Philippines by Age: 1991 and 2020


Thousands

1991 2020

0

100

200

300

400

500

600

700

75+65-7455-6445-5435-4425-3415-245-140-4

Figure 4-7.

Change in Rank Order of Disease Burden for Top Ten Leading Causes in the World: 1990 and 2020

Source: Murray and Lopez, 1996.

(Disease burden measured in disability-adjusted life years)

1990 2020

Rank Disease or injury Disease or injury

1 Lower respiratory infections Ischemic heart disease2 Diarrhoeal diseases Unipolar major depression3 Conditions arising during Road traffic accidents

the perinatal period4 Unipolar major depression Cerebrovascular disease5 Ischemic heart disease Chronic obstructive pulmonary disease6 Cerebrovascular disease Lower respiratory infections7 Tuberculosis Tuberculosis8 Measles War9 Road traffic accidents Diarrhoeal diseases

10 Congenital anomalies HIV


Figure 4-8.

Share of Population Versus Health Expenditureby Age in Nine Countries: 1993

Source: OECD, 1997.

75+

65+

<65

75+

65+

<65

75+

65+

<65

75+

65+

<65

75+

65+

<65

Australia

Finland

Germany

New Zealand

Portugal

88

12

4

86

14

6

85

15

6

89

11

5

86

14

5

66

34

20

62

38

22

68

32

16

67

33

21

64

36

19

Population Health expenditure

Percent of total

75+

65+

<65

75+

65+

<65

75+

65+

<65

75+

65+

<65

Sweden

Switzerland

United Kingdom (England)

United States

21

82

18

8

86

14

6

84

16

7

87

13

5

62

38

21

60

40

26

58

42

27

63

37

AGING INCREASES HEALTH is included in public health schemesCARE COSTS (e.g., Germany), per capita expendi-

tures for people aged 65 and overPopulation aging might be expectedmay be two to three times higherto increase costs of health care inthan those for younger people; inmost societies because healthcountries with more inclusive long-expenditures by and for older ageterm care coverage (e.g., Australiagroups tend to be proportionallyand Finland), the ratio is four timesgreater than their population sharehigher (OECD, 1997). (Figure 4-8). This expectation

applies especially to nations where Although the picture of rising healthacute care and institutional (long- care costs with age is accurate in aterm care) services are widely avail- general sense, disaggregation ofable. Cross-national comparative data by age shows some surprisingdata on health care expenditures by facets. A large fraction of healthage are relatively uncommon, but care costs associated with advanc-ongoing work by the Organization ing age is incurred in the periodfor Economic Co-Operation and just prior to death, and since anDevelopment has begun to docu- increasing proportion of people arement age-specific differentials. living to very old age, overall healthTable 4-2 shows that per capita care costs rise with age.health expenditures for people aged Treatments to prolong life have65 and over are uniformly higher made once-certain death much lessthan for the nonelderly, and that certain, but there is some indicationthis difference varies by country. that health care costs taper off atMuch of the between-country differ- very old ages (OECD, 1998b), sug-ence may be attributed to variations gesting that life may be prolongedin program coverage. In nations up to a point but that treatment iswhere relatively little long-term care not desired indefinitely. Likewise,

among noninstitutionalized elderly,per capita health expenditure oftenpeaks at ages 75 to 79 and declinesthereafter. Costs per service (suchas hospital stays and medicine pre-scriptions) for older people are lessthan for the population as a whole,although usage rates for older peo-ple are much higher and hence theper capita costs are higher (OECD,1997). Governments and interna-tional organizations are now recog-nizing the need for cost-of-illnessstudies on age-related diseases, inpart to anticipate the likely burdenof increasingly-prevalent and expen-sive chronic conditions (of whichAlzheimer’s disease may be themost costly), and in part to under-stand the potentially salubriouseffects that may accrue to futuregenerations due to higher levels ofeducation and access to informationabout healthier lifestyle behaviors.

EARLY-LIFE CONDITIONSAFFECT ADULT HEALTH

The last decade has seen a rapidlygrowing interest in examining adulthealth outcomes from a life-courseperspective. Researchers increas-ingly suggest that many negativehealth conditions in adulthood stemfrom risks established early in life(Elo and Preston, 1992). Some(notably, Barker, 1995) argue thatadult health has a fetal origin,wherein nourishment in utero andduring infancy has a direct bearingon the development of risk factorsfor adulthood diseases (especiallycardiovascular diseases). Childhoodinfections may have long-termeffects on adult mortality. A WorldHealth Organization report statesunequivocally that slow growth andlack of emotional support in prena-tal life and early childhood reducephysical, cognitive, and emotionalfunctioning in later years (Wilkinsonand Marmot, 1998), as do certain


Table 4-2.Relative Per Capita Health Expenditure by Age Group in 12Countries: Circa 1993(0-64 = 1.0)

Country 65-74 65+ 75+

Australia . . . . . . . . . . . . . . . . . .Finland. . . . . . . . . . . . . . . . . . . .France . . . . . . . . . . . . . . . . . . . .Germany . . . . . . . . . . . . . . . . . .Japan . . . . . . . . . . . . . . . . . . . . .Netherlands . . . . . . . . . . . . . . .New Zealand . . . . . . . . . . . . . .Portugal . . . . . . . . . . . . . . . . . . .Sweden . . . . . . . . . . . . . . . . . . .Switzerland . . . . . . . . . . . . . . . .United Kingdom (England). . .United States . . . . . . . . . . . . . .

2.82.8

12.22.3

43.1(NA)

2.31.42.32.62.53.1

4.04.0

23.02.74.84.43.91.72.84.03.94.2

6.05.5

33.73.2

35.7(NA)

6.22.13.45.75.65.2

NA Not available.

1Refers to ages 60-69.2Refers to ages 60+.3Refers to ages 70+.4Refers to ages 65-69.

Note: Data are relative to the leis set at 1.0.

Source: OECD, 1997.

vel of per capita spending for people aged 0-64, which

parental behaviors (particularlysmoking and alcohol consumption)and socioeconomic circumstances(e.g., poverty). Parental divorce hasbeen linked to decreased longevityof children (Schwartz et al., 1995).

While it seems intuitive that child-hood conditions should affect adultdevelopment and health outcomes,separating cohort effects from peri-od effects (e.g., from changing liv-ing conditions) is empirically diffi-cult. Indeed, some evidencesuggests that current conditionsmay be more important than early-life conditions; Kannisto (1996) hasfound period effects to be muchmore significant than cohort effectson oldest-old mortality (i.e., afterage 80). And in a study of cohortsborn just before, during, and justafter a severe famine in Finland inthe mid-1860s, the researchersfound no major differences in later-life survival; the extreme nutritionaldeprivation in utero and duringinfancy appeared not to translateinto higher adult mortality risks(Kannisto, Christensen, and Vaupel,1997). Such findings are likely tostimulate considerable futureresearch to explore the linkagesbetween lingering effects of early-life and survival at advanced ages(Vaupel, 1997).

SOCIOECONOMIC CORRELATESOF MORTALITY AND HEALTH

If early-life factors affect futurehealth and survival, then socioeco-nomic differences in childhood andthroughout life are likely to play anintrinsic role. A diverse and long-standing literature from the

industrialized world6 has identifieda number of socioeconomic factorsthat affect health and longevity:people with higher education tendto live longer (Kitigawa and Hauser,1973); being married encourageshealthier behaviors in U.S. adults,including people in old age (relativeto other marital statuses), and theeffects may be greater for oldermen than for older women (Schoneand Weinick, 1998); there are cleargradients in the United Kingdom inboth mortality and health when bro-ken down by social class, i.e., high-er social/occupational class is relat-ed to better health and loweredmortality risks (Devis, 1993;Wilkinson and Marmot, 1998); andamong the oldest old in Sweden,former white-collar workers hadbetter physical functioning than for-mer blue-collar workers (Parker,Thorslund, and Lundberg, 1994). Inthe United States (Crimmins,Hayward, and Saito, 1996) and inseveral European countries (Robineand Romieu, 1998), socioeconomicconditions more strongly affectfunctional change than mortality,which means that socioeconomicdifferences in active or healthy lifeexpectancy are greater than thosein total life expectancy. Such find-ings might be expected to haveimplications for the future healthstatus of elderly populations. For


6 Research on socioeconomic correlates ofmortality and health in developing countries isstill sparse. Wu and Rudkin (2000) found thatlower socioeconomic status was associatedwith poorer health among Malaysians aged 50and over, and that this association held for allthree major ethnic groups (Malay, Chinese, andIndian). Liang et al. (2000) have found evi-dence of a socioeconomic gradient in old-agemortality in China, but they note that there aremajor differences between developed anddeveloping countries in terms of major healthparameters, and that much more work needs tobe done in validating gradients in Third Worldsettings.

example, if marriage equates withbetter health among olderindividuals, do rising rates ofdivorce and increased proportionsof never-married individuals por-tend poorer average health? Andwhat of other life dimensions? Aconsiderable amount of currentresearch is focused on not onlysocial but also psychological andbiological pathways by whichsocioeconomic status affects health(see, e.g., Adler et al., 1999).

While the weight of existing studiesclearly supports a strong relation-ship between social and economicfactors on the one hand and healthand mortality outcomes on theother, this relationship may not beas strictly predictive as some havesuggested. Research on marital sta-tus and health among the elderly inthe United States, for instance, hasshown that while widowhood is infact associated with poorer health,single women are likely to have bet-ter health outcomes than marriedwomen (Goldman, Korenman, andWeinstein, 1994). One Japanesestudy (Sugisawa, Liang, and Liu,1994) found no significant effect ofmarital status on the risk of dying;however, higher levels of social par-ticipation of older people werestrongly linked to lowered mortalityrisks. Research in Florence, Italyand Tampere, Finland uncovered nosystematic association betweenfunctional ability levels and educa-tion/previous occupation(Heikkinen, Jokela, and Jylha, 1996).In a study of nine industrializednations, differences in mortality byeducational level were found to befairly small in the Netherlands andthree Scandinavian nations, but

much more substantial in larger higher mortality in Northern results point to the importance ofcountries such as the United States, European countries, but no such understanding population diversityFrance, and Italy. The authors sug- relationship in France, Switzerland, within countries, and suggest thatgest that between-country differ- and Mediterranean nations (Kunst et policy planners pay particular atten-ences may be related to different al., 1999). Another multicountry tion to socioeconomic differencessocial and economic policies. A study of income and mortality by gender and among subgroups12-country study of occupational implies that the effect of income on when developing interventionclass and ischemic heart disease mortality is largely determined by strategies (see Sacker et al., 2001mortality found the expected rela- the distribution of income within a and National Research Council,tionship between lower class and given nation (Duleep, 1995). Such 2001 for further discussion).



CHAPTER 5.

Urban and Rural Dimensions

Urbanization is one of the most economic and political changes. both sending and receiving areas.significant population trends of the Closed national economies and Definitions of urban and rural resi-last 50 years. Though we may trading blocs have given way to dence often differ greatly from onethink of cities as synonymous with open economies that increasingly country to the next, which compli-historical development, not until the are international in scope. In gener- cates global and regional discus-nineteenth century did substantial al, the most rapidly-growing sions of urbanization. The view ofportions of national populations live economies since 1950 also are the United Nations has been thatand work in large cities, and only in those with the most rapid increase “differences in definition may reflectcertain parts of the world. In 1900, in their levels of urbanization. The differences in the characteristic fea-about 14 percent of the world’s world’s largest cities tend to be con- tures of urban and rural settlementspopulation lived in cities (United centrated in the world’s largest considered most relevant in individ-Nations, 1991), and this percentage economies (United Nations Centre ual countries” (United Nations,was still below 20 by 1950. for Human Settlements, 1996). 1973). In spite of definitional incon-However, the global population of Urbanization is linked to changes in sistencies, the basic questions con-all ages living in urban areas (as the socioeconomic profile of a cerning aging are similar in all soci-defined by each country) more than workforce as workers shift from eties: are the elderly increasinglydoubled between 1950 and 1975, predominantly agricultural pursuits concentrated in particular areas? Ifand increased another 55 percent to industrial employment and then so, what are the implications forfrom 1975 to 1990. By 1995, to services. Clark and Anker (1990) social support and delivery of serv-about 46 percent (2.6 billion) of the have shown that urbanization is ices? For individual cities, doearth’s people lived in urban areas related to decreased participation of changes in age structure bring(United Nations, 1998). Soon after older people in the labor force. In about demands to reorder budgetthe year 2000, the world likely will developed countries, this decrease priorities?have more urban dwellers than accompanies a decline in manufac-

DEVELOPED-COUNTRYrural dwellers. About three-fourths turing employment, an increasedELDERLY ABOUT THREE-of the population in developed prevalence of early retirementFOURTHS URBAN; ONE-THIRD

countries is urban, compared with schemes, and lower levels of educa- IN DEVELOPING COUNTRIESslightly more than one-third in tion and job flexibility among older

In keeping with the worldwide pat-developing countries as a whole. workers relative to younger work-tern of increased urbanization, theHowever, the pace of urbanization ers. In urban areas of developingelderly population has becomeis much faster in the developing nations, the increased importancemore concentrated in urban areasworld. And while the urban growth of the formal sector tends toduring the past 50 years. In devel-rate in most world regions has exclude older workers who find itoped countries as a whole, an esti-begun to decline, some parts of the difficult to compete with better-mated 73 percent of people agedglobe (notably Africa and South educated younger workers. With65 and over lived in urban areas inAsia) are now experiencing peak urbanization come changes in the1990, and this figure is projected torates of urban growth. In spite of family unit and kinship networksreach 80 percent by the year 2015.declining growth rates, the world’s that have both beneficial andIn developing nations, which stillurban population is projected to adverse consequences for the well-are predominantly rural, just overvirtually double between 1995 and being of elderly members.one-third (34 percent) of people2030, reaching a projected level of

Urban growth affects all age groups aged 65 and over were estimated to5.1 billion people (United Nations,of a population. Since urbanization live in urban areas in 1990. This1998).often is driven by youthful migra- proportion is expected to exceed

Twentieth-century trends in urban- tion from rural areas to cities, it one-half by the year 2015 (Unitedization have stemmed from broad influences the age distribution in Nations, 1991).

The elderly of Africa are more likelyto live in rural areas than are theelderly of other regions, eventhough the African population over-all is slightly more urbanized thanthat of the Asia/Oceania region(excluding Japan). The aggregatetrend toward urbanization isstronger in Asia than in Africa, how-ever. Half of the Asia/Oceania eld-erly are projected to live in cities by2015, compared with 42 percent in Africa.

As a region, Latin America and theCaribbean is already highly urban-ized. The proportion of elderly inurban locales is very similar to thatof the developed-country average.Unlike in other developing areas,the elderly in Latin America and theCaribbean have been somewhatmore likely than the general popula-tion to live in cities (Heligman,Chen, and Babakol, 1993).

ELDERLY MORE LIKELY THANNONELDERLY TO LIVE IN RURAL AREAS

Despite the increasingly urbannature of today’s elderly popula-tions, rural areas remain dispropor-tionately elderly in a majority ofcountries. In most nations, this isprimarily the result of the migrationof young adults to urban areas, andto some extent of return migrationof older adults from urban areasback to rural homes. Data for 39countries from the period 1989 to1997 show that the percent of allelderly living in rural areas washigher than the percent of totalpopulation in rural areas in 27 ofthe 39 nations, with no differencein 4 nations (Figure 5-1). Five ofthe eight countries where the elder-ly were less likely than the totalpopulation to live in rural areas arepredominantly-Muslim nations thatwere formerly part of the SovietUnion. Differences in the share of


Figure 5-1.

Percent of Total and Elderly Population Living in Rural Areas in 39 Countries


United States, 1990

New Zealand, 1991

Ecuador, 1990

Chile, 1997

Brazil, 1991

Bolivia, 1992

Uzbekistan, 1989

Ukraine, 1995

Tajikistan, 1993

Russia, 1995

Moldova, 1989

Lithuania, 1996

Latvia, 1996

Krygyzstan, 1997

Kazakhstan, 1996

Georgia, 1993

Estonia, 1996

Belarus, 1997

Azerbaijan, 1989

Armenia, 1992

Sweden, 1990

Norway, 1990

Greece, 1991

France, 1990

Austria, 1991

Turkey, 1990

Thailand, 1990

South Korea, 1995

Philippines, 1990

Malaysia, 1991

Japan, 1995

Indonesia, 1990

China, 1990

Bangladesh, 1991

Zimbabwe, 1992

Zambia, 1990

Tunisia, 1994

South Africa, 1991

Botswana, 1991

Total Aged 65+

Africa

Asia

Europe

Former Soviet Union

Latin America/Other

54

43

39

61

69

70

37

42

85

86

80

74

69

22

49

51

22

81

41

85

76

74

28

54

54

43

84

51

35

26

41

28

17

31

31

49

32

17

32

46

31

30

44

45

66

31

32

53

27

71

32

59

32

45

53

31

51

42

60

33

44

65

32

64

44

52

43

24

15

45

15

25

59

24

17

49

10

25

total versus elderly populationresiding in rural areas are moststriking in Belarus, Bolivia,Botswana, Zambia, and Zimbabwe.

SEX RATIOS OF URBANELDERLY TYPICALLY LESSTHAN 80

An examination of national data for54 countries from the period 1986to 1997 shows that more elderlywomen than elderly men have beenrecorded in urban areas in allexcept eight nations, six of whichare in Africa. Sex ratios (number ofmen per 100 women) for the urbanelderly usually are well below 100(Figure 5-2), and are below 50 inparts of the former Soviet Union.

ELDERLY MEN MORE LIKELYTHAN ELDERLY WOMEN TORESIDE IN RURAL AREAS

Since women live longer than menvirtually everywhere, we mightexpect to see sex ratios of less than100 for the elderly throughout agiven population. Although olderwomen outnumber older men inalmost every nation, the ratio ofolder men to older women general-ly is higher in rural areas than incities. In the rural areas of somecountries — e.g., New Zealand,Paraguay, and Sweden — older menactually outnumber older women.This rural male surplus is seen mostprominently in many countries ofLatin America and the Caribbean,which suggests region-specific pat-terns of gender-specific migrationthat have implications for healthand social security systems in bothrural and urban areas.


Figure 5-2.

Urban Sex Ratios for Persons Aged 65 and Over: 1986 or Later


Uruguay, 1990United States, 1990

Peru, 1993New Zealand, 1991

Mexico, 1995Ecuador, 1990

Costa Rica, 1995Colombia, 1993

Chile, 1997Canada, 1991

Brazil, 1991Bolivia, 1992

Australia, 1986Argentina, 1995

Ukraine, 1995Russia, 1995

Moldova, 1989Lithuania, 1996

Latvia, 1996Georgia, 1993Estonia, 1996Belarus, 1997

Armenia, 1992

Sweden, 1990Poland, 1994

Norway, 1990Hungary, 1995

Greece, 1991France, 1990

Czech Republic, 1994Bulgaria, 1994Austria, 1991

Turkey, 1990Thailand, 1990

South Korea, 1995Singapore, 1990

Philippines, 1990Pakistan, 1990Malaysia, 1991

Japan, 1995Israel, 1994

Indonesia, 1990China, 1990

Bangladesh, 1991

Zimbabwe, 1992Zambia, 1990Tunisia, 1994

Tanzania, 1988South Africa, 1991

Malawi, 1987Kenya, 1989Egypt, 1986

Cote d'Ivoire, 1988Botswana, 1991

(Males per 100 females)

Africa

Asia

Europe

Former Soviet Union

Latin America/Caribbean/Other

67

69106

123106109

7989

99134

108

13786

8276

7080

11377

8155

7577

5177

6162

7359

6657

69

664948

5446

5254

4450

6770

7776

6764

8077

8281

7087

64

Conversely, elderly women tend tobe somewhat more likely than eld-erly men to live in urban areas(Figure 5-3).1 The gender differencein residential concentration proba-bly is related to marital status andhealth. As discussed in Chapter 6,elderly women are much more like-ly than elderly men to be widowed,and also are more likely to havechronic illnesses. One study of theelderly in developed countries(Kinsella and Taeuber, 1993) notedan inverse relationship betweenwidowhood rates and sex ratios inurban areas. Urban residence mayprovide elderly women, especiallywidows, the benefits of closer prox-imity to children and/or to socialand health services.

SUBNATIONAL URBAN/RURALDIFFERENCES IN AGESTRUCTURE MAY BE STRIKING

The profile of aging in subnationalareas may be very different whenexamined in view of urban/rural dif-ferences. In Russia’s 73 oblasts(administrative areas), for example,the rural population of manyoblasts is skewed in favor of olderpeople.2 Figure 5-4 displays the ageand sex distribution of urban ver-sus rural populations in the KurskOblast, located in the CentralChernozem Region borderingUkraine. The pyramid for the ruralpopulation has a particularly oddshape, with people aged 65 andolder accounting for nearly one-fourth of the total population. Incontrast, the urban population ofKursk is 12 percent elderly, about


1 Grewe and Becker (2000), in a preliminaryexamination of within-country migration ratesfor 65 countries with 128 observations fromthe period 1952-1996, also have noted a likelytrend toward disproportionate shares of elderlywomen in urban areas, and of elderly men inrural areas.

2 Although Russia is highly urbanized (over70 percent of the population lives in urbanareas), its rural population remains substantial,numbering approximately 40 million in 1996.

the same as the overall national population. One reason that ruralaverage. The majority of Kursk’s areas have such high proportions inurban population is concentrated in older age groups is out-migration ofthe working ages, which is not true younger people to urban areas inin the rural areas. These pyramids search of work. Out-migration ofalso show disparities in sex compo- young people may leave oldersition. Nearly 31 percent of Kursk’s women and men without the directrural females are aged 65 and older, support of their family. Harsh livingcompared with just 15 percent of conditions and lack of amenities inrural males. The sex ratio for the many rural areas pose additionalrural elderly population is 41 men difficulties for the elderly. In 1996,per 100 women. for instance, official statistics indi-

cate that only 23 percent of Russia’sKursk is not the only Russian oblast

rural population had running waterto have a large proportion of its

in their homes, and only 3 percentrural population, particularly

had indoor toilet facilities. women, in older age groups. Inseveral other oblasts, more than Skewed age structures may presentone-fourth of the rural female popu- problems for certain localities inlation is aged 65 or over. In seven terms of the provision of servicesoblasts, elderly women account for and aid to older people. Skeldon30 percent of the entire rural female (1999) has noted, based on the

Figure 5-3.

Percent of All Elderly Living in Urban Areas by Sex in Ten Countries

13Zimbabwe, 1992

Tunisia, 1994

South Korea, 1995

Colombia, 1993

China, 1990

United States, 1990

Russia, 1995

Poland, 1994

New Zealand, 1991

France, 1990

Developed countries


MaleFemale

68

87

54

69

73

24

67

55

56

16

72

92

57

67

77

24

75

59

61

Source: United Nations Demographic Yearbook, 1996.

experiences of Japan and Korea, the important emerging issues will residents. In countries where theconfluence of overall population revolve around the social conditions youthful influx of rural-to-urbanaging with rural depopulation and of elderly individuals in relatively migrants has slowed in recentstagnation of small and medium- isolated rural areas. decades, many cities may now havesized towns, and suggests that this aging populations (Chesnais, 1991).

NO CLEAR TREND TOWARDpattern will be seen increasingly Conversely, in countries whereDISPROPORTIONATE AGING OFthroughout Asia in the first half of urbanization rates remain high andLARGE CITIES

this century. A similar situation has younger residents continue to gravi-been noted by Golini (2000) with Although rural areas tend to be dis- tate toward cities, one wouldregard to Italy. While there are few proportionately elderly compared expect the proportion of elderly inif any negative national economic with urban areas in general, data cities to be lower than for the coun-consequences associated with this for some large cities reveal a rela- try as a whole. Data for 13 majordevelopment, it seems clear that tively high proportion of elderly cities (Table 5-1), however, do not


Figure 5-4.

Urban and Rural Population in Kursk Oblast: 1996


Urban

Thousands

40 30 20 10

0-45-9

10-1415-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-84

85+

0 10 20 30 40

Rural

40 30 20 10

0-45-9

10-1415-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-84

85+

0 10 20 30 40

Male FemaleAge

lend themselves to a clear interpre-tation of trends. The populations ofBudapest, London, and Moscow arein fact older than their respectivenational averages, but this is notthe case in Berlin, Paris, and Tokyo.Bangkok and Harare are youngerthan Thailand and Zimbabwe as awhole, but a similar relationshipdoes not hold in the Chinese citiesof Beijing and Shanghai, nor inMexico City. In the United States ingeneral, census data from 1960through 1990 indicate that the cen-tral cities of metropolitan areashave, on balance, consistently lostelderly migrants to nonmetropolitanareas (Fuguitt and Beale, 1993).

ARE RURAL ELDERLYDISADVANTAGED?

The exodus of younger people fromthe countryside to cities raises therural proportion of elderly residentsin many countries. As a result, tra-ditional family support systems forthe frail elderly may change.Younger family members living inurban areas are unlikely to providedirect care for distant elders remain-ing in rural areas. At the sametime, younger family members whomove to cities may have improvedfinancial resources that can be usedto help elderly relatives still living inthe rural birthplace.

Quality-of-life issues for older popu-lations in rural versus urban areasare beginning to receive additionalattention as migration streamsincrease and the costs of healthcare and public benefits escalate.Whereas graying rural communitieswere once associated with negativesocioeconomic consequences, morerecent research in developed coun-tries has considered positive resultsthat may stem from increased pro-portions of increasingly affluent eld-erly (Bean et al., 1994). Data from

Wales (Wenger, 1998) suggest that MIGRATION PATTERNS OFrural dwellers are more likely than OLDER PEOPLE NOT WELL

DOCUMENTEDtheir urban counterparts to beinvolved in community and volun- International migration of elderlytary activities. Nevertheless, the people, as noted in Chapter 2, isprovision of health and other sup- not a significant demographic factorportive services to ill and disabled in many countries. Within-countryolder people in rural areas contin- migration, however, may be sub-ues to present special challenges. stantial. One common perceptionPerhaps because of these difficul- of older people is that they tend toties, the percentage of older dis- be much less mobile than youngerabled people remaining in the people, typically “aging in place” incommunity without being institu- communities that have been hometionalized is lower in predominantly for many years. While this may berural areas than in urban areas true in a general sense, various(Suzman, Kinsella, and Myers, national studies suggest that geo-1992). graphical mobility among older


Table 5-1.Percent of Older Population in 13 Cities Compared WithRespective National Average

City YearAge

groupCity

percentCountrypercent

Bangkok,Thailand. . . . . . . . . . . . . . . . . . . . . . . . . .

Beijing,China . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Berlin,Germany . . . . . . . . . . . . . . . . . . . . . . . . . .

Budapest,Hungary. . . . . . . . . . . . . . . . . . . . . . . . . .

Buenos Aires,Argentina . . . . . . . . . . . . . . . . . . . . . . . . .

Harare,Zimbabwe . . . . . . . . . . . . . . . . . . . . . . . .

Greater London,United Kingdom . . . . . . . . . . . . . . . . . . .

Mexico City,Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . .

Moscow,Russia . . . . . . . . . . . . . . . . . . . . . . . . . . .

New York,United States . . . . . . . . . . . . . . . . . . . . .

Paris,France . . . . . . . . . . . . . . . . . . . . . . . . . . .

Shanghai,China . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Tokyo,Japan . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1995

1990

1993

1990

1991

1992

1991

1995

1989

1990

1990

1990

1990

65+

65+

65+

60+

65+

65+

65+

65+

65+

65+

60+

65+

65+

4.2

6.2

13.7

21.5

8.2

1.6

14.4

5.2

12.0

13.0

15.7

10.1

9.4

5.4

5.6

15.1

18.9

8.9

3.3

10.0

4.4

9.6

12.6

19.9

5.6

12.0

Note: Data for Mexico City refer to the Federal District.

Source: Compiled by the U.S. Census Bureau from national statistical volumes.


people is increasing. In the 1970s, more prevalent as levels of adults, there is mounting evidencethe mobility of the Japanese popula- education and retirement income that the movement of older peopletion declined in all age groups with increase. In the United States, the to urban areas is becoming signifi-

the exception of the elderly (Otomo oldest old have been seen to move cant (Myers and Clark, 1991).

and Itoh, 1989). Census data for more frequently than younger elder- There is much less empirical infor-

Canada show that 23 percent of all ly, suggesting that the moves of the mation on the topic of return migra-

people aged 60 and over changed oldest old are related to health tion of older people to rural places

their principal residence at least problems and the need for different of origin. One review of available

once during the 5-year period 1986 living arrangements (Hobbs and data for Africa (Becker, 1991) con-

to 1991. Thirteen of the fifty states Damon, 1996). Recent Canadian cludes that, while return migration

in the United States had net elderly survey data find that older people of older people to their ancestral

inmigration rates of more than 10 moved most often because of the homes is not uncommon, several

per 1,000 elderly population during size of their home (usually opting factors — growing land pressure,

the 1985-90 period, and one out of for a smaller residence), a desire to formalization of rural propertyrights, the increasing viability offive residents of Florida is now aged live in a better neighborhood, or tofamily support for elders in urban65 or older. A “retirement effect,” build/purchase a home (Che-Alfordareas — will dampen the likelihoodi.e., an increase in mobility rates at and Stevenson, 1998). Amongof future return migration. Skeldonages 60 to 64, has been noted in older Canadians with daily activity(1999) notes that, while returnthe United States and the United limitations in 1991, the percentmigration may increase the size ofKingdom (Long, 1992). Refugee who moved in the previous 5 yearsolder rural cohorts and aggravatemovements in Bosnia, Mozambique, was roughly the same as among thesocial support issues, returnand elsewhere have involved vast overall older population (22 per-migrants also may bring with themnumbers of older people (Kalache, cent), but about one-third of thesewealth, knowledge, and other1995) who are often overlooked in people relocated to homes withresources, particularly in the formrelief operations that focus on chil- special health features. A Germanof pension income earned duringdren and young adults. study of motivating factors for eld-years spent in the urban labor mar-erly mobility in the city of

One of the few cross-national stud- ket. Migration from and withinHeidelberg (Oswald, Wahl, and

ies of elderly migration (Rogers, developing countries in general hasGang, 1997) suggests that basic

1988) identified two basic patterns. come to be seen as a strategic fami-needs (e.g., health) were roughly as

One is characterized by amenity- ly decision rather than as an indi-important as “higher-order” needs

motivated, long-distance relocation, vidual decision on the part of youngsuch as privacy.

the other by intracommunity, leavers (Vatuk, 1995). To the extent

assistance-motivated short-distance Information on migration patterns that migration raises family

moves. Available studies in devel- of older people in developing coun- incomes and the ability to reunite

oped countries suggest that the lat- tries is fragmented at best. members, increased movement of

ter are much more common, Although rural-to-urban migration older people may be expected in

although the former may become usually is associated with younger the future.


CHAPTER 6.

Sex Ratios and Marital Status

One common characteristic of pop-ulations throughout the world is thepreponderance of women at olderages. Women are the majority ofthe elderly population in the vastmajority of countries, and theirshare of the population increaseswith age. This gender imbalance atolder ages has many implicationsfor population and individual aging,perhaps the most important ofwhich involve marital status and liv-ing arrangements. As discussedfurther in Chapter 8, family mem-bers are the main source of emo-tional and economic support for theelderly, although in some developedcountries the state has assumed alarger share of the economicresponsibilities.

Marital status strongly affects manyaspects of one’s life. Studies indeveloped countries show that mar-ried people, particularly marriedmen, are healthier and live longerthan their nonmarried counterparts(Goldman, 1993; Hadju, McKee, andBojan, 1995; Waite, 1995; Schoneand Weinick, 1998). Older marriedcouples tend to be more financiallysecure than nonmarried people.Changes in marital status at olderages can affect pension potential,retirement income, and an individ-ual’s social support network; manyolder widowed men, in particular,may lose contact with much of theirsupport network after their wifedies (O’Bryant and Hansson, 1996).In contrast, widowed women tendto maintain their support networkafter the death of a spouse (Scottand Wenger, 1995). Marital statusalso influences one’s living arrange-ments and affects the nature of

caregiving that is readily available male mortality rates is that betweenin case of illness or disability. age 30 and 40, women usually

begin to outnumber men. In mostHIGHER MALE MORTALITY countries, the relative female advan-RESULTS IN GENDER tage increases with successivelyIMBALANCE AT

older age (Figure 6-1).OLDER AGES

The primary reason for the numeri- WORLD WAR II IS STILLcal female advantage at older ages EVIDENT IN SEX COMPOSITION

AT OLDER AGESis the sex differential in mortalitydiscussed in Chapter 3. Although Historical events can play a majormore boys than girls are born, role in shaping the gender composi-males typically have higher mortali- tion at older ages. For instance, thety rates than females. The sex dif- lingering effects of heavy war mor-ferential in mortality begins at birth tality during World War II still can beand continues throughout the life seen in the proportion female atcourse. One outcome of higher older ages in certain countries. In

Figure 6-1.

Percent Female for Older Age Groups: 2000


United States

India

Brazil

Germany

Russia

65-69 70-74 75-79 80+

Age

66

6266

75

80

5358

6774

5659

61

67

49

50

4948

5456

58

Russia, women account for 80 per-cent of the oldest old (aged 80 andolder) and in Germany they repre-sent nearly 74 percent. In con-trast, women account for only two-thirds of the oldest-old populationin Brazil and the United States.

THERE IS GREAT NATIONALDIVERSITY IN SEX RATIOS AMONG ELDERLY

A sex ratio is a common measureused to portray a population’s gen-der composition. A sex ratio is con-ventionally defined as the numberof men per 100 women in a givenpopulation or age category. Sexratios greater than 100 indicatemore men than women, and sexratios under 100 indicate thereverse (i.e., more women thanmen). In most countries of theworld, sex ratios at older ages arebelow 100, in some cases quite abit below (e.g., Russia’s sex ratio is46 men per 100 women aged 65and older). Developed countriestend to have lower sex ratios atolder ages than do developingcountries (Figure 6-2), althoughthere are many exceptions to thisgeneralization. The typical differ-ence between developed and devel-oping countries is explained by sexdifferentials in life expectancies atbirth. As shown in Chapter 3,developed countries tend to havelarger sex differentials in lifeexpectancy at birth than do devel-oping countries, which results ingreater numbers of women thanmen at older ages.

PROJECTED TREND IN SEXRATIO DIFFERS BYDEVELOPMENT STATUS

In the future, sex ratios at olderages are projected to move in oppo-site directions in the aggregate


Figure 6-2.

Sex Ratio for Population 65 Years and Over: 2000 and 2030


Zimbabwe

Turkmenistan

Turkey

Mexico

Kyrgyzstan

India

Guatemala

Brazil

Bangladesh

Argentina

United States

United Kingdom

Ukraine

Sweden

Russia

New Zealand

Italy

France

Canada

Australia

20002030

(Males per 100 females)

Developed countries


78

74

68

70

77

46

73

49

71

71

81

79

74

76

79

58

80

53

80

80

71

119

68

88

103

60

81

86

62

103

75

98

70

81

91

63

71

86

65

58

developed and developing worlds.Between today and 2030, sex ratiosfor the elderly are expected toincrease in many developed coun-tries because the gender gap in lifeexpectancy is projected to narrow(Figure 6-3). In other words, mostdemographers expect that male lifeexpectancies in developed countriesare likely to improve at a fasterpace than female life expectancies.The opposite is anticipated in manydeveloping countries. In view ofthe historical pattern in developednations, sex differentials in develop-ing-country life expectancies areprojected to widen, which will inturn lead to lower future sex ratios.

Regardless of the projected trends,women are expected to make upthe majority of the world’s elderlypopulation (particularly at the old-est ages) well into the next century.Continuing or growing disparities insex ratios mean that many of thechallenges and problems faced bythe elderly of today and tomorroware, in essence, challenges andproblems faced by older women.

Sex ratios at younger ages in somecountries of the world already arequite skewed in favor of women.This imbalance may be due toexcess male mortality at youngages because of wars and otherforms of violence, disease, or todisproportionate out-migration ofyoung men seeking work in othercountries. If mortality is the causeof such severe sex ratios at youngerages, then the implications for theeventual aging of these cohorts isdifferent than if the cause is


Figure 6-3.

Aggregate Sex Ratios for Older Age Groups: 2000 and 2030


81

57

86

6672

45

91

70

80+65-7980+65-79

20002030

Developed countries Developing countries

Table 6-1.Sex Ratios for Population Aged 65 and Over for CountriesWith More Elderly Men Than Women: 2000

Country Sex ratio

Qatar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .United Arab Emirates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Kuwait . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Sudan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Bangladesh. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Saudi Arabia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Iran . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Taiwan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Afghanistan. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Niger . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Oman. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .The Gambia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Eritrea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Yemen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Bahrain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Bhutan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Tunisia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

243226182133119118112113112111111111104104104103103101



Figure 6-4.

Percent Married at Older Ages


75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64

DEVELOPED COUNTRIES

Canada, 1991

Belgium, 1998

United States, 1995

Japan, 1990

Czech Republic, 1991

83

80

67

71

54

24

82

80

65

74

56

23

79

78

68

66

53

25

92

89

74

77

54

21

84

80

60

65

42

14

MaleFemale

75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64


Argentina, 1991

Indonesia, 1990

Chile, 1992

South Korea, 1995

Zimbabwe, 1992

21

79

76

63

61

42

17

90

84

70

55

33

18

74

69

59

57

42

22

94

88

72

66

34

11

90

85

78

60

39


Figure 6-5.

Percent Widowed at Older Ages


75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64

DEVELOPED COUNTRIES

Canada, 1991

Belgium, 1998

United States, 1995

Japan, 1990

Czech Republic, 1991

3

8

22

14

33

64

4

9

27

13

33

67

3

9

22

13

33

65

3

8

24

14

39

75

4

11

33

23

48

77

MaleFemale

75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64

75+

65-74

55-64


Argentina, 1991

Indonesia, 1990

Chile, 1992

South Korea, 1995

Zimbabwe, 1992

73

5

11

25

22

44

70

6

11

22

39

61

76

5

12

26

19

37

60

5

11

28

33

65

88

3

7

14

31

54

migration and the migrants returnto their native country when theyretire (or return for other reasons).

ELDERLY MEN OUTNUMBERELDERLY WOMEN IN SOMECOUNTRIES

While women outnumber men atolder ages in most countries, thereare 18 countries in Asia and Africawhere available data suggest thatthe reverse is true (Table 6-1). Onelikely explanation involves the socialstatus of women versus men in cer-tain cultures. The relatively lownumbers of women at older agesmay reflect past levels of higherfemale than male mortality, whichcould be related to discriminatorytreatment accorded girls and womenthroughout their lifetime. High sexratios at older ages also may be sta-tistical artifacts. That is, women(especially older women) may beundercounted to a greater extentthan men in some national census-es, insofar as men are more likely tointeract with census enumeratorsand may neglect to provide informa-tion on all female household mem-bers. Furthermore, certain concen-trated patterns of male labormigration may affect sex ratios tothe extent that a significant portionof migrants remains in the hostcountry after reaching age 65.

OLDER MEN ARE MARRIED;OLDER WOMEN ARE WIDOWED

Older men are more likely to bemarried and older women are morelikely to be widowed in most coun-tries of the world (Figures 6-4 and6-5). In all but six of the 51 studycountries with data on martial sta-tus, over 70 percent of men aged65 and older were married. Even atages 75 and older, a majority ofmen were married. In contrast,only 30 to 40 percent of women

aged 65 and over were married in 3 percent of men and 31 percent ofmost study countries. Elderly women aged 55 to 64 were wid-women are much more likely to be owed in 1992. At ages 75 and over,widowed. In 32 of the study coun- the respective figures were tries, over half of elderly women are 14 percent of men and 73 percentwidowed. of women. These data are typical of

the pattern seen in both developedFor both men and women, the pro-

and developing countries.portion married decreases witholder age and the proportion wid- The gender difference in marital sta-owed increases. However, gender tus results from a combination ofdifferences in survival and other fac- factors. The first is the aforemen-tors (see below) result in very differ- tioned sex difference in longevity;ent average ages of widowhood/ women simply live longer thanwidowerhood. In the case of men. Secondly, women tend toBelgium in 1998, 82 percent of men marry men older than themselvesaged 55 to 64 were married, com- which, combined with the sex dif-pared with 74 percent of women in ference in life expectancy, increasesthat age group. At ages 75 and the chance that a woman will findover, 65 percent of men were still herself without a spouse in hermarried, compared with only older age. Furthermore, older wid-23 percent of women. The gender owed men have higher remarriagedifference in proportions widowed is rates than older widowed women incorrespondingly pronounced (Figure many countries, often as a function6-6). Data for Zimbabwe show that of cultural norms (Velkoff and


Figure 6-6.

Percent Widowed in Belgium: 1998

Source: Belgium National Institute of Statistics, 1998.

0

20

40

60

80

100

100+90-9480-8470-7460-6450-5440-4430-3420-24

Percent

Age

Female

Male

Kinsella, 1993; Cattell, 1997). The decreased. Some of the change isfact that women are likely to lose attributable to improved joint sur-their spouse has important econom- vival of husbands and wives (Myers,ic consequences for individuals and 1992). In certain countries, somesocieties. A comparison of longitu- of the change can be explained bydinal data from Germany and the the different marital experiences ofUnited States revealed that, birth cohorts. For instance, thealthough the level of poverty is dif- diminishing effects of World War IIferent in the two counties, most can be seen when the widowhoodwomen in both nations experienced rates of older women in Russia area decline in living standards upon compared for 1979 and 1994. Inwidowhood, and many fell into 1979, 72 percent of older women inpoverty as a result of the loss of Russia were widowed while only public/private pension support 58 percent were widowed in 1994.(Hungerford, 2001). By 1994, the cohorts that were

most affected by the war were agedELDERLY MORE LIKELY TO BE 75 and older. MARRIED THAN IN THE PAST

SMALL PROPORTIONS OFOver the last two or three decades,ELDERLY HAVE NEVER MARRIEDthe marital status of the elderly has

changed. In a majority of the study Relatively few elderly in most coun-countries, the proportion of older tries have never married. In moremen and women who are married than half of the study countries, has increased slightly and the pro- 5 percent or less of elderly men andportion who are widowed has 10 percent or less of elderly women

have never married. In someEuropean countries, the largerproportions of elderly women whohave never married may be attribut-able to World War II. Many oftoday’s elderly women were ofprime marriage age soon after thewar, when there was a shortage ofpotential spouses due to wardeaths. Higher-than-average pro-portions of never-married elderlyare found in several Latin Americanand Caribbean nations, which couldbe a function of the prevalence ofconsensual unions. While the cate-gory “consensual union” is widelyused in census tabulations in thesecountries, some people living (orwho have lived) in a consensualunion are likely to report them-selves to be never married.

FUTURE ELDERS MORE LIKELYTO BE DIVORCED

Percentages currently divorcedamong elderly populations tend tobe low. However, this will changein the near future in many countriesas younger cohorts with higher pro-portions of divorced/separated peo-ple move into the ranks of the eld-erly (Gierveld, 2001). For instance,in 1999 in the United States, around9 percent of the elderly weredivorced or separated comparedwith nearly 15 percent of men and19 percent of women aged 55 to64. The proportion divorced/sepa-rated is higher still for the agegroup 45 to 54 (Figure 6-7). Thechanging marital composition of theelderly population as these youngercohorts reach age 65 will affect thenature and types of support servic-es that both families and govern-ments may need to provide, espe-cially with regard to the growingnumber of elderly who lack directfamilial support (Pezzin and Schone,1999).


Figure 6-7.

Percent Divorced and Separated in the United States: 1999


17.6

20.821.7

18.6

9.3

15.8

18.0 17.8

15.1

8.8

65+55-6445-5440-4435-39

MaleFemale

Age group


CHAPTER 7.

Living Arrangements

Living arrangements are affected by those living in the community, the countries of the world, it is nota host of factors including marital chances of institutionalization. surprising to find that the share ofstatus, financial well-being, health older women living alone is higher

Three major observations emergestatus, and family size and struc- than that of men. For elderly men in

from a cross-national comparison ofture, as well as cultural traditions developed countries, the propor-

living arrangements of the elderly.such as kinship patterns, the value tions range from a low of 5 percent

First, women in developed coun-placed upon living independently, in Japan to a high of 25 percent in

tries are much more likely than menthe availability of social services Sweden. Proportions of elderly

to live alone as they age; older menand social support, and the physical women residing singly are univer-

are likely to live in family settings.features of housing stock and local sally higher, reaching half or more

Second, both elderly men andcommunities. On the individual in Denmark, Germany, and Sweden.

women in developing countrieslevel, living arrangements are Percentages in developing countries

usually live with adult children.dynamic, representing both a result tend to be much lower, although

Third, the use of nonfamily institu-of prior events and an antecedent the levels for men and women in

tions for care of the frail elderlyto other outcomes (Van Solinge, some countries (e.g., Argentina,

varies widely around the world.1994). On the societal level, pat- Cyprus) rival those of certainterns of living arrangements among European nations. Again, olderMORE THAN HALF OF ELDERLYthe elderly reflect other characteris- DANISH WOMEN LIVE ALONE women are more likely than oldertics — demographic, economic, and men to live alone; St Lucia and

Table 7-1 presents data from thecultural — which influence the cur- Taiwan are the only exceptions in

1990s on proportions of older peo-rent composition and robustness of Table 7-1.

ple living alone in what are usuallyolder citizens. In turn, living

considered to be private (i.e., nonin- The gender gap for those livingarrangements affect life satisfaction,

stitutional) households. Since alone generally increases with agehealth, and most importantly for

women outlive men in virtually all (Figure 7-1). However, for countries

Table 7-1.Percent of Elderly Population Living Alone: Data From 1990 to 1999

Developed countries Male Female Developing countries Male Female

Australia . . . . . . . . . . . . . . . . . . . . .Canada . . . . . . . . . . . . . . . . . . . . . .Czech Republic . . . . . . . . . . . . . . .Denmark . . . . . . . . . . . . . . . . . . . . .Finland. . . . . . . . . . . . . . . . . . . . . . .France . . . . . . . . . . . . . . . . . . . . . . .Germany . . . . . . . . . . . . . . . . . . . . .Greece. . . . . . . . . . . . . . . . . . . . . . .Ireland . . . . . . . . . . . . . . . . . . . . . . .Japan . . . . . . . . . . . . . . . . . . . . . . . .New Zealand . . . . . . . . . . . . . . . . .Norway . . . . . . . . . . . . . . . . . . . . . .Portugal . . . . . . . . . . . . . . . . . . . . . .Romania . . . . . . . . . . . . . . . . . . . . .Sweden . . . . . . . . . . . . . . . . . . . . . .United States . . . . . . . . . . . . . . . . .

13.714.119.023.319.515.316.9

8.718.9

5.217.821.3

9.412.425.115.1

29.333.747.552.046.540.250.822.827.714.838.044.723.931.749.936.8

Argentina . . . . . . . . . . . . . . . . . . . .Aruba . . . . . . . . . . . . . . . . . . . . . . .Bolivia. . . . . . . . . . . . . . . . . . . . . . .Cyprus . . . . . . . . . . . . . . . . . . . . . .Hong Kong . . . . . . . . . . . . . . . . . .Mexico . . . . . . . . . . . . . . . . . . . . . .Morocco (60+) . . . . . . . . . . . . . . .Philippines(60+) . . . . . . . . . . . . . .South Korea(60+) . . . . . . . . . . . .St. Lucia. . . . . . . . . . . . . . . . . . . . .Taiwan . . . . . . . . . . . . . . . . . . . . . .Thailand(60+) . . . . . . . . . . . . . . . .Vietnam(60+) . . . . . . . . . . . . . . . .

11.212.513.210.611.67.5

11.34.43.1

20.913.0

2.92.5

21.115.415.724.813.214.044.7

6.411.818.9

7.45.58.1

Note: Data for Mexico are for seven cities, and refer to 1989. Data are for household populations aged 65 and over, unless otherwisenoted. Data for Morocco refer to urban areas only.

Sources: Compiled from data in United Nations Demographic Yearbooks (various dates) and national sources.

that disaggregate data at advancedages, the gender difference tends todiminish at very old ages, presum-ably as a result of health and/oreconomic factors that require insti-tutional caretaking, communal liv-ing, or sharing of housing costs.Both numbers and proportions ofelderly living alone have risensharply in developed countriessince the early 1960s, althoughrecent information suggests thatthe rise in proportions might beleveling off in some nations.Everywhere, however, the absolutenumbers are increasing. Figure 7-2illustrates a trend common to mostdeveloped countries, i.e., theincrease has been largely fueled bywomen. Data from the 1996 cen-sus of Canada show more than700,000 elderly women livingalone, a jump of more than 180,000since 1986. The number of elderlywomen living alone grew at anaverage annual rate of 5.4 percentfrom 1961 to 1996, compared witha rate of 1.4 percent for the entireCanadian population. One implica-tion of such change is that, in mostdeveloped countries, women mustanticipate a period of living alone atsome point during their older years.

“ELDERLY-ONLY” HOUSEHOLDSARE INCREASINGLY COMMON

An earlier version of this report(Kinsella and Taeuber, 1993) point-ed out that elderly people livingalone were a significant factor innational household profiles inEurope. In several nations (e.g.,Belgium, Denmark, France, and theUnited Kingdom) in the 1980s,more than 11 percent of all nationalhouseholds consisted of a solitaryindividual aged 65 or over. Themost common living arrangementfor the elderly in Europe was with


Figure 7-1.

Percent of Elderly Living Alone in Germany and the United States by Available Age Groups

Source: National sources.

32

45

66

32

51

61

13 14

24

14

20

36

85+75-8465-7475+70-7465-69

Germany, 1999 United States, 1995

MaleFemale

Age group

Figure 7-2.

Elderly Living Alone in Canada: 1961 to 1996

Source: National sources.

0

200

400

600

800

19961991198619811976197119661961

Thousands

Female

Male

another elderly person in a two- reimbursement payments which dis- national differences in elderly livingperson household. A related calcu- courage institutional living. arrangements in Europe are charac-lation revealed that three out of terized more by diversity than by

MAJORITY OF ELDERLY INevery ten households in a 12-nation similarity. DEVELOPED COUNTRIES LIVEEuropean aggregate contained atWITH OTHER PEOPLE TWO- OR THREE-GENERATIONleast one elderly person.

HOUSEHOLD STILL THEAlthough high proportions of elder-Data from the 1991 census of Great DEVELOPING-COUNTRY NORMly often live alone in developedBritain (for England, Wales, and countries, a majority of those aged In all developing regions of theScotland) are even more striking; 65 and over still live with other world, with the possible exception15 percent of all households in Great people. Data from 13 European of the Caribbean, the most commonBritain consisted of a single pension- nations (Table 7-2) show that the living arrangement for elderly peo-er living alone, while another 10 per- proportion of elderly living with one ple (married or widowed) is withcent of households had two or more other elderly person only (in most children and/or grandchildren.pensioners with no other people cases a spouse) tends to be higher Between 72 and 79 percent of olderpresent. Hence, 25 percent of all than the proportion living singly. (60 and over) respondents in 1984households in the country consisted Between 10 and 14 percent of the World Health Organization surveysof pensioners only. Overall, one- elderly in the 13 nations live with in Malaysia, the Philippines, Fiji, andthird of Britain’s households had at one other person who is less than South Korea lived with childrenleast one resident pensioner. 65 years of age; many of these eld- (Andrews et al., 1986), and similar

erly are likely to be either men liv- results have been observed in coun-In developed countries, the growthing with younger spouses, or wid- tries as diverse as India, Indonesia,in “elderly-only” households may beowed or divorced individuals living Cote d’Ivoire, Singapore, and (atdue in part to changes in social andwith a child. Nations vary greatly in earlier times) six Latin Americaneconomic policies. These include:the proportion of elderly people liv- nations (Kinsella, 1990). Moreincreases in benefits that allow oldering in households of three or more recent data from four Asian nationspeople to live independently of theirpeople, from only 5 to 6 percent in (Figure 7-3) show a persisting pat-children; programs that more easilySweden and Denmark to 35 percent tern. While the levels may appearpermit the conversion of housingor more in Ireland, Greece, Portugal, similar, the broad category of “livingwealth into income; programs thatand Spain. As earlier studies (Wall, with offspring” encompasses aencourage the building of elder-1989; Pampel, 1992) have noted, plethora of specific family andfriendly housing; and revisions in


Table 7-2.Composition of European Households With Elderly Members: Early 1990s

Country

Percent elderly in households with:

One person 65years or over

(1 personhousehold)

Another person Another person65 years or under 65 years Two

over (2 person (2 person otherhousehold) household) persons

Three ormore other

persons

Denmark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Greece . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Spain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .France . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Ireland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Italy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Netherlands. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Austria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Portugal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Finland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Sweden . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .United Kingdom . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Switzerland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

42.417.716.632.126.225.935.535.318.538.441.135.734.0

40.629.431.439.925.331.345.429.433.832.244.440.541.2

11.414.211.311.913.112.711.512.911.912.810.011.912.6

4.115.017.4

9.716.414.75.5

10.214.4

8.93.67.98.1

1.523.723.3

6.518.915.4

2.212.221.3

7.70.93.94.1

Source: Eurostat, 1996.

household types, differing not onlyamong nations but among ethnicgroups within nations. Such diver-sity points to the importance of cul-tural and ideological as well asdemographic factors in the determi-nation of living arrangements ofolder people (Albert and Cattell,1994).

A growing concern in developingcountries is the extent to which thetwin processes of modernizationand urbanization will change tradi-tional family structures (Zhou,2000). Data for most of the devel-oping world generally are insuffi-cient for documenting changes inliving arrangements of the elderly.Although the case of Japan may notseem especially relevant to develop-ing nations, the extended familystructure common to the latter hashistorically been a feature ofJapanese society as well. Timeseries data (Figure 7-4) show thatthe number and proportion ofextended-family households inJapan have been declining, and thatthe proportions of elderly livingalone or with spouse only havebeen increasing.

These trends in Japan have led tothe suggestion (Kamo, 1988) thatthe impact of industrialization hasundermined the indigenous cultureof Japan vis-a-vis the status of itselderly citizens, and set the stagefor the eventual predominance ofthe nuclear family. Related to thisis the notion of “intimacy at a dis-tance” (see, e.g., Stehouwer, 1968;Rowland, 1991). That is, as thefinancial (and to some extenthealth) status of elderly peopleimproves, a larger proportion areable to afford to live alone andchoose to do so in independentdwellings, while at the same timemaintaining close familial contactand exchange supports. A growing

literature relates improvements in normative changes toward individ-social security programs and gen- ualism and personal independenceeral economic welfare to the ability (see, e.g., the discussion and refer-and desire of older persons to ences in Gierveld, 2001). This con-choose independent living arrange- cept has found general currency inments, presumably reflecting a variety of cultural settings,


Figure 7-3.

Percent of People Aged 60 and Over Living With Children in Four Asian Countries: Circa 1996

Sources: Anh et al., 1997; Chan, 1997; Knodel and Chayovan, 1997; and Natividad and Cruz, 1997.

67.4

90.6

69.471.871.9

86.5

72.776.5

Vietnam(Red River Delta)

ThailandSingaporePhilippines

MaleFemale

Figure 7-4.

Living Arrangements of Japanese Elderly: 1960 to 1995

Note: "With kin" includes very small numbers of elderly cohabitating with nonkin. Source: Japan Management and Coordination Agency, cited in Atoh, 1998.

Institution

0 20 40 60 80 100

1995

1985

1975

1960

With kin Elderly couple only

Alone

Percent

although a recent analysis of data lowered fertility, increased geo-from the Indonesian Family Life graphical mobility, and the rapidSurvey (Cameron, 2000) finds little advance in medical technology —evidence that increases in the has led to a steep rise in numbersincome of the elderly, or that of their of institutionalized elderly. Thechildren, lead to a significant change highest rates of institutional use arein traditional family structure. found in many of the world’s oldest

countries, and the absolute num-NUMBERS OF bers of users are expanding even inINSTITUTIONALIZED ELDERLY the face of increasing efforts toRISING

enhance community-based servicesA number of studies (e.g., Manton, and avoid or greatly reduce levelsStallard, and Liu, 1993; Weiner and of institutionalization.Illston, 1995; Leung, 2000) have

In spite of the intense media scruti-documented the direct relationshipny of and controversy surroundingbetween population age-sex struc-institutional residence, the factture, age-sex-specific rates of chron-remains that relatively small propor-ic disease and disability, and thetions of elderly populations resideneed for long-term care. The con-in institutions at any given time.fluence of several macro trends inCross-national comparisons of insti-developed countries — older popu-tutionalized populations are prob-lation age structures, higher inci-lematic due to the absence ofdence of noncommunicable disease,

internationally consistent data, anddifferences between countriesshould be construed as orders ofmagnitude rather then as precisemeasurements. One attempt to col-late reasonably-comparative data onresidential care in the 1990s (OECD,1996) suggests that usage rates fordeveloped countries (Figure 7-5)range from 2 percent in Portugal to9 percent in the Netherlands.1

There is substantial variation in theuse of custodial institutions and inthe mix of long-term care alterna-tives and services (see, e.g., Ribbeet al., 1997; Mechanic andMcAlpine, 2000). One study (Doty,1992) suggests that Japan,Australia, and North America havemade greater relative use of med-ical residential care, while anemphasis on nonmedical facilitieshas been more apparent in Belgium,Sweden, and Switzerland.

In Eastern Europe and parts of theformer Soviet Union, the combina-tion of low fertility and the rapidincrease in oldest-old populationmight be expected to translate intoa growing use of institutional healthcare and maintenance services. Todate, however, available informationindicates that institutionalization ofolder people is not common. InRussia, for instance, the capacity of(number of existing places in) oldpeople’s homes and nursing homesthroughout the former USSR in thelate 1980s was estimated to be


1 Although the percentage of elderly in insti-tutions at any given moment may be relativelylow, on average around 5 percent in developedcountries, an estimated 25 to 30 percent ofpeople who survive to age 65 can expect tospend some time in an institutional settingbefore they die (Sundstrom, 1994). Thus thelongitudinal risk of experiencing institutional-ization is much higher than cross-sectionalrates might suggest. Considerable researchinterest currently is devoted to untangling thedynamics of institutional use, including transi-tions to and from such facilities and the under-lying health conditions that drive the transi-tions.

Figure 7-5.

Percent of Elderly in Residential Care: Early to Mid-1990s

Notes: Canada and Finland: figures represent the midpoint of an estimated range. Japan and the Netherlands: some of the residential care is provided in hospitals. Sources: OECD, 1996; Jacobzone, 1999.

Turkey

Portugal

Spain

Italy

Austria

Ireland

United Kingdom

United States

Japan

Finland

Belgium

France

Norway

New Zealand

Luxembourg

Germany

Canada

Australia

Denmark

Sweden

Netherlands

0.2

8.8

8.7

7.0

6.86.8

6.8

6.8

6.7

6.6

6.56.4

6.4

6.0

5.75.1

5.04.9

3.9

2.9

2.0

between 320,000 (Muzafarov andKurleutov 1994) and 380,000(Bezrukov, 1993); the higher esti-mate represents less than 1.5 per-cent of the USSR population aged65 and over as of 1988. While theaverage Russian view of institution-alization may be extremely negative(Powell, 1991), there does appear tobe an unmet need for institutionalservices. Lengthy waiting lists forinstitutional admission have beenthe norm for many years, and offi-cial time series data for Russiashow a steady rise in the number ofnursing/old people’s homes, fromaround 700 in 1985 to more than900 in 1996. At the same time, thenumber of places in such institu-tions has remained fairly constant,suggesting a downsizing of theaverage facility. Older people livingalone, and especially never-marriedelderly men, are said to be at partic-ularly high risk of institutionaliza-tion. In rural areas of the country,district hospitals frequently serve aslong-term residences for the elderly,for social as well as health reasons(Bezrukov, 1993).

Rates of institutionalization usuallyare very low or negligible in thedeveloping world. In official rheto-ric, at least, the Western model ofinstitutional care for older peopleoften is rejected as culturally inap-propriate (Gibson, 1992). Outsideof Europe and North America, socialtraditions and official decrees of fil-ial and familial responsibility haveobviated, at least until recently,debate about living arrangementsof the elderly. Lately, however, anumber of countries have recog-nized that even if the family retainsmuch of its support function for theelderly, demographic and socioeco-nomic changes will inevitably pro-duce strains. Consequently, manydeveloping nations have adopted

new policies aimed at alleviating octogenarians. More than half ofcurrent and anticipated problems. all Norwegians aged 85 and overLong-term care provision and/or reside in institutions at a givenhomes for the aged have become point in time, as do one-third orincreasingly accepted and common more of this age group in Australiain countries — especially in and New Zealand. In fact, a major-Southeast Asia — where sustained ity of people entering institutionsfertility declines have led to rapid or other types of collectivepopulation aging and reduced the dwellings have reached verynumbers of potential family care- advanced age. Those who enter atgivers (Phillips, 2000; Bartlett and less-advanced ages tend to beWu, 2000). either single or widowed and child-

less, i.e., people who are unlikelyELDERLY WOMEN to have young family members toPREDOMINATE IN rely upon for support (Soldo, 1987).INSTITUTIONAL POPULATIONS

Women and the oldest old, therefore,Institutional use is strongly associ-are disproportionately representedated with increasing age regardlessamong the institutionalized elderlyof national setting (Figure 7-6). In(Figure 7-7). In the United States inmost developed countries, fewer1997, three-fourths of all nursingthan 2 percent of the young oldhome residents were women, and(aged 65 to 69) are in institutions.slightly more than half of all nursingThis level rises fairly slowly untilhome residents were aged 85 orage 80, but many nations experi-older. People in institutions at oneence a sharp increase in institu-point in time, however, do nottionalization rates among


Figure 7-6.

Percent of Elderly in Institutions in Austria and New Zealand: 1991

Source: OECD, 1996.

1.62.4

4.2

8.9

22.2

1.32.4

5.9

14.9

37.7

1.02.0

3.1

5.7

10.7

0.92.3

5.1

9.5

20.8

85+80-8475-7970-7465-6985+80-8475-7970-7465-69

Male Female

AustriaNew Zealand

Age group

necessarily remain there and “age in multiple transitions. Some nationalplace” indefinitely. Many older indi- nursing home systems (e.g., theviduals who enter an institution Netherlands) have well-developedeventually leave, and many make rehabilitative programs which

discharge a high proportion of usersback into the community, while oth-ers systems have relatively limitedrehabilitative services (Ribbe et al.,1997).

NATURE OF INSTITUTIONALUSE HAS CHANGED

Policies toward and practices ofinstitutionalization of older peoplein developed countries havechanged over the past half-century.In the United States and elsewhere,institutionalization in the early1900s was generally associatedwith poverty and/or inability towork. The elderly often werehoused with younger “welfare popu-lations” and were supported largelyby local agencies. By the middle ofthe twentieth century, hospital-based care for the elderly hadbecome more common, at least inthe United States, with financial andoperational control likely to comefrom state governments. Beginningin the 1950s, social policy encour-aged a shift away from hospital usetoward nursing-home use. TheUnited States experienced a rapidexpansion of nursing home capacity(OECD, 1996), with emphasis onproviding for chronic disease andphysical disability needs. Federalfunding assumed greater promi-nence, as did private sources offunding. More recently, the privatelong-term care insurance industryhas grown rapidly, while new formsof home and community-basedservices (e.g., assisted living) haveemerged. With U.S. long-term carecosts doubling each decade since1970 (reaching an annual level of$106 billion in 1995; Stallard,1998), the mix of institutional andhome-based care has been shiftingrapidly toward the latter, especiallyfor the oldest old (Cutler and Meara,1999).


Figure 7-7.

Percent of U.S. Elderly in Nursing Homes by Age: 1973-74, 1985, 1995, and 1997

Source: U.S. Centers for Disease Control, 1999.

PercentMale

PercentFemale

0

5

10

15

20

25

30

1997199519851973-74

0

5

10

15

20

25

30

1997199519851973-74

65-74

75-84

85+

65-74

75-84

85+

Countries in Europe also have been attributed largely to differences in mere fact of elderly coresidenceactive in changing long-term care the organization and financing of with a younger generation(s) tellspolicies and practices in response long-term care as well as differing us little about the quality of intra-to population aging. Heightened sectoral responsibilities for care. household relationships and life sat-spending on institutional care Nations clearly are struggling with isfaction.prompted Great Britain to revamp alternative methods of long-term

Instead of focusing on livinglegislation in the 1990s, transfer- care financing and provision, and it

arrangements per se, attentionring more fiscal control to local gov- is hoped that countries can learn

might better be directed to under-ernments and tightening means- from one another via cross-national

standing the complex set of mecha-tested provisions. Austria instituted research that proceeds from the

nisms and interpersonal relation-a new federal act in 1993 aimed types of efforts now underway in

ships that determine the timing andprimarily at increasing options relat- Europe.

content of support for older per-ed to personal care arrangements

BEYOND LIVING sons. This perspective is summedand supporting individuals in their

ARRANGEMENTS up well by the phrase “functionown homes for as long as possible.

rather than form,” meaning that theGermany, in 1995, unveiled a sys- Living arrangements of older per-

mechanisms and characteristics oftem of universal long-term care sons clearly are an important com-

an individual’s support network areinsurance which features expanded ponent of life, but we should be

much more salient to well-beingbenefits without major changes in careful not to infer too much from

(and to policymaking) than are meremeans-testing. Importantly, the effi- cross-sectional descriptive data on

attributes of who lives with whomcacy of such changes will be moni- residence patterns. We need to be

(Hermalin, 1999). Survey researchtored and evaluated by research aware of how living arrangements

and methodology increasingly areprojects underway in each country change as a function of the growth

focused on the full mapping of(Wolf, 1998). in elderly populations and their

complex kin networks, householdshifting health and kin-availability

As noted above, developed coun- and kin microsimulation techniques,profiles (Palloni, 2000). And as

tries vary enormously in their use and new data-record linkages thatalluded to earlier, the well-being of

and view of institutional residency allow analysts and policymakers toindividuals is not necessarily reflect-

for older citizens. A study (Ribbe et better understand the underlyinged in living arrangements. Living

al., 1997) of nursing homes in ten dynamics of intergenerational trans-alone in old age has sometimes

nations found no apparent relation fers and well-being in old agebeen interpreted as a lack of famil-

between the level of population (Hagestad, 2000; Wolf, 2000).ial and social integration, when in

aging and the number of nursing Chapters 8 and 11 look further atfact it may be indicative of good

home beds. The surprising lack of family and social support for olderhealth, economic well-being, and

cross-national consistency is persons.social connectedness. Likewise, the


Shifts in population age structure and not all working-age people because the relatively large post-generally result in new service actually work or provide direct sup- World War II birth cohorts will stilldemands and economic require- port to elderly family members. be of working age through at leastments. With an increasingly older The statistics discussed in the first 2010. In several nations (notablyage structure comes change in the part of this chapter may be seen as the United Kingdom, the Unitedrelative numbers of people who can rough guides to when we can States, and Russia), the elderly sup-provide support to those who need expect the particular age distribu- port ratio will not change signifi-it. In the early 1980s, Myers and tion of a country to affect the need cantly from 2000 to 2010. SomeNathanson (1982) identified three for distinct types of social services, developed nations, however, areprominent issues regarding popula- housing, and consumer products. aging at a much faster pace.tion and the family: 1) the extent to These data suggest some of the fac- Between 2000 and 2015, the elderlywhich changes in social norms and tors that will shape patterns of support ratio in Denmark is likely toresponsibilities, driven by the secu- social relationships and societal increase 33 percent (from 24 to 32),lar processes of urbanization and expenditures in the coming and the increase in the Czechmodernization, alter traditional decades, but tell us little about the Republic will likely be 36 percentfamilial modes of caring for older changing nature of the health and (22 to 30). Most notably, Japan’speople; 2) the possible social sup- economic resources of the aged in elderly support ratio is expected toport burden resulting from reduced the future. jump 63 percent (from 27 to 44)economic self-sufficiency of aged during the 15-year period.

RAPID RISE IN ELDERLYpeople and the likelihood of height-SUPPORT RATIOS EXPECTED IN From 2015 to 2030, the elderly sup-

ened chronic disease morbidity andDEVELOPED COUNTRIES port ratio will increase by more than

functional impairment related to AFTER 2010 40 percent in several developedlonger life expectancy; and 3) the

Broad changes in a nation’s age nations as the large working-ageways in which countries develop

structure are reflected in changing cohorts begin to retire. In 2030,funding priorities for public care

societal support ratios. These ratios Japan’s elderly support ratio is pro-systems given competing demands

typically indicate the number of jected to be 52 (Figure 8-1). Italy isfor scarce resources.

youth and/or elderly people per 100 likely to have an elderly supportTo gain a broad view of these people aged 20 to 64 years, primary ratio of 49 in 2030, and nearly alldynamics, demographic assess- ages for participation in the labor European countries will have elderlyments of intergenerational support force. A commonly used measure support ratios over 40. Newoften consider various ratios of one of potential social support needs is Zealand has the lowest projectedage group to another. This chapter the elderly support ratio (sometimes ratio (30) among the developedconsiders societal support ratios, called the elderly dependency ratio), nations in this study, with other rela-parent support ratios, and changes defined here as the number of peo- tively low figures seen in the Unitedin kin availability. As seen through- ple aged 65 and over per 100 peo- States and Eastern Europe.out this report, the elderly popula- ple aged 20 to 64 in a given popula-

ELDERLY SUPPORT RATIOS INtion is diverse in terms of its tion. In the coming decades, elderlyMOST DEVELOPING COUNTRIESresources, needs, and abilities. The support ratios will rise in developed TO CHANGE SLOWLY

stereotype of the elderly as a pre- countries as a result of both declin-dominately dependent group that Elderly support ratios are muching fertility and increasing longevity.drains a nation’s economy has erod- lower in developing than in devel-The rise has been and will continueed. Not all elderly require support oped countries, often with ten orto be modest in most countries


CHAPTER 8.

Family and Social Support of Older People

fewer elderly people per 100 peopleaged 20 to 64. Among the 30developing countries in this study,Uruguay had the highest level (24)in 2000, followed by Argentina (19)and Israel (18). Many developingcountries will experience little if anychange in their elderly supportratios from 2000 to 2015, becausethe high-fertility cohorts of the1960s and 1970s will still be underage 65 in 2015. Thailand andSouth Korea stand out as excep-tions as they are expected to expe-rience relatively large increases inthe ratio between 2000 and 2015.In Bangladesh, Kenya, Malawi,Morocco, and Uruguay, on the otherhand, the elderly support ratio isexpected to remain stable between2000 and 2015. In Jamaica andPakistan the elderly support ratio isprojected to decline by 2015, eventhough the absolute numbers ofelderly population are increasing.

In countries where fertility remainshigh or has just recently begun todecline significantly — as in muchof Africa and South Asia — elderlysupport ratios should change littleduring the entire period 2000 to2030. Eastern and SoutheasternAsia and parts of Latin America, onthe other hand, could witness signif-icant change during that time. Theelderly support ratio is projected toat least double between 2000 and2030 in 11 Asian and LatinAmerican study countries, and totriple in South Korea.

YOUTH SUPPORT RATIOS TODECLINE

The working-age population alsoprovides support for young people.


Figure 8-1.

Elderly Support Ratios: 1950 to 2030


Number of people aged 65 and over per 100 people aged 20 to 64Developed countries

Number of people aged 65 and over per 100 people aged 20 to 64Developing countries

0

10

20

30

40

50

60

202520101995198019651950

0

10

20

30

40

50

60

202520101995198019651950

United States

South Korea

Argentina

Egypt

Belgium

Japan

Children outnumber working-age DIVERGENT TOTAL SUPPORTadults in many developing RATIO PATTERNS IN

DEVELOPED VERSUScountries. As a result, youth sup-DEVELOPING COUNTRIES

port ratios — defined here as peo-ple under age 20 per 100 adults The total support ratio (youth plus

aged 20 to 64 years — for 2000 elderly in relation to the working-

were in excess of 100 in several age population) provides a gross

developing countries (mainly in indication of the overall support

Africa). In the developed countries burden on working-age adults. The

in this study, however, youth sup- level of the total support ratio over

port ratios ranged from only 31 in time is pertinent to policymakers,

Italy to 49 in New Zealand. but knowing the balance of old ver-sus young may be more important

In most countries of the world, because supporting the young isyouth support ratios are projected probably less costly than support-to decline between 2000 and 2030. ing the elderly (especially as theIn countries where the present level elderly population itself ages). Withis high, the youth support ratio may the major exception of education,decline by half or more. In Kenya, the costs of young people are bornefor example, the 2000 level of 133 by families more than by govern-is projected to plummet to 61 in ment programs, although some2030. European governments provide the

bulk of support to both young andold alike.

From 2000 to 2015, the total sup-port ratio (TSR) should remain rela-tively stable in most developedcountries as declining numbers ofchildren more than offset growingnumbers of elderly (Figure 8-2).From 2015 to 2030, however,increasing numbers of elderly peo-ple will boost the TSR in all devel-oped nations even though theyouth component may declineslightly. Among the study countries,the proportional gain in the TSRfrom 2015 to 2030 is projected tobe greatest in Russia (30 percent).The United States is projected tohave the highest TSR (87) amongthe developed countries in the year2030, with 7 other developed coun-tries also projected to have TSRs inexcess of 80.

For the foreseeable future in devel-oping countries, major fertilityreductions are likely to outweighgrowing numbers of elderly people.At the same time, the working-agepopulation is increasing. Hence,future TSRs for the vast majority ofdeveloping countries are projectedto be lower than in 2000. Eventhough growth rates for the youthand elderly will be higher than indeveloped countries during thenext three decades, TSRs in devel-oping countries often will be lowerbecause of the massive numbers ofworking-age adults in their popula-tions. Such change may portend awindow of economic opportunityfor developing countries. As theratio of working-age to total popula-tion rises, economies have relativelymore productive units and thereforemore opportunity to grow (otherfactors being equal).


Figure 8-2.

Youth and Elderly Components of the Total Support Ratio: 2000, 2015, and 2030


2030

2015

Philippines, 2000

2030

2015

Uruguay, 2000

2030

2015

France, 2000

2030

2015

Australia, 2000

(Youth ratio: people aged 0 to 19 per 100 people aged 20 to 64; Elderly ratio: people aged 65 and over per 100 people aged 20 to 64)

YouthElderly

13

46

40

40

43

39

38

59

55

50

98

76

60

21

26

37

27

32

44

24

24

28

7

9

THE USEFULNESS OF ELDERLYSUPPORT RATIOS

Implicit in the standard definition ofan elderly support ratio is thenotion that all people over age 64are in some sense dependent on thepopulation in the working ages (20to 64) who provide indirect supportto the elderly through taxes andcontributions to social welfare pro-grams. We know, of course, thatelderly populations are extremelydiverse in terms of resources,needs, and abilities, and that manyelderly are not dependent in eithera financial or a physical (health)sense. Older people pay taxes,often have income and wealth thatfuel economic growth, and providesupport to younger generations.Likewise, substantial portions of theworking-age population may not befinancial earners, for reasons ofunemployment, inability to work,pursuit of education, choosing to beout of the labor force, and so forth.

While it is empirically difficult toinclude factors such as intrafamilyfinancial assistance and child careactivities into an aggregate measureof social support, it is feasible totake account of employment charac-teristics in both the working-ageand elderly populations. In Figure8-3, the topmost bar for each coun-try represents the standard elderlysupport ratio as defined above. Thesecond bar includes only the eco-nomically active population aged 20to 64 in the denominator, therebyexcluding people who choose not towork, unpaid household workers,nonworking students, and perhapsthose individuals whose health sta-tus keeps them out of the laborforce. The third bar represents acalculation similar to the second bar,but removes economically activepeople aged 65 and over from thenumerator on the assumption that

they are not economically depend- factors as (1) workers under age 20;ent. The fourth bar builds on the (2) trends in unemployment; (3)third bar by adding these economi- average retirement ages; and (4)cally active elderly to the ratio levels of pension receipt and institu-denominator of other economically tionalization among the elderly,active individuals, on the assump- and/or the prevalence of high-costtion that these working elderly con- disabilities.tinue to contribute tax revenue to

RAPIDLY CHANGING AGEnational coffers. STRUCTURE IS A CHALLENGE

The alternative ratios in each coun- TO SUPPORT IN SOMEDEVELOPING COUNTRIEStry are higher than the standard eld-

erly support ratio, except in Japan One of the more dramatic demo-where the elderly have a relatively graphic developments in the lasthigh rate of labor force participation two decades has been the pace of(often as part-time workers). To the fertility decline in many developingextent that policy and program countries. The common perceptionagencies use support ratio calcula- is that below-replacement fertilitytions, the effect of including versus levels are seen only in the industri-excluding labor force participation alized nations of the Northernrates appears considerable in most Hemisphere. As of 2000, however,countries. Data permitting, other the total fertility rate was belowadjustments might be made to replacement level in 21 developingthese ratios to account for such countries, mostly in Latin America


Figure 8-3.

Standard and Alternative Elderly Support Ratios: 1998

Sources: International Labour Office Yearbook of Labour Statistics, 1999 and U.S. Census Bureau, 2000a.

Germany

UnitedStates

Spain

Japan

Finland

Total population 65 and over per 100total population 20-64

Noneconomically active population 65 and over per100 economically active population 20 and over

Noneconomically active population 65 and over per100 economically active population 20-64

Total population 65 and overper 100 economically activepopulation 20-64

32

24

313131

2633

25

23

2739

3939

2227

24

23

2534

33


Figure 8-4.

Population by Single Years of Age for China: 2000


Millions

Male FemaleAge

15 12 9 6 3

0

5

10

15

20

25

30

35

40

45

50

55

60

65

70

75

80

85+

0 3 6 9 12 15

and the Caribbean and parts of Asia(U.S. Census Bureau, 2000a), and isdeclining steeply in many otherdeveloping countries.

The situation in the People’sRepublic of China illustrates thepotential effect that rapidly-declining fertility may have vis-a-vispopulation aging. In 1979, Chinaestablished an official one-child-per-family policy aimed at curbinggrowth in the world’s most popu-lous nation. While the policy wasrelaxed somewhat in subsequentyears, China’s total fertility ratedeclined to an estimated level of1.8 children per woman in 2000.As a result, China will age soonerand more quickly than most devel-oping countries.

China’s age profile in 2000 con-tained a large “bulge” consisting ofpeople aged 26 to 37 (Figure 8-4).The oldest people in this age bulgewill be entering their sixties justprior to the year 2025. This popu-lation momentum will produce arapid aging of the Chinese popula-tion in the third and fourth decadesof the twenty-first century. Recentanalyses of 1995 sample censusdata from China suggest higher old-age mortality than had been previ-ously estimated, resulting in lowernumbers of projected elderly peo-ple. Nevertheless, the number ofChinese aged 65 years and over isnow projected to increase from 88 million in 2000 to 197 million in2025, and to 341 million in 2050.Short of a catastrophic rise in adultmortality or massive emigration ofan unprecedented scale, we can bereasonably certain that this growthwill occur, because the elderly ofthe middle decades of the twenty-first century are already born.Eventually, China’s projected youthand elderly support ratios are likely


Figure 8-5.

Youth and Elderly Support Ratios in China: 1985 to 2050


0

20

40

60

80

100

20502045204020352030202520202015201020052000199519901985

Youth ratio: people aged 0 to 19 per 100 people aged 20 to 64; Elderly ratio: people aged 65 and over per 100 people aged 20 to 64

Youth

Elderly

Figure 8-6.

Parent Support Ratios in Four World Regions: 1950, 2000, and 2030

Note: South America includes: Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, French Guiana, Guyana, Paraguay, Peru, Suriname, Uruguay, and Venezuela. Eastern Asia includes: China, North Korea, South Korea, Hong Kong, Japan, Macau, Mongolia, and Taiwan Western Europe includes: Austria, Belgium, France, Germany, Liechtenstein, Luxembourg, Monaco, Netherlands, and Switzerland. Western Africa includes: Benin, Burkina Faso, Cape Verde, Cote d' Ivoire, Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Mali, Mauritania, Niger, Nigeria, St. Helena, Senegal, Sierra Leone, and Togo.


1517

37

710 9

20

44 37

3

Western AfricaWestern EuropeEastern AsiaSouth America

195020002030(People aged 80 and over per 100 people aged 50 to 64)

to converge (Figure 8-5), and wemay anticipate a social and eco-nomic fabric radically different fromthat of today.

MORE PEOPLE WILL FACECARING FOR FRAIL RELATIVES

In the eighteenth and nineteenthcenturies, low levels of lifeexpectancy meant that people onaverage lived a relatively shortamount of time in a multigenera-tional family (United Nations,1990b). While most older individu-als lived with family members,years spent in an extended-familyarrangement were limited becausethe average person died shortlyafter becoming a grandparent(Hareven, 1996). Declining mortali-ty and increased longevity haveincreased the odds of joint survivalof different generations within afamily. In developed countries,joint survival has manifested itselfin the “beanpole family,” a verticalextension of family structure char-acterized by an increase in thenumber of living generations withina lineage and a decrease in thenumber of members within eachgeneration (Bengston, Rosenthal,and Burton, 1995). As mortalityrates continue to improve, moreand more people in their fifties andsixties are likely to have survivingparents, aunts, and uncles. Morechildren will know their grandpar-ents and even their great-grandparents, especially their great-grandmothers. There is nohistorical precedent for a majorityof middle-aged and young-oldadults having living parents.Menken (1985) has estimated thatone in three women 50 years oldhad living mothers in the UnitedStates in 1940, whereas by 1980the proportion had doubled to twoin three.

SANDWICH GENERATION ADEVELOPED-COUNTRYPHENOMENON

One aspect of the changing agestructure of families that hasreceived recent attention is the so-called “sandwich generation,” thatis, people who find themselves car-ing for elderly parents while stillcaring for/supporting their ownchildren or grandchildren and oftenparticipating in the labor force. Indeveloped countries especially,more people will face the concernand expense of caring for their veryold, frail relatives with multiple,chronic disabilities and illnesses.The need for help is likely to comeat the very time when the adult chil-dren of the frail elderly are near orhave reached retirement age.1 Indeveloping countries, the adult chil-dren may well have children of theirown living in the household. Someof the adult children may bearhealth limitations of their own.Those frail elderly without childrenmay face institutionalization at ear-lier ages than will people with sur-viving adult children.

One measure of the pressure thesandwich generation may experi-ence by caring for elderly parents isthe parent support ratio (PSR),defined here as the number of peo-ple aged 80 and over per 100 peo-ple aged 50 to 64, which in a gen-eral sense relates the oldest old totheir offspring who were born when


1 It should be noted that the idea of a “sand-wich generation” needs further empirical eluci-dation. Some researchers question the extentto which middle generations actually providecare for younger and older generations. Onestudy of 12 European Union countries (reportedin Hagestad, 2000) reports that only 4 percentof men and 10 percent of women aged 45-54have overlapping responsibilities for childrenand for older persons who require care. Theimportance of the “sandwich” concept in agiven society is likely to be determined, in part,by the nature of formal institutions that provideassistance to elderly individuals and to familiesin general.

most of the oldest old were aged20 to 35. Of course, people in thenumerator (80 and over) are notnecessarily in the same families asthose in the denominator (50 to 64years). Thus, the PSR is only arough indication of need for familysupport over time.

Relatively few people aged 50 to 64in 1950 worried about caring forpeople aged 80 or older. In thedeveloped countries in this study,the PSR ranged from five in Japanand Hungary to eleven in Norway in1950. In developing countries, thePSR ranged from two in Bangladeshto eleven in Tunisia and Uruguay.Increases in the PSR since 1950imply that a relatively larger shareof middle-aged adults now mayexpect to provide care.Additionally, life expectancy hasincreased for the disabled, the men-tally retarded, and the chronicallyill. Today’s care for older peoplemay be more physically and psy-chologically demanding than in thepast, especially with regard to theincreased numbers of people withcognitive diseases. As advances inmedical technology affect the abilityto extend life, it is at least plausibleto expect the duration of chronic ill-ness and the consequent need forhelp to increase further, even if theaverage age at onset of disabilityrises.

In all countries examined exceptBangladesh, Jamaica, Morocco, andPakistan, the PSR is projected to behigher in 2030 than in 2000. Theratio has and will evolve very differ-ently within and among worldregions, however (Figure 8-6). InSouth America, Eastern Asia, andWestern Europe, PSRs more thandoubled between 1950 and 2000.PSRs will continue to rise between2015 and 2030. In Western Africa,most countries experienced little

change in the PSR from 1950 to2000, and the aggregate level willremain low in 2030 even thoughabsolute numbers of oldest-old people in some nations are growingrapidly. The most pronouncedchanges have occurred in the industrialized world. In 2000, the PSRwas 20 or higher in 12 such nation(and also in Israel and Uruguay).The difference in parent supportratios between developed anddeveloping countries reflects differ-ent trends in fertility. In 2030,those aged 50 to 64 (the potentialsupport givers) were born between1966 and 1980. In most develop-ing countries, fertility was still highduring this period, or just begin-ning to decline. Hence, this agegroup will be fairly large, resultingin low parent support ratios. Indeveloped countries, fertility wasfairly low during this period, pro-ducing small birth cohorts that willresult in higher parent supportratios in 2030.

SPOUSE MAY BE MOST LIKELYTO PROVIDE CARE FORELDERLY

A clear cross-national picture ofcaregiving for the elderly has yet toemerge. In the 1980s, the stereo-typical view of caregiving was thatof children caring for their agedparent(s). More specifically, it gen-erally was thought that adultdaughters and daughters-in-law provided most of the personal care anhelp with household tasks, trans-portation, and shopping for the eld-erly (United Nations, 1985).Although this may still be the case,increases in joint survival meanthat, for many older people in bothdeveloping as well as developedcountries, the main person whoprovides care is their spouse(Shuman, 1994). One survey inSpain found that 74 percent of

-

-

s

-d

older men who were receivingassistance with an instrumentalactivity of daily living2 had theirwife as the caregiver. However,only 33 percent of older womenrelied on their husband as the care-giver, while 58 percent were aidedby a daughter (Beland andZunzunegui, 1996).

Whether in the role of spouse ordaughter, the fact remains thatwomen provide the bulk of informaland/or long-term care for elderlypeople worldwide. While joint sur-vival increases the number of elder-ly couples, the average womaneventually outlives her husband andmay have to rely on other familymembers for personal care.3 Moststudies (see, for example, Jensonand Jacobzone, 2000, and the com-pilation of research in Blieszner andBedford, 1996) have indicated thatthese other family members arewomen. Therefore, a variant of theparent support ratio may be useful,namely, the ratio of people aged 80and over to women aged 50 to 64.Changes in this parent support ratiofor females (PSRF) are similar tothose in the PSR, but the PSRF levelsare much higher. In 2000, the PSRFwas 54 in Norway and Sweden, thehighest level among the 52 studynations. Most developed countrieshad PSRF levels in the 30s and 40s,while many developing nations hadPSRFs of 15 or less in 2000.Projections for the year 2030 sug-gest that in Japan there will be 100people aged 80 and over per 100women aged 50 to 64, the highestlevel among the 52 nations.


2 Instrumental activities of daily livinginclude preparing meals, shopping for personalitems, managing money, using the telephone,and doing light housework.

3 Although, in countries with relatively highlevels of income, market developments increas-ingly allow older individuals or their children topurchase care services directly if desired.

FAMILY ABILITY TO CARE FORELDERLY MEMBERS MAY BECHANGING

Living with other people reducesthe likelihood of using formal med-ical care and increases the use ofinformal care, at least in the U.S.context (Cafferata, 1988). Sincemost physical, emotional, and eco-nomic care to older individuals isprovided by family members, thedemography of population aging isincreasingly concerned with under-standing and modeling kin availabil-ity. Kin availability refers to thenumber of family members who willpotentially be available to elderlyindividuals if and when variousforms of care are needed. A studyby Tomassini and Wolf (2000) exam-ined the effects of persistent lowfertility in Italy on shrinking kin net-works for the period 1994-2050;throughout the simulation period,about 15-20 percent of Italianwomen aged 25 to 45 are the onlyliving offspring of their survivingmothers and thus are potentiallyfully responsible for their mothers’care. While reduced fertility andsmaller families obviously implyfewer potential caregivers, thiseffect is offset to some extent byincreased longevity. Modeling isfurther complicated by the fact thatwhile demographic forces imposeconstraints on family, household,and kin structures, these structuresalso are determined by social andcultural factors that are difficult tomeasure (Myers, 1992; Wolf, 1994;Van Imhoff, 1999).

Research is now addressingwhether the high rates of divorceobserved in some nations will resultin a lack of kin support for peoplein older age, and whether “blended”families and other forms of socialarrangements will, in the future,provide the types of care and

support that are common today(Wachter, 1998; Murphy, 2001).The consensus to date foresees adeclining biological kinship supportnetwork for elderly people in devel-oped and many developing coun-tries. Childlessness is another traitthat will affect the nature of futurecaregiving. Data over time for theUnited States in Figure 8-7 show theincreasing likelihood of being child-less among women aged 40 to 44;nearly one out of five such womenin 1998 had no children. Trends inthis characteristic could be animportant determinant of eventualcare arrangements as current andfuture cohorts of middle-agedwomen reach older age.

The issue of kin availability hasbecome especially important in thecontext of East and Southeast Asiancountries, driven in large part bythe rapid declines in fertility thathave greatly reduced the averagefamily size of young-adult cohorts.The complex interplay of demo-graphic and cultural factors is illus-trated by the case of the Republicof Korea. There, two-thirds of theelderly are economically dependenton their adult children (KoreaInstitute for Health and SocialAffairs, 1991), and cultural normsdictate that sons provide economicsupport for elderly women whohave lost their spouses. Lee andPalloni (1992) have shown thatdeclining fertility means an increasein the proportion of Korean womenwith no surviving son (Figure 8-8).At the same time, increased malelongevity means that the proportionof elderly widows also will decline.Thus from the elderly woman’spoint of view, family status may not


Figure 8-7.

Childlessness Among U.S. Women 40 to 44 Years Old: 1976 to 1998

Source: U.S. Census Bureau, June Current Population Surveys, 1976 to 1998.

10 1011

1516

19

199819921988198419801976

(Percent)

Figure 8-8.

Percent of Women at Age 65 in South Korea With No Surviving Son: 1975 to 2025

Source: Lee and Palloni 1992.

1715 15

17

26

30

1110 10

13

24

29

202520152005199519851975

MarriedWidowed

deteriorate significantly in thecoming years. From society’s per-spective, however, the demand forsupport of elderly women is likelyto increase. The momentum ofrapid population aging means thatthe fraction of the overall popula-tion that is elderly women (especial-ly sonless and childless widows)will increase among successivecohorts. Given the strong trendtoward nuclearization of familystructure in the Republic of Korea,and the traditional absence of stateinvolvement in socioeconomic sup-port, the future standard of livingfor a growing number of elderlywidows is tenuous. A similarprospect looms in Taiwan and Japan(Hermalin, Ofstedal, and Chi, 1992;Jordan, 1995). Simulations of kinavailability in rural China (Jiang,1994) are more optimistic, suggest-ing that, in spite of relatively lowfertility, improvements in mortalitywill ease the future burden on thefamily support system. Only a verysmall percentage of rural house-holds will have to support two ormore elderly parents, and relativelyfew elderly will be childless. At thesame time, simulations using fami-ly-status life table models devel-oped by Zeng, Vaupel, andZhenglian (1997; 1998) suggestthat the family household structureand living arrangements of Chineseelders may change markedly duringthe first half of this century; by2050, the percentage of Chineseelderly living alone could be 11 and12 times larger in rural and urbanareas, respectively, than in 1990.

HOME HELP SERVICES AREMOST PREVALENT INSCANDINAVIA

The previous chapter alluded to achange in social and governmentalthinking about the desirability ofinstitutionalization. Some nations

now promote policies to maintain countries (Figure 8-9). Suchand support frail elderly people in services reached nearly one-fourththeir own homes and communities of all elderly in Finland in 1990, upfor as long as possible. Given the slightly from the level of 22 percentchanging nature of the family (in its in 1980. The available data sug-many perturbations) and patterns of gest that countries with morekin availability, the development extensive provision of home helpand use of home help services services are those that have had awould appear to be a reasonable prolonged process of populationstep toward reducing the need for aging and now have relatively high-institutionalization. To date, how- er proportions of oldest-old resi-ever, the use of home help appears dents (OECD, 1996). Structural pro-to be widespread only in grammatic factors also areScandinavian countries and the important, insofar as governmentUnited Kingdom. Comparative data support or subsidization of homeassembled by the Organization for help will almost certainly result inEconomic Co-Operation and greater use. In the United States,Development from the early-to-mid- the use of home health care servic-1990s show that the proportion of es has grown substantially since theelderly people receiving home help late 1980s, largely as a result ofexceeds 10 percent in only five changes in medicare policy that


Figure 8-9.

Proportion of Elderly People Receiving Home Help Services: Early-to-Mid 1990s

Note: Data for France, Australia, and Italy refer to 1985, 1988 and 1988, respectively. Source: OECD, 1996.

(In percent)

Italy

New Zealand

Portugal

Spain

Canada

Japan

Germany

Ireland

Austria

United States

Belgium

Australia

France

Netherlands

United Kingdom

Sweden

Norway

Denmark

Finland

1

24

17

14

13

13

8

7

7

6

4

3

3

2

2

2

2

1

1

have made home health benefitsavailable to more beneficiaries forlonger periods of time. This in turnhas stimulated the home healthcare industry; the number of homehealth agencies more than tripledbetween 1980 and 1994(Freedman, 1999).

ELDERLY PROVIDE AS WELL ASRECEIVE SUPPORT

Many elderly receive financial helpfrom adult children, but support isnot a one-way street. In countrieswith well-established pension andsocial security programs, manyolder adults give support (includingfinancial help, shelter, childcare, andthe wisdom of experience) to theiradult children and grandchildren.In the North American context,studies suggest that elderly parentsare more likely to provide financialhelp than to receive it (Soldo andHill, 1993; Rosenthal, Martin-Matthews, and Matthews, 1996).The elderly in developing countriesappear less likely than in developedcountries to provide financial help;data from the Malaysian Family LifeSurvey indicate that the main direc-tion of monetary transfers betweennoncoresident parents and childrenis from the latter to the former(Lillard and Willis, 1997). Ongoingresearch in Asia is beginning toreveal the complexity of familialexchange, not just among parentsand children but among wider fami-ly and social networks as well(Agree, Biddlecom, and Valente,1999). Beyond the financial realm,it seems clear that older persons indeveloping countries make substan-tial contributions to family well-being, in ways ranging from social-ization to housekeeping and childcare. Such activities free youngeradult women for employment inunpaid family help in agricultural

production as well as paid employ-ment (Hashimoto, 1991; Apt, 1992).

An important component of manyolder people’s lives is their role asthe giver of care. Older people pro-vide care for a variety of people(spouses, older parents, siblings,children, and grandchildren) and doso for many reasons (illness of aspouse or sibling, increased numberof single-parent families, increasedfemale labor force participation,orphaned grandchildren). Often thecare provided by older family mem-bers is essential to the well-being ofa family.

THE IMPORTANCE OFGRANDPARENTS

In some countries, nontrivial pro-portions of older women and menare providing care to their grand-children. This care ranges fromoccasional babysitting to being acustodial grandparent. Survey datafor the United States from the mid-1990s (Fuller-Thomson and Minkler,2001) indicate that 9 percent of allAmericans with grandchildren underage 5 were providing extensivecaregiving.4 In 1997, 3.9 millionchildren (5.5 percent of all childrenunder age 18) lived in a householdmaintained by their grandparents(Casper and Bryson, 1998). Since1990, the number of children livingin households headed by grandpar-ents has increased, especially forchildren in households with onlygrandparents and grandchildren.Trends in several factors (e.g.,divorce, HIV/AIDS, drug abuse, andchild abuse) may have contributedto the increase in these types offamilies.


4 Extensive caregiving in this context meantproviding at least 30 hours of child care in anaverage week and/or caring for grandchildrenfor at least 90 nights in 1 year.

Grandparents in some developedcountries often provide day care forchildren so the grandchildren’s par-ents can work or go to school. Inthe United States in 1995, 29 per-cent of preschool children whoseparent(s) worked or were in schoolwere cared for by a grandparent(Smith, 2000), typically the grand-mother. Because of the lack of ade-quate day care in many EasternEuropean countries and nations ofthe former Soviet Union, the carethat grandmothers (babushkas) pro-vide for grandchildren may be inte-gral to family functioning.

In many Asian countries, wherecoresidency is the norm, propor-tions of grandparents providingcare for grandchildren are substan-tial. In the Philippines, Thailand,and Taiwan, approximately 40 per-cent of the population aged 50 andolder lived in a household with aminor grandchild (under 18 years ofage). In these same countries,approximately half or more of thoseaged 50 and older who had a cores-ident grandchild aged 10 oryounger provided care for the child(Hermalin, Roan, and Perez, 1998).As in the United States, grandmoth-ers are more likely than grandfa-thers in Asian countries to providecare for their grandchildren (Chan,1997; Uhlenberg, 1996).

Many grandparents find themselvesin the position of going beyond pro-viding occasional care to becomingthe sole providers of care for theirgrandchildren. One reason for thissituation is the migration of themiddle generation to urban areas towork. Past research has found thatthis is not unusual in Afro-Caribbean countries (Sennott-Miller,1989). These “skip-generation”families are found in all regions of

the world and may be quite preva-lent. One study in rural Zimbabwefound that 35 percent of house-holds were skip-generation house-holds (Hashimoto, 1991).

THE HIV/AIDS EPIDEMIC ISCHANGING GRANDPARENTS’ROLES

The AIDS epidemic has affected thenumber of grandparents who arecaring for grandchildren in manycountries of the world. The effects

of the epidemic are particularlydevastating in Sub-Saharan Africa,where it is estimated that in 19998.6 percent of the population aged15 to 49 was infected with an HIVvirus that causes AIDS. High ratesof adult infection and AIDS deathsleave many children in need ofcare. The cumulative number ofAIDS orphans5 in Sub-Saharan


5 AIDS orphans are defined as HIV-negativechildren who lost their mother or both parentsto AIDS when the children were under age 15.

Africa is estimated to be 12.1 mil-lion (UNAIDS/WHO 2000). Formany of these children, grandpar-ents have become the main care-giver (Levine, Michaels, and Back,1996). One study (Ryder et al.,1994) in the city of Kinshasa foundthat the principal guardian for 35 percent of AIDS orphans was agrandparent.


CHAPTER 9.

Educational Attainmentand Literacy

Educational attainment is linked tomany aspects of a person’s well-being. Research has shown thathigher levels of education usuallytranslate into better health status,higher incomes, and consequentlyhigher standards of living (Guralniket al., 1993; Preston and Taubman,1994; Smith and Kington, 1997; Liu,Hermalin and Chuang, 1998).People with higher educational lev-els tend to have lower mortalityrates and better overall health thantheir less-educated counterparts (Eloand Preston, 1996; Zimmer et al.,1998), as well as better cognitivefunctioning in older age (Stern andCarstensen, 2000). Part of the rea-son for this finding is that more-educated people tend to have higherincomes throughout their lifetime,which means they can afford betterhealth care than people with lowerlevels of education. Higher work-ing-life income also translates intohigher levels of retirement savingsand income. Hence, people withhigher educational levels may beless dependent on their family forfinancial assistance in later years.

Education significantly affects howeffectively people utilize healthcare. In the United States, forexample, where educational levelsof the elderly are relatively high,many older people, especially thoseaged 85 and older, have troubleunderstanding basic medicalinstructions. Even something assimple as taking medicine correctlymay be a problem. Education fur-ther affects health because well-educated people may be more

aware of the benefits and disadvan- implications for intergenerationaltages of certain types of behaviors solidarity (Choi, 1992).associated with personal health.

Educational attainment of the eld-Education also is related to joint

erly varies substantially among thesurvival of spouses, to living

countries in this report. The latestarrangements, and to changing

data for the United States showvalue systems which have

Figure 9-1.

Percent of People With Completed Secondary Education or More

Note: Data for Sweden 65+ refer to ages 65-74. Sources: U.S. Census Bureau, 2000a and national sources.

Sweden, 1998

Singapore, 1995

Russia, 1994

Romania, 1992

China, 1990

Bolivia, 1992

Brazil, 1991

United States, 1998

Male, 25-44 Female, 25-44 Male, 65+ Female, 65+

86.989.0

67.666.6

21.623.9

6.64.9

17.212.8

4.72.3

20.413.4

2.80.5

94.692.1

45.531.9

87.391.9

31.821.6

64.061.3

15.25.4

79.682.5

44.0 38.0

that two-thirds of all people aged65 and older had completed at leastsecondary education.1 Comparablecompletion levels in other devel-oped countries are somewhat lower.Less than a third of the elderly inRussia, for example, had finishedsecondary-level education (Figure 9-1). Levels of education of the eld-erly are much lower in developingcountries. In Brazil, Bolivia, andChina, less than 5 percent of theelderly population had a completedsecondary education.

FUTURE ELDERLY WILL HAVEMORE EDUCATION

During the twentieth century, educa-tional attainment has increasedmarkedly in most countries of theworld. This improvement is clearlyreflected in the data on educationalattainment by age. In some devel-oped countries, younger cohorts aremore than twice as likely as the eld-erly to have completed secondaryeducation. In developing countries,the difference between younger andolder cohorts is even more striking.Women aged 25 to 44 in Bolivia weremore than five times as likely aswomen aged 65 and older to have acompleted secondary education.

The educational attainment of theelderly has risen during the lastseveral decades in many countries,and will continue to increase in thefuture. For example, around 27 percent of the elderly in theUnited States had completed atleast secondary education in 1970;by 1998 the percentage had


1 Educational attainment in this report refersin theory to completion of a particular educa-tional level. Data have been derived from pri-mary national tabulations as well as from fig-ures reported to international organizations.While large differences in educational attain-ment exist, at least some of the variation is like-ly due to different concepts, definitions, andmethods of data collection. We have attemptedto make the data on educational attainment inthis report as comparable as possible acrosscountries.

Figure 9-2.

Percent of People With Completed University Level of Education: 1998

Note: Percent for females aged 55-64 in Indonesia is zero. Source: Organization for Economic Co-Operation and Development, 2001.

Turkey

South Korea

Jordan

Indonesia

India

China

Brazil

Argentina

United States

Sweden

Portugal

Poland

Netherlands

Italy

Germany

Australia

Male, 35-44Female, 35-44Male, 55-64Female, 55-64

1

19 18

119

1914

155

1211

73

2923

2212

91111

96

75

414

1312

1127

2626

18

911

54

89

644

25

211

35

13

11

033

1815

226

1114

29

45

Developed countries


jumped to 67 percent. As younger, 5 to 25 percent in the developedmore-educated cohorts continue to countries and from 1 to 12 percentage, their attainment levels will be in developing countries. Small pro-reflected in the educational status portions of women aged 55 to 64of tomorrow’s elderly. in developed countries have a uni-

versity education, and proportionsUNIVERSITY EDUCATION NOT in most developing countries areYET THE NORM AT ANY AGE smaller still.Although educational attainment

LITERACY RATE OF MANYhas been improving throughout theELDERLY POPULATIONS STILLtwentieth century, university-levelLOW

education still is not widespread.Relatively few people complete this In many developed countries, litera-

level of education and the propor- cy data no longer are collected

tion is usually lowest among the because education, at least at the

elderly. In many developed coun- primary level, is so widespread that

tries, less than a third of people literacy is considered to be univer-

aged 35 to 44 have a university sal. However, this is not always the

education (OECD, 1998a; 2001). case for the elderly, particularly for

The proportion of the “near elderly” older women and the oldest old.

(i.e., aged 55 to 64) with this level Data from some countries that still

of education is even lower (Figure collect literacy information show

9-2). For the set of countries that substantial proportions of the

included in this graph, among men elderly may be unable to read and

aged 55 to 64, the proportion with write. In Greece, for example, only

a university education ranged from 77 percent of people aged 65 and

older were literate in 1991, and just67 percent of the age group 75 andover. Proportions literate amongolder Greek women were evenlower — approximately two-thirdsof women aged 65 and older andslightly over half of women aged 75and older.

In developing countries, literacymay be uncommon among olderpopulations. Many of today’s elder-ly lived much of their lives prior tothe rapid increase in educationalattainment that occurred in the sec-ond half of the twentieth century.Consequently, many older people,and again particularly women, havelow levels of literacy. While cohortchanges ensure that the future edu-cation profile of the elderly willimprove, it is important to remem-ber that in many countries, a major-ity of today’s elderly are illiterate(Hugo, 1992). This fact needs to beexplicitly recognized and consid-ered when developing programs toassist older populations.

Figure 9-3 presents estimated litera-cy rates for the population aged 60and over, by sex, in five developingregions for 1980 and 1995.2 In allfive regions, older men are more lit-erate than older women. In three ofthe five regions, less than half ofolder men and less than 15 percentof older women were literate in1995. Among developing regions,Latin America and the Caribbeanhas the highest aggregate literacylevels for older populations; three-quarters of men and two-thirds ofwomen aged 60 and over were liter-ate, similar to the levels notedabove in Greece.


2 These estimates were produced by theDivision of Statistics of UNESCO using the mostrecently available national data. For detailsabout the methodology used to produce theseestimates see UNESCO, 1995, MethodologyUsed in the 1994 Estimates and Projections ofAdult Illiteracy, Statistical Issue STE-18, Divisionof Statistics, Paris.

Figure 9-3.

Estimated Literacy Rates for Population Aged 60 and Over, by Sex, in Five Developing Regions: 1980 and 1995

Source: United Nations Educational Scientific and Cultural Organization, 1995.

Southern Asia

Sub-Saharan Africa


Eastern Asia/Oceania

Arab States

(Percent literate)19801995

M

F

M

F

M

F

M

F

M

F 13

2636

611

4064

927

6875

5868

2134

914

3341

8

Countries vary greatly in rates of lit-eracy among the elderly. In Chile,over 80 percent of the elderly wereliterate in 1992, while in Ugandaless than a fifth of the elderly wereliterate (Figure 9-4). In most coun-tries, older men are much morelikely to be literate than olderwomen. In Brunei, older men werefour times as likely to be literate aswere older women. Although verysmall proportions of the elderlypopulation are literate in manydeveloping countries, the rates riserapidly for younger cohorts. For allthe countries in Figure 9-4, with theexception of women in Uganda,well over half of the populationaged 25 to 44 were literate. Andamong this younger age group, thedifference in literacy by sex tendsto dissipate.

GENDER DIFFERENTIAL INEDUCATIONAL LEVELS AMONGTHE ELDERLY IS OFTENSUBSTANTIAL

In nearly all countries, older menhave higher average levels of educa-tion than do older women. Just asoverall levels of education vary wide-ly among countries, so does the gen-der difference in education at olderages. The gender gap3 in education-al attainment of the elderly is largerin many developed countries than indeveloping countries, where thelevel of education for the elderly isso low for both men and womenthat the difference between them issmall. In many developed countries,where overall attainment levels are


3 The gender gap is defined as the absolutedifference in percentage points between theeducational level of men and women. Forinstance, in Romania in 1992, 45.5 percent ofmen and 31.9 percent of women aged 65 andolder had completed secondary or higher edu-cation. The gender gap for the population aged65 and older with these levels of schoolingwould be the difference between the two levels(13.6 points).

Figure 9-4.

Percent Literate in Two Age Groups: Latest Available Year

Sources: United Nations Educational Scientific and Cultural Organization, 1995 and country sources.

65+

25-44

65+

25-44

65+

25-44

65+

25-44

65+

25-44

65+

25-44

65+

25-44

65+

25-44

65+

25-44

MaleFemale

23.3

Bolivia, 1992

Botswana, 1993

Brunei, 1991

Chile, 1992

Iran, 1991

Jordan, 1994

Thailand, 1990

Uganda, 1991

Zimbabwe, 1992

91.976.6

53.828.3

70.275.2

12.911.3

96.091.1

45.110.6

96.696.9

81.380.9

79.456.1

31.314.0

96.686.9

51.016.9

97.395.4

76.353.2

73.044.0

26.77.2

89.574.5

41.0

higher, the difference between older older cohorts. In various coun-men and women is larger. tries, younger women complete

secondary education at higherAs suggested by the data on litera-

rates than do men, and in somecy discussed earlier, gender differ-

nations the gender difference inences in educational attainment

university-level attainment atare much smaller for younger than

younger ages is negligible. Thus,

the disadvantages that today’solder women may face because oftheir lower levels of education rela-tive to men should begin to abatewhen these younger cohorts reachthe ranks of the elderly.

GENDER GAP IS INVERSELYRELATED TO AGE AT OLDERAGES

Examining the gender gap by age indeveloping countries reveals thedifferential rate of improvement ineducational attainment. Figure 9-5presents the gender gap in literacyrates for five age groups in severalcountries with data from the 1990s.A somewhat counter-intuitive pic-ture emerges for the three older agegroups, namely, that the gendergap decreases as age increases. Inother words, there is a largerabsolute difference between maleand female literacy rates at ages 55to 59 than among people aged 65and over. The increase in the gen-der gap for younger-old age groupsreflects historical patterns of educa-tional promotion. When countrieswith low overall levels of educationand limited resources began toimprove the educational attainmentof their populations, the initialfocus was more on educating malesthan females. In most developingcountries, people aged 55 and overwere of school age when formaleducation was not widespread.Although educational attainmentwas improving, it was improvingmore for men than for women.Thus, for these older age groups,the gender gap is less among theelderly than among people aged 55to 64. For some countries in Figure9-5, the gender gap at ages 25 to29 and 35 to 39 is smaller than atthe older ages, indicating a moreequal inclusion of both sexes ineducational programs in recentyears.


Figure 9-5.

Gender Gap in Literacy Rates for Selected Age Groups: Latest Available Year

Note: The gender gap is defined as the absolute difference in percentage points between the literacy rate for men and women.Source: United Nations Educational Scientific and Cultural Organization, 1995 and country sources.

65+

60-64

55-59

35-39

25-29

65+

60-64

55-59

35-39

25-29

65+

60-64

55-59

35-39

25-29

65+

60-64

55-59

35-39

25-29

65+

60-64

55-59

35-39

25-29

65+

60-64

55-59

35-39

25-29

Bolivia, 1992

Brunei, 1991

Iran, 1991

Jordan, 1994

Uganda, 1991

Yemen, 1994

19.4

9.1

18.6

32.9

31.6

25.5

0.9

6.4

48.0

43.7

34.5

18.9

26.5

23.4

19.7

17.3

3.9

13.9

47.3

44.8

34.1

23.9

32.5

35.4

27.3

19.5

48.5

37.8

28.7

21.6

EDUCATIONAL DISADVANTAGEIS COMMON IN RURAL AREAS

The quality and quantity of ruraleducational facilities in mostnations tend to be inferior to thosein urban areas. Consequently, liter-acy levels and educational attain-ment are lower in rural areas, par-ticularly in developing countries.Data for Yemen (Figure 9-6) illus-trate the common pattern whereinthe rural disadvantage in literacy isevident for both sexes (i.e., ruralmales have lower rates than urbanmales and rural females have lowerrates than urban females). Itappears that differences by genderare greater than differences byurban/rural residence. Urbanwomen have lower literacy ratesthan rural men, except at the veryyoungest ages. The sexes also dif-fer in size of the rural/urban gap byage. Rural males consistently havelower literacy rates than urban


Figure 9-6.

Percent Literate by Age, Sex, and Urban and Rural Residence, Yemen: 1994

Source: Population and Housing Census of Yemen, 1994.

0

20

40

60

80

100

75+70656055504540353025201510

Percent

Age

Female rural

Male urban

Male rural

Female urban

Table 9-1.Earnings Ratios of Selected Age Groups in 15 Countries by Level of EducationalAttainment: 1995

Country

45-54 years/25-29 years 55-64 years/45-54 years

Less than uppersecondary

Upper Nonuniversitysecondary tertiary University Overall

Australia . . . . . . . . . . . . . . . . . . . . . . . . . . .Canada . . . . . . . . . . . . . . . . . . . . . . . . . . . .Denmark . . . . . . . . . . . . . . . . . . . . . . . . . . .Finland. . . . . . . . . . . . . . . . . . . . . . . . . . . . .France . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Germany . . . . . . . . . . . . . . . . . . . . . . . . . . .Ireland . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Japan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . . . .New Zealand . . . . . . . . . . . . . . . . . . . . . . .

Norway . . . . . . . . . . . . . . . . . . . . . . . . . . . .Sweden . . . . . . . . . . . . . . . . . . . . . . . . . . . .Switzerland . . . . . . . . . . . . . . . . . . . . . . . . .United Kingdom . . . . . . . . . . . . . . . . . . . . .United States . . . . . . . . . . . . . . . . . . . . . . .

1.301.051.211.431.18

0.971.241.231.131.25

1.101.381.060.931.29

1.261.461.231.361.47

1.281.591.441.611.39

1.261.261.251.091.28

1.351.371.291.691.45

1.101.591.641.331.16

1.881.671.521.411.39

2.061.961.602.111.95

1.762.251.991.651.93

1.671.701.801.501.67

0.850.860.920.901.07

0.97(NA)0.860.840.95

(NA)0.900.970.810.89

NA Not available.

Note: Ratios reflect gross annual earnings before taxes. Data for Finland and Ireland refer to 1994 and 1993 respectively.

Source: Organization for Economic Co-Operation and Development (Employment Outlook 1998).

males in Yemen, and the gap reading skills generally worsen with labor force entrants (25 to 29 years)between the two areas is fairly even age; a recent study also demon- generally rises with educationalacross the age spectrum. For strated that functional health attainment level, but the right-handwomen, on the other hand, the gap literacy is markedly lower at older column of Table 9-1 indicates anbetween rural and urban literacy ages, even after controlling for vari- overall decline in earnings of peoplelevels is much wider at the younger ables such as cognitive dysfunction, 55 to 64 relative to people 45 tothan the older ages, suggesting that physical functioning and visual acu- 54. Because educational attainmentin recent years urban women have ity (Baker et al., 2000). This study may be very different by agebeen afforded greater relative raises questions about the effects of cohort, this table may confoundaccess to education than have their life-long education, the efficacy of pure age effects with returns torural counterparts. tests that measure cognitive ability, education. Further analysis of avail-

and other age-related changes that able data suggests that, when aver-EDUCATION AFFECTS OTHER may affect testing procedures. aged over all countries, the earn-DIMENSIONS OF LIFE ings premium of peak-earning

Table 9-1 shows ratios of averageAs mentioned earlier, education is workers relative to recent entrants

earnings for workers in three agerelated to health behavior and rises considerably with higher edu-

groups. The earnings ratio of per-income accumulation throughout cational attainment (OECD, 1998

sons in the so-called peak earningthe life course. Studies in the Employment Outlook).

years (45 to 54) to those of recentUnited States have shown that



CHAPTER 10.

Labor Force Participationand Retirement

Rapid growth of elderly populationsmay put pressure on a nation’sfinancial resources. This concern isbased, at least partially, on theassumption that the elderly do notcontribute to the economy. However,many older people do work, andexamining the labor force participa-tion and characteristics of olderworkers gives a clearer picture oftheir contribution. Information onolder workers also is useful in plan-ning economic development and thefinancing of retirement.

Some characteristics of older work-ers seem not to vary among coun-tries. In all countries, the elderlyaccount for a small proportion ofthe overall labor force. Their shareof the total labor force in the studycountries ranges from less than 1 percent to 7 percent. A secondcommonality is that labor force par-ticipation declines as people nearretirement age. A third is that par-ticipation rates are higher for oldermen than for older women.

Other characteristics of older work-ers show interesting differencesacross countries. The rate ofparticipation of older workers variessubstantially, and generally is lowerin developed than in developingcountries. Only 2 percent of menaged 65 and over participate in thelabor force in some developedcountries, whereas in certain devel-oping countries well over half ofelderly men are economically active.The occupational concentration ofolder workers also varies widelyamong countries.

Figure 10-1 presents data on formal with age. On the other hand, theeconomic activity for older women work status of older workers differsand men in three countries, chosen dramatically among the countries.to represent different levels of eco- In Rwanda, more than three-nomic development. Some of the quarters of all women aged 60 topatterns mentioned above are 64 are economically active, andapparent in these data; older even at ages 70 and older, a sub-women have lower participation stantial number remain active in therates than older men, and participa- labor force. In contrast, although ation rates for both sexes decrease nontrivial proportion of women

Figure 10-1.

Economically Active Older Population by Age for Rwanda, Peru, and New Zealand: Late 1990s

Source: International Labour Office (various issues of the Yearbook of Labour Statistics).

75+

70-74

65-69

60-64

75+

70-74

65-69

60-64

75+

70-74

65-69

60-64

MaleFemale

Rwanda, 1996

New Zealand, 1999

Peru, 1999

1.1

86.977.8

81.573.4

66.051.7

45.632.5

72.538.2

56.323.4

46.226.2

29.011.1

57.532.5

20.410.0

8.82.92.8

(Percent)

aged 60 to 64 are economicallyactive in New Zealand, participationrates decrease dramatically withage so that for women aged 70 to74, less than 3 percent are stillactive. Cross-national differences inlevels of labor force activity areassociated with societal wealth;countries with high GNP (grossnational product) tend to havemuch lower labor force participa-tion rates of the elderly and nearelderly than do low-income coun-tries (Clark, York, and Anker, 1997).In richer countries, the elderly ornear elderly can afford to retirebecause of pension schemes orsocial security systems. These pro-grams are often lacking in poorercountries.


Figure 10-2a.

Labor Force Participation Rates for Men Aged 55 to 59 in Developed Countries

Sources: U.S. Census Bureau, 2000a and International Labour Office (various issues of the Yearbook of Labour Statistics).

United States

Sweden

Poland

New Zealand

Luxembourg

Japan

Italy

Hungary

Germany

France

Czech Republic

Canada

Bulgaria

Belgium

Austria

Australia

Early 1970s Late 1990s

78.4

88.472.5

83.763.7

82.352.4

86.558.0

84.972.2

85.077.1

81.870.4

86.876.5

84.445.9

75.054.1

94.2

94.7

79.353.4

92.181.2

90.955.2

88.4

84.4

86.8

(Percent)

TIME TREND IN LABOR FORCEPARTICIPATION DIFFERS BYGENDER

The trend in most developed coun-tries has been for labor forceparticipation rates for older men todecline in recent decades. Figure10-2 shows male labor force partici-pation rates for three older agegroups in 16 developed countries;in all of these countries, participa-tion rates declined between theearly 1970s and the late 1990s.These declines are particularly pro-nounced for men aged 60 to 64.In ten of the sixteen countries inthe early 1970s, well over half ofmen aged 60 to 64 were still active.


Figure 10-2b.

Labor Force Participation Rates for Men Aged 60 to 64 in Developed Countries


United States

Sweden

Poland

New Zealand

Luxembourg

Japan

Italy

Hungary

Germany

France

Czech Republic

Canada

Bulgaria

Belgium

Austria

Australia


(Percent)

54.8

75.646.7

44.916.7

79.318.6

33.611.1

74.146.6

33.327.5

54.616.4

68.830.3

43.710.6

40.6

31.785.8

74.1

45.515.5

69.257.4

83.033.4

75.755.5

73.0

In the remaining six countries activ-ity rates ranged from 33 percent to46 percent. By the late 1990s, onlyJapan, New Zealand, Sweden, andthe United States had male partici-pation rates over 50 percent. Ratesalso have fallen for the 65-and-overage group.1 In the early 1970s,only two countries in Figure 10-2had participation rates lower than10 percent for elderly men; by thelate 1990s, most of the countrieshad rates less than 10 percent. Butas discussed later in this chapter,the trend in declining participationrates for older men has stopped oreven reversed in a number of devel-oped countries.


1 In the United States, much of the decline inlabor force participation rates for elderly menoccurred earlier in the twentieth century.According to Costa (1998), 70 percent of thedecline in participation rates between 1880 and1990 for men aged 65 and older occurredbefore 1960.

Figure 10-2c.

Labor Force Participation Rates for Men Aged 65+ in Developed Countries

Note: Later data for Belgium 65+ refer to ages 65-69 and for Hungary to ages 65-74; data for Sweden 65+ are not reported by the ILO. Sources: U.S. Census Bureau, 2000a and International Labour Office (various issues of the Yearbook of Labour Statistics).

United States

Sweden

Poland

New Zealand

Luxembourg

Japan

Italy

Hungary

Germany

France

Czech Republic

Canada

Bulgaria

Belgium

Austria

Australia


(Percent)

16.9

22.29.6

8.04.6

6.82.8

10.34.5

23.69.9

14.67.2

10.72.3

16.04.5

16.73.8

13.46.3

54.535.5

10.11.9

21.310.4

56.415.3

15.2

24.8

The trend for older women in thesedeveloped countries differs fromthe male pattern. In many coun-tries, female participation rateshave increased for almost all adultage groups up to age 60, whereasrates for elderly women havedeclined (Figure 10-3). In somecases, the increase among womenaged 55 to 59 has been quitemarked. In New Zealand, for exam-ple, 60 percent of women aged 55to 59 were economically active in1998, up from 28 percent in 1971.


Figure 10-3a.

Labor Force Participation Rates for Women Aged 55 to 59 in Developed Countries


United States

Sweden

Poland

New Zealand

Luxembourg

Japan

Italy

Hungary

Germany

France

Czech Republic

Canada

Bulgaria

Belgium

Austria

Australia


(Percent)

61.8

28.344.6

35.825.4

20.027.6

26.110.7

38.7

50.6

36.533.2

42.1

51.7

34.555.3

29.216.6

16.922.7

53.8

58.718.6

24.6

27.560.1

68.135.0

41.179.0

47.4

While female participation wasincreasing at younger ages, nearlyall developed countries experienceda decrease in elderly female laborforce participation between theearly 1970s and the late 1990s.Very small proportions of elderlywomen currently are economicallyactive in developed nations; amongthe 22 developed countries inAppendix A, Table 10, only Japan,Poland, and the United States haveelderly female participation ratesabove 4 percent.2


2 Rates for Norway and Ukraine in AppendixTable 10 are about 9 percent, but these refer toonly a portion of their elderly female popula-tions, i.e., women aged 65 to 74.

Figure 10-3b.

Labor Force Participation Rates for Women Aged 60 to 64 in Developed Countries


United States

Sweden

Poland

New Zealand

Luxembourg

Japan

Italy

Hungary

Germany

France

Czech Republic

Canada

Bulgaria

Belgium

Austria

Australia


(Percent)

38.8

16.018.3

13.28.7

7.66.7

8.24.7

29.126.0

18.212.9

27.915.2

17.712.7

17.15.5

9.98.1

43.339.8

12.011.7

15.532.5

51.119.2

25.746.5

36.1

WHY THE BIG DECREASE FOROLDER MEN?

Several reasons may account for thesharp decline in activity rates ofolder men in developed countries.An increase in societal wealth ismost likely the main reason for thedrop in participation rates. A sec-ondary reason may be that newtechnologies have changed theindustrial and occupational organi-zation of many economies, andgenerated the need for a recentlytrained labor force. New technolo-gies can make the skills of olderworkers obsolete and these workersmay choose to retire rather thanlearn new skills (Ahituv and Zeira,2000; Bartel and Sicherman, 1993).In countries with persistently highlevels of unemployment, there maybe formal and informal pressureson older workers to leave the laborforce to make room for youngerworkers. Perhaps most importantly,the growth and proliferation offinancial incentives for early retire-ment have enabled many olderworkers to afford to stop working.In much of Eastern Europe and theformer Soviet Union, older workersare choosing early retirement overunemployment as new marketmechanisms prompt firms to fireredundant workers (Commanderand Yemtsov, 1997).


Figure 10-3c.

Labor Force Participation Rates for Women Aged 65+ in Developed Countries

Note: Later data for Belgium 65+ refer to ages 65-69 and for Hungary to ages 65-74; data for Sweden 65+ are not reported by the ILO. Sources: U.S. Census Bureau, 2000a and International Labour Office (various issues of the Yearbook of Labour Statistics).

United States

Sweden

Poland

New Zealand

Luxembourg

Japan

Italy

Hungary

Germany

France

Czech Republic

Canada

Bulgaria

Belgium

Austria

Australia


(Percent)

8.9

4.23.1

3.22.0

2.20.8

1.72.1

8.33.4

5.22.7

5.02.0

5.71.6

5.81.6

3.21.7

19.7

14.9

4.00.6

3.53.9

33.08.5

3.2

10.0

ELDERLY IN DEVELOPINGCOUNTRIES HAVE HIGHPARTICIPATION RATES

The proportion of economicallyactive elderly men is high in devel-oping countries compared withmore-industrialized nations. Notsurprisingly, many elderly people inpredominantly rural agrarian soci-eties work of necessity, while“retirement” may be a luxuryreserved for urban elites. In nationsas diverse as Bangladesh,Indonesia, Jamaica, Mexico,Pakistan, and Zimbabwe, more than50 percent of all elderly men areconsidered to be economicallyactive. Economic activity rates ofolder and elderly women also arehigher in developing than in devel-oped countries. Some national datamay understate the true economicactivity of women, particularly indeveloping countries where muchof the work that women engage inis not counted or captured in cen-suses and labor force surveys, or isnot considered to be “economic.”Many of the activities that olderwomen are involved in, such assubsistence agriculture or house-hold industries, often are not welldocumented by conventional datacollection methods (Hedman,Perucci, and Sundström, 1996).


Figure 10-4a.

Labor Force Participation Rates for Men Aged 55 to 59 in Developing Countries

Note: Data for Ethiopia in the early 1970s are not available. Sources: U.S. Census Bureau, 2000a and International Labour Office (various issues of the Yearbook of Labour Statistics).

Uruguay

Turkey

Tunisia

South Korea

Singapore

Peru

Mexico

Ethiopia

Chile

Argentina


(Percent)

89.3

80.482.882.683.4

93.3

86.286.8

92.885.6

73.977.9

85.481.0

86.078.4

88.060.3

81.2

Figure 10-4b.

Labor Force Participation Rates for Men Aged 60 to 64 in Developing Countries


Uruguay

Turkey

Tunisia

South Korea

Singapore

Peru

Mexico

Ethiopia

Chile

Argentina


(Percent)

59.3

57.263.2

72.169.2

89.4

81.577.3

83.972.5

55.648.6

67.965.566.5

54.183.0

54.058.9

Data on economic activity ratesover time for developing countriesdo not show as clear a trend forolder workers as seen in developedcountries. Although many devel-oping countries have experienceda decrease in economic activity ofolder male workers, in most suchcountries the decrease is muchsmaller than in developed coun-tries (Figure 10-4). Akin to the pat-tern in developed countries, manydeveloping countries have wit-nessed an increase in labor forceparticipation rates for women aged55 to 64 (Figure 10-5). Unlike thepattern in developed nations, sev-eral developing countries also haveexperienced increases in participa-tion for women aged 65 and older.Because of the problems with sta-tistics on female economic activitymentioned above, these changescould reflect “real” increases inactivity rates as well as improve-ments in data collection.


Figure 10-4c.

Labor Force Participation Rates for Men Aged 65+ in Developing Countries


Uruguay

Turkey

Tunisia

South Korea

Singapore

Peru

Mexico

Ethiopia

Chile

Argentina


(Percent)

19.4

29.127.6

42.427.4

65.7

67.152.4

61.541.1

31.921.7

35.140.2

38.034.0

67.833.6

20.9

Figure 10-5a.

Labor Force Participation Rates for Women Aged 55 to 59 in Developing Countries


Uruguay

Turkey

Tunisia

South Korea

Singapore

Peru

Mexico

Ethiopia

Chile

Argentina


(Percent)

41.0

16.235.4

15.532.4

58.615.4

32.416.1

47.516.2

28.4

39.151.2

11.312.2

50.0

30.421.7

AGRICULTURE STILLIMPORTANT SOURCE OFEMPLOYMENT FOR ELDERLY

Just as labor force participationrates of older workers vary amongcountries, so do levels of concentra-tion in various occupations.Economies in developed countrieshave shifted from agriculture andheavy industries toward servicesand light industries, which is a shiftfrom physically demanding andsometimes hazardous jobs to workwhich requires less brawn and dif-ferent technical skills. This shiftmay benefit older workers insofaras jobs requiring mental abilityrather than physical strength mayenable them to remain activelonger. Conversely, the shift couldbe detrimental to older workers ifthe new jobs require skills or train-ing which older workers may nothave or easily acquire.


Figure 10-5b.

Labor Force Participation Rates for Women Aged 60 to 64 in Developing Countries


Uruguay

Turkey

Tunisia

South Korea

Singapore

Peru

Mexico

Ethiopia

Chile

Argentina


(Percent)

23.9

10.322.6

11.121.0

50.014.4

25.9

13.438.2

13.414.9

26.946.3

8.67.7

47.623.4

12.2

Figure 10-5c.

Labor Force Participation Rates for Women Aged 65+ in Developing Countries


Uruguay

Turkey

Tunisia

South Korea

Singapore

Peru

Mexico

Ethiopia

Chile

Argentina


(Percent)

6.7

4.78.9

6.56.5

27.511.8

14.68.5

19.2

6.55.2

10.621.4

4.83.5

35.113.3

3.6

Not surprisingly, agriculture is byfar the most common occupationfor older and elderly workers inmost developing countries (Figure10-6). And despite the worldwidetrend away from employment inagriculture, this sector was still animportant source of employment inmany developed countries duringthe 1970s and 1980s. Even in the1990s, a nontrivial proportion ofeconomically active elderly in somedeveloped countries worked in theagricultural sector. In 1995 inJapan, 31 percent of elderly menand 35 percent of elderly womenwere involved in agriculture.Aggregate data from the early1990s for 12 European Unionnations showed that agriculture


Figure 10-6.

Percent of Elderly Workers in Agriculture

Note: Data for New Zealand refer to ages 60 and over. Source: National sources.

United States, 1998

Turkey, 1990

Philippines, 1990

New Zealand, 1991

Japan, 1995

Ecuador, 1990

China, 1990

MaleFemale

3.2

88.393.2

57.030.030.7

34.721.2

15.376.4

32.275.7

95.6

11.4

Table 10-1.Older Workers (55 and Over) per 100 Younger Workers (Under 55) in Selected JobSectors: 1998

Goods-producing sector Service sector

Agriculture,hunting and Manu- Personal Social

Total forestry facturing Total services services

OECD average 15 39 10 12 11 12

Austria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 28 6 7 7 7Belgium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 21 5 7 8 7Canada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 27 10 10 9 10Czech Republic . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 12 9 10 9 13Denmark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 34 11 12 15 13

Finland. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 24 9 9 8 10France . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 20 6 8 10 8Germany . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 30 14 15 16 16Greece. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 68 11 11 12 9Ireland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 45 7 10 10 13

Italy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 33 8 13 12 13Korea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 131 8 13 (NA) (NA)Luxembourg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 19 6 7 5 10Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 28 8 11 13 7Netherlands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 21 8 7 6 8

New Zealand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 26 7 7 - 8Norway . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 36 16 15 9 18Portugal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 112 10 15 18 12Spain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 36 11 12 14 13Sweden . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 50 17 19 15 21

Switzerland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 39 18 17 20 18United Kingdom . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 32 14 13 14 14United States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 25 13 15 11 16

- Represents zero. NA Not available.

Source: Excerpted from Organization for Economic Co-Operation and Development (Employment Outlook 2000).

continued to employ a dispropor-tionate share of older relative toyounger workers (Eurostat, 1993a).More than 20 percent of economi-cally active men and women aged60 and older in these countriesworked in agriculture comparedwith about 5 percent of peopleaged 14 to 59. More recent infor-mation for 23 OECD countriesshows that the ratio of older (55+)to nonolder (54 and under) workersis generally much higher in agricul-ture, hunting, and forestry than inany other goods-producing or serv-ice sector (Table 10-1).

NEARLY TWO-THIRDS OFELDERLY FEMALE U.S.WORKERS IN SERVICE ANDSALES

Figure 10-7, which presents theoccupational distribution of elderlymale and female workers in theUnited States, shows distinct differ-ences by gender. In 1998, almosthalf of elderly working women wereemployed in clerical or service jobscompared with only 17 percent ofelderly men. A majority of workingelderly men held either manageri-al/professional/technical positions(34 percent) or production jobs (23 percent). Corresponding figuresfor elderly women were 25 percentand 8 percent. Unlike the situationin some developed countries, only11 and 3 percent of active elderlyU.S. men and women, respectively,worked in agriculture.

BRIDGES TO RETIREMENT

Just as the propensity to work atolder ages varies considerably fromcountry to country, so too do pat-terns of retirement and the concept

of retirement itself. During periods OLDER WOMEN MORE LIKELYof economic contraction in highly THAN OLDER MEN TO WORK

PART TIMEindustrialized nations, governmentsmay actively encourage older work- Some older workers use part-timeers to cease active employment at work as a gradual transition torelatively young ages. On the other retirement (Walker, 1999). Part-timehand, when the labor market is work is an option that may appealtight, governments may look for to older workers by enabling themmethods to entice older workers to to remain active in the labor forceremain in the labor force or re-enter while also pursuing leisure activitiesthe labor force. (Quinn and Kozy, 1996). Data for

working men aged 60-64 in nineIn developed countries, retirement

developed countries show large dif-from the workforce was an event

ferences in the prevalence of part-that occurred almost exclusively at

time employment, ranging froma regulated age until the 1950s,

less than 8 percent in Italy andwith little possibility of receiving a

Germany to more than 35 percentpension prior to that age (Tracy,

in Sweden and the Netherlands1979). Since then, countries have

(OECD, 2000). Available data fromadopted a wide range of approach-

developed countries suggest thates to providing old-age security,

older working women are muchand different potential routes have

more likely than older men to beemerged for people making the

involved in part-time work (Figuretransition from labor force participa-

10-8). In Australia, three-fourths oftion to retirement. Some of these

elderly women who were economi-different routes are working part

cally active in 1999 worked parttime, leaving career jobs for transi-

time, compared to fewer than halftion jobs, or leaving the labor force

of economically active elderly men.because of a disability.


Figure 10-7.

Percent Distribution of Elderly Workers by Occupation in the United States: 1998

Source: Bureau of Labor Statistics, unpublished tabulations from the Current Population Survey, average annual data, 1998.

Agriculture

Production

Clerical/Service

Sales

Managerial/Professional/

Technical

MaleFemale

3.2

33.824.7

14.816.7

16.947.8

23.27.6

11.4

In the 15 European Union countries gradual retirement is still relativelyas a whole, 41 percent of working uncommon in industrialized nations.women aged 55-64 were in part- The strongest tendency toward part-time positions in 1998, compared time work was seen in Japan,with just 8 percent of working men Sweden, and the United States. in that age group (Eurostat, 2000).

UNEMPLOYMENT LOW AMONG The rate of part-time work for peo- THE ELDERLYple nearing retirement generally was

The elderly typically have low lev-increasing with time in the late

els of unemployment compared to1980s/early 1990s (Eurostat,

younger workers. In developed1993b). Even though percentages

countries, unemployment rates forof older workers who work part

the elderly frequently are less thantime may be substantial, a recent

5 percent (OECD Labour ForceOECD (2000) analysis notes that

Statistics, 2000). However, peoplethese percentages often represent

aged 55 to 64 often have unem-only a small fraction of the total

ployment rates higher than or simi-older population, since many people

lar to rates for people aged 25 tohave retired by age 60. Looking at

54 (Figure 10-9). Establishing aolder male cohorts as they aged in

time trend in unemployment ratesthe 1990s, the study concludes that

for older people is hindered by

data availability, the effects of thebusiness cycle, and differences indefinitions across countries.3 Incountries with available data,unemployment rates for all agegroups commonly were higher in1999 than in 1980. Gender differ-ences in unemployment rates atolder ages are not consistent; insome countries, men have higherrates and in others the reverse istrue. When unemployment ratesfor ages 55 to 64 are disaggregat-ed, rates for the age group 55 to59 tend to be somewhat higherthan for the age group 60 to 64,perhaps because people in theolder age group may opt to retire ifpossible rather than be unemployed.

Although the unemployment ratemay be lower for older than foryounger workers, older people whoare unemployed tend to remainunemployed longer than theiryounger counterparts. In severalOECD countries, well over half ofunemployed people aged 55 andover had been unemployed continu-ously for more than 1 year. In mostOECD countries, the proportion oflong-term unemployed people aged55 and older is much higher thanamong younger age groups. A simi-lar pattern is seen in some EasternEuropean nations. In Bulgaria in1995, 74 percent of unemployedmen aged 50 to 59 and 78 percentof unemployed women aged 50 to54 had been without work for morethan 1 year (European Commission,1995).


3 And, in many developing countries, thelack of programs to provide monetary supportduring unemployment means that most peoplecannot “afford” to be unemployed.

Figure 10-8.

Percent of Economically Active Elderly Population Working Part Time in Australia, Canada, and France

Note: Data for France refer to ages 60 and over. Source: National sources.

74.2

53.2

38.6

44.1

33.2

20.7

France 1995Canada 1991Australia 1999

MaleFemale


Figure 10-9.

Unemployment for Three Age Groups: 1980, 1990, and 1999

Notes: Unemployment rates for people aged 65+ in Canada, Germany, Japan, and Sweden were reported to be zero in certain years. Latest data for Canada refer to 1998. 1980 data for Germany refer to West Germany. Source: Organization for Economic Co-Operation and Development, 2000 (Labor Force Statistics 1979-1999).

Male Female

1980 1990 1999

7.2 7.0

2.7

6.9 6.7

2.9

7.26.2

1.5

7.6

5.75.1

4.4

1.8

6.8

5.1

65+55-6425-5465+55-6425-54

(Percent)

Canada

Male Female



7.3

12.8

0.8

8.7

15.5

2.2

3.6

6.5

0.4

5.8

8.1

0.6

2.0

4.9

3.8

5.9

65+55-6425-5465+55-6425-54

Germany

3.0 2.7 3.0 3.42.6

3.2

4.63.8

3.0

4.6

2.8 3.1

5.1

3.4 3.1

6.0

3.3 3.1

65+55-6425-5465+55-6425-54

United States

6.57.3

5.9 5.9

1.3 1.3 1.0 1.2 1.6 1.31.21.6 1.7 1.7

65+55-6425-5465+55-6425-54

Sweden

3.7

6.7

2.9

4.4

3.3

0.51.4

3.4

1.42.1

1.41.5

3.7

2.2 2.01.2

65+55-6425-5465+55-6425-54

Japan

9.0 8.7

1.9

12.6

8.7

1.5

5.9 6.0

0.5

10.7

7.6

0.8

2.8

4.8

0.5

6.3 6.2

0.6

65+55-6425-5465+55-6425-54

France

Age group Age group

DISCOURAGEMENT REDUCES there is no work available orNUMBER OF OLDER WORKERS because they do not know where to

look. Workers who become dis-The definition of discouraged work-couraged from actively seekinger differs somewhat from country towork are no longer considered partcountry, but the basic conceptof the economically active popula-refers to people who are no longertion. In some countries,looking for work because they think

discouragement of older workers isthought to be related to changes inoccupational structure and the sub-sequent need for a more-educatedworkforce which favor youngerover older workers.

Cross-national data on discouragedworkers are fairly sparse. One com-parison of 13 countries for 1993indicates that older workers makeup a disproportionate share of alldiscouraged workers, except inSweden. Illustrative data for six ofthese countries (Figure 10-10) showthat while people aged 55 to 64account for a small proportion of alleconomically active people, theyaccount for a much larger propor-tion of all discouraged workers,especially in the United Kingdomwhere more than two-thirds of alldiscouraged male workers wereaged 55 to 64. In countries withdata over time, discouraged olderworkers were more numerous inthe early 1990s than in the early1980s. Discouragement seems tobe more permanent among olderworkers, as they are less likely tore-enter the labor force than theiryounger counterparts. Survey datafor 1990 for Belgium and Franceshow that more than half of menaged 55 to 59 who had lost theirjobs in the 3 years preceding thesurveys were no longer in the laborforce (OECD, 1995). The correspon-ding figure for all workers was clos-er to one-quarter. Because of thedifficulties older people face inobtaining a new job, discourage-ment often becomes a transitionfrom unemployment to retirement.


Figure 10-10.

Older Share of Economically Active Population and Discouraged Worker Population: 1993

Note: Data for Norway include persons aged 64-74; data for the United States include people aged 65 and over.Sources: Organization for Economic Co-Operation and Development, Employment Outlook 1995 and International Labour Office Yearbook of Labour Statistics, 1994.

Females

Males

Female

Male

Female

Male

Female

Male

Female

Male

Female

Male

(In percent)Economicallyactive peopleaged 55-64 asa percent ofall economicallyactive peopleaged 25-64

Australia

Canada

Mexico

Discouragedworkers aged55-64 as a percentof all discouragedworkers aged25-64

United States

Denmark

United Kingdom

24

1155

729

1150

942

1344

1153

1236

826

1469

1253

1226

11

INVALIDITY AND DISABILITYPROGRAMS MAY BE AVENUESTO RETIREMENT

Another path to retirement for olderworkers has been disability pro-grams. In Europe during the lastthree decades, economic recessionsand high unemployment led somegovernments (e.g., Germany, theNetherlands, Sweden) to encourageretirement by means of publicmeasures such as disabilityschemes and long-term sicknessbenefits. In many countries in thelate 1980s and early 1990s, disabil-ity pensioners made up the largestproportion of all early pensioners(OECD, 1992). Data for 1990showed that the proportion of olderpeople receiving an invalidity bene-fit could be very large, e.g., nearlyone-third of all people aged 60 to64 in Finland and Sweden, andnearly half of the same age groupin Norway (OECD, 1995). Whilenumerous nations have modified orrevamped their disability/invalidityprograms during the last decade, itappears likely that the varyingnational provisions of such pro-grams have an impact on retirementpatterns. Comparative data for 16European countries in the mid-1990s (Figure 10-11) show that thepercentage of older retired menwho retired due to their own illnessor disability ranged from 2 percentin Portugal to 29 percent inSwitzerland.

ACTUAL RETIREMENT AGEOFTEN LOWER THANSTATUTORY AGE

Over several decades, many indus-trialized nations lowered the stan-dard age at which people become

fully entitled to public pension awarded. In spite of the loweringbenefits. These reductions were of statutory retirement ages, thepropelled by a combination of fac- actual average age of retirement istors including general economic lower than the statutory age in aconditions, changes in welfare phi- large majority of industrializedlosophy, and private pension countries. Of the 24 countries intrends. The proliferation of early Table 10-2, the actual age exceedsretirement schemes has increased the standard age only in Greece,the number and usually the propor- Japan, and Turkey, and also intion of older workers who avail Iceland for men and in Italy forthemselves of such programs (Tracy women. In several countries (e.g.,and Adams, 1989). Austria, Belgium, and Finland), the

average man retires 6 years or moreOne important issue for policymak-

before the standard retirement age.ers and pension funds is the rela-

Differences are often greater fortionship between the standard

women, approaching 10 years in(statutory) retirement age and “actu-

Luxembourg and the Netherlands. al” retirement age, the average ageat which retirement benefits are


Figure 10-11.

Percent of Retired Men Aged 55 to 64 Who Left Last Job Due to Own Illness or Disability: 1995-96

Source: Excerpted from Organization for Economic Co-Operation and Development (Employment Outlook, 2000).

Portugal

Austria

Greece

Italy

Sweden

France

Belgium

Denmark

Ireland

Netherlands

Luxembourg

Spain

United Kingdom

Germany

Finland

Switzerland

2.1

28.9

25.0

22.9

22.8

18.3

16.6

15.6

15.1

9.5

7.7

7.3

7.0

5.2

4.1

2.6

TREND IN EARLY RETIREMENT health of older workers were twoMAY BE CHANGING other factors said to have increased

early retirement. More recentThe downward shift in the statutoryresearch, however, discounts theage at retirement during the 1970simportance of these factors (Levineand 1980s in developed countriesand Mitchell, 1993; Blondal andwas accompanied by an increase inScarpetta, 1998; Fronstin, 1999)the number of public early retire-and points instead to changes inment programs and a correspon-social security/private pension pro-ding increase in the number ofvisions as well as to improved eco-retirees leaving the labor force priornomic status of older workers andto the statutory age. Some coun-increases in wealth overall. Astries promoted early retirement as aRuggles (1992) has noted in themeans of offsetting persistentlycontext of the United States, com-high levels of unemployment. Inparisons of today’s elderly with theDenmark, for example, a voluntaryelderly in previous decades suggestearly retirement scheme was con-great increases in economic status.structed to encourage older work-People entering the ranks of theers to leave the labor marketelderly have higher educational(Petersen, 1991). Mandatory retire-attainment, higher-paid employmentment practices and worseninghistories, and higher average

income than did earlier cohorts ofelderly.

Some nations have raised (or areconsidering an increase in) statutoryretirement age as one means of off-setting the fiscal pressures of popu-lation aging,4 in addition to foster-ing policies that encourage laborforce participation at older ages.The effect of such actions is not yetcertain. Data for nine OECD coun-tries from 1975 to 1990 reveal ageneral downward trend in actualretirement age during the period1975-1990, with an apparent level-ing off in the latter part of the peri-od. Gendell’s (1998) analysis ofGermany, Japan, Sweden, and theUnited States generally supportsthis picture (Figure 10-12).However, several studies haveargued that the early retirementtrend in the United States hasstopped (Smeeding and Quinn,1997; Burkhauser and Quinn, 1997;Quinn, 1997). Furthermore, a recentOECD (2000) analysis of employ-ment rates notes that the rates formen aged 55 to 59 and 60 to 64have increased slightly in the late1990s in both the United States andthe Netherlands, and have stoppeddeclining in Canada, Germany,Finland, Japan, Sweden and theUnited Kingdom. The OECD studysuggests that this change is relatedto the secular economic upturn inthe latter 1990s.


4 In the United States, for example, theSocial Security system was revised in 1983 toestablish higher statutory retirement ages forpeople born after 1937 (i.e., who reach age 65after the year 2002). An individual’s retirementage is linked to year of birth; beginning in theyear 2003, the “normal” retirement age of 65will edge higher in small increments until reach-ing 67 years in the year 2025 (Robertson,1992). Germany’s 1992 Pension Act also pro-vides for a progressive increase in pensionableage beginning at the turn of the century.

Table 10-2.Standard and Actual Retirement Age in 24 Countries:1995

CountryMale Female

Standard Actual Standard Actual

Australia . . . . . . . . . . . . . . . . . . . . . . . . . . .Austria . . . . . . . . . . . . . . . . . . . . . . . . . . . .Belgium . . . . . . . . . . . . . . . . . . . . . . . . . . .Canada . . . . . . . . . . . . . . . . . . . . . . . . . . .Denmark . . . . . . . . . . . . . . . . . . . . . . . . . .Finland . . . . . . . . . . . . . . . . . . . . . . . . . . . .France . . . . . . . . . . . . . . . . . . . . . . . . . . . .Germany . . . . . . . . . . . . . . . . . . . . . . . . . .Greece . . . . . . . . . . . . . . . . . . . . . . . . . . . .Iceland . . . . . . . . . . . . . . . . . . . . . . . . . . . .Ireland . . . . . . . . . . . . . . . . . . . . . . . . . . . .Italy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Japan . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Luxembourg . . . . . . . . . . . . . . . . . . . . . . .Netherlands. . . . . . . . . . . . . . . . . . . . . . . .New Zealand. . . . . . . . . . . . . . . . . . . . . . .Norway . . . . . . . . . . . . . . . . . . . . . . . . . . . .Portugal . . . . . . . . . . . . . . . . . . . . . . . . . . .Spain . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Sweden . . . . . . . . . . . . . . . . . . . . . . . . . . .Switzerland . . . . . . . . . . . . . . . . . . . . . . . .Turkey . . . . . . . . . . . . . . . . . . . . . . . . . . . .United Kingdom . . . . . . . . . . . . . . . . . . . .United States . . . . . . . . . . . . . . . . . . . . . .

656565656765606562676662606565626765656565606565

61.858.657.662.362.759.059.260.562.369.563.460.666.558.458.862.063.863.661.463.364.663.662.763.6

6060606567656065576766575865656267

62.5656562556065

57.256.554.158.859.458.958.358.460.366.060.157.263.755.455.358.662.060.858.962.160.666.659.761.6

Note: The standard age of retirement (also called the statutory age) refers to the ageof eligibility for full public pension benefits. The actual age reflects the estimated averageage of transition to inactivity among older workers.

Source: Organization for Economic Co-Operation and Development, 1998 (AgeingWorking Paper 1.4).


Figure 10-12.

Average Age at Labor Force Exit in Four Countries: Late 1960s to Early 1990s

Source: Gendell, 1998.

Male

Female

Male

Female

Male

Female

Male

Female

Germany Sweden

Japan United States

0

55

60

65

70

1995199019851980197519701965

Age

0

55

60

65

70

1995199019851980197519701965

Age

0

55

60

65

70

1995199019851980197519701965

Age

0

55

60

65

70

1995199019851980197519701965

Age

ADULTS SPENDING GREATER years before entry into the labor number of years in retirement hadPORTION OF LIFE IN market (primarily spent in school); jumped to 12. Unlike the trend forRETIREMENT years not in work due to unemploy- men, the average number of years

Gains in life expectancy during the ment and/or economic inactivity; in employment for women has been

twentieth century have intersected years in the labor force; and years increasing, reflecting the temporal

with declining retirement ages to in retirement. Figure 10-13 shows changes in female labor force par-

produce an increase in the propor- that in 1960, men on average could ticipation described earlier. At the

tion of an individual’s life spent in expect to spend 46 years in the same time, the amount of time

retirement. The OECD, using an labor force and a little more than women live after reaching retire-

average of unweighted data for 15 1 year in retirement. By 1995, the ment age increased greatly, from

member countries, has decomposed number of years in the labor force 9 years in 1960 to more than

the life course into four states: had decreased to 37 while the 21 years in 1995.


Figure 10-13.

Decomposition of the Life Course, OECD Average: 1960 to 1995

Note: Based on an unweighted average of data for 15 member countries, using average life expectancies and labor force patterns as they existed for the years shown. These graphs are illustrative of overall trends, and should not be construed as representing the experience of any particular age cohort. Source: Organization for Economic Co-Operation and Development, 1998b.

Male Female

0

10

20

30

40

50

60

70

80

90

19951990198019701960

Age

0

10

20

30

40

50

60

70

80

90

19951990198019701960

Age

Age of entry inthe labormarket

Age ofretirement

Years in employment

Years in retirement

Years in employment

Years in retirementLife expectancy

Age of entry inthe labormarket

Age ofretirement

Life expectancy

Years not in work

Years not in work

Years before the labor market Years before the labor market

PUBLIC PENSION SYSTEMPROVISIONS SOMETIMESINDUCE EARLY RETIREMENT

Research has begun to considernational differences among laborforce participation at older ages asa consequence (intended or unin-tended) of retirement provisionsand/or tax policy. In some coun-tries, retirement benefit paymentsare increased for people who post-pone their retirement beyond theallowable early retirement age. Inother countries, there is no futurebenefit to be gained by postponingretirement. One synthesis of vari-ous studies in industrialized nations(Gruber and Wise, 1999) looked atthe “implicit tax on work,” a con-cept which contrasts the longerstream of future benefit paymentsthat a worker would receive byretiring at an early age versus theshorter stream of future paymentsthat a worker might receive bydelaying his/her retirement. InFrance, for example, social securitybenefits are first available at age60, and there is no increase in the

eventual benefit payment rate for benefits may be initially obtained atpeople who retire after age 60. In age 62, but the benefit paymentthe United States, social security rate is less than if a worker retires


Figure 10-14.

Implicit Tax Rate on Work in France and the United States: Circa 1995

Source: Gruber and Wise, 1999. Reproduced with permission from graphs in "Social Security and Retirement Around the World," Research Highlights in the Demography and Economics of Aging, Issue No. 2, June 1998.

-60

-30

0

30

60

90

7068666462605856

Percent

Age

France

United States

later, e.g., at age 65. Figure 10-14 States. The age-specific retirementcompares the implicit tax rates on age in France shows a steep jumpwork in France and the United in retirement at age 60, which not

surprisingly corresponds to thelarge implicit tax rise at that age.

The same study also considered a“tax force to retire,” defined as thetotal of the annual tax rates onwork between the ages of 55 and69. Plotting this variable against ameasure of unused productivecapacity (simply, the percentage ofpeople aged 55 to 65 who were notworking) reveals a strong cross-national relationship between thetwo (Figure 10-15). This findingsuggests that the financial structureof national social security systemsmay reward early retirement, andthat attempts to encourageincreased labor force participationat older ages may be largely contin-gent upon policy changes in thesesystems. This study also highlightsthe potential power of focusing onsystem design features, and standsas a powerful example of theimportance of cross-nationalresearch on aging-related issues.


Figure 10-15.

Tax Rates and Unused Capacity in 11 Developed Countries: Circa 1995

Source: Gruber and Wise, 1999. Reproduced with permission from graphs in "Social Security and Retirement Around the World," Research Highlights in the Demography and Economics of Aging, Issue No. 2, June 1998.

Unused productive capacity (55-65), in percent

Tax force to retire (55-69)

0

10

20

30

40

50

60

70

80

109876543210

United States

Japan

Canada

Sweden

Spain

France

Germany

Netherlands

Belgium

Italy

United Kingdom


CHAPTER 11.

Pensions and Income Security

Public pensions have become the retirement age. This example is tional transfers to provide adequatefinancial lifeline of the elderly in based on average ages of retire- retirement income for older citi-many societies. While some ment for employees in 1995 esti- zens. The number of countriesEuropean public pension systems mated by the Organization for with an old age/disability/survivorsdate back to the end of the nine- Economic Co-Operation and program increased from 33 in 1940teenth century, current systems are Development (OECD) and popula- to 167 in 1999 (Figure 11-2). Thethe result of changes instituted tion age/sex structures for 2000 World Bank (1994) has estimatedlargely after World War II. The most and 2030 estimated and projected that formal public programs provideobvious and, to governments, most by the U.S. Census Bureau. The coverage for approximately 30 per-worrisome consequence of project- numerator of the ratio comprises all cent of the world’s older (aged 60ed population aging will be an people at or over the average age and over) population, with some 40increase in budgetary outlays in the of retirement in each country, and percent of the world’s working-ageform of old-age pension payments, the denominator all people between population making contributionsespecially in those countries in the age of 20 and the average toward that support.which public pensions are predomi- retirement age, assuming no

LABOR FORCE PENSIONnately financed on a pay-as-you-go change in the average age of retire-COVERAGE VARIES FROMbasis. Increases in migration also ment between 2000 and 2030. TheUNIVERSAL TO NIL

are prompting governmental con- ratio increases notably over time incern about the “exporting” of cash all cases, and more than doubles Mandatory old-age pension plans

benefits to retirees in other coun- for men in the Netherlands. now cover more than 90 percent of

tries (Bolderson and Gains, 1994). the labor force in most developedPUBLIC OLD-AGE SECURITYMany nations, both developed and countries. Governments are respon-SYSTEMS PROLIFERATINGdeveloping, are now reconsidering sible for mandating, financing, man-

their existing old-age security sys- Since the Second World War, public aging, and insuring public pensions.

tems, often with an eye toward pension plans have played an Public pension plans usually offer

introducing or strengthening private increasingly important role in pro- defined benefits that are not tied to

pension schemes. viding retirement income to older individual contributions, but rather,

people. Old-age pension schemes are financed by payroll taxes. ThisDEMOGRAPHIC CHANGE have become social institutions in arrangement is commonly referredALONE MAY DOUBLE many if not most countries through- to as a “pay-as-you-go” system inso-RETIREE/WORKER RATIO

out the world. The goal of most far as current revenues (taxes onThe potential effect of demographic public old-age pension schemes is working adults) are used to financechange on future retired popula- to provide all qualifying individuals the pension payments of peopletion/worker ratios, holding other with an income stream during their who are retired from the labor forcefactors constant, may be approxi- later years, income which is: 1) (Mortensen, 1992).mated in various ways. The most continuous; 2) adequate; 3) con- Most pay-as-you-go systems incommonly used indicator, as dis- stant, in terms of purchasing industrialized countries initiallycussed in Chapter 8, is an elderly power; and 4) capable of maintain- promised generous benefits.support ratio which contrasts one ing the socioeconomic position of These pension programs, at theirpopulation segment (people aged the retired in relation to that of the inception, were based on a small65 and over) to another (people active population (Nektarios, 1982). number of pensioners relative to aaged 20 to 64). One variation on

The major impetus for development large number of contributorsthis theme, shown in Figure 11-1

of public pension systems, particu- (workers). As systems matured,for 10 developed countries, allows

larly in industrialized countries, was ratios of pensioners to contributorsfor national differences in average

the inability of private intergenera- grew and in some countries

became unsustainable, particularlyduring periods of economic stag-nation. One result of suchchanges was the development ofprivate pension systems to com-plement public pension systems(Fox, 1994). Other measures takenor considered have includedincreasing worker contributionrates, restructuring or reducingbenefits, and raising the standardage of retirement (ISSA, 1993;Holtzmann and Stiglitz, 2001).

In developing countries, public pen-sion systems typically cover a muchsmaller fraction of workers than inindustrialized nations (Figure 11-3).Even economically vibrant societiessuch as Hong Kong and Thailandoffer no publicly supported, compre-hensive retirement pension scheme(Bartlett and Phillips, 1995;Domingo, 1995). In many cases,coverage in developing countries isrestricted to certain categories ofworkers such as civil servants, mili-tary personnel, and employees inthe formal economic sector. Rural,predominantly agricultural workershave little or no pension coverage inmuch of the developing world,although some governments havetaken steps to address this situa-tion. Each state in India, for exam-ple, has implemented an old agepension scheme for destitute peoplewith no source of income and nofamily support (Kumar, 1998). Whilepension amounts are minimal andcoverage far from universal, the for-mal institution of such a systemaffords a nation a foundation uponwhich to expand future coverage.


Figure 11-1.

Ratio of Retirement-Age to Working-Age Population in Ten Countries: 2000 and 2030

Note: Ratios represent the number of persons at or above average retirement age per 100 persons between age 20 and the average retirement age in 1995. Each national average is shown in parentheses. Sources: OECD, 1998 (Aging Working Paper 1.4) and U.S. Census Bureau, 2000a.

United States (63.6)

United Kingdom (62.7)

Spain (61.4)

Netherlands (58.8)

Japan (66.5)

Italy (60.6)

France (59.2)

Finland (59.0)

Denmark (62.7)

Australia (61.8)

United States (61.6)

United Kingdom (59.7)

Spain (58.9)

Netherlands (55.3)

Japan (63.7)

Italy (57.2)

France (58.3)

Finland (58.9)

Denmark (59.4)

Australia (57.2)

(Average retirement age shown in parentheses)

20002030

37

52

23

43

24

44

40

75

34

57

35

63

21

41

30

63

30

54

26

45

20

40

72

42

69

46

81

48

80

58

105

3565

50

96

46

85

44

71

31

Male

Female

Informal (usually family) systemsprovide the bulk of social supportfor older individuals in many coun-tries, particularly in Africa andSouth Asia. As economies expandand nations urbanize, informal sup-port systems such as extended fam-ily care and mutual aid societieshave tended to weaken. A majorchallenge for governments in devel-oping nations is to effect the expan-sion of formal-system coverage(especially in rural areas) whilemaintaining support for extantinformal mechanisms.

HOW GENEROUS ARE PUBLICPENSIONS?

The “value” of pensions can be con-strued and measured in differentways, depending on how many andwhich people in a given householdrely on pension income, the taxablestatus of such income, the type ofjob a retiree was engaged in, thelevel of pension income in a givensociety vis-a-vis other benefits suchas universal health care, and soforth. The concept of “replacementrate” is often used as a measure ofhow much of a person’s pre-retirement income is supplied byher/his pension. MacKellar andMcGreevey (1999) note that, inindustrialized countries, the aver-age pension rose from 14 percentof the average wage in 1930 to 55percent in 1980. A comparison ofgross income replacement of socialsecurity and other compulsoryretirement pension programs in 12 European nations circa 1990(International Benefits Information


Figure 11-2.

Number of Countries With Public Old-Age/Disability/Survivors Program: 1940 to 1999

Source: U.S. Social Security Administration, 1999.

33

44

58

97

123

135

167

1999198919791969195819491940

Figure 11-3.

Percent of Labor Force Covered by Public Old-Age Pension Program: Circa 1995

Source: World Bank, 1998.

Italy

Germany

Russia

Poland

Brazil

Jordan

South Korea

Morocco

Zambia

Nigeria

96

1

10

21

30

40

50

66

72

94

Service, 1993) revealed that replace-ment rates ranged from 46 percentto 102 percent, based on averageannual pay for a manufacturingworker with dependent spouse.

For reasons mentioned above, thereis no single replacement rate in anynational retirement program, andcross-national comparisons there-fore are difficult. For comparativepurposes, however, the OECD hasconstructed, for 1995, a syntheticindicator of the expected grossreplacement rate (as a percent ofearnings) for a 55-year-old individ-ual who retires at the standard ageof entitlement to a public pension.This indicator takes account of twoearnings levels (average and two-thirds of average) and two types ofhouseholds (single earner andworker with a dependent spouse).Pensions in some countries can beexpected to replace a large percent-age of earnings, and even to matchor exceed the latter in Greece andSpain. At the other end of the spec-trum are Australia and Ireland,where the public-pension replace-ment rates are on the order of 40 percent. For the majority ofcountries examined, the expectedreplacement rates are about one-half to two-thirds of pre-retirementincome (Figure 11-4).


Figure 11-4.

Expected Old-Age Public Pension Replacement Rate in 26 Countries: 1995

Note: Synthetic indicator based on different earning levels and household types; see text and source for more detail. Source: OECD, 1998 (Aging Working Paper 1.4).

(Percent)

United States

United Kingdom

Switzerland

Sweden

Spain

Portugal

Poland

Norway

New Zealand

Netherlands

Luxembourg

Japan

Italy

Ireland

Iceland

Hungary

Greece

Germany

France

Finland

Denmark

Czech Republic

Canada

Belgium

Austria

Australia

56

41

80

68

52

53

56

60

65

55

120

5593

40

80

5293

46

61

6054

83

100

74

49

50

PUBLIC PENSIONS ABSORBONE-SEVENTH OF GDP IN SOMECOUNTRIES

The cost of public pensions general-ly is greatest among industrialnations, most of which have pay-as-you-go systems. Pension expendi-ture had, on average, come toexceed 9 percent of gross domesticproduct (GDP) in OECD nations inthe early 1990s, and represented 8percent of GDP in Eastern Europe.Between 1960 and 1990, one-quarter of the increase in total pub-lic expenditure in OECD countrieswas growth in pension expenditure;on average, the latter grew twice asfast as did GDP. By 1996, publicpension spending in Italy andUruguay had reached 15 percent ofGDP (Palacios and Pallares-Miralles,2000). Expenditure levels typicallyare much lower in most developingcountries (Figure 11-5), where rela-tively younger populations andsmaller pension programs do notyet place large demands on GDP.

ADMINISTRATIVE COSTS OFPUBLIC PENSION SYSTEMSHIGH IN SOME DEVELOPINGCOUNTRIES

The cost of administering a publicpension scheme is an important fac-tor in the scheme’s overall efficacy.In many developing countries,administrative costs as a percent oftotal old-age benefits have beenhigh (e.g., 10-15 percent in Braziland Turkey) relative to the devel-oped world — administrative costsas a percent of old-age benefits areless than 2 percent in most OECDcountries. In many developedcountries, the cost/benefit ratiodeclined in the 1970s and early


Figure 11-5.

Public Pension Expenditure as a Percent of Gross Domestic Product in 25 Countries: Circa 1996

Source: Palacios and Pallares-Miralles, 2000.

Cote d'Ivoire, 1997Mexico, 1996

Togo, 1997Uganda, 1997Ecuador, 1997Vietnam, 1998Algeria, 1997

Sri Lanka, 1996China, 1996

Turkey, 1995Australia, 1995

Brazil, 1996Kazakhstan, 1997

Russia, 1996Israel, 1996

Cyprus, 1996Japan, 1995

United States, 1995Hungary, 1996

United Kingdom, 1995Croatia, 1997

Germany, 1995France, 1995

Uruguay, 1996Italy, 1995

0.3

15.015.0

13.312.0

11.610.2

9.77.2

6.66.4

5.95.7

5.04.74.6

3.72.7

2.42.1

1.61.0

0.80.6

0.4

Figure 11-6.

Net Administrative Fees as a Percent of Total Contributions in Eight Latin American Individual-Account Systems: 1999

Source: James, Smalhout and Vittas, 2001.

Bolivia

Colombia

Uruguay

Chile

El Salvador

Peru

Mexico

Argentina

5.5

23.0

22.1

19.0

17.6

15.6

14.3

14.1

1980s (Estrin, 1988) as a result of:1) government austerity programsthat helped contain administrativecosts; 2) increases in total benefitexpenditures, reflecting not onlythe maturation and/or expansion ofprograms but also the impact ofinflation; and 3) greater use of com-puters for the processing of bene-fits, with corresponding gains inefficiency.

The World Bank (1994) compiledinformation on administrative costsper participant in publicly managedpension plans as a percent of percapita income in the early 1990s,demonstrating that such costs wereconsiderably higher in lower-incomecountries. For example, costs perparticipant as a percent of nationalper capita income were 8 percent inTanzania, 7 percent in Burundi, and2.3 percent in Chile, compared withone-tenth of 1 percent or less inSwitzerland and the United States.These data illustrate the importanceof an educated labor force, commu-nications infrastructure, and otheradvanced technological input to thepension production function. Morerecently, James, Smalhout, andVittas (2001) estimated the netadministrative fee in individualaccount systems as a percent of aperson’s total contribution in eightLatin American countries (Figure 11-6). These fees were in double dig-its in seven of the eight nations asof 1999, and exceeded 20 percentin Argentina and Mexico.

ROUGHLY ONE-THIRD OF OECD WORKERS COVERED BYOCCUPATIONAL PENSION PLANS

While public pension systems aremore widespread than occupationalpension plans, the latter are grow-ing in coverage. Occupationalpension plans tend to be a moreimportant source of retirementincome than public pensions for

high income workers in developedcountries. About one-third of thelabor force in OECD countries wasenrolled in occupational pensionplans circa 1990, but a muchsmaller proportion is covered inmost developing countries and tran-sitional economies, where employ-er-sponsored schemes tend to coveronly public-sector workers (WorldBank, 1994).

Cross-national estimates of occupa-tional-scheme coverage among allworkers vary widely in the pub-lished literature, due in part to dif-ferent temporal references as wellas different definitions of what anoccupational scheme is.1 Mostoccupational plans are employer-specific, but in some nations (e.g.,Denmark and the Netherlands)plans are organized on an industry-wide basis, with compulsory partici-pation a result of collective bargain-ing. Switzerland requires all


1 For a useful discussion of occupationalpension schemes within the context of broaderretirement system reforms, see OECD, 1998,Ageing Working Paper 3.4.

employers to provide pension bene-fits for employees above a certainincome level. OECD estimates forthe early 1990s, compiled from var-ious sources, show occupationalscheme coverage in 19 industrial-ized countries ranging from 5 per-cent in Italy and Greece to 90 per-cent in Sweden and the Netherlands(OECD, 1998, Ageing Working Paper2.2).

Of course, not all workers who arecovered by occupational plans arein fact enrolled in them. Further,the percent of older people actuallyreceiving benefits from employer-provided plans is likely to be lowerstill, because many retirees eitherdid not have access to such plansduring their working years, or didnot participate for enough years tobecome vested. Whitehouse (2000)has compiled data on the percent-age of pensioners with income fromemployer-provided pensions ineight developed countries in thelate 1990s (Figure 11-7). In coun-tries where a gender breakdown is

Figure 11-7.

Percent of Pensioners With Income From Employer-Provided Pensions: Late 1990s

Source: Whitehouse, 2000.

United States

United Kingdom

Netherlands

Germany

Canada

Australia

MaleFemale

26

20

7

5431

21

9

7623

66

32

48


Box 11-1.Chile is the Developing-Country Model for Pension Privatization

Chile first enacted a public pension scheme in 1911, administered retirement fund (additional payrolland expanded its program following the European deductions are made for life insurance and fundsocial insurance model financed on a pay-as-you-go expenses). Workers themselves select from manybasis. Between 1960 and 1980, the ratio of pension- competing investment companies, are free to switchers to contributing workers increased from 9 per 100 their accounts, and have several options for with-to 45 per 100, due to rapidly changing demographics drawal and annuities upon retirement. To reduce mis-and increasing tax evasion on the part of employees management risks, the government assumes a majorand employers (Williamson, 1992). These changes, supervisory and regulatory role (Schulz, 1993).occurring in the context of a stagnant economy,

By most accounts, the Chilean experiment during itsresulted in a situation where the pension system was

initial decade was a success, with real annual returnsno longer able to meet current obligations. Faced

on contributions averaging in excess of 12 percentwith an increasingly bleak future scenario, the Chilean

during the 1980s. From 1995 to 1998, however,government in 1980 abandoned its public system in

annual rates of return were much lower and in favor of a compulsory savings plan administered by

2 years were negative, before rebounding in 1999private-sector companies.

(Figure 11-8). Overall, the long-term (19-year) aver-Since 1981, all wage and salary earners are required to age real return exceeds 11 percent. Observers havecontribute 10 percent of their earnings to a privately pointed out several drawbacks to the system, such as

high administrative costs,workers’ loss of freedom vis-a-vis one-tenth of their earn-ings, and the fact that even-tual income replacementrates are not guaranteed, i.e.,are reliant on investmentearnings that may suffer intimes of economic stagnation(Gillion and Bonilla, 1992).Nevertheless, many countriesin Latin America, EasternEurope, and Asia have adopt-ed or are seriously consider-ing aspects of the Chileansystem, or are experimentingwith variations on the theme(Kritzer, 2000; Fox andPalmer, 2001). Considerationof increased privatization ofsocial security systems isnow commonplace in muchof the developed world aswell, and has become a hotlydebated political topic.

Figure 11-8.

Real Rate of Return of Chile's Private Pension System: 1981 to 1999

Source: Reported in Palacios and Pallares-Miralles, 2000.

-5

0

5

10

15

20

25

30

1999199719951993199119891987198519831981

Percent

Average, 1981-1999:11.2%

available, the data show that menare much more likely to receivesuch benefits, as would be expect-ed from past gender patterns oflabor force participation.

Company-based pension programsin the developing world are foundmost frequently in former Britishcolonies and in countries with largemultinational subsidiaries. Mostsuch programs are subject to lessregulation and lower fundingrequirements than their counter-parts in industrialized countries,although both Indonesia and SouthAfrica have developed comprehen-sive and well-regulated private pen-sion systems. Coverage of private-sector workers is increasing in anumber of other large developingnations such as Brazil, India, andMexico (World Bank, 1994).

PRIVATE PENSION FUNDASSETS A MAJOR SOURCE OFLONG-TERM CAPITAL

Private pension fund assets aresizeable in many developed coun-tries. In 1998, such assets wereequivalent to more than 80 percentof GDP in the Netherlands, theUnited Kingdom, and the UnitedStates (Figure 11-9). Most occupa-tional-plan funds have been invest-ed in private-sector assets, areinternationally diversified, and haveearned higher returns than publiclymanaged funds (Davis, 1993;1998).

These funds have grown consider-ably over the last three decades.The average annual growth rate ofpension funds for OECD countriesas a whole between 1990 and 1996was 11 percent (OECD, 1998b).


Figure 11-9.

Private Pension Fund Assets as a Percent of GDP: 1970 and 1998

Note: Later Swiss figure refers to 1996. Sources: World Bank, 1994 and OECD, 2000.

United States

United Kingdom

Switzerland

Netherlands

Denmark

Canada

19701998

86

14

48

19

22

29

86

38

75

2184

29

Table 11-1.Payroll Tax Rates for Provident Fund Schemes:Early-to-Mid-1990s(Percentage of wages)

Country Employees Employer

AfricaThe Gambia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 10Ghana. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 12.5Kenya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 5Nigeria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 6Swaziland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 5Tanzania. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 10Uganda. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 10Zambia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 5

AsiaFiji . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 7India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 10Indonesia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 2Kiribati . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 5Malaysia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 11Nepal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 10Singapore . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-30 10Solomon Island. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 8Sri Lanka . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 12Western Samoa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 5

Latin AmericaArgentina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 0Chile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 0Colombia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 9Peru . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 0

Source: World Bank, 1994.

This increase is expected to contin- Where provident-fund coverage is nonmonetary indicators of welfare,ue for at least the short term, extensive, such funds may in effect and concluded that in all 12because many aging nations with be the public pension system. nations, the nonelderly were betterrelatively underdeveloped pre- off than the elderly (Tsakloglou,

The performance of provident fundsfunded systems have considerable 1996). Data for France, however,

globally has been erratic. In someroom for growth. The looming poli- suggest that extreme poverty

East Asian countries (notablycy question is whether population (below the level of guaranteed mini-

Singapore, which has the world’saging will depress rates of return mum income) is much less common

largest provident fund), funds typi-on private pension funds. As the among the elderly than among

cally have earned positive annuallarge post-World War II cohorts younger households (David and

investment returns. In othermove into retirement, they are Starzec, 1993).

nations, inflation and poor econom-expected to divest some of their

ic growth have lessened the value The OECD (2000) has concludedfinancial assets accumulated during

of fund contributions; in Sri Lanka, that there has been a stable ortheir working years. This prospect

for example, the real annual rate of improving economic picture forhighlights the importance of the

return for the Employee Provident older people, both in absolutenature of pension fund manage-

Fund in the 1980s and early 1990s terms and relative to the nonelderlyment, changes in government regu-

often was negative (International population. Poverty rates for olderlations, and the varying sociocultu-

Labour Office, 1993). Such perform- people have declined in mostral impetuses for retirement savings

ance has led several countries to nations, as has the share of older(OECD, 2000; National Research

abandon provident schemes in people among the poor. In theCouncil, 2001).

favor of defined-benefit pension United States, the overall situation

PROVIDENT FUNDS plans (Palacios and Pallares-Miralles, of elderly people improved dramati-

PARAMOUNT IN SOME 2000). cally during the last third of theDEVELOPING COUNTRIES twentieth century. Studies of real

ARE LIVING STANDARDS OF median household income (adjustedA provident fund is a form of com- THE ELDERLY CHANGING IN for household size) have demon-pulsory defined-contribution pro- DEVELOPED COUNTRIES?strated much larger gains for elder-gram wherein regular contributions

Given the maturation of public pen- ly people relative to the generalare withheld from employee wagessions systems, increases in the level population (Radner, 1995; McNeil,and invested for later repayment.of female labor force participation, 1998). And, poverty among thePayouts typically are in the form ofand the development of private elderly has declined. One-third ofa lump sum upon retirement, butpension schemes, one might expect all U.S. elderly were below themay also be made earlier in timesthat older citizens in industrialized poverty line in 1960; by the mid-of special need. Except in somenations are better off, economically, 1990s, the level had declined to Latin American countries, employ-than previous generations of elderly 10 percent, lower than among chil-ers match or exceed the employeepeople. And, there is a growing dren under the age of 18 (Friedlandcontribution. Although providentperception in some countries that and Summer, 1999).funds can cover private-sectorthe elderly as a whole are faring

workers, they are managed publicly. Data from the Luxembourg Incomebetter than other population sub-Study reveal considerable inter-Malaysia, in 1951, was the first groups. However, the complexity ofcountry variation in poverty ratesnation to establish a wide scale measuring economic well-beingamong elderly citizens. An analysisprovident fund, and other Asian often precludes a definitive assess-of standardized information fromnations (e.g., India, Singapore, and ment of these issues, and there isnine nations (Smeeding andSri Lanka) have had provident funds considerable concern about the will-Saunders, 1998) suggests thatfor more than 40 years. By the ingness and ability of households toCanada, Germany, and Hungary pro-mid-1990s more than 20 nations adequately save for retirementvide their elderly the best overallhad developed such schemes (Table needs (see, e.g., MacKellar, 2000).protection from poverty relative to11-1). None of these countries had One study of 12 European Unionthe other six countries (Figure a public pay-as-you-go system at countries in the late 1980s com-11-10). This analysis also highlightsthe time its provident fund was pared survey data on consumptionthe fact that overall figures mayestablished (World Bank, 1994). expenditure, income, and


mask large differences amongpopulation subgroups, as seen inthe data for elderly women livingalone. The economic vulnerabilityof single elderly women also hasbeen noted in a 14-country study ofdata from the European CommunityHousehold Panel (Heinrich, 2000).

One obviously important compo-nent of elderly living standards ishealth care and its costs. As thelatter have escalated in the 1990s, agrowing body of research hasfocused on identifying the costs ofspecific illnesses and on projectinghealth expenditures (see, e.g.,Cutler and Meara, 1999; Mayhew,1999; and OECD, 2000). Othermajor thrusts of current research inthe economics of aging seek: tomore fully and accurately measurelevels of household wealth andassets; to better assess differencesin these variables within popula-tions; and to understand transitionsin income and poverty status,particularly as they relate to chang-ing health status at older ages.Data from the European CommunityHousehold Panel Survey is begin-ning to shed light on the interplayof health status and retirement deci-sions of older European couples

(Jiminez-Martin, Labeaga, and the Health and Retirement Survey inGranado, 1999). In order to capture the United States (see Burkhauserthe complexity of such transitions and Gertler, 1995 for a comprehen-and understand their significance sive overview of this study, andfor policy planning, several nations National Research Council, 2001 forhave mounted (or are planning to future recommendations).initiate) longitudinal studies akin to


Figure 11-10.

Percent of Elderly Living in Households With Less Than 50 Percent of Adjusted National Median Disposable Income

Note: Percent for elderly women living alone in Japan is not reported. Source: Smeeding and Saunders, 1998.

United States, 1994

Taiwan, 1991

Poland, 1992

Japan, 1992

Hungary, 1995

Germany, 1989

Finland, 1991

Canada, 1991

Australia, 1990

All elderlyElderly womenliving alone

43

2962

716

1635

813

914

18

N/A11

19

2574

23


APPENDIX A.

Detailed Tables

Table 1.Total Population, Percent Elderly, and Percent Oldest Old: 1975, 2000, 2015, and 2030(In thousands)

Country

1975 2000

Totalpopulation

Percent of Percent ofpopulation population

65+ 80+

80+ as apercent of

65+Total

population


65+ 80+

80+ as apercent of

65+

United States . . . . . . . . . . . . . . .

Western EuropeAustria . . . . . . . . . . . . . . . . . . . . . . .Belgium . . . . . . . . . . . . . . . . . . . . . .Denmark . . . . . . . . . . . . . . . . . . . . .France . . . . . . . . . . . . . . . . . . . . . . .Germany . . . . . . . . . . . . . . . . . . . . .Greece. . . . . . . . . . . . . . . . . . . . . . .Italy. . . . . . . . . . . . . . . . . . . . . . . . . .Luxembourg . . . . . . . . . . . . . . . . . .Norway . . . . . . . . . . . . . . . . . . . . . .Sweden . . . . . . . . . . . . . . . . . . . . . .United Kingdom . . . . . . . . . . . . . . .

Eastern EuropeBulgaria . . . . . . . . . . . . . . . . . . . . . .Czech Republic . . . . . . . . . . . . . . .Hungary. . . . . . . . . . . . . . . . . . . . . .Poland . . . . . . . . . . . . . . . . . . . . . . .Russia . . . . . . . . . . . . . . . . . . . . . . .Ukraine . . . . . . . . . . . . . . . . . . . . . .

North America/OceaniaAustralia . . . . . . . . . . . . . . . . . . . . .Canada . . . . . . . . . . . . . . . . . . . . . .New Zealand . . . . . . . . . . . . . . . . .

AsiaBangladesh. . . . . . . . . . . . . . . . . . .China . . . . . . . . . . . . . . . . . . . . . . . .India . . . . . . . . . . . . . . . . . . . . . . . . .Indonesia. . . . . . . . . . . . . . . . . . . . .Israel . . . . . . . . . . . . . . . . . . . . . . . .Japan . . . . . . . . . . . . . . . . . . . . . . . .Malaysia . . . . . . . . . . . . . . . . . . . . .Pakistan. . . . . . . . . . . . . . . . . . . . . .Philippines. . . . . . . . . . . . . . . . . . . .Singapore . . . . . . . . . . . . . . . . . . . .South Korea . . . . . . . . . . . . . . . . . .Sri Lanka. . . . . . . . . . . . . . . . . . . . .Thailand. . . . . . . . . . . . . . . . . . . . . .Turkey . . . . . . . . . . . . . . . . . . . . . . .

Latin America/CaribbeanArgentina. . . . . . . . . . . . . . . . . . . . .Brazil . . . . . . . . . . . . . . . . . . . . . . . .Chile. . . . . . . . . . . . . . . . . . . . . . . . .Colombia . . . . . . . . . . . . . . . . . . . . .Costa Rica . . . . . . . . . . . . . . . . . . .Guatemala . . . . . . . . . . . . . . . . . . .Jamaica . . . . . . . . . . . . . . . . . . . . . .Mexico . . . . . . . . . . . . . . . . . . . . . . .Peru . . . . . . . . . . . . . . . . . . . . . . . . .Uruguay. . . . . . . . . . . . . . . . . . . . . .

AfricaEgypt . . . . . . . . . . . . . . . . . . . . . . . .Kenya. . . . . . . . . . . . . . . . . . . . . . . .Liberia . . . . . . . . . . . . . . . . . . . . . . .Malawi . . . . . . . . . . . . . . . . . . . . . . .Morocco. . . . . . . . . . . . . . . . . . . . . .Tunisia . . . . . . . . . . . . . . . . . . . . . . .Zimbabwe . . . . . . . . . . . . . . . . . . . .

220,165

7,5799,7965,060

52,69978,679

9,04755,441

3624,0078,193

56,226

8,7229,997

10,53234,022

134,23349,016

13,90023,209

3,083

76,582927,808620,701135,666

3,455111,52412,25874,73443,010

2,26335,28113,60341,35940,025

26,049108,167

10,33725,381

1,9686,0182,013

59,09915,161

2,829

38,84113,741

1,6095,244

17,3055,6686,143

10.5

14.913.913.413.514.812.212.013.013.715.114.0

10.912.912.6

9.58.9

10.5

8.78.48.7

3.64.43.83.27.87.93.73.02.74.13.64.13.04.5

7.63.95.33.63.42.85.84.03.59.6

4.23.73.72.23.73.52.6

2.1

2.32.32.42.52.22.11.92.22.52.72.4

1.41.71.71.21.21.6

1.51.61.4

0.30.60.30.31.01.10.50.30.40.40.40.50.30.4

0.90.50.80.40.50.40.80.70.31.6

0.40.50.90.20.50.50.3

20.4

15.516.418.018.314.617.116.017.018.217.817.0

12.813.513.312.414.015.0

17.419.316.4

8.412.5

8.18.6

12.313.513.310.913.4

9.710.113.210.9

7.9

12.112.514.511.813.613.114.517.9

9.116.9

9.712.823.3

8.014.213.1

9.9

275,563

8,13110,242

5,33659,33082,79710,60257,634

4374,4818,873

59,508

7,79710,27210,13938,646

146,00149,153

19,16531,278

3,820

129,1941,261,8321,014,004

224,7845,842

126,55021,793

141,55481,160

4,15247,47119,23961,23165,667

36,955172,860

15,15439,686

3,71112,640

2,653100,350

27,0133,334

68,36030,340

3,16410,38630,122

9,59311,343

12.6

15.416.814.916.016.217.318.114.015.217.315.7

16.513.914.612.312.613.9

12.412.711.5

3.37.04.64.59.9

17.04.14.13.66.87.06.56.46.0

10.45.37.24.75.23.66.84.34.7

12.9

3.82.73.42.84.66.03.5

3.3

3.43.54.03.73.53.54.03.04.45.04.0

2.22.42.52.12.02.2

3.03.12.9

0.50.90.60.42.43.70.50.50.51.51.01.00.90.9

2.20.81.20.60.90.51.50.60.72.7

0.40.40.60.30.70.80.5

26.5

22.220.826.723.321.620.222.221.228.629.225.5

13.217.117.416.815.916.0

24.024.825.0

15.013.113.110.023.921.713.513.313.621.313.915.613.915.2

21.715.316.812.217.913.521.614.915.021.2

10.213.016.8

9.914.213.314.7


Table 1.Total Population, Percent Elderly, and Percent Oldest Old: 1975, 2000, 2015, and2030—Con.(In thousands)

Country

2015 2030

Totalpopulation


65+ 80+

80+ as apercent of

65+Total

population


65+ 80+

80+ as apercent of

65+

United States . . . . . . . . . . . . . . . . . . .

Western EuropeAustria . . . . . . . . . . . . . . . . . . . . . . . . . . .Belgium . . . . . . . . . . . . . . . . . . . . . . . . . .Denmark . . . . . . . . . . . . . . . . . . . . . . . . .France . . . . . . . . . . . . . . . . . . . . . . . . . . .Germany . . . . . . . . . . . . . . . . . . . . . . . . .Greece . . . . . . . . . . . . . . . . . . . . . . . . . . .Italy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Luxembourg . . . . . . . . . . . . . . . . . . . . . .Norway . . . . . . . . . . . . . . . . . . . . . . . . . . .Sweden . . . . . . . . . . . . . . . . . . . . . . . . . .United Kingdom . . . . . . . . . . . . . . . . . . .

Eastern EuropeBulgaria . . . . . . . . . . . . . . . . . . . . . . . . . .Czech Republic . . . . . . . . . . . . . . . . . . .Hungary . . . . . . . . . . . . . . . . . . . . . . . . . .Poland . . . . . . . . . . . . . . . . . . . . . . . . . . .Russia . . . . . . . . . . . . . . . . . . . . . . . . . . .Ukraine. . . . . . . . . . . . . . . . . . . . . . . . . . .

North America/OceaniaAustralia . . . . . . . . . . . . . . . . . . . . . . . . . .Canada. . . . . . . . . . . . . . . . . . . . . . . . . . .New Zealand. . . . . . . . . . . . . . . . . . . . . .

AsiaBangladesh . . . . . . . . . . . . . . . . . . . . . . .China . . . . . . . . . . . . . . . . . . . . . . . . . . . .India . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Indonesia . . . . . . . . . . . . . . . . . . . . . . . . .Israel. . . . . . . . . . . . . . . . . . . . . . . . . . . . .Japan . . . . . . . . . . . . . . . . . . . . . . . . . . . .Malaysia. . . . . . . . . . . . . . . . . . . . . . . . . .Pakistan . . . . . . . . . . . . . . . . . . . . . . . . . .Philippines . . . . . . . . . . . . . . . . . . . . . . . .Singapore . . . . . . . . . . . . . . . . . . . . . . . .South Korea . . . . . . . . . . . . . . . . . . . . . .Sri Lanka . . . . . . . . . . . . . . . . . . . . . . . . .Thailand . . . . . . . . . . . . . . . . . . . . . . . . . .Turkey. . . . . . . . . . . . . . . . . . . . . . . . . . . .

Latin America/CaribbeanArgentina . . . . . . . . . . . . . . . . . . . . . . . . .Brazil. . . . . . . . . . . . . . . . . . . . . . . . . . . . .Chile . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Colombia . . . . . . . . . . . . . . . . . . . . . . . . .Costa Rica. . . . . . . . . . . . . . . . . . . . . . . .Guatemala . . . . . . . . . . . . . . . . . . . . . . . .Jamaica . . . . . . . . . . . . . . . . . . . . . . . . . .Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . .Peru . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Uruguay . . . . . . . . . . . . . . . . . . . . . . . . . .

AfricaEgypt . . . . . . . . . . . . . . . . . . . . . . . . . . . .Kenya . . . . . . . . . . . . . . . . . . . . . . . . . . . .Liberia. . . . . . . . . . . . . . . . . . . . . . . . . . . .Malawi . . . . . . . . . . . . . . . . . . . . . . . . . . .Morocco . . . . . . . . . . . . . . . . . . . . . . . . . .Tunisia . . . . . . . . . . . . . . . . . . . . . . . . . . .Zimbabwe . . . . . . . . . . . . . . . . . . . . . . . .

312,524

8,31610,336

5,52161,54585,19210,73556,631

5194,7678,900

61,047

6,66310,048

9,66638,668

141,07345,294

21,69735,653

4,396

160,4861,397,4141,241,572

275,1526,992

125,84328,414

185,715106,098

6,64652,23921,52768,13976,685

42,916192,313

17,40549,189

4,58318,105

2,992121,712

33,5513,730

85,21933,612

4,65512,01737,83211,17410,548

14.7

18.819.418.918.820.220.622.215.317.421.418.4

20.218.817.615.013.815.0

15.816.113.7

4.49.55.96.2

11.124.9

5.94.54.98.7

11.39.59.87.9

11.88.1

10.76.57.34.17.46.36.4

13.5

5.13.84.03.15.57.65.0

3.8

4.95.74.45.85.46.36.84.14.65.74.9

4.64.24.33.83.13.2

4.14.33.5

0.61.70.91.13.07.00.80.70.72.12.21.71.81.6

3.11.52.11.01.40.71.81.01.23.8

0.60.60.80.41.01.51.0

25.8

26.229.323.630.926.630.530.527.126.326.826.8

23.022.324.225.122.721.1

25.926.825.7

12.518.014.516.926.628.214.315.014.624.119.317.718.019.9

26.018.719.315.619.217.824.116.618.328.2

11.916.621.112.717.419.820.2

351,326

8,27810,175

5,64961,92684,93910,31652,868

5805,0188,868

61,481

5,6689,4099,034

37,377132,859

42,273

23,49739,128

4,768

184,4781,483,1211,437,103

312,5927,873

116,74035,306

226,251129,448

9,04753,76322,93771,31184,195

47,229203,489

18,91557,666

5,27224,038

3,353139,125

39,2534,109

99,58334,836

6,74512,81744,66412,322

9,086

20.0

25.225.423.024.025.825.428.119.822.025.123.5

25.924.722.522.220.519.7

21.122.917.8

7.216.0

9.010.914.928.3

9.46.57.7

14.819.515.216.412.9

14.713.216.411.512.8

5.612.510.2

9.915.5

8.05.24.23.29.1

12.76.4

5.3

7.07.37.17.57.27.89.05.26.68.67.0

7.27.46.35.54.14.2

6.06.25.0

1.02.91.41.73.9

11.11.60.91.23.04.23.13.12.4

4.02.73.71.82.41.02.31.91.94.4

1.11.11.00.61.42.31.8

26.4

27.928.830.831.228.130.832.126.230.034.329.7

27.830.027.924.820.021.5

28.526.928.2

13.518.315.715.626.539.316.914.415.920.421.320.219.318.7

27.320.622.315.918.917.618.718.719.028.1

14.220.724.917.515.217.727.7

Source: United Nations, 1999 and U.S. Census Bureau, 2000a.

127An Aging World: 2001U.S. Census Bureau

Table 2.Population by Age: 2000 and 2030(In thousands)

Country

2000

All ages0 to 24

years25 to 54

years55 to 64

years65 to 69

years70 to 74

years75 to 79

years80 yearsand over

United States . . . . . . . . . . . . . . .







275,563

8,13110,242

5,33659,33082,79710,60257,634

4374,4818,873

59,508

7,79710,27210,13938,646

146,00149,153

19,16531,278

3,820

129,1941,261,8321,014,004

224,7845,842

126,55021,793

141,55481,160

4,15247,47119,23961,23165,667

36,955172,860

15,15439,686

3,71112,640

2,653100,350

27,0133,334

68,36030,340

3,16410,38630,122

9,59311,343

97,064

2,3253,0331,594

18,85222,309

3,08814,873

1331,4352,655

18,549

2,3543,2503,207

13,91549,23216,052

6,62910,154

1,417

76,298515,155536,947113,419

2,61734,78211,58386,10946,410

1,33318,091

8,75925,87932,182

16,32684,691

6,73319,897

1,8887,9221,312

54,69914,735

1,348

37,70620,064

1,9856,955

16,8264,8347,281

119,662

3,6294,4322,340

25,51336,224

4,48025,640

1991,9373,674

25,496

3,2554,5054,336

16,67664,19720,607

8,42714,322

1,637

42,947572,082373,956

88,2312,257

53,8588,175

43,16528,087

2,28122,191

7,93327,04525,619

13,85668,842

6,19415,867

1,4383,7651,027

36,2419,6061,257

24,5728,423

9292,757

10,4723,6383,238

24,001

9261,052

6105,471

10,8131,1956,696

44426

1,0106,138

9021,0931,1133,319

14,1605,647

1,7272,838

324

5,64586,82256,03713,080

39116,385

1,1526,4853,717

2533,8751,2954,3863,935

2,94610,136

1,1332,071

193496135

5,0921,409

298

3,5091,021

141385

1,434542422

9,436

347521219

2,7114,104

6053,093

19167380

2,585

453448479

1,6165,9962,080

6681,147

124

1,74434,92618,477

4,616168

7,031353

2,3171,220

981,365

4551,5911,514

1,2093,501

391742

70184

561,722

500138

1,162340

43126538223156

8,753

332462194

2,4663,592

5212,766

17164363

2,347

382409420

1,3726,1822,294

6331,012

116

1,20625,42613,785

2,872152

5,812260

1,637820

76895358

1,0861,099

1,0262,594

310546

53132

481,197

351118

748237

2985

393173112

7,422

294383167

2,1002,846

3412,253

12156343

2,018

282323326953

3,2991,377

509822

91

71015,908

8,6271,559

1204,012

1511,071

50449

594244699721

7611,693

210338

357936

757223

84

401146

1949

262106

74

9,225

278358212

2,2162,911

3712,313

13196447

2,373

169244257794

2,9361,096

573984110

64311,5136,1751,006

1384,670

119770401

61460195545597

8311,403

184225

346239

642189

91

261108

1828

1977759


Table 2.Population by Age: 2000 and 2030—Con.(In thousands)

Country

2030

All ages0 to 24

years25 to 54

years55 to 64

years65 to 69

years70 to 74

years75 to 79


United States . . . . . . . . . . . . . . .







351,326

8,27810,175

5,64961,92684,93910,31652,868

5805,0188,868

61,481

5,6689,4099,034

37,377132,859

42,273

23,49739,128

4,768

184,4781,483,1211,437,103

312,5927,873

116,74035,306

226,251129,448

9,04753,76322,93771,31184,195

47,229203,489

18,91557,666

5,27224,038

3,353139,125

39,2534,109

99,58334,836

6,74512,81744,66412,322

9,086

115,218

1,9162,5531,515

16,40520,074

2,28710,165

1641,4052,210

16,077

1,0961,9332,0129,260

35,65011,383

6,64310,368

1,400

71,167437,787558,161112,472

2,72425,58915,01795,92955,474

2,34514,515

7,10221,21926,295

16,08266,334

5,86321,940

1,79612,128

1,06252,12814,952

1,444

38,87815,729

3,9586,856

17,2203,8064,622

128,484

3,0343,6832,076

22,59931,104

3,81418,788

2291,8563,267

22,663

2,2403,7183,662

15,18453,58917,099

8,94114,987

1,914

84,043588,812614,683132,916

3,15440,44113,89198,62553,369

4,15820,967

9,58028,98736,793

19,37487,458

7,81723,069

2,2489,1051,447

58,22516,694

1,593

43,51615,402

2,2135,087

19,1415,4283,566

37,305

1,2441,357

7608,073

11,8861,5949,033

72653

1,1678,296

8661,4361,3304,642

16,4285,479

2,9604,800

607

16,060219,501135,423

33,067825

17,6613,063

17,00810,581

1,2047,8192,7719,441

10,231

4,83422,898

2,1336,034

5541,455

42514,646

3,735434

9,2121,902

292466

4,2251,517

317

19,844

636709357

3,7756,502

6924,115

35295555

4,215

381583485

2,0878,2882,553

1,3562,581

233

5,24884,95849,01312,612

3277,0941,2365,8263,738

4683,4701,1423,9273,940

1,9639,0911,0062,481

235493158

5,1651,394

183

3,144610

92144

1,546581146

17,878

500628295

3,4355,192

6203,307

29261482

3,336

362532506

2,2677,7762,292

1,2122,249

209

3,82159,23035,886

9,740288

6,391919

4,1862,814

3602,959

9453,1892,899

1,7057,080

8231,872

188368110

3,7001,031

156

2,261472

69111

1,180442147

14,029

367501246

3,0054,036

5032,685

22217424

2,598

315512472

1,8825,6811,683

9751,728

166

2,35649,36723,744

6,450246

6,562617

2,5681,877

2391,803

6942,3032,002

1,3765,099

5821,217

124252

732,621

711119

1,437349

5081

735270127

18,569

582744400

4,6356,145

8074,775

30331763

4,296

408696566

2,0565,4461,783

1,4102,414

238

1,78343,46620,194

5,335310

13,002563

2,1091,596

2742,231

7032,2452,036

1,8955,530

6911,053

127238

782,639

736179

1,136373

7071

618278161



Table 3.Average Annual Growth Rate and Percent Change Over Time for Older Age Groups:2000 to 2015 and 2015 to 2030(In percent)

Country

Average annual growth rate

2000 to 2015 2015 to 2030

55 to 64years

65 to 79 80 yearsyears and over

65 years 55 to 64and over years


65 yearsand over

United States . . . . . . . . . . . . . . . . . . .







2.5

0.81.50.71.90.30.70.51.81.70.51.0

0.21.21.02.61.80.3

2.22.71.9

2.82.82.52.92.7

–0.23.12.23.05.22.52.62.62.5

1.62.52.33.43.62.92.82.62.60.9

2.61.21.5

–3.02.6

–0.2

1.4

0.90.21.60.50.90.20.40.91.11.20.9

–0.41.10.30.5

–0.2–0.4

1.71.71.5

2.61.82.22.31.31.53.21.82.73.42.52.32.41.9

1.12.42.52.52.72.10.92.82.50.3

2.51.92.41.11.81.51.1

1.3

1.92.50.72.42.33.02.52.50.50.61.2

3.02.82.33.02.01.3

2.22.21.7

1.63.62.75.32.03.23.52.53.14.24.53.13.93.5

2.33.63.34.03.13.81.63.43.72.2

3.43.43.82.53.03.93.0

1.4

1.10.81.41.01.20.90.91.31.01.10.9

0.21.40.71.00.3

–0.1

1.81.91.6

2.52.12.22.71.51.93.21.92.83.62.92.52.62.2

1.42.62.62.72.82.41.12.92.70.8

2.62.12.71.32.01.91.4

–0.5

0.9–0.3

0.60.10.20.91.30.90.60.30.7

–0.60.2

–0.1–1.3–1.4–0.6

0.7–0.1

1.6

3.22.52.62.31.30.72.43.53.03.51.41.71.73.0

1.22.11.12.62.33.44.03.63.11.3

2.92.62.91.33.33.4

–1.6

2.8

1.71.70.81.71.51.11.02.61.60.31.4

0.10.70.82.42.51.3

2.23.02.1

4.13.83.64.72.7

–0.84.33.84.35.93.73.33.64.0

2.03.53.24.84.74.04.73.93.81.6

3.92.02.50.34.74.3

–

3.0

2.31.63.31.72.01.21.52.22.82.72.4

1.83.32.12.31.41.5

3.13.02.9

4.74.04.34.12.72.65.73.45.04.54.54.44.23.4

2.44.34.44.94.64.02.54.84.21.6

5.23.83.92.83.63.32.7

2.8

1.91.71.51.71.61.11.12.51.91.01.7

0.61.41.22.42.21.4

2.53.02.3

4.23.93.74.62.70.34.53.74.45.63.83.53.73.9

2.13.63.44.84.74.04.24.13.91.6

4.02.32.80.64.54.10.6


Table 3.Average Annual Growth Rate and Percent Change Over Time for Older Age Groups:2000 to 2015 and 2015 to 2030—Con.(In percent)

Country

Percent change

2000 to 2015 2015 to 2030

55 to 64years


65 years 55 to 64and over years


65 yearsand over

United States . . . . . . . . . . . . . . . . . . .







66

17341445

6161045391022

527226943

6

557147

7675647972–3845582

18264676766

36645999

1057774686720

702735–18068–4

33

194

371020

58

19262819

–725

510–3–7

404135

6943545829348942739766596246

256264667154207464

6

66476225433624

29

4864166157816565111427

837360835030

555640

37107

73188

4989

1026487

130148

86120103

59107

95123

871133999

10855

9996

1166583

12081

32

2516322228202029222421

5331522

5–1

444536

645157713446914575

10478647055

32697073746224787116

69537129494732

–7

15–4

913

15221410

511

–84

–2–17–19

–8

11–127

6245474122114470576823292957

20381947406581725821

554754226366

–22

52

303013282518164726

523

21114444522

405636

857872

10251

–11927692

14373657381

356861

106103

83102

807827

783545

4103

90–1

56

4227633034202540525042

326538422325

595754

1028289845047

13467

1129696948768

449093

110988146

1078726

118767951726550

53

3329242927191845331728

92319434023

455641

8778759951

5987595

13178707579

377267

107102

8388848027

83425210978510



Table 4.Median Population Age: 2000, 2015, and 2030

Country 2000 2015 2030

United States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Western EuropeAustria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Belgium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Denmark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .France . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Germany . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Greece. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Italy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Luxembourg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Norway . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Sweden . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .United Kingdom . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Eastern EuropeBulgaria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Czech Republic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Hungary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Poland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Russia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Ukraine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

North America/OceaniaAustralia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Canada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .New Zealand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

AsiaBangladesh. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Indonesia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Israel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Japan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Malaysia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Pakistan. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Philippines. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Singapore . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .South Korea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Sri Lanka. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Thailand. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Turkey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Latin America/CaribbeanArgentina. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Brazil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Chile. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Colombia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Costa Rica . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Guatemala . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Jamaica . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Peru . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Uruguay. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

AfricaEgypt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Kenya. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Liberia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Malawi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Morocco. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Tunisia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Zimbabwe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

36

3839383840394038373938

403838353737

353732

2030232528412319213431282926

29262925251825232331

22181817222519

38

4443424245444640414342

444342393939

394137

2736283032452624253838333532

32313329302131282734

27231820273222

39

4746434447495241424544

504947464444

424440

3341323436503029294143394038

36373933362538343336

32282023333925



Table 5.Total and Elderly Urban Population by Sex: Available Data From 1970 to the Present

Country

Year

Males Females

Elderlysex ratioAll ages Elderly

Percentelderly All ages Elderly

Percentelderly

United States . . . . . . . . . . . .

Western EuropeAustria . . . . . . . . . . . . . . . . . . . .

Denmark . . . . . . . . . . . . . . . . . .

France . . . . . . . . . . . . . . . . . . . .

Greece. . . . . . . . . . . . . . . . . . . .

Norway . . . . . . . . . . . . . . . . . . .

Sweden . . . . . . . . . . . . . . . . . . .

Eastern EuropeBulgaria . . . . . . . . . . . . . . . . . . .

Czech Republic . . . . . . . . . . . .

Hungary. . . . . . . . . . . . . . . . . . .

Poland . . . . . . . . . . . . . . . . . . . .

Russia . . . . . . . . . . . . . . . . . . . .

Ukraine . . . . . . . . . . . . . . . . . . .

North America/OceaniaAustralia . . . . . . . . . . . . . . . . . .

Canada . . . . . . . . . . . . . . . . . . .

197019801990

197119811991

19701981

197519821990

197119811991

197019801990

1970197519801990

1975198719941996

19941996

19701980198819951996

19701978198819941996

1970197919891995

1970197919891995

197119761986

1971197619811991

71,958,56480,287,24390,386,114

1,762,7751,919,6382,386,002

1,922,5582,089,529

18,658,54019,239,34020,194,431

2,781,7003,311,5652,914,404

1,241,8731,409,6631,488,678

3,232,0963,327,5133,378,5303,494,512

2,517,8162,923,0292,789,5012,741,483

3,731,1863,719,889

2,217,6582,733,6003,000,8263,038,8443,037,842

8,167,1849,667,100

11,120,38911,422,33711,429,857

36,930,89743,754,73450,332,66850,405,185

11,823,17713,953,87815,981,44216,298,622

5,424,3455,768,5846,567,861

8,104,5358,528,9759,013,665

10,175,040

5,859,4727,327,7749,179,593

223,701244,735272,021

206,818251,479

1,858,5401,912,0802,236,685

239,820316,153301,833

122,137133,166188,455

342,732403,825452,876517,841

174,000221,049277,493272,800

365,443378,763

205,423283,600289,051328,028331,902

464,200660,000716,691847,910916,922

1,432,2002,300,0032,566,0763,684,024

586,310887,799972,137

1,292,193

379,844436,202605,540

557,750635,970746,085

1,002,465

8.19.1

10.2

12.712.711.4

10.812.0

10.09.9

11.1

8.69.5

10.4

9.89.4

12.7

10.612.113.414.8

6.97.69.9

10.0

9.810.2

9.310.4

9.610.810.9

5.76.86.47.48.0

3.95.35.17.3

5.06.46.17.9

7.07.69.2

6.97.58.39.9

77,366,36686,767,39596,667,373

2,103,7902,241,4072,646,187

2,023,5992,207,563

19,728,80020,560,48021,728,802

2,904,0403,478,3833,124,577

1,313,0401,483,5301,567,516

3,342,8373,461,9193,534,9633,670,257

2,543,6532,998,2152,926,4032,893,119

3,989,2753,974,872

2,449,1932,968,0003,284,7133,401,2263,405,105

8,887,22010,472,60012,054,33712,435,70212,466,966

43,700,47451,187,56257,626,33457,373,948

13,722,47316,215,05918,315,78918,529,728

5,489,1065,881,8926,749,084

8,306,2508,838,0009,422,265

10,731,835

8,771,64311,672,99214,388,961

403,229463,164533,663

290,237376,266

3,054,9203,204,6603,625,554

317,300413,686412,831

182,976211,705287,279

474,392564,329642,174753,536

218,000281,896360,531364,313

602,153618,011

326,340447,900486,970551,982559,268

847,9001,171,0001,286,3681,476,4951,560,339

3,909,3275,966,2106,960,4128,329,645

1,248,4231,897,6682,222,8282,602,852

557,526636,732867,372

762,300905,065

1,096,8601,500,100

11.313.514.9

19.220.720.2

14.317.0

15.515.616.7

10.911.913.2

13.914.318.3

14.216.318.220.5

8.69.4

12.312.6

15.115.5

13.315.114.816.216.4

9.511.210.711.912.5

8.911.712.114.5

9.111.712.114.0

10.210.812.9

9.210.211.614.0

676364

555351

7167

616062

767673

676366

72727169

80787775

6161

6363595959

5556565759

37393744

47474450

686970

73706867


Table 5.Total and Elderly Urban Population by Sex: Available Data From 1970 to the Present—Con.

Country

Year

Males Females



Percentelderly

New Zealand . . . . . . . . . . . . . .

AfricaEgypt . . . . . . . . . . . . . . . . . . . . .

Kenya. . . . . . . . . . . . . . . . . . . . .

Malawi . . . . . . . . . . . . . . . . . . . .

Morocco. . . . . . . . . . . . . . . . . . .

Tunisia . . . . . . . . . . . . . . . . . . . .

Zimbabwe . . . . . . . . . . . . . . . . .

AsiaBangladesh. . . . . . . . . . . . . . . .

China . . . . . . . . . . . . . . . . . . . . .

India . . . . . . . . . . . . . . . . . . . . . .

Indonesia. . . . . . . . . . . . . . . . . .

Israel . . . . . . . . . . . . . . . . . . . . .

Japan . . . . . . . . . . . . . . . . . . . . .

Malaysia . . . . . . . . . . . . . . . . . .

Pakistan. . . . . . . . . . . . . . . . . . .

Philippines. . . . . . . . . . . . . . . . .

Singapore . . . . . . . . . . . . . . . . .

South Korea . . . . . . . . . . . . . . .

19811991

19761986

19791989

19771987

19711982

197519841994

19821992

1974198119881991

19821990

19711981

197119801990

1972198319941995

197019751980198519901995

197019801991

197219811990

1970197519801990

197019801990

1975198019851995

1,299,0061,395,495

8,539,62310,908,850

1,307,1581,933,437

253,545445,863

2,627,9184,378,706

1,401,5101,869,0102,717,168

940,6201,636,352

3,538,5317,370,0008,163,604

11,301,085

107,915,090157,491,587

58,718,37183,876,401

10,194,35916,439,90027,683,319

1,343,3411,793,3972,390,9002,452,000

36,889,50041,988,96043,979,40345,766,35847,124,42048,210,196

1,402,0002,044,8734,472,970

9,019,17112,767,06114,514,629

5,670,8166,553,3248,765,413

14,546,463

1,062,1271,231,7601,517,776

8,369,90910,697,84313,154,13017,595,723

115,065140,316

265,355444,257

21,14223,090

3,8427,085

94,678138,248

50,65083,920

137,874

28,54032,614

84,854226,000212,600305,677

4,183,4707,081,751

1,526,2692,486,231

196,839374,916800,720

100,705156,353205,500211,000

2,044,9002,579,5043,094,7573,559,6344,224,7455,385,903

40,62869,340

133,071

289,765446,804433,128

149,101182,848244,103415,222

30,58951,20275,403

128,569183,694271,087536,398

8.910.1

3.14.1

1.61.2

1.51.6

3.63.2

3.64.55.1

3.02.0

2.43.12.62.7

3.94.5

2.63.0

1.92.32.9

7.58.78.68.6

5.56.17.07.89.0

11.2

2.93.43.0

3.23.53.0

2.62.82.82.9

2.94.25.0

1.51.72.13.0

1,351,8781,471,236

8,018,04910,306,654

1,075,0451,606,451

217,113407,527

2,740,0464,354,801

1,377,6701,816,4602,644,759

825,1301,551,368

2,734,7815,858,0006,918,3099,571,119

98,332,070142,665,833

50,378,27473,803,766

10,255,96116,401,82527,750,471

1,341,2281,822,6322,453,0002,518,500

37,799,20042,933,41745,138,38947,082,51948,519,10149,798,911

1,378,2542,028,2324,425,611

7,561,18011,074,41013,542,746

5,999,3886,752,7579,178,240

14,893,690

1,012,3801,182,1851,498,603

8,400,03710,711,60613,263,84217,396,241

165,414200,823

247,043358,645

18,12821,877

3,2036,479

103,436140,753

46,99075,490

138,586

16,29028,651

63,247157,000131,859222,943

5,186,5908,260,440

1,494,6682,545,642

245,422489,857981,431

104,050177,579271,200281,200

2,612,5003,387,1214,218,7375,138,3866,279,9117,693,917

45,91679,699

167,315

213,461327,383383,029

170,339198,287341,658537,747

38,77562,72293,266

253,528365,207521,815978,119

12.213.6

3.13.5

1.71.4

1.51.6

3.83.2

3.44.25.2

2.01.8

2.32.71.92.3

5.35.8

3.03.4

2.43.03.5

7.89.7

11.111.2

6.97.99.3

10.912.915.4

3.33.93.8

2.83.02.8

2.82.93.73.6

3.85.36.2

3.03.43.95.6

7070

107124

117106

120109

9298

10811199

175114

134144161137

8186

10298

807782

97887675

787673696770

888780

136136113

88927177

798281

51505255


Table 5.Total and Elderly Urban Population by Sex: Available Data From 1970 to the Present—Con.

Country

Year

Males Females



Percentelderly

Sri Lanka. . . . . . . . . . . . . . . . . .

Thailand. . . . . . . . . . . . . . . . . . .

Turkey . . . . . . . . . . . . . . . . . . . .

Latin America/CaribbeanArgentina. . . . . . . . . . . . . . . . . .

Brazil . . . . . . . . . . . . . . . . . . . . .

Chile. . . . . . . . . . . . . . . . . . . . . .

Colombia . . . . . . . . . . . . . . . . . .

Costa Rica . . . . . . . . . . . . . . . .

Guatemala . . . . . . . . . . . . . . . .

Jamaica . . . . . . . . . . . . . . . . . . .

Mexico . . . . . . . . . . . . . . . . . . . .

Peru . . . . . . . . . . . . . . . . . . . . . .

Uruguay. . . . . . . . . . . . . . . . . . .

19711981

197019801990

198019851990

19801995

197019801991

1970198219921997

197319851993

197319841995

19731981

19821991

19701995

197219811993

1975198519901996

1,513,1021,665,539

2,257,0683,744,4254,941,000

10,272,13014,010,67017,247,553

11,213,93814,820,662

25,173,43939,192,23053,854,256

3,173,3234,464,3745,364,7606,052,039

5,904,6138,927,542

11,211,708

360,701514,426674,634

905,685949,676

494,155543,108

13,882,91432,720,158

4,028,1695,517,7697,606,489

1,099,6341,222,2601,306,6011,366,092

58,34668,979

55,778109,059173,200

345,047399,207518,630

820,6871,185,585

803,4701,447,9192,333,327

139,527219,108288,375324,862

172,482321,963472,784

14,03324,26153,926

29,21635,220

23,23027,635

463,0481,277,431

125,390193,224324,827

99,670119,891130,547148,110

3.94.1

2.52.93.5

3.42.83.0

7.38.0

3.23.74.3

4.44.95.45.4

2.93.64.2

3.94.78.0

3.23.7

4.75.1

3.33.9

3.13.54.3

9.19.8

10.010.8

1,335,0141,528,940

2,296,0323,888,4915,265,900

9,372,87712,855,08716,078,798

11,978,95415,736,243

26,801,50641,172,54257,136,734

3,501,8144,851,7545,775,6456,368,467

6,703,2369,786,011

12,302,362

399,378560,828694,787

972,5061,030,857

551,886605,083

14,425,64234,283,357

4,030,3265,574,1547,852,110

1,214,7221,358,8271,441,7211,505,985

56,08472,270

79,328147,891230,700

457,407532,949675,302

1,159,3701,761,004

1,010,1841,864,9003,082,663

193,934313,023427,059503,897

232,676407,186593,057

18,49732,41669,823

36,71742,529

33,21639,724

580,7301,570,619

154,174225,243372,285

138,060177,647194,640225,783

4.24.7

3.53.84.4

4.94.14.2

9.711.2

3.84.55.4

5.56.57.47.9

3.54.24.8

4.65.8

10.0

3.84.1

6.06.6

4.04.6

3.84.04.7

11.413.113.515.0

10495

707475

757577

7167

807876

72706864

747980

767577

8083

7070

8081

818687

72676766

Notes: ‘‘Urban’’ refers to localities defined as such by each country. Individual national definitions are available in the annotations torespective International Data Base tables.

‘‘Elderly Sex Ratio’’ is defined as the number of men aged 65 years and over per 100 women aged 65 years and over.



Table 6.Sex Ratio for Population 25 Years and Over by Age: 2000 and 2030(Men per 100 women)

Country

2000 2030

25 to54

years

55 to64

years

65 to 70 to69 74

years years

75 to79


25 to54

years

55 to64

years

65 to 70 to69 74

years years

75 to79


United States. . . . . . . . . . .

Western EuropeAustria . . . . . . . . . . . . . . . . . .Belgium . . . . . . . . . . . . . . . . .Denmark. . . . . . . . . . . . . . . . .France . . . . . . . . . . . . . . . . . .Germany . . . . . . . . . . . . . . . .Greece . . . . . . . . . . . . . . . . . .Italy . . . . . . . . . . . . . . . . . . . . .Luxembourg. . . . . . . . . . . . . .Norway . . . . . . . . . . . . . . . . . .Sweden . . . . . . . . . . . . . . . . .United Kingdom . . . . . . . . . .

Eastern EuropeBulgaria . . . . . . . . . . . . . . . . .Czech Republic. . . . . . . . . . .Hungary . . . . . . . . . . . . . . . . .Poland . . . . . . . . . . . . . . . . . .Russia. . . . . . . . . . . . . . . . . . .Ukraine . . . . . . . . . . . . . . . . . .

North America/OceaniaAustralia . . . . . . . . . . . . . . . . .Canada. . . . . . . . . . . . . . . . . .New Zealand . . . . . . . . . . . . .

AsiaBangladesh . . . . . . . . . . . . . .China . . . . . . . . . . . . . . . . . . .India . . . . . . . . . . . . . . . . . . . .Indonesia . . . . . . . . . . . . . . . .Israel . . . . . . . . . . . . . . . . . . . .Japan . . . . . . . . . . . . . . . . . . .Malaysia . . . . . . . . . . . . . . . . .Pakistan . . . . . . . . . . . . . . . . .Philippines . . . . . . . . . . . . . . .Singapore. . . . . . . . . . . . . . . .South Korea . . . . . . . . . . . . .Sri Lanka . . . . . . . . . . . . . . . .Thailand . . . . . . . . . . . . . . . . .Turkey. . . . . . . . . . . . . . . . . . .

Latin America/CaribbeanArgentina . . . . . . . . . . . . . . . .Brazil . . . . . . . . . . . . . . . . . . . .Chile . . . . . . . . . . . . . . . . . . . .Colombia . . . . . . . . . . . . . . . .Costa Rica . . . . . . . . . . . . . . .Guatemala . . . . . . . . . . . . . . .Jamaica . . . . . . . . . . . . . . . . .Mexico . . . . . . . . . . . . . . . . . .Peru . . . . . . . . . . . . . . . . . . . .Uruguay . . . . . . . . . . . . . . . . .

AfricaEgypt. . . . . . . . . . . . . . . . . . . .Kenya . . . . . . . . . . . . . . . . . . .Liberia. . . . . . . . . . . . . . . . . . .Malawi . . . . . . . . . . . . . . . . . .Morocco . . . . . . . . . . . . . . . . .Tunisia . . . . . . . . . . . . . . . . . .Zimbabwe . . . . . . . . . . . . . . .

98

103102103100105100100102104104102

97101

98100

9693

102101101

104106106100101102

99104

9694

1039396

105

100969994

101989892

10197

102101

90969899

101

91

959699969894929999

10197

879080857373

1019797

116108108899195969891

10094909196

92859182

1009493899787

9185

10973848997

85

8587908589898588919191

827870756266

949295

1151011038384898498858876928593

82788385959389879382

8578

109708395

105

79

7278827773837778838382

756762655154

888389

11893

1007974838097798362938291

74707683919185848775

7980

103698699

108

72

5066706649756653707570

675553543337

757174

12680

1067472647195767655937584

66636880848378778068

7080926984

105104

52

3841494635675042505445

624243442629

555253

12859

1066470486496775940945962

56504672717568656853

6477876881

11790

98

10410210210310210510298

100104105

102103102102

9797

102102103

104107107101104104104105102

85108

96102102

10298

10297

104101104

98101103

102108

98111101104130

92

99989896989896949799

101

899792948480

9897

101

101100

9995

101100

97102

9284978690

101

95889689999499899796

1008885819498

105

89

9693968894919192959696

798980847267

939392

9795909096948695838688788298

89809084918990799386

85737757889270

86

8987908287878686909190

728170766258

878786

9690928587887687748682727791

83748579868479738978

78667647848755

81

7980827677827779828381

637161665249

807979

10080927880817178678175687183

75677670817675688272

69617941757952

64

5857625756655859626460

485342493934

666162

10563895966616170616456635663

58525553676765576852

53568737586956



Table 7.Marital Status of Older Persons by Sex: Selected Years 1970 to 1995

Country, year, and age

Males Females

Total Single Married WidowedSeparated/

divorcedPercent

widowed Total Single Married WidowedSeparated/

divorcedPercent

widowed

United States

1977

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .75 and over . . . . . . . . . . . . . .

1987


1990


1995


Western Europe

Austria

1975


1982


1991


Belgium

1970


9,476,0009,132,0002,991,000

10,277,00011,576,0003,969,000

9,981,41712,565,173

4,623,560

9,878,00013,002,000

4,905,000

292,514419,222128,104

325,102398,381151,921

368,200404,400

81,000

510,104531,595165,281

549,000539,000139,000

591,000526,000172,000

556,412618,893226,579

494,000543,000201,000

18,06727,803

8,290

18,77025,044

9,974

24,30021,500

4,900

41,67436,82210,634

8,109,0007,007,0002,070,000

8,439,0008,806,0002,692,000

8,004,4919,398,6723,111,154

7,821,0009,693,0003,353,000

251,872303,413

75,050

282,401288,932

92,455

309,800303,400

45,500

432,431367,496

87,673

323,0001,298,000

727,000

293,0001,622,000

937,000

347,4681,781,5021,079,851

275,0001,755,0001,062,000

11,95876,22642,124

11,91072,42645,729

14,60066,10028,700

27,202121,407

65,842

495,000288,000

55,000

954,000622,000168,000

1,073,046766,106205,976

1,288,0001,011,000

289,000

10,61711,7802,640

12,02111,9793,763

19,50013,400

1,900

8,7975,8701,132

3.414.224.3

2.914.023.6

3.514.223.4

2.813.521.7

4.118.232.9

3.718.230.1

4.016.335.4

5.322.839.8

10,601,00012,968,000

4,968,000

11,606,00016,396,000

6,773,000

11,166,50618,676,658

8,511,713

10,878,00018,262,000

8,145,000

418,214712,408270,703

464,436717,382318,738

406,700762,500201,800

568,179764,113278,504

492,000831,000327,000

485,000898,000435,000

508,0481,025,944

535,978

467,000768,000360,000

45,13489,80736,463

48,05583,30939,736

33,40078,90022,600

47,65376,47531,894

7,434,0005,029,0001,070,000

7,903,0006,565,0001,577,000

7,398,2257,218,0181,964,130

7,152,0007,421,0002,057,000

234,142198,134

37,532

287,062189,290

45,590

269,400229,900

19,900

397,082289,108

57,762

2,023,0006,750,0003,463,000

1,935,0008,070,0004,541,000

1,776,8939,225,9905,638,182

1,405,0008,636,0005,284,000

115,307398,481189,810

100,012414,188223,728

76,300414,900152,200

112,424388,803185,981

652,000358,000108,000

1,283,000863,000220,000

1,483,3401,206,706

373,423

1,854,0001,437,000

444,000

23,63125,986

6,898

29,30730,595

9,684

27,60038,800

7,100

11,0209,7272,867

19.152.169.7

16.749.267.0

15.949.466.2

12.947.364.9

27.655.970.1

21.557.770.2

18.854.475.4

19.850.966.8

An

Agin

gW

orld

:2

00

1U

.S.C

ensu

sBu

reau1

37

Table 7.Marital Status of Older Persons by Sex: Selected Years 1970 to 1995—Con.


Males Females


divorcedPercent


divorcedPercent

widowed

1981

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .75 and over . . . . . . . . . . . . . .1995


Denmark

1970


1984


1988


1991


France

1977


1987


486,328559,796195,638

539,184639,393206,173

266,499267,785

91,710

259,041317,829116,038

246,548327,558126,193

242,100330,700

63,100

2,133,6082,814,161

916,605

2,829,0632,865,9621,216,803

35,16740,17213,055

38,17941,42012,878

23,95521,551

6,581

21,44824,953

8,771

20,43825,010

9,558

19,70024,900

4,600

185,516216,482

59,680

264,794213,622

87,804

416,825394,288110,742

446,888473,136127,024

215,864181,551

49,619

206,028220,280

68,576

192,434225,922

75,402

186,300226,200

32,900

1,796,1212,040,539

565,618

2,347,4122,100,203

775,866

21,167115,14969,243

20,822104,998

61,994

11,86255,45733,294

11,72656,83834,579

11,12358,37936,033

10,50059,30023,300

91,896499,832278,799

104,386476,298326,761

13,16910,187

2,598

33,29519,839

4,277

14,8189,2262,216

19,83915,758

4,112

22,55318,247

5,200

25,60020,300

2,300

60,07557,30812,508

112,47175,83926,372

4.420.635.4

3.916.430.1

4.520.736.3

4.517.929.8

4.517.828.6

4.317.936.9

4.317.830.4

3.716.626.9

530,935855,497371,064

572,927957,152415,938

284,835342,456127,693

278,757443,742198,627

264,292463,443218,577

256,500471,200129,200

2,389,7084,409,4881,897,529

3,117,2994,535,7452,375,929

38,83076,66836,273

28,87770,01634,652

27,81547,99819,072

16,89844,90325,116

14,59240,97824,291

13,00037,70014,600

194,106434,915203,787

235,945388,255220,211

381,994311,47875,727

426,701378,210

84,299

189,277124,958

26,203

191,979160,494

40,903

181,376167,399

45,449

175,500169,600

17,600

1,623,5601,523,015

345,672

2,182,3031,581,611

495,629

94,830450,087253,171

81,861477,307286,508

47,679154,680

78,229

44,941209,959122,344

41,819222,770136,450

39,000229,000

90,100

477,2612,331,0371,308,857

542,6872,406,4071,591,504

15,28117,264

5,893

35,48831,61910,479

20,06414,820

4,189

24,93928,38610,264

26,50532,29612,387

29,00034,900

6,900

94,781120,521

39,213

156,364159,472

68,585

17.952.668.2

14.349.968.9

16.745.261.3

16.147.361.6

15.848.162.4

15.248.669.7

20.052.969.0

17.453.167.0

An

Agin

gW

orld

:2

00

1U

.S.C

ensu

sBu

reau1

38



Males Females


divorcedPercent


divorcedPercent

widowed

1990


1991


Germany

1970


1982


1988


1991


Greece

1971

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

1981


1991


2,614,9862,773,4791,114,976

2,878,3003,139,500

649,000

3,136,6003,086,797

879,316

2,737,4003,216,0001,251,000

3,265,1333,245,6881,403,904

4,373,9004,020,000

839,100

443,948418,340

423,832549,829189,998

631,100617,900127,800

235,586211,88576,838

282,000242,300

43,900

135,849132,357

36,175

110,800130,100

55,800

171,216123,379

57,930

222,400135,000

32,800

21,16020,520

18,59021,442

7,189

24,40021,300

3,800

2,194,8042,022,866

712,221

2,366,0002,344,500

378,400

2,795,3802,317,143

517,775

2,445,6002,425,600

793,100

2,822,0462,473,976

921,075

3,763,8003,068,800

464,100

404,516333,732

392,225455,562139,959

583,800506,700

83,200

98,060477,313306,957

103,900473,400216,400

123,806585,809315,902

101,800595,500383,500

126,924567,492397,205

167,100713,300328,000

13,76060,980

9,09069,13241,876

15,10085,20040,300

86,53661,41518,960

126,40079,30010,300

81,56551,488

9,464

79,20064,80018,600

144,94780,84127,694

220,600102,900

14,200

4,5123,108

3,9273,693

974

7,8004,700

500

3.717.227.5

3.615.133.3

3.919.035.9

3.718.530.7

3.917.528.3

3.817.739.1

3.114.6

2.112.622.0

2.413.831.5

2,902,7484,421,1242,193,119

3,149,1004,860,7001,465,600

4,304,1304,903,7871,680,054

3,806,5005,957,1002,631,400

3,638,2786,269,3293,158,012

4,666,5007,894,3002,173,200

475,724537,928

474,844689,372264,206

669,000786,200182,400

229,922403,594218,872

240,100416,200140,600

391,801573,521200,600

338,900568,700287,600

278,386575,328301,265

314,800684,600201,800

27,66027,268

29,62632,76310,700

37,20039,900

7,400

2,023,7511,512,800

450,458

2,213,0001,780,300

209,000

2,501,6281,547,339

275,032

2,494,5001,702,800

422,800

2,515,1481,874,546

515,681

3,274,1002,422,900

221,700

330,596209,620

339,831300,341

75,114

505,800333,700

38,200

522,5742,367,8511,469,550

529,3002,495,3001,078,400

1,240,0282,655,9391,172,131

788,4003,478,2001,853,800

650,7793,581,4102,247,150

782,6004,431,4001,682,600

109,892296,292

96,267349,441176,850

111,100403,300135,800

126,501136,879

54,239

166,700168,900

37,600

170,673126,988

32,291

184,700207,400

67,200

193,965238,045

93,916

295,000355,400

67,100

7,5764,748

9,1206,8271,542

14,9009,3001,000

18.053.667.0

16.851.373.6

28.854.269.8

20.758.470.4

17.957.171.2

16.856.177.4

23.155.1

20.350.766.9

16.651.374.5

An

Agin

gW

orld

:2

00

1U

.S.C

ensu

sBu

reau1

39



Males Females


divorcedPercent


divorcedPercent

widowed

Italy

1971


1981


1991


Luxembourg

1970


1981


1990


1991


Norway

1977


2,801,2122,551,027

792,656

2,701,1493,069,244

968,219

3,181,5173,543,7101,390,939

19,24417,886

5,214

15,76819,475

6,355

20,98718,605

7,490

20,00018,700

3,500

225,959246,374

87,866

298,550274,11876,604

202,979202,032

58,630

280,975266,190

98,795

1,9791,875

541

1,1521,828

640

1,5411,448

652

1,6001,400

300

25,74729,37210,638

2,349,2351,767,979

440,808

2,373,4862,332,399

610,114

2,743,0582,723,996

934,508

15,55611,7172,581

13,32013,483

3,562

17,62213,364

4,464

17,40013,600

1,800

183,355169,746

49,369

122,338490,320271,304

88,985508,423293,738

101,805521,379349,425

9873,9292,030

7303,7532,064

9053,4032,253

9003,4001,400

7,81141,32926,362

31,08918,610

3,940

35,69926,390

5,737

55,67932,145

8,211

722365

62

56641189

919390121

100300

-

9,0465,9271,497

4.419.234.2

3.316.630.3

3.214.725.1

5.122.038.9

4.619.332.5

4.318.330.1

4.518.240.0

3.516.830.0

3,113,2654,291,6611,599,749

3,101,9064,415,8821,715,514

3,508,1945,187,2152,412,277

21,48024,953

8,252

19,58030,07112,003

22,35532,07915,305

21,70031,500

8,200

240,003330,581137,309

462,317560,307196,832

346,690559,459226,393

319,232598,889296,759

2,5363,5131,213

1,9913,7701,666

1,7163,4781,795

1,5003,4001,000

22,68956,14127,338

1,964,4721,199,330

231,759

2,106,2521,574,337

328,589

2,514,8351,936,734

521,426

13,2208,1211,363

12,7029,3542,002

15,48810,077

2,586

15,20010,100

900

170,526122,789

28,632

658,6702,516,3421,167,450

603,7722,255,2071,155,103

611,0812,609,3961,583,248

5,06012,933

5,594

4,23416,393

8,198

4,19617,80410,657

4,00017,400

6,200

36,105141,280

77,551

27,80615,682

3,708

45,19226,879

5,429

63,04642,19610,844

664386

82

653554137

955720267

1,000600100

10,68310,371

3,788

21.258.673.0

19.551.167.3

17.450.365.6

23.651.867.8

21.654.568.3

18.855.569.6

18.455.275.6

15.042.756.5

An

Agin

gW

orld

:2

00

1U

.S.C

ensu

sBu

reau1

40



Males Females


divorcedPercent


divorcedPercent

widowed

1987


1990


Sweden

1977


1987



1991


United Kingdom

1971


1986


1989


205,426279,469103,545

189,896287,792109,513

485,407569,226196,040

430,710656,804262,793

410,001656,389267,774

410,000656,400131,900

3,066,2652,797,594

836,948

2,887,5003,353,2001,200,900

2,858,4143,572,0101,337,065

22,39630,27211,613

19,49930,27011,652

60,35272,69224,546

51,96175,83630,692

47,09673,10129,616

47,10073,10014,600

261,004205,576

54,024

254,700253,000

90,200

243,222274,562102,474

162,185196,651

62,201

148,294202,542

66,783

373,892379,408108,314

314,445442,831155,617

300,165453,183169,597

296,500440,600

69,400

2,625,1232,017,125

477,624

2,378,3002,424,800

735,900

2,338,2942,575,814

827,817

6,93843,20927,508

6,24143,93428,460

17,19093,51357,709

12,89097,29665,161

11,37987,66857,379

11,70096,80042,900

144,487558,282302,586

122,800595,600355,300

112,999620,944380,173

13,9079,3372,223

15,86211,0462,618

33,97323,613

5,471

51,41440,84111,323

51,36142,43711,182

54,70045,900

5,000

35,65116,6112,714

131,70079,80019,500

163,899100,690

26,601

3.415.526.6

3.315.326.0

3.516.429.4

3.014.824.8

2.813.421.4

2.914.732.5

4.720.036.2

4.317.829.6

4.017.428.4

214,785389,091175,379

197,620403,097187,275

503,768731,307299,053

453,167873,689418,064

430,341883,652431,817

430,400883,700245,500

3,429,8304,478,1901,758,765

3,081,3005,141,0002,401,500

3,016,1785,381,7562,595,328

13,94248,42528,112

11,17644,69826,518

41,444111,36055,811

29,89292,42256,500

27,47182,93650,656

27,50082,90033,300

381,665670,920286,784

215,300543,800304,900

190,734523,576301,632

154,254149,830

37,746

141,924157,295

41,784

353,317277,795

61,415

312,671344,972

97,876

292,651347,240102,240

292,700347,200

37,500

2,362,6741,560,502

328,555

2,206,3001,901,900

513,600

2,170,8982,025,176

575,773

32,800175,993104,299

29,311184,534112,943

69,435306,841170,692

54,378375,320241,690

49,418384,817253,530

49,400384,900162,500

627,1352,215,0891,138,201

496,5002,560,5001,543,600

460,0632,664,3991,664,908

13,78914,843

5,222

15,20916,570

6,030

39,57235,31111,135

56,22660,97521,998

60,80168,65925,391

60,80068,70012,200

58,35631,679

5,225

163,200134,800

39,400

194,483168,605

53,015

15.345.259.5

14.845.860.3

13.842.057.1

12.043.057.8

11.543.558.7

11.543.666.2

18.349.564.7

16.149.864.3

15.349.564.2

An

Agin

gW

orld

:2

00

1U

.S.C

ensu

sBu

reau1

41



Males Females


divorcedPercent


divorcedPercent

widowed

1991


Eastern Europe

Bulgaria

1975


1985


Czech Republic

1980



1991


Hungary

1976


1986


2,830,9003,615,000

623,800

399,856443,012124,090

546,879457,842167,096

646,909748,674216,008

720,089704,266265,668

485,282489,675

75,446

471,397557,457162,652

567,845515,498192,833

239,000270,100

42,600

5,2005,2611,302

12,0037,5802,710

30,91530,868

8,322

34,65528,96910,527

21,76019,107

2,608

16,80720,147

4,692

22,57218,487

7,412

2,302,1002,588,200

335,600

371,413337,884

72,341

496,119337,949

97,001

560,440552,105128,248

614,501533,614175,047

409,028356,042

37,850

418,320414,958

94,283

487,560374,827113,810

111,300649,500236,500

18,15896,18749,703

25,456106,035

65,537

25,694144,297

75,290

29,873118,54874,270

21,26593,83833,167

19,074108,933

60,856

27,575107,177

67,929

178,500107,200

9,100

5,0853,680

744

13,3016,2781,848

29,86021,404

4,148

41,06023,135

5,824

33,22920,688

1,821

17,19613,419

2,821

30,13815,007

3,682

3.918.037.9

4.521.740.1

4.723.239.2

4.019.334.9

4.116.828.0

4.419.244.0

4.019.537.4

4.920.835.2

2,972,2005,395,1001,464,200

421,076523,533168,484

585,811565,291227,723

757,7751,142,571

423,983

846,6641,130,671

511,891

565,195811,044181,553

564,878800,008280,962

685,094819,853357,205

181,300500,500181,200

7,5117,3971,994

12,27510,024

3,910

35,49070,78530,902

30,02355,21027,642

16,13534,93310,137

31,12150,95518,199

29,79247,98023,005

2,141,8002,067,700

225,200

325,704254,612

47,626

440,441244,652

61,026

501,161362,731

65,033

554,083359,250

91,946

368,270239,197

15,299

361,430257,228

38,698

433,756231,717

49,790

440,3002,664,0001,037,000

79,592256,559117,873

112,741300,620159,920

175,962669,794317,468

199,660664,393375,925

131,779492,742150,259

139,244464,137217,790

166,222503,256273,930

208,800162,900

20,800

8,2694,965

991

20,3549,9952,867

45,16239,26110,580

62,89851,81816,378

49,01144,172

5,858

33,08327,688

6,275

55,32436,90010,480

14.849.470.8

18.949.070.0

19.253.270.2

23.258.674.9

23.658.873.4

23.360.882.8

24.758.077.5

24.361.476.7

An

Agin

gW

orld

:2

00

1U

.S.C

ensu

sBu

reau1

42



Males Females


divorcedPercent


divorcedPercent

widowed

1989


1990


Poland

1978


1984


1990


Russia

1979


1989


1994


Ukraine

1979


547,931535,389204,680

539,776527,464199,768

1,211,2001,388,900

385,600

1,641,2711,341,418

938,479

1,742,1971,404,164

528,952

3,598,6103,700,3621,998,396

6,942,9453,692,0942,329,920

366,460252,865118,227

1,536,2261,817,7941,057,319

22,28518,887

7,760

21,09016,842

6,594

38,40043,00011,400

54,07138,95026,397

70,90746,28718,610

32,25126,02114,470

102,30235,22920,141

9,1554,1482,128

12,88312,834

7,467

465,530390,517121,514

453,667390,600125,595

1,101,7001,104,900

256,700

1,473,3491,043,812

695,277

1,533,8811,081,221

348,848

3,322,8793,098,6711,565,276

6,116,4882,930,1721,750,402

317,394201,743

86,897

1,434,1561,498,157

811,681

27,561109,317

71,327

29,436102,433

62,906

45,200222,300113,900

73,417241,080205,868

83,049253,365155,425

139,191517,776392,666

364,262649,073521,426

19,72940,67227,074

55,538285,300227,721

32,55516,668

4,079

35,58317,589

4,673

25,90018,700

3,600

40,43417,57610,937

54,36023,291

6,069

104,28957,89425,984

359,89377,62037,951

20,1826,3022,128

33,64921,50310,450

5.020.434.8

5.519.431.5

3.716.029.5

4.518.021.9

4.818.029.4

3.914.019.6

5.217.622.4

5.416.122.9

3.615.721.5

662,671862,052385,184

653,691846,458376,704

1,522,0002,172,200

766,200

2,024,3262,207,1761,644,993

2,074,6922,322,8831,042,532

7,055,1989,968,7786,182,892

9,771,29210,398,320

7,268,664

486,535610,580371,823

2,830,6034,014,9822,488,489

25,59747,27923,653

24,07344,03921,843

113,600181,500

67,800

123,823166,816128,420

118,507184,703

89,835

411,867363,730203,761

488,703565,746343,289

21,69146,96430,489

157,805123,325

67,845

416,800248,978

52,833

409,295253,434

58,239

993,200703,300123,000

1,345,924666,087397,829

1,377,955721,607170,848

3,545,5802,142,027

948,649

5,699,2502,440,0301,186,416

291,920173,707

68,415

1,491,6561,013,444

477,088

161,665521,985296,162

163,563509,434284,462

368,6001,258,800

570,100

483,8661,344,2801,101,010

491,9121,378,164

772,187

2,519,2777,140,1704,883,918

2,631,8326,921,9215,492,090

119,644352,483255,071

978,7172,768,9431,894,225

58,60943,81012,536

56,76039,55112,160

46,60028,600

5,300

70,71329,99317,734

86,31838,409

9,662

578,474322,851146,564

951,507470,623246,869

53,28137,42517,847

202,425109,270

49,331

24.460.676.9

25.060.275.5

24.258.074.4

23.960.966.9

23.759.374.1

35.771.679.0

26.966.675.6

24.657.768.6

34.669.076.1

An

Agin

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orld

:2

00

1U

.S.C

ensu

sBu

reau1

43



Males Females


divorcedPercent


divorcedPercent

widowed

1989


North America/Oceania

Australia

1971


1981

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

1990


1991

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

Canada

1976


1986


1991


New Zealand

1976


2,587,8741,760,8521,098,497

545,204446,861139,676

650,931601,119

732,290812,087281,389

710,813816,199

928,045875,410295,525

1,124,0551,133,320

394,450

1,180,0251,330,435

478,980

127,006118,52835,170

29,96415,367

8,774

45,33639,51211,843

49,77144,954

56,12856,22719,384

54,12856,745

76,19583,76029,160

83,03585,55532,270

80,37592,38534,990

8,9748,0052,405

2,327,8361,388,448

808,501

447,152304,336

76,882

529,859433,077

602,022609,784188,195

566,398599,208

777,515627,260176,600

925,650843,940255,565

976,2601,001,765

320,305

107,51287,94821,654

128,685326,937266,538

25,20384,04546,206

25,98394,236

24,079112,30865,739

22,934111,264

32,395133,350

81,415

36,590153,370

93,035

33,670171,620105,820

5,22419,07410,368

101,38930,10014,684

27,51318,968

4,745

45,31828,852

50,06133,768

8,071

67,35348,982

41,94031,040

8,350

78,78050,45513,580

89,72064,66517,865

5,2963,501

743

5.018.624.3

4.618.833.1

4.015.7

3.313.823.4

3.213.6

3.515.227.5

3.313.523.6

2.912.922.1

4.116.129.5

3,591,2484,272,9082,891,993

561,775618,134245,906

675,286828,278

725,2321,095,493

474,737

709,3891,090,493

996,3851,126,900

452,260

1,204,2551,505,735

653,025

1,219,6001,842,540

795,925

136,617159,917

61,522

202,424203,089114,439

40,44966,02429,185

32,79267,572

30,06566,57335,973

31,26767,929

79,035115,26047,805

72,30576,30065,000

68,575141,155

73,545

8,86915,828

6,816

2,148,5751,110,959

514,048

379,001205,434

43,297

473,366307,052

528,761476,259132,427

507,554469,178

689,700421,745

94,615

849,405618,240146,185

864,175755,165191,820

97,18862,42313,161

925,4962,790,5712,180,036

113,384327,640168,544

120,806423,622

111,423510,286294,852

100,234499,139

177,195561,060303,770

188,285753,915428,370

169,170859,380509,490

24,63877,59440,616

314,753168,289

83,470

28,94119,036

4,880

48,32230,032

54,98342,37511,485

70,33454,247

50,45528,835

6,070

94,26057,28013,470

117,68086,84021,070

5,9224,072

929

25.865.375.4

20.253.068.5

17.951.1

15.446.662.1

14.145.8

17.849.867.2

15.650.165.6

13.946.664.0

18.048.566.0

An

Agin

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orld

:2

00

1U

.S.C

ensu

sBu

reau1

44



Males Females


divorcedPercent


divorcedPercent

widowed

1986


1991


Africa

Egypt

1976

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

1986

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

Liberia

1974

55 to 59 . . . . . . . . . . . . . . . . .60 and over . . . . . . . . . . . . . .1984


Malawi

1977

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

1987

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

Morocco

1971

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

142,167141,021

47,736

137,658157,056

97,992

958,317634,402

1,238,704948,486

17,77551,862

45,43250,08821,859

113,484122,194

146,761157,832

332,610373,255

10,1498,6972,910

9,3129,5735,724

37,17733,320

48,14983,080

8602,317

2,2282,3231,005

1,5411,740

1,8471,725

11,02213,137

114,519103,446

30,357

108,423113,31067,209

874,779514,470

1,120,342724,867

14,67638,598

37,23737,36215,579

105,276106,166

135,439136,110

304,773314,402

5,77822,38912,903

5,50225,24820,589

41,40782,736

63,506135,776

8245,418

2,3915,6063,112

2,6708,794

3,62012,234

10,54036,746

11,7216,4891,566

14,4218,9254,470

4,9543,876

6,7074,763

1,4155,529

3,5764,7972,163

3,9975,494

5,8557,763

6,2758,970

4.115.927.0

4.016.121.0

4.313.0

5.114.3

4.610.4

5.311.214.2

2.47.2

2.57.8

3.29.8

142,566195,846

81,558

136,578215,802150,327

899,492667,501

1,259,315849,250

11,74237,525

36,60337,02915,661

121,332125,828

163,741168,526

299,453340,641

6,99614,643

7,431

6,04813,98310,656

40,88038,058

43,45771,024

3231,252

1,2041,475

663

1,2481,711

1,2111,724

10,48614,275

101,25077,77818,600

95,71285,41346,923

443,885153,724

680,465201,228

7,49614,539

22,80114,740

4,952

75,81349,739

101,13965,391

132,26065,949

23,19696,27353,670

20,871106,851

87,549

405,378470,612

518,032569,026

2,78317,150

9,34817,105

8,440

30,27161,215

38,94479,558

139,550243,393

11,1247,1521,857

13,9479,5555,199

9,3495,107

17,3617,972

1,1404,584

3,2503,7091,606

14,00013,163

22,44721,853

17,15717,024

16.349.265.8

15.349.558.2

45.170.5

41.167.0

23.745.7

25.546.253.9

24.948.6

23.847.2

46.671.5

An

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00

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.S.C

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45



Males Females


divorcedPercent


divorcedPercent

widowed

1982


Tunisia

1975

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

1984


Zimbabwe

1982


1992


Asia

Bangladesh

1974

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

1981

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

China

1982

50 to 59 . . . . . . . . . . . . . . . . .60 to 79 . . . . . . . . . . . . . . . . .80 and over . . . . . . . . . . . . . .

1990

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

481,613424,846170,260

158,120118,990

191,330167,260

48,480

144,250115,93047,310

190,189161,452

51,977

1,695,3111,372,987

1,969,4881,704,863

38,995,45033,773,360

1,760,680

39,380,26028,717,770

8,0357,5463,703

3,9203,390

4,3906,4903,510

6,4956,9063,523

4,7334,5021,616

14,14412,345

28,7474,187

1,158,670858,010

44,160

1,257,460645,970

451,518367,417137,207

147,150100,740

180,140141,600

35,850

127,45594,86836,815

170,402133,898

40,495

1,595,4511,211,675

1,864,9851,518,419

33,740,04023,850,350

654,620

33,411,98019,113,740

13,88140,39724,492

5,81013,540

5,84018,220

8,870

4,5159,2675,255

6,01614,600

7,223

83,804147,891

74,559181,204

3,315,6008,534,6601,047,130

4,083,4708,623,420

8,1799,4864,858

1,2401,320

960950250

5,7854,8891,717

9,0388,4522,643

1,9121,076

1,1971,053

781,140530,340

14,770

627,350334,640

2.99.5

14.4

3.711.4

3.110.918.3

3.18.0

11.1

3.29.0

13.9

4.910.8

3.810.6

8.525.359.5

10.430.0

456,984375,217143,225

129,470100,420

172,480131,950

41,190

126,060122,770

53,440

170,913181,464

68,301

1,339,2061,001,340

1,599,5351,249,841

35,626,30037,708,310

3,280,380

36,427,78034,476,600

5,5157,5422,939

3,0904,160

3,3404,7802,690

3,8525,9023,138

2,8093,7961,670

4,1044,916

13,7361,360

75,270109,310

8,710

72,370104,770

240,76285,41418,571

81,40030,890

113,80044,280

6,760

76,40744,38314,879

101,72557,98014,061

577,702208,707

743,735344,564

29,271,14016,658,820

234,240

27,982,04012,794,280

188,131266,817116,189

41,84061,720

53,31081,49031,420

39,08866,99533,147

53,358110,81349,974

752,369785,640

838,107901,865

6,112,76020,794,240

3,033,140

8,234,09021,463,040

22,57615,444

5,526

3,1403,650

2,0301,400

320

6,7135,4902,276

13,0218,8752,596

5,0312,077

3,9572,052

167,130145,940

4,290

139,280114,510

41.271.181.1

32.361.5

30.961.876.3

31.054.662.0

31.261.173.2

56.278.5

52.472.2

17.255.192.5

22.662.3

An

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46



Males Females


divorcedPercent


divorcedPercent

widowed

India

1971

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

1981

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

Indonesia

1971


1976


1980


1985



Israel

1972

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

1983


14,352,0029,383,212

17,887,88012,625,093

2,208,4191,439,842

380,399

2,599,5151,572,899

417,437

3,279,7312,188,609

688,422

4,150,0702,618,922

729,005

4,540,6903,142,674

867,636

127,355110,538

141,342169,283

60,465

347,164226,541

368,498253,621

35,09619,751

5,848

20,8609,5952,362

23,88119,761

7,251

56,18926,1185,767

113,977118,93247,364

3,5962,677

4,2264,0301,388

11,826,4186,620,836

15,361,8249,375,358

1,950,3471,128,295

268,882

2,316,7861,251,201

300,153

3,015,9281,787,537

507,540

3,771,2372,124,396

532,776

4,088,2072,518,407

606,681

116,91588,717

129,478137,302

43,366

2,112,1332,491,958

2,087,5762,947,660

194,512269,286

99,578

249,730301,798111,812

191,399340,079159,786

264,788426,160178,879

272,502449,038193,902

4,91817,656

4,39324,74414,684

66,28743,877

69,98248,454

28,46422,510

6,091

12,13910,305

3,110

48,52341,23213,845

57,85642,24811,583

66,00456,29719,689

1,9261,488

3,2453,2071,027

14.726.6

11.723.3

8.818.726.2

9.619.226.8

5.815.523.2

6.416.324.5

6.014.322.3

3.916.0

3.114.624.3

12,841,0668,928,952

16,697,61012,377,227

2,356,1151,528,535

406,459

2,649,3231,803,247

478,171

3,339,1752,581,307

836,951

4,473,9332,954,026

916,813

4,817,4583,608,4321,104,720

134,120113,961

163,422192,019

67,408

58,03132,093

59,94850,035

20,12512,753

3,749

20,14612,599

2,938

32,65426,825

9,420

40,51221,759

6,372

53,96870,75431,098

3,3103,430

3,5304,9512,055

5,965,8132,220,930

9,116,9513,579,769

932,949354,997

68,887

1,058,867348,882

58,956

1,618,490657,722144,331

2,041,873549,132

90,512

2,655,7171,021,497

194,441

94,42041,604

119,59879,33615,846

6,753,2046,646,582

7,438,7398,705,536

1,314,9441,115,343

324,097

1,545,2601,431,870

414,644

1,477,1931,764,132

648,026

2,061,6472,213,245

780,658

1,856,4292,361,881

842,176

32,80266,832

34,253102,41147,982

64,01829,347

81,97241,887

88,09745,442

9,726

25,0509,8961,633

210,838132,628

35,174

329,901169,890

39,271

251,344154,300

37,005

3,5882,095

6,0415,3211,525

52.674.4

44.570.3

55.873.079.7

58.379.486.7

44.268.377.4

46.174.985.1

38.565.576.2

24.558.6

21.053.371.2

An

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00

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47



Males Females


divorcedPercent


divorcedPercent

widowed

Japan

1970


1985


1990


1995


Malaysia

1970

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

1980

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

1991


Pakistan

1972


1981

55 to 59 . . . . . . . . . . . . . . . . .60 and over . . . . . . . . . . . . . .

3,772,6003,226,900

876,600

5,784,9825,095,7461,813,509

6,990,9855,963,8912,220,234

7,518,5697,504,2532,563,989

251,597164,368

287,996233,965

402,570305,244

98,529

1,683,1181,478,378

552,803

859,4883,313,787

43,10032,100

8,400

109,14147,20913,310

176,50464,36517,428

272,591105,804

22,958

9,8989,384

8,6548,795

9,8525,7851,936

80,86544,02418,045

14,88486,400

3,478,0002,442,700

529,800

5,364,5334,180,1331,278,654

6,413,8134,988,3641,645,043

6,701,1876,303,8931,936,331

214,974119,938

255,709178,027

368,465245,931

70,060

1,393,6511,079,356

362,656

794,8012,831,735

198,500711,900329,200

191,339797,467500,860

221,829823,176531,680

227,297932,077567,389

20,92429,028

18,76340,205

20,40848,51224,467

204,778352,154171,132

48,028388,411

53,00040,200

9,200

119,96970,93720,685

178,83987,98626,083

254,228128,926

30,047

5,8016,018

4,8706,938

3,8455,0162,066

3,8242,844

970

1,7757,241

5.322.137.6

3.315.627.6

3.213.823.9

3.012.422.1

8.317.7

6.517.2

5.115.924.8

12.223.831.0

5.611.7

4,343,8004,107,7001,361,100

6,609,4537,351,7512,887,622

7,410,5358,810,9283,686,493

7,910,02010,756,569

4,605,588

227,642152,489

299,080239,300

419,473350,597120,098

1,273,4003,234,616

419,931

751,3692,419,875

78,40048,50014,200

263,400124,142

32,324

312,820204,089

53,258

325,156321,441

86,456

4,2873,535

5,4775,088

8,5104,9701,804

20,17821,044

9,162

7,28163,724

2,722,2001,281,600

186,200

4,881,6452,694,778

538,231

5,710,5903,569,894

777,384

6,144,3094,634,4641,010,944

122,92143,179

172,77771,172

273,984126,996

28,858

809,2382,030,933

119,092

605,3831,200,062

1,414,3002,704,2001,141,500

1,181,8434,346,6362,265,126

1,071,4934,773,3262,776,361

1,030,4045,391,7603,366,835

93,20699,730

104,199145,507

124,282204,693

84,330

440,7411,179,010

290,965

136,5841,148,854

128,90073,40019,200

282,565186,195

51,941

315,632263,619

79,490

373,261344,639106,299

7,2286,045

16,62717,533

12,69713,938

5,106

3,2433,629

712

2,1217,235

32.665.883.9

17.959.178.4

14.554.275.3

13.050.173.1

40.965.4

34.860.8

29.658.470.2

34.636.469.3

18.247.5

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48



Males Females


divorcedPercent


divorcedPercent

widowed

Philippines

1970

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

1975

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

1980


1990


Singapore

1970


1980


1990


South Korea

1975

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

1980


713,283504,464

877,576604,964

968,578792,595228,270

1,252,033948,705307,422

59,04230,589

5,840

66,78451,20212,036

90,50073,30044,000

783,671458,360

894,976539,414116,991

20,11413,479

40,72733,886

29,25224,520

8,051

38,67729,66910,761

3,5312,147

453

3,1762,350

579

5,7003,7002,000

1,095615

1,912876268

630,558381,080

768,372461,399

854,546616,185154,003

1,116,273738,412208,594

50,31421,621

3,347

59,03938,762

7,702

78,10054,20030,500

728,831355,840

834,595431,132

74,234

58,108106,603

63,484105,292

77,289146,465

64,728

86,573173,753

85,965

4,7516,5822,000

3,7499,5483,643

5,50014,80011,200

50,993100,902

55,062106,394

42,324

4,5033,302

4,9934,387

7,4915,4251,488

10,5106,8712,102

446239

40

820542112

1,200600300

2,7521,003

3,4071,012

165

8.121.1

7.217.4

8.018.528.4

6.918.328.0

8.021.534.2

5.618.630.3

6.120.225.5

6.522.0

6.219.736.2

705,960525,339

827,618595,711

1,029,004838,298246,437

1,313,4561,108,875

378,595

55,24638,77511,187

64,30862,72219,234

91,40089,00058,800

892,965748,040

1,052,347906,571283,692

55,31238,095

48,83542,056

72,61669,60121,440

87,63797,03938,167

3,1332,161

527

2,2523,4051,030

3,2003,4002,500

1,254941

1,466913286

461,663207,556

580,469269,671

693,846366,999

67,126

892,949467,385103,757

28,8938,7871,325

38,52018,485

2,999

60,10029,80015,600

467,699181,991

565,995220,236

32,966

181,836276,324

189,778277,730

250,470394,730156,115

315,344534,591234,128

22,78427,683

9,311

22,37240,33715,111

26,40055,00040,300

420,490563,677

480,351683,937250,092

7,1493,364

8,5366,254

12,0726,9681,756

17,5269,8602,543

436144

24

1,164495

94

1,700800400

3,5221,431

4,5351,485

348

25.852.6

22.946.6

24.347.163.3

24.048.261.8

41.271.483.2

34.864.378.6

28.961.868.5

47.175.4

45.675.488.2

An

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49



Males Females


divorcedPercent


divorcedPercent

widowed

1995


Sri Lanka

1971

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

1981

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

Thailand

1970

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

1980


1990


Turkey

1970

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

1975

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

1980

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

1985

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

1,596,591974,330260,048

342,783292,430

405,454338,873

687,607460,737

932,326671,668386,275

1,627,8221,131,407

667,111

951,639684,680

895,135801,249

967,439955,360

1,380,066954,926

5,9271,808

427

25,21422,033

25,77222,779

25,33423,922

15,36410,201

5,939

52,84644,51927,407

16,69411,572

32,22444,047

22,12320,399

28,29118,470

1,499,393815,153186,012

293,162223,007

355,413265,274

594,563333,654

822,471501,902267,797

1,417,897835,546460,389

865,461549,466

805,594619,132

893,743752,991

1,284,548748,052

74,968153,578

73,003

21,89945,656

21,67648,884

54,01691,808

77,139145,231103,989

127,917231,174167,344

60,010117,734

48,186130,474

41,817172,800

54,261180,204

16,3033,791

606

2,5081,734

2,5931,936

13,69411,353

17,35214,334

8,550

29,16220,16811,971

9,4745,908

9,1317,596

9,7569,170

12,9668,200

4.715.828.1

6.415.6

5.314.4

7.919.9

8.321.626.9

7.920.425.1

6.317.2

5.416.3

4.318.1

3.918.9

1,810,9371,665,290

573,460

274,747246,160

358,507305,118

721,851583,995

997,614853,188528,191

1,723,0751,363,274

860,452

946,802817,867

914,943969,729

975,8501,157,887

1,398,8501,170,704

5,9422,927

834

12,43511,096

14,57914,813

15,94511,594

25,93817,26810,279

56,16330,20517,973

11,55011,765

38,93160,407

13,16414,871

18,97616,223

1,186,514440,708

65,165

177,589100,276

244,312136,087

434,047202,726

613,225296,823146,404

1,142,804536,726274,956

638,241308,100

614,073388,614

693,394481,671

1,017,093475,642

598,7091,215,198

506,334

82,827133,899

97,734152,809

243,036353,804

320,551517,907360,432

465,812764,705550,120

284,091486,917

245,626500,981

256,682648,208

346,272667,269

19,7726,4571,127

1,896889

1,8821,409

28,82315,871

37,90021,19011,076

58,29631,63817,403

12,92011,085

16,31319,727

12,61013,137

16,50911,570

33.173.088.3

30.154.4

27.350.1

33.760.6

32.160.768.2

27.056.163.9

30.059.5

26.851.7

26.356.0

24.857.0

An

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00

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50



Males Females


divorcedPercent


divorcedPercent

widowed

1990

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .


Argentina

1970


1980


1991


Brazil

1970

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

1980

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

Chile

1971


1982


1992


1,761,2981,090,850

938,600724,450208,200

1,090,965987,982590,415

1,129,0771,138,581

386,680

2,080,9061,396,751

2,709,6622,199,520

247,633201,11860,675

302,711287,638

92,864

406,075373,449132,292

34,44620,965

118,65087,85024,000

116,159107,11764,492

120,783110,29736,748

117,99272,597

143,380117,384

24,53918,802

5,427

31,29928,954

8,885

41,71637,65712,463

1,650,099886,618

749,600493,150117,300

896,474706,281395,104

888,809812,425243,419

1,758,3551,015,451

2,356,3651,668,831

197,296136,287

35,258

241,927197,508

55,420

323,126257,933

81,197

59,431173,513

49,950129,950

64,100

50,401155,419120,372

57,121174,899

95,506

133,771258,351

132,353347,749

19,35941,20718,761

19,55852,48226,075

20,70062,47534,045

17,3229,754

20,40013,500

2,800

27,93119,16510,447

62,36440,96011,007

70,78850,352

77,56465,556

6,4394,8221,229

9,9278,6942,484

20,53315,384

4,587

3.415.9

5.317.930.8

4.615.720.4

5.115.424.7

6.418.5

4.915.8

7.820.530.9

6.518.228.1

5.116.725.7

1,793,3261,325,943

992,750876,700291,500

1,191,6871,302,582

826,343

1,319,8461,627,578

648,202

2,043,3821,544,432

2,778,5722,470,392

276,181251,027

86,307

344,408371,879137,260

462,026503,595207,623

22,03718,206

124,750110,85036,750

133,844160,471103,444

127,009176,108

74,766

175,812140,333

231,878235,135

37,41137,91213,288

43,25553,12521,109

58,34663,81327,380

1,335,717569,358

614,800308,400

63,700

755,984452,848222,769

807,549522,746110,816

1,124,890441,444

1,673,165793,478

151,61574,80315,349

203,488126,330

28,832

280,729180,658

48,547

413,793724,501

226,800445,750188,650

262,711669,452490,740

296,062881,156451,171

621,538893,075

716,2131,356,397

74,114131,433

56,174

76,669178,798

83,984

88,224235,912125,070

21,77913,878

26,40011,7002,400

39,14819,8119,390

89,22647,56811,449

121,14269,580

157,31685,382

13,0416,8791,496

20,99613,626

3,335

34,72723,212

6,626

23.154.6

22.850.864.7

22.051.459.4

22.454.169.6

30.457.8

25.854.9

26.852.465.1

22.348.161.2

19.146.860.2

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Males Females


divorcedPercent


divorcedPercent

widowed

Colombia

1973

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

1985

55 to 59 . . . . . . . . . . . . . . . . .60 and over . . . . . . . . . . . . . .

Costa Rica

1973


1984

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

Guatemala

1973


1981


1990

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

Jamaica

1970

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

1982

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

395,786299,484

345,873784,394

39,35132,70210,807

54,51452,041

100,05873,95923,579

125,90893,14032,128

195,354146,250

53,80743,594

49,52161,420

43,41431,809

26,76465,881

4,1153,5991,247

5,2135,477

8,1596,5822,097

5,6443,9681,342

7,8633,228

16,13811,381

15,24015,029

316,836207,661

290,287586,751

32,02922,642

6,291

45,00336,492

83,27951,97214,316

108,74269,58821,124

172,362116,379

34,41526,398

30,69736,874

26,77053,065

14,411100,880

1,9095,1682,851

1,9137,570

7,95314,867

7,007

9,04017,315

8,915

10,00523,400

2,1995,028

2,0507,793

8,7666,949

14,41130,882

1,2981,293

418

2,3852,502

667538159

2,4822,269

747

5,1243,243

1,055787

1,5341,724

6.817.7

4.212.9

4.915.826.4

3.514.5

7.920.129.7

7.218.627.7

5.116.0

4.111.5

4.112.7

403,634342,120

352,050831,744

39,16733,29611,544

56,02755,933

94,10874,80225,081

117,09294,01433,955

199,174159,006

50,36055,256

54,97973,341

69,30660,872

41,175107,056

6,4586,2992,302

8,7639,852

13,02311,8143,993

8,2277,8392,971

7,5433,788

13,97420,420

17,46424,550

207,199105,687

203,819308,816

23,10612,145

2,770

34,00121,046

53,13824,653

5,524

70,35933,092

7,922

118,13161,285

27,28816,128

28,05324,016

111,126167,070

74,116364,403

7,09613,548

6,202

8,52221,942

26,24737,42415,362

31,77448,82821,920

56,07583,944

8,11418,108

7,97723,453

16,0038,491

32,94051,469

2,5071,304

270

4,7413,093

1,700911202

6,7324,2551,142

17,4259,989

984600

1,4851,322

27.548.8

21.143.8

18.140.753.7

15.239.2

27.950.061.2

27.151.964.6

28.252.8

16.132.8

14.532.0

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Males Females


divorcedPercent


divorcedPercent

widowed

Mexico

1970


1980

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

1990

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

Peru

1972


1981

55 to 64 . . . . . . . . . . . . . . . . .65 and over . . . . . . . . . . . . . .

Uruguay

1975


1985


952,598859,166271,779

1,273,5321,203,238

1,675,1401,556,114

280,616235,807147,746

368,119323,413

125,100118,10037,500

141,422138,397

49,013

55,63281,67937,022

65,29462,144

82,52777,296

20,81618,54512,549

23,42819,897

17,70014,800

4,700

17,79016,131

5,327

823,597645,216177,074

1,113,910937,252

1,477,3231,206,941

227,278161,290

94,501

307,249231,329

97,00081,10021,900

110,43397,20830,593

53,600110,83350,339

69,869179,373

79,133234,191

26,79851,95638,427

29,66165,962

5,10017,500

9,700

5,09018,83311,225

19,76921,438

7,344

24,45924,469

36,15737,686

5,7244,0162,269

7,7816,225

5,3004,7001,200

8,1096,2251,868

5.612.918.5

5.514.9

4.715.0

9.522.026.0

8.120.4

4.114.825.9

3.613.622.9

977,114932,239328,790

1,304,6221,353,191

1,797,3421,766,379

288,578279,079182,453

363,542356,488

132,000150,500

59,100

155,862191,265

79,218

81,251120,540

54,929

98,556117,562

125,817139,195

32,22735,79824,630

30,15930,420

17,50023,100

9,900

15,92424,85111,440

623,100392,106102,390

860,345617,558

1,226,032796,040

169,41698,59154,489

232,596139,776

79,50047,60010,900

95,95061,44014,451

229,334382,919159,468

286,550577,993

356,232766,937

77,644139,363100,448

86,250176,824

27,50074,50036,700

31,57796,33650,854

43,42936,67412,003

59,17140,078

89,26164,207

9,2915,3272,886

14,5379,468

7,5005,3001,600

12,4118,6382,473

23.541.148.5

22.042.7

19.843.4

26.949.955.1

23.749.6

20.849.562.1

20.350.464.2

Note: Data for ‘‘Married’’ include people living in consensual unions. Data for Czech Republic prior to 1991 refer to Czechoslovakia.


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Table 8.Support Ratios: 2000, 2015, and 2030

CountryTotal1 Youth2 Elderly3 Oldest old4

2000 2015 2030 2000 2015 2030 2000 2015 2030 2000 2015 2030

United States . . . . . . . . . .Western EuropeAustria . . . . . . . . . . . . . . . . . .Belgium . . . . . . . . . . . . . . . . .Denmark . . . . . . . . . . . . . . . .France . . . . . . . . . . . . . . . . . .Germany . . . . . . . . . . . . . . . .Greece . . . . . . . . . . . . . . . . . .Italy . . . . . . . . . . . . . . . . . . . . .Luxembourg . . . . . . . . . . . . .Norway. . . . . . . . . . . . . . . . . .Sweden . . . . . . . . . . . . . . . . .United Kingdom . . . . . . . . . .

Eastern EuropeBulgaria . . . . . . . . . . . . . . . . .Czech Republic . . . . . . . . . .Hungary . . . . . . . . . . . . . . . . .Poland . . . . . . . . . . . . . . . . . .Russia . . . . . . . . . . . . . . . . . .Ukraine. . . . . . . . . . . . . . . . . .

North America/OceaniaAustralia. . . . . . . . . . . . . . . . .Canada . . . . . . . . . . . . . . . . .New Zealand. . . . . . . . . . . . .

AfricaEgypt . . . . . . . . . . . . . . . . . . .Kenya. . . . . . . . . . . . . . . . . . .Liberia . . . . . . . . . . . . . . . . . .Malawi . . . . . . . . . . . . . . . . . .Morocco. . . . . . . . . . . . . . . . .Tunisia . . . . . . . . . . . . . . . . . .Zimbabwe . . . . . . . . . . . . . . .

AsiaBangladesh . . . . . . . . . . . . . .China . . . . . . . . . . . . . . . . . . .India . . . . . . . . . . . . . . . . . . . .Indonesia . . . . . . . . . . . . . . . .Israel. . . . . . . . . . . . . . . . . . . .Japan . . . . . . . . . . . . . . . . . . .Malaysia. . . . . . . . . . . . . . . . .Pakistan. . . . . . . . . . . . . . . . .Philippines. . . . . . . . . . . . . . .Singapore . . . . . . . . . . . . . . .South Korea . . . . . . . . . . . . .Sri Lanka . . . . . . . . . . . . . . . .Thailand. . . . . . . . . . . . . . . . .Turkey . . . . . . . . . . . . . . . . . .

Latin America/CaribbeanArgentina . . . . . . . . . . . . . . . .Brazil . . . . . . . . . . . . . . . . . . .Chile . . . . . . . . . . . . . . . . . . . .Colombia . . . . . . . . . . . . . . . .Costa Rica. . . . . . . . . . . . . . .Guatemala. . . . . . . . . . . . . . .Jamaica . . . . . . . . . . . . . . . . .Mexico . . . . . . . . . . . . . . . . . .Peru . . . . . . . . . . . . . . . . . . . .Uruguay . . . . . . . . . . . . . . . . .

70

6268637160646063707169

645961676465

676369

97139133149103

87134

112679482866196

1261054658756583

8480778690

13289959982

70

6168717164666564707068

585858565457

676265

7390

139115735898

7056736976788187854258626060

7664657367

10961737579

87

7783798180747573808280

696866717068

777869

6570

11584675984

6165676573827968735468666660

71647073668860676877

48

3739394334363140444143

373738464342

464249

90133125142

9376

126

105568574673388

117983647645472

6571647780

12376879059

45

3135393931322839413437

262830333334

403542

6483

129109

644688

6341635856347079763040464447

5551476155

10149626455

49

3236383833302639403637

252729333535

403739

5161

10678513972

4939524748316257603135403840

46424253457840505150

21

2528242726282923262927

272224202123

212119

77879

118

712

98

1827

897

1011111111

191013

910

813

89

24

25

3033323233343625303631

323028232124

262623

97

1079

1210

715101120441189

1218151613

2113181112

912111124

37

4546414446444934404642

444237383533

374130

13996

152012

1226151826521711132333252721

25222820211120171728

26

2221272322202221292925

131717171616

242525

10131710141315

1513131024221413142114161415

22151712181422151521

26

2629243127303027262727

232224252321

262726

12172113172020

1318141727281415152419181820

26191916191824171828

26

2829313128313226303430

283028252021

282728

14212517151828

1318161626391714162021201919

27212216191819191928

1Total support ratio is the number of people 0 to 19 years and 65 years and over per 100 people 20 to 64 years.2Youth support ratio is the number of people 0 to 19 years per 100 people 20 to 64 years.3Elderly support ratio is the number of people 65 years and over per 100 people 20 to 64 years.4Oldest old support ratio is the number of people 80 years and over per 100 people 65 years and over.

Note: Youth and elderly ratios may not sum to total due to rounding.Source: U.S. Census Bureau, 2000a.


Table 9.Parent Support Ratios: 1950, 2000, and 2030

CountryParent support ratio Parent support ratio for females

1950 2000 2030 1950 2000 2030

United States . . . . . . . . . . . . . . . . . . . . . . . . .

Western EuropeAustria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Belgium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Denmark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .France . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Germany . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Greece. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Italy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Luxembourg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Norway . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Sweden . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .United Kingdom . . . . . . . . . . . . . . . . . . . . . . . . . . .

Eastern EuropeBulgaria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Czech Republic . . . . . . . . . . . . . . . . . . . . . . . . . . .Hungary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Poland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Russia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Ukraine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

North America/OceaniaAustralia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Canada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .New Zealand . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

AfricaEgypt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Kenya. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Liberia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Malawi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Morocco. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Tunisia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Zimbabwe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

AsiaBangladesh. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Indonesia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Israel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Japan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Malaysia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Pakistan. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Philippines. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Singapore . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .South Korea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Sri Lanka. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Thailand. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Turkey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Latin America/CaribbeanArgentina. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Brazil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Chile. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Colombia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Costa Rica . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Guatemala . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Jamaica . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Mexico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Peru . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .Uruguay. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

8

788

106988

1199

66569

10

898

24343

113

23343585573853

444683364

11

22

2021212319202218272723

111314141313

192020

4684999

7865

2018

676

137989

178

106

107

1878

20

33

3338363936343728354536

303027272121

323326

7111499

1230

7149

10245012

79

1419161512

24152112151012111226

16

1216161811171416211817

111210111417

151816

47675

216

656979

18119

125

2095

989

1116

77

127

23

43

3941424637394337545446

222526262323

394039

812158

161717

141613

939341215122514171418

34151912201434141637

63

6675727872677354699073

576052533938

646651

2226

2365

28

1948

1002315

2738303025

47294122291924212451

Note: The parent support ratio is the number of people aged 80 and over per 100 people aged 50 to 64. The parent support ratio forfemales is the number of people aged 80 and over per 100 women aged 50 to 64.


15

1618

13

19

18


Table 10.Labor Force Participation Rates by Age and Sex: Selected Years 1970 to 1999

Country

Year

Males Females

25 to 44years

45 to 49years


60 to 64years

65 yearsand over

25 to 44years

45 to 49years


60 to 64years

65 yearsand over

United States . . . . . . . . . . . . . . . . .

Western Europe

Austria . . . . . . . . . . . . . . . . . . . . . . . . .

Belgium . . . . . . . . . . . . . . . . . . . . . . . .

Denmark . . . . . . . . . . . . . . . . . . . . . . .

France . . . . . . . . . . . . . . . . . . . . . . . . .

Germany . . . . . . . . . . . . . . . . . . . . . . .

Greece. . . . . . . . . . . . . . . . . . . . . . . . .

Italy. . . . . . . . . . . . . . . . . . . . . . . . . . . .

197019801982199119961999

1971198119881996

19701977198119971999

19701976197919861996

19751982198419901996

19701980198819961999

19711981198719971998

19711981198919961998

94.393.492.293.992.893.0

97.196.595.093.6

96.296.894.594.494.7

93.494.396.694.193.2

96.295.595.496.195.8

96.796.194.192.993.8

93.896.890.196.296.2

95.596.295.691.291.7

93.592.092.092.290.890.3

95.896.394.794.3

92.292.490.890.591.1

96.393.996.192.791.5

95.494.995.095.995.0

95.996.896.494.594.5

191.795.198.095.294.3

92.193.295.693.193.5

91.488.590.188.486.987.0

92.791.590.086.6

89.287.785.781.680.3

94.891.693.387.487.7

92.190.990.891.692.6

93.293.393.290.490.5

(NA)90.084.289.286.7

87.285.787.579.380.1

86.880.681.179.077.978.4

83.777.365.363.7

82.379.270.749.252.4

91.187.790.881.281.2

81.876.970.068.670.4

86.882.379.873.976.5

275.381.174.375.071.7

75.065.167.858.954.1

73.060.457.954.854.354.8

44.923.314.216.7

79.342.132.318.418.6

81.379.362.049.642.0

54.639.129.918.116.4

68.844.234.528.730.3

(NA)61.753.547.845.4

40.629.135.230.631.7

24.819.317.715.816.916.9

8.03.11.84.6

6.84.23.31.9

162.8

23.524.016.312.8

1218.5

10.75.04.32.82.3

16.07.44.94.44.5

33.426.214.010.7

9.7

13.46.97.96.06.3

47.564.869.074.976.476.8

52.862.263.976.7

39.151.160.177.079.3

55.571.784.287.984.7

55.066.671.377.281.3

47.457.164.674.877.1

30.933.452.264.466.2

31.849.859.559.860.8

53.061.565.375.478.078.9

53.757.359.469.2

30.833.338.259.565.0

54.465.676.181.982.3

49.458.361.071.880.9

48.352.260.974.778.3

127.928.943.949.951.7

29.736.244.749.050.9

52.056.359.267.871.974.0

48.553.551.659.3

27.627.330.744.248.5

49.558.366.972.972.7

48.254.154.163.271.5

42.847.253.767.470.5

(NA)25.837.239.340.4

26.330.234.137.138.7

47.448.450.255.759.861.8

35.832.424.625.4

20.018.617.321.827.6

39.847.554.860.558.7

42.145.041.446.851.7

34.538.741.150.555.3

219.820.029.330.728.1

16.916.920.221.522.7

36.134.034.235.138.238.8

13.29.55.78.7

7.65.85.74.66.7

24.930.132.526.620.5

27.922.318.016.715.2

17.713.011.111.312.7

(NA)13.422.020.321.2

9.98.09.88.28.1

10.08.27.98.68.68.9

3.21.80.92.0

2.21.21.00.7

160.8

4.64.84.33.3

128.7

5.02.22.11.52.0

5.73.01.81.61.6

8.45.05.13.43.6

3.21.52.21.81.7

An

Agin

gW

orld

:2

00

1U

.S.C

ensu

sBu

reau1

56

Table 10.Labor Force Participation Rates by Age and Sex: Selected Years 1970 to 1999—Con.

Country

Year

Males Females

25 to 44years

45 to 49years


60 to 64years

65 yearsand over

25 to 44years

45 to 49years


60 to 64years

65 yearsand over

Luxembourg . . . . . . . . . . . . . . . . . . . .

Norway . . . . . . . . . . . . . . . . . . . . . . . .

Sweden . . . . . . . . . . . . . . . . . . . . . . . .

United Kingdom . . . . . . . . . . . . . . . . .

Eastern Europe

Bulgaria . . . . . . . . . . . . . . . . . . . . . . . .

Czech Republic . . . . . . . . . . . . . . . . .

Hungary. . . . . . . . . . . . . . . . . . . . . . . .

Poland . . . . . . . . . . . . . . . . . . . . . . . . .

Russia . . . . . . . . . . . . . . . . . . . . . . . . .

19701981198719961999

197019801985198919961999

197019751980198519961999

19711981198619931999

197519851992

19701980199119971999

1970198019961999

197019781996

1989199219961999

98.097.496.095.795.1

396.1394.395.393.792.692.3

90.091.990.690.689.688.7

98.097.593.994.5

1092.6

96.896.494.4

98.398.297.996.996.5

98.197.790.088.0

96.696.192.9

97.31092.11090.1

91.0

95.996.096.095.094.7

495.7493.395.293.891.992.2

92.992.292.092.192.090.7

98.197.3

191.692.8(NA)

95.794.691.9

96.096.095.594.594.9

95.492.983.181.2

95.192.185.1

95.8(NA)(NA)88.6

91.490.090.284.087.1

591.4587.791.790.590.589.2

91.990.289.890.389.689.2

97.195.7(NA)88.1

1744.7

92.088.184.6

93.292.791.589.890.1

91.886.270.072.5

94.087.176.8

91.793.987.485.3

79.354.355.452.753.4

(NA)(NA)86.483.283.284.8

88.485.584.485.383.384.4

95.191.580.375.7(NA)

86.580.958.0

85.084.280.077.277.1

84.472.246.145.9

90.981.555.2

79.380.574.265.2

45.528.021.216.715.5

673.6662.772.764.962.561.1

75.768.565.963.259.755.5

86.474.653.452.2(NA)

33.639.211.1

33.346.328.430.327.5

43.713.2

9.210.6

83.062.433.4

35.438.1

1419.029.2

10.16.53.82.51.9

715.7712.6827.123.616.5

813.4

15.211.08.1

11.3(NA)(NA)

19.410.7

7.57.4

(NA)

10.315.2

4.5

14.619.511.68.97.2

16.74.04.3

83.8

56.434.915.3

14.21320.7

(NA)6.4

26.346.453.461.365.6

342.9367.875.778.981.983.2

49.668.277.085.684.283.4

50.459.466.973.5

1076.6

92.795.393.7

79.791.895.179.979.9

68.679.269.870.4

78.379.279.5

93.81088.91082.0

84.4

23.930.336.449.060.3

448.7474.078.282.083.285.9

55.074.882.987.589.988.1

61.368.5

169.977.9(NA)

86.491.092.9

77.388.193.490.490.8

64.077.576.175.3

79.278.579.1

93.7(NA)(NA)86.8

22.125.628.735.644.1

546.8561.072.675.879.180.1

50.368.877.883.187.685.6

58.963.5(NA)70.0

1728.2

75.483.675.5

70.179.985.782.381.5

56.667.455.461.9

75.971.663.1

83.883.671.378.9

18.620.118.614.924.6

(NA)(NA)60.063.268.371.3

41.157.766.472.578.479.0

50.752.051.554.5(NA)

26.132.010.7

36.540.831.135.033.2

29.218.815.516.6

68.157.935.0

34.843.030.933.7

12.012.410.3

5.111.7

628.0632.235.944.148.949.5

25.735.141.445.649.846.5

27.822.518.824.7(NA)

8.216.5

4.7

18.221.516.213.312.9

17.18.76.05.5

51.137.419.2

20.421.0

147.216.0

4.02.81.00.90.6

73.772.9

814.011.89.3

88.8

3.23.52.63.1

(NA)(NA)

6.43.72.73.5

(NA)

1.74.32.1

5.26.54.92.72.7

5.82.92.1

81.6

33.019.4

8.5

6.41311.0

(NA)2.5

An

Agin

gW

orld

:2

00

1U

.S.C

ensu

sBu

reau1

57


Country

Year

Males Females

25 to 44years

45 to 49years


60 to 64years

65 yearsand over

25 to 44years

45 to 49years


60 to 64years

65 yearsand over

Ukraine . . . . . . . . . . . . . . . . . . . . . . . .

North America/Oceania

Australia . . . . . . . . . . . . . . . . . . . . . . .

Canada . . . . . . . . . . . . . . . . . . . . . . . .

New Zealand . . . . . . . . . . . . . . . . . . .

Africa

Egypt . . . . . . . . . . . . . . . . . . . . . . . . . .

Liberia . . . . . . . . . . . . . . . . . . . . . . . . .

Malawi . . . . . . . . . . . . . . . . . . . . . . . . .

Morocco. . . . . . . . . . . . . . . . . . . . . . . .

198919951999

197119761981198619971999

197119761981198619961999

1971197619811989199219971999

1976198619951998

19741984

19771987

19711982199019951999

97.3387.889.2

94.895.994.892.192.691.8

92.791.695.394.991.892.1

98.498.196.094.493.487.389.0

97.696.2

1089.31091.4

86.884.3

95.397.5

95.897.194.396.095.0

95.6497.986.3

193.094.592.589.8

187.389.5

91.390.793.693.390.891.1

98.097.795.893.394.290.590.7

99.094.2(NA)(NA)

91.892.7

196.198.2

94.596.6

1190.31190.11190.0

89.988.576.4

(NA)91.989.485.7(NA)85.1

89.188.090.989.986.886.1

96.395.994.191.989.588.588.4

98.091.3

597.9598.3

90.491.3

(NA)96.8

91.693.3(NA)(NA)(NA)

78.282.269.7

88.486.981.376.472.372.5

84.982.484.481.372.572.2

92.190.587.578.180.079.281.2

96.088.8(NA)(NA)

89.690.5

294.494.3

88.989.5(NA)(NA)(NA)

32.01534.3

28.3

75.668.453.144.845.746.7

74.169.168.859.944.746.6

69.257.945.733.833.550.557.4

77.968.376.461.8

80.385.8

(NA)94.2

63.368.9

938.1933.5943.7

10.9(NA)89.8

22.216.812.3

9.010.19.6

23.619.217.314.610.3

9.9

21.316.210.910.6

8.88.9

10.4

40.925.536.533.5

66.069.7

83.685.3

33.542.1(NA)(NA)(NA)

93.4384.683.3

41.553.356.259.069.869.5

44.253.865.273.078.179.9

33.240.245.367.669.267.171.1

7.513.2

1027.81024.7

28.855.5

67.489.9

11.317.932.538.535.4

93.3498.984.3

140.055.256.558.2

168.573.8

45.451.759.667.176.378.6

40.046.652.575.879.777.579.9

3.56.0

(NA)(NA)

33.963.9

172.690.5

15.014.1

1117.11119.01130.1

86.082.770.1

(NA)46.246.346.4(NA)65.0

43.346.952.157.966.270.6

35.240.643.769.865.774.273.6

3.14.3

516.0515.4

31.462.8

(NA)89.4

18.914.6(NA)(NA)(NA)

29.545.833.4

28.335.232.830.941.944.6

38.739.541.944.748.950.6

27.529.030.947.149.953.260.1

2.83.4

(NA)(NA)

30.459.1

269.989.8

22.514.6(NA)(NA)(NA)

15.31522.1

16.7

16.018.215.513.618.918.3

29.127.628.327.523.826.0

15.513.911.714.415.729.332.5

2.22.06.66.5

23.749.5

(NA)84.3

7.711.298.997.7

913.0

4.5(NA)86.0

4.25.14.93.02.93.1

8.36.96.04.73.53.4

3.52.81.93.52.93.03.9

1.00.72.12.1

16.232.5

55.371.9

3.85.3

(NA)(NA)(NA)

An

Agin

gW

orld

:2

00

1U

.S.C

ensu

sBu

reau1

58


Country

Year

Males Females

25 to 44years

45 to 49years


60 to 64years

65 yearsand over

25 to 44years

45 to 49years


60 to 64years

65 yearsand over

Tunisia . . . . . . . . . . . . . . . . . . . . . . . . .

Zimbabwe . . . . . . . . . . . . . . . . . . . . . .

Asia

Bangladesh. . . . . . . . . . . . . . . . . . . . .

China . . . . . . . . . . . . . . . . . . . . . . . . . .

India . . . . . . . . . . . . . . . . . . . . . . . . . . .

Indonesia. . . . . . . . . . . . . . . . . . . . . . .

Israel . . . . . . . . . . . . . . . . . . . . . . . . . .

Japan . . . . . . . . . . . . . . . . . . . . . . . . . .

Malaysia . . . . . . . . . . . . . . . . . . . . . . .

1975198419941997

196919821992

1974198119861995

19821990

197119811991

1971197619801988199219961999

19721983198919961999

1970197519801985198919961999

1970198019911999

97.996.994.395.4

69.893.896.0

97.992.499.498.2

98.798.9

396.01096.11095.3

94.298.294.397.196.898.097.2

90.788.586.084.483.0

98.498.498.398.197.097.897.1

93.497.392.398.4

97.396.295.695.6

61.393.995.1

198.393.699.799.2

97.597.9

497.1(NA)(NA)

93.497.594.197.897.6

1199.698.0

192.791.5

189.3187.4186.5

98.198.198.098.097.697.797.5

91.196.192.496.8

94.292.890.190.4

52.592.592.2

(NA)90.699.398.4

91.493.5

594.0593.3592.6

90.696.390.095.493.8(NA)95.7

(NA)89.1(NA)(NA)(NA)

97.397.597.397.196.097.497.1

86.792.287.192.6

86.082.178.378.4

49.190.488.8

295.290.798.096.6

83.083.9

(NA)(NA)(NA)

86.092.484.689.189.6(NA)87.6

286.384.278.675.974.3

94.294.794.093.191.694.694.7

76.478.165.074.6

66.559.254.654.1

43.1969.177.5

(NA)84.793.488.9

63.763.7

973.8965.0671.4

79.387.576.779.279.787.9

966.5

(NA)78.266.359.056.4

85.885.481.578.371.474.574.1

66.169.553.359.2

38.038.531.534.0

24.9(NA)52.0

84.268.770.471.2

30.133.6

(NA)(NA)

742.3

62.969.753.456.356.856.1(NA)

34.532.221.416.914.6

54.549.746.041.635.836.735.5

46.649.731.8(NA)

16.823.026.829.2

11.850.351.3

3.04.7

10.661.2

87.890.8

320.81034.81039.5

39.955.140.559.955.457.957.7

35.957.660.565.167.5

52.649.252.956.961.163.664.5

40.643.041.952.3

14.112.917.621.6

10.252.454.0

13.64.4

10.358.9

70.681.1

422.4(NA)(NA)

45.462.246.863.660.5

1161.462.2

133.851.1

153.1165.8169.2

64.761.962.365.970.771.671.8

42.242.335.846.5

13.011.612.614.4

9.850.649.7

(NA)4.7

10.857.1

50.962.0

519.4529.8535.5

43.560.944.360.757.7(NA)60.0

(NA)43.2(NA)(NA)(NA)

60.958.658.759.864.266.967.9

38.237.729.638.3

11.39.89.6

12.2

9.250.747.1

24.04.49.8

49.6

32.945.1

(NA)(NA)(NA)

40.554.140.855.652.2(NA)54.3

223.736.739.044.747.6

53.850.950.749.952.258.158.7

30.732.620.627.6

8.64.47.37.7

9.0931.540.0

(NA)4.59.0

41.1

16.927.4

910.5914.0620.8

35.248.432.946.142.742.7

934.0

(NA)22.019.019.923.6

43.339.238.837.939.239.039.8

25.126.714.620.8

4.83.53.33.5

2.7(NA)21.7

3.33.6

10.927.1

4.78.4

(NA)(NA)78.2

24.531.219.025.425.126.3(NA)

7.29.26.35.14.6

19.715.816.115.215.715.414.9

13.719.0

6.7(NA)

An

Agin

gW

orld

:2

00

1U

.S.C

ensu

sBu

reau1

59


Country

Year

Males Females

25 to 44years

45 to 49years


60 to 64years

65 yearsand over

25 to 44years

45 to 49years


60 to 64years

65 yearsand over

Pakistan. . . . . . . . . . . . . . . . . . . . . . . .

Philippines. . . . . . . . . . . . . . . . . . . . . .

Singapore . . . . . . . . . . . . . . . . . . . . . .

South Korea . . . . . . . . . . . . . . . . . . . .

Sri Lanka. . . . . . . . . . . . . . . . . . . . . . .

Thailand. . . . . . . . . . . . . . . . . . . . . . . .

Turkey . . . . . . . . . . . . . . . . . . . . . . . . .


Argentina. . . . . . . . . . . . . . . . . . . . . . .

1972198119891994

1970197519781983198919961999

1970198019891996

1970197519801989199219961999

1971198119961999

197019761980199419971999

19701975198019881996

1970198019891995

96.089.598.197.5

89.594.097.695.597.997.997.4

98.297.797.997.8

93.097.795.894.895.494.792.6

89.093.195.695.1

96.21093.9

94.2397.4397.1396.3

94.592.495.897.897.3

97.894.997.194.6

96.393.997.497.2

89.795.7

195.9196.6197.4196.8196.8

96.295.796.196.8

95.296.895.293.694.995.393.0

92.092.391.995.3

95.9(NA)93.7

497.5497.5497.3

94.992.191.189.283.0

95.892.495.093.6

94.392.094.196.5

87.193.5(NA)(NA)(NA)(NA)(NA)

88.189.689.291.4

91.993.790.689.791.691.789.9

89.187.491.888.6

93.5592.390.7

592.8592.6592.3

91.988.684.982.771.0

91.787.690.690.0

90.890.491.291.5

85.890.7

289.1288.4288.9287.2288.1

73.970.766.677.9

85.485.682.682.484.983.781.0

77.974.373.081.1

89.3(NA)84.4(NA)(NA)(NA)

88.082.576.871.560.3

80.477.679.482.8

85.675.781.078.8

79.384.3(NA)(NA)(NA)(NA)(NA)

55.652.548.248.6

67.968.368.965.671.0

954.565.5

63.456.6

938.6943.3

74.6954.967.8

947.2946.4943.9

83.076.867.459.254.0

57.251.956.163.2

65.7(NA)55.752.7

56.562.660.660.159.057.354.5

31.928.620.721.7

35.134.440.639.042.3(NA)40.2

40.335.7(NA)(NA)

44.6(NA)39.3(NA)(NA)(NA)

67.864.943.933.833.6

29.117.923.527.6

8.63.3

12.914.1

37.125.448.156.953.355.357.2

23.245.960.666.6

38.845.937.951.351.856.055.6

27.332.546.048.3

79.31061.5

74.1378.0383.4381.6

51.846.143.337.732.7

31.335.338.955.5

7.72.7

13.815.6

38.724.8

147.5160.4158.2162.3164.0

17.526.541.353.9

48.559.851.363.560.962.262.8

26.225.239.045.8

79.6(NA)73.5

476.7483.8481.9

52.948.248.336.329.7

25.230.231.953.2

9.53.1

10.813.9

36.523.4(NA)(NA)(NA)(NA)(NA)

17.520.430.743.7

45.257.149.060.460.857.255.4

21.519.332.334.4

73.8556.268.6

563.8567.9567.6

53.648.946.136.429.3

22.125.427.846.6

7.32.4

11.215.3

33.421.7

240.9256.4250.7254.1255.8

16.214.519.428.4

39.150.943.352.754.153.351.2

14.613.227.230.4

65.9(NA)59.1(NA)(NA)(NA)

50.046.342.429.430.4

16.217.619.835.4

8.62.39.4

11.8

28.619.6(NA)(NA)(NA)(NA)(NA)

13.411.311.014.9

26.933.631.341.644.9

929.246.3

8.46.9

97.899.8

47.5923.243.1

923.5926.0921.1

47.640.736.320.923.4

10.39.8

11.222.6

8.9(NA)

2.47.4

17.713.723.128.029.429.029.8

6.56.45.05.2

10.612.013.018.119.6(NA)21.4

3.63.8

(NA)(NA)

21.2(NA)19.0(NA)(NA)(NA)

35.127.920.810.913.3

4.73.23.78.9

An

Agin

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orld

:2

00

1U

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ensu

sBu

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60


Country

Year

Males Females

25 to 44years

45 to 49years


60 to 64years

65 yearsand over

25 to 44years

45 to 49years


60 to 64years

65 yearsand over

Brazil . . . . . . . . . . . . . . . . . . . . . . . . . .

Chile. . . . . . . . . . . . . . . . . . . . . . . . . . .

Colombia . . . . . . . . . . . . . . . . . . . . . . .

Costa Rica . . . . . . . . . . . . . . . . . . . . .

Guatemala . . . . . . . . . . . . . . . . . . . . .

Jamaica . . . . . . . . . . . . . . . . . . . . . . . .

Mexico . . . . . . . . . . . . . . . . . . . . . . . . .

Peru . . . . . . . . . . . . . . . . . . . . . . . . . . .

19701980198619961998

19701982199219971999

1973198519961999

19731984198919961999

1973198119871994

1998-99

19751978198219881990

19701980198819961999

1972198119891999

95.1396.3

1096.3394.9395.3

97.394.895.995.795.6

92.81091.11892.41892.4

97.993.8

1096.2395.9396.3

95.693.298.394.297.3

97.997.380.780.195.8

89.295.596.497.297.1

96.396.395.295.0

92.3493.2(NA)

493.5492.9

94.090.194.995.395.9

91.1(NA)

495.1496.0

97.992.3(NA)

494.4495.9

95.393.298.094.797.7

197.2196.980.1

194.6194.9

89.695.396.995.695.7

97.198.794.496.8

87.7582.3580.5582.1581.5

88.582.892.490.691.3

87.11186.0585.3588.2

96.488.7

587.1585.4588.4

94.091.795.291.195.1

(NA)(NA)78.2(NA)(NA)

88.093.891.991.991.9

95.597.388.393.3

82.6(NA)(NA)(NA)(NA)

82.672.882.181.283.4

81.6(NA)(NA)(NA)

94.383.0(NA)(NA)(NA)

92.490.395.088.894.1

290.9290.975.1

290.5284.3

86.291.485.585.686.8

92.894.983.285.6

73.5657.5944.6946.9947.5

72.161.566.669.069.2

72.9958.4651.7655.4

86.069.6

945.3651.4658.2

87.785.888.581.687.2


81.585.677.574.177.3

83.988.575.072.5

49.8721.8(NA)(NA)(NA)

42.425.531.527.927.4

49.6(NA)

724.4725.2

57.138.9(NA)

721.1726.7

69.866.963.361.971.4

64.765.637.952.453.6

67.168.658.452.052.4

61.563.234.641.1

21.3334.9

1048.0363.2365.8

26.032.245.247.650.1

25.31044.01865.91874.8

23.629.5

1038.8343.3349.0

14.314.931.221.551.4

78.686.052.860.985.7

17.332.640.844.846.1

22.330.360.369.9

18.6430.0(NA)

460.8462.6

21.426.039.747.547.1

19.1(NA)

457.5469.1

16.820.9(NA)

444.2446.6

13.612.231.318.556.4

176.1180.345.1

173.7182.0

16.829.138.241.343.0

19.526.954.468.1

16.5521.4530.4545.3546.6

19.321.939.338.742.9

17.11131.4535.3543.7

13.515.5

520.5522.2530.8

12.911.626.616.046.9


16.227.531.735.037.6

17.926.042.957.2

14.2(NA)(NA)(NA)(NA)

15.516.228.231.832.4

14.8(NA)(NA)(NA)

10.711.6(NA)(NA)(NA)

12.010.123.713.145.1

256.5263.634.6

265.4261.3

15.424.624.631.232.4

16.123.638.847.5

11.4610.3

99.5918.5919.1

11.110.119.217.121.0

12.4916.7615.7619.3

7.86.9

96.469.1

611.8

10.29.0

20.611.041.0


14.424.123.223.825.9

13.423.423.938.2

6.372.8(NA)(NA)(NA)

6.54.56.36.96.5

8.1(NA)76.175.4

3.93.1

(NA)72.873.8

7.16.5

13.77.9

28.8

27.030.79.8

24.923.6

11.818.616.914.114.6

8.512.512.019.2

An

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orld

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00

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61


Country

Year

Males Females

25 to 44years

45 to 49years


60 to 64years

65 yearsand over

25 to 44years

45 to 49years


60 to 64years

65 yearsand over

Uruguay. . . . . . . . . . . . . . . . . . . . . . . . 197519851995

96.996.597.4

95.294.396.4

90.589.494.3

81.280.089.3

58.951.859.3

20.916.219.4

40.551.773.0

35.346.464.6

29.637.559.5

21.725.341.0

12.213.323.9

3.63.66.7

NA - Data not available.1 Refers to ages 45 to 54 years.2 Refers to ages 55 to 64 years.3 Refers to ages 25 to 39 years.4 Refers to ages 40 to 49 years.5 Refers to ages 50 to 59 years.6 Refers to ages 60 to 69 years.7 Refers to ages 70 years and over.8 Refers to ages 65 to 74 years.9 Refers to ages 60 years and over.10 Refers to ages 25 to 49 years.11 Refers to ages 45 to 59 years.12 Refers to ages 65 to 66 years.13 Refers to ages 65 to 72 years.14 Refers to ages 60 to 72 years.15 Refers to ages 60 to 70 years.16 Refers to ages 65 to 69 years.17 Refers to ages 50 years and over.18 Refers to ages 20 to 39 years.

Note: For some countries in this table, data areral census enumerations and, therefore, may yieforce participation rates within a country may, in pcountries.

Note: Data for Germany prior to 1996 refer to

Source: U.S. Census Bureau, 2000a and vario

e derived frold more comprehensiveart reflect different modes of data col

the former West Germany; data for the Czech R

us issues of the International Labour Office Yearbook of La

m labor force surveys asinformation o

well as pon various aspects of election. The discussion

pulation ce

epublic prio

bour

nsuses. Labconomic actin Chapter

r to 1991 refer to the fo

Statistics.

or force survivity. The user should re10 touches upon other potential disc

rmer Czechoslovakia.

eys are more focused oncognize that temporal d

economic

repancies

activity thanifferences in

are gen-labor

within and among

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APPENDIX B.

Sources and Limitations of the Data

This report includes data compiled data in An Aging World: 2001 come the countries covered in this reportby the International Programs from data files of the IPC. have produced their own nationalCenter (IPC), Population Division, population projections, and different

With the initial and ongoing supportU.S. Census Bureau from publica- statistical agencies generate country-

of the Office of the Demography oftions and electronic files of national specific sets of projections for all

Aging, U.S. National Institute onstatistical offices, several agencies but the least populous countries.

Aging, the Census Bureau hasof the United Nations, and other For the most part, the convergence

undertaken a systematic effort tointernational organizations (e.g., the of national, IPC, United Nations, and

locate and compile data on olderOrganization for Economic Co-oper- other projection series is close for

populations for a subset of IDBation and Development and the the next 20 to 30 years. This is

countries and subject matter. TheEuropean Union). It also includes especially true with regard to older

intent of this effort is to make avail-cross-national information from population groups, since persons

able to researchers a relatively con-sources such as the Luxembourg who will constitute the elderly in

sistent, documented set of data thatIncome Study (http://lisweb.ceps.lu), 2020 and 2030 already have been

can be used to analyze and antici-the Network on Health Expectancy born. Because the elderly of tomor-

pate international concerns relatedand Disability Process (see Chapter row have survived the risks of infant

to the aging of the world’s popula-4), the Global Burden of Disease and childhood mortality, their con-

tion. To date, 105 countries havestudy (http://www.hsph.harvard. tinued survival is subject to adult

been examined in detail, and select-edu/organizations.bdu/), and other mortality rates that can be estimat-

ed data for a subset of theseuniversity-based research projects. ed with a relatively high degree of

nations appear in the tables inSome ongoing efforts (e.g., the confidence until the very old ages.

Appendix A. Since 1985, IDB dataLuxembourg Income Study and the Because the effects of migration on

have been available in an evolvingUnited Nations Economic projected cohorts are in most cases

variety of formats, including printedCommission for Europe Population minimal, absolute numbers of elder-

hard copy, mainframe computerActivities Unit Census Microdata ly persons may therefore be consid-

tape, and PC diskettes. The currentSamples Project ered fairly reliable.

IDB is maintained on and made(http://www.unece.org/ead/pau)

accessible via the Internet at the fol- Of less certainty are projected popu-involve recoding of data from differ-

lowing address: lation proportions and related meas-ent countries in order to enhance

http://www.census.gov/ipc/www/ ures such as youth support ratios.comparability.

idbnew.html The size of youth cohorts is oftenThe majority of statistics, including the most important factor in deter-

General information about theall tabular data shown in Appendix mining overall population aging.

Census Bureau’s IDB may beA, are contained in an International Population projections for develop-

obtained by contacting the Chief,Data Base (IDB), maintained and ing countries usually assume a

International Programs Center, U.S.updated by the IPC. The IDB con- future decline in fertility rates that

Census Bureau, Washington, DCtains annotated statistical tables of will eventually result in older popu-

20233.demographic, economic, and social lation age structures. The pace andinformation for all countries of the level of fertility reduction is debat-BASIC DEMOGRAPHIC DATAworld. Available information from able, however; elderly proportions

Estimated and projected population1950 to the present is supplement- in population projections will vary todistributions, by age and sex, areed with population projections to the extent that actual fertilitytaken from IPC data files exceptthe year 2050. Most of the projected change deviates from its assumedwhere otherwise noted. Many of

trajectory. Projections for developed may be confronted. This suggests a With regard to the age structure ofcountries are less sensitive to such need for more analytical attention to elderly populations, potentialuncertainty because of the extent of the assumptions and outcomes of sources of error usually have beenfertility decline that has already population projections vis-à-vis assumed to be minor in most (butoccurred. With fertility now well numbers of elderly persons. Toward not all) countries. To date, demogra-below replacement level in numer- this end, organizational units includ- phers have devoted much moreous developed countries, the issue ing the United Nations Population attention to analyzing age inaccura-for projections is whether to assume Division, Eurostat, and the U.S. cies at younger rather than oldera future rise in fertility. In some Census Bureau Population Division, ages. Inaccuracies at older ages dodeveloped countries, changes in in conjunction with members of aca- occur. An individual’s age is oftenmigration levels could conceivably demia and sponsors such as the U.S. undocumented in some societieshave a greater future impact than National Institute on Aging and the and subcultures, and knowledge ofbirth rates on overall age structure. American Association of Retired exact age may not be an important

Persons, have begun a concerted concern. Hence, reported ages ofAs discussed in Chapter 3, most of

effort to use their combined expert- elderly respondents tend to heap onthe variation in projections of elder-

ise to refine and improve projection certain round numbers (60, 65, 70,ly population appears to result from

procedures. For a detailed critique etc.). Many of these inaccuracies canuncertainty about mortality at the

and discussion of such procedures, be detected and statistically adjust-oldest ages. Projections require

see Bongaarts and Bulatao, 2000. ed, and are commonly accounted forassumptions about future trends,

in population projections.and most past projections have not IPC population projections for aanticipated the continued decline in given country incorporate several Available evidence suggests that themortality rates at older ages that components. The initial population elderly as a whole are not under-have occurred in developed coun- age/sex structure usually is based counted in censuses to any signifi-tries. In the Census Bureau’s 1987 on a national census distribution, cantly different extent than areAging World report, projections with or without adjustment as deter- other age groups. In many coun-made in 1984 implied that the mined by Census Bureau analysts. tries, the elderly are less apt thanJapanese population aged 80 and Analysts then derive — either direct- younger age groups to be geograph-over would constitute slightly less ly using reported data or indirectly ically mobile and thus should bethan 5 percent of the total Japanese using demographic techniques — easier in theory to enumerate.population by the year 2025. In the empirical age-sex-specific mortality, Within the elderly population, how-years after 1984, however, the fertility, and international migration ever, there are strong indicationsdecline in fertility and the increase rates, considering the range of avail- that women are missed more often

able data (e.g., from demographicin life expectancy (both at birth and than men. In some South Asian andand other surveys; vital registrationat older ages) have been sharper African societies, national censusessystems; and other administrativethan expected. Hence, revised pro- routinely count more men thanstatistics). These benchmark esti-jections to 2025 imply a somewhat women in older age groups, in spitemates form the basis for projectedsmaller total population, and the of the fact that the estimated lifechanges in the population age/sexoldest-old share of the total is now expectancy of women is and hasstructure. In countries where reli-projected to be on the order of been greater than that of men inable, nationally representative data9 percent by the year 2025. For the practically all countries.for one or more of these variablesmost part, best-guess demographicare lacking, rates from demographic SOCIOECONOMICforecasts have tended to be “conser-models or culturally similar neigh- CHARACTERISTICSvative” vis-a-vis assumed mortalityboring countries may be employed.improvement, with the result that Data on labor force participation,Future levels of fertility, mortality,future numbers of the elderly may marital status, and other socioeco-and migration are incorporated

be understated. In terms of social nomic characteristics are primarilybased on observed country-specific

service planning for future cohorts derived from published census andtrends and the accumulated experi-

of the oldest old, the example of survey data of various countries asence of other nations at different

Japan underscores the magnitude of compiled by the U.S. Census Bureau.stages of demographic and socio-

potential “error” with which planners Although no techniques have beeneconomic development.


applied to evaluate the quality of has been made during the past half are included in IDB files to allow thethese socioeconomic statistics, the century in encouraging disparate user to recognize differencesCensus Bureau attempts to resolve national statistical agencies to among countries.discrepancies in reported figures, adhere to defined international stan-

As population aging has assumedand to compile information in standards of data collection and tabula-

greater importance and receiveddard formats within the structure of tion. As a result, some concepts (lit-

greater recognition over time, inter-the International Data Base. eracy, for example) are more

national agencies have begun tointernationally comparable than oth-

IDB data are not always comparable produce a growing amount of dataers (e.g., labor force participation).

among countries, essentially for two on older populations. This is espe-reasons: (1) complete statistics may To the extent possible, the U.S. cially true in the areas of health,not be available to allow manipula- Census Bureau has accounted for economic activity, income, andtion of data into standard formats; statistical and conceptual differ- retirement. As a result, this reportand (2) concepts and definitions ences when compiling IDB country draws substantially on cross-nation-vary according to the specific needs files. Remaining deviations from al data and comparisons producedof each country. For example, a standard formats, and other data by a variety of organizations andcountry with only a few small urban anomalies, are documented in the research consortia whose subject-centers may need a different defini- annotation that forms part of the matter expertise in these areas istion of urban than does a highly IDB files. Where applicable, national invaluable to a better understandingindustrialized country that is pre- definitions of major concepts such of an aging world.dominantly urban. Uneven progress as “urban” and “economically active”



APPENDIX C.

International Comparisons of Urban and Rural Definitions

Because of national differences in 2. Population Size. This concept required size for urban used bythe characteristics that distinguish treats as urban those places (for countries in this report during theurban from rural areas, the distinc- example, cities, towns, agglomer- 1980 census round ranged fromtion between urban and rural popu- ations, localities) having either a agglomerations of at least 200lation is not amenable to a single specified minimum number of inhabitants to localities of 10,000definition applicable to all countries. inhabitants or a specified mini- or more inhabitants.For this reason, the United Nations mum population density. The UN

3. Local Government Area. This(UN) recommended in 1970 that discussion of the concept “popu-

concept defines urban in terms ofeach country should decide for itself lation density” recognizes that

those places, agglomerations, orwhich areas are urban and which are suburbs of large places, densely

localities with a local govern-rural. populated fringes around incor-

ment. For some countries, thisporated municipalities, and the

The rural population as defined by practice might be interpreted aslike, are sometimes classified as

most national statistical organiza- referring to a particular form ofurban in this approach.

tions is usually not defined directly, local government, especially onebut is simply the residual population Within a fairly broad range, the having relatively great autonomy.after the urban population is distin- choice of the minimum qualifying The equivalent in the Unitedguished. The UN Statistical Office size or density value is arbitrary, States would be the incorporatedhas classified extant urban defini- although original efforts may municipality (city, town, borough,tions into the five principal types have based the cutting score on or village). Other terms cited bylisted below. statistics regarding the presence the UN include chartered towns,

or absence of various facilities or local government areas, munici-1. Administrative Area. This con-

functions in places of given sizes. pal communities, and burghs. Nocept treats as urban the adminis-

The variety of minimum sizes minimum population size is usedtrative divisions (for example,

that are or have been in use in in this definition. The remarksmunicipalities, cities, communes,

national statistical programs about the relatively static charac-districts, boroughs) that have

reflects the lack of consensus on ter of classifications under thebeen so classified by the national

these matters. It also reflects the first concept apply here also.government, or certain parts of

fact that a place of given size in asaid divisions, such as their 4. Urban Characteristics. This

small country with a subsistence-administrative centers, capitals, concept requires an urban place

agricultural economy will be rela-or principal localities. This classi- to possess specific characteris-

tively more important than in afication is based primarily on his- tics such as established street

highly industrialized, populoustorical, political, or administrative patterns, contiguously aligned

country such as Japan. Similarly,considerations rather than on sta- buildings, and public services

a size that might have represent-tistical considerations. It tends to that might include a sewer sys-

ed a fairly important place in feu-be relatively static and is not tem, a piped water supply, elec-

dal Japan might not be relevantautomatically changed after each tric lighting, a police station, a

to modern Japan. In some coun-census to recognize the decreas- hospital, a school, a library, a

tries (for example, New Zealand)ing size of formerly important court of law, and/or a local trans-

the minimum required size usedplaces or the increasing size of portation system. A classifica-

to record the growth of urbanplaces that have recently become tion of this sort would need to

population has increased fromimportant. be developed during or shortly

census to census. The minimumbefore a census enumeration.

5. Predominant Economic Individual national definitions of The Methods and Materials ofActivity. In this formulation, urban areas are included in each Demography, Volume 1, U.S. Bureauplaces or areas qualify as urban International Data Base country file of the Census, Washington, DC, pp.if a specified minimum propor- annotation. For a more thorough 151-68.tion of their economically active discussion of international differ-population is engaged in nona- ences and similarities in urban andgricultural activities. rural areas, see Henry Shryock,

Jacob Siegel, and Associates, 1971,



APPENDIX D.

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Bartlett, Helen P. and David R.census and survey volumes of indi- Organization.

Phillips, 1995, “Aging Trends—vidual nations, as well as periodic

Anh, Troung Si, Bui The Cuong, Hong Kong,” Journal of Cross-issues of international compendia

Daniel Goodkind, and John Cultural Gerontology, Vol. 10,such as the International Labour

Knodel, 1997, “Living No. 3, pp. 257-65.Office Yearbook of Labour Statistics,

Arrangements, Patrilineality andthe United Nations Demographic Bartlett, Helen P. and Shwu-Chong

Sources of Support amongYearbook, and the World Health Wu, 2000, “Ageing and Aged

Elderly Vietnamese,” Asia-PacificOrganization World Health Statistics Care in Taiwan,” pp. 210-22 in

Population Journal, Vol. 12, No.Annual). David Phillips, ed., Ageing in the

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Adler, Nancy E., Michael Marmot,Apt, Nana Araba, 1992, “Family Policies and Future Trends,

Bruce S. McEwen, and JudithSupport to Elderly People in London: Routledge.

Stewart, 1999, SocioeconomicGhana,” pp. 203-12 in Hal L.

Status and Health in Industrial Bean, Frank D., George C. Myers,Kendig, Akiko Hashimoto, and

Nations. Social, Psychological and Jacqueline L. Angel, and Omer R.Larry C. Coppard, eds., Family

Biological Pathways, Annals of Galle, 1994, “GeographicSupport for the Elderly, Oxford:

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Sicherman, 1993, “Technological Statistics, 1998, Statistiques

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Bengston, Vern, Carolyn Rosenthal, Bongaarts, John and Rodolfo A. Cattell, Maria, 1997, “Africanand Linda Burton, 1995, Bulatao, eds., 2000, Beyond Six Widows, Culture and Social“Paradoxes of Families and Billion: Forecasting the World’s Change: Case Studies fromAging,” pp. 254-82 in R. H. Population, National Research Kenya,” pp. 71-98 in JayBinstock and L. K. George, eds., Council, Washington, DC: Sokolovsky, ed., The CulturalHandbook of Aging and the National Academy Press. Context of Aging, Second Edition,Social Sciences, Fourth Edition, Westport, CT: Greenwood.

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