rural-urban differences in a thesis in sociology …

RURAL-URBAN DIFFERENCES IN

SUBJECTIVE WELL-BEING

by

DAVID ALLEN ARMSTRONG, B.A.

A THESIS

IN

SOCIOLOGY

Submitted to the Graduate Faculty of Texas Tech University in

Partial Fulfillment of the Requirements for

the Degree of

MASTER OF ARTS

Appro~

Accepted

May, 1991

(l.C 8() 5

/3 1CfC1/

'AI tJ . I c.oo:l~

I would like

ACKNOWLEDGEMENTS

to express my thanks to Dr. George Lowe

for the extreme patience that he showed through this

endeavor. He was there when I needed him, and his time

spent went above and beyond what could be expected. I

would also like to thank Drs. Charles Chandler and Yung

Mei Tsai for their.helpful advice. Dr. Charlotte Dunham

also deserves acknowledgment for stepping in at my time

of need. My thanks also go to Russell P.O. Burton for

his assistance with the literature on this subject.

Perhaps most importantly, I would like to thank my

parents, Jack and LaVelle Armstrong, for their support

throughout my academic career. Without their moral and

financial support, I could never have made it this far.

ii

CONTENTS

ACKNOWLEDGEMENTS .

LIST OF TABLES . .

I. INTRODUCTION . .

Review of Literature .

The Negative Impact of Urban Life--Greater Stress . . . • . • . . . • Evidence of Mental Illness in Urban Areas . . . • . • • . . . The Negative Impact of Rural Life--Greater Stress • . . • . . . . . . Evidence of Mental Illness in Rural Areas . . . . . . . . . . . . . . . The Merging of Rural and Urban Life . "The Community Question" - Urbanism and Social Networks . . . . . . . . . Social Support in Rural Areas . . . . Problems With Previous Measurement ...

Subjective Well-Being as a New Approach . . . . . . . .

Social Stability and Subjective Well-Being .

The Research Problem

II. METHODS

III.

IV.

The Sample .

Operationalization of Variables

The Dependent Variable The Independent Variable Control Variables . . . .

FINDINGS .

SUMMARY . . . . . . .

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30 31 31

38

50

REFERENCES 56

APPENDIX 66

iv

1.

2.

3.

4.

5.

6.

7.

8.

LIST OF TABLES

Principal Component Factor Analysis of Subjective Well-Being Items . . . .

Principal Component Factor Analysis of Socioeconomic Status Items . • • . . .

Zero-Order Correlation Coefficients for Subjective Well-Being . . . . . . . .

Mean Level of Subjective Well-Being for Rural and Urban Residents . . . . . .

Mean Level of Subjective Well-Being for Rural and Urban Residents Adjusted for Age and Gender . . . . . . . . . .

Mean Level of Subjective Well-Being for Rural and Urban Residents Adjusted for Age, Gender, and Socioeconomic Status . . . . . . . . . . . . . .

Mean Level of Subjective Well-Being for Rural and Urban Residents Adjusted for Age, Gender, Socioeconomic Status, and Social Stability . . . • . . . . .

Results by Step for Urbanism in Stepwise Multiple Regression on Subjective Well-Being . . • . . . . . . . . .

9. Regression Results for Subjective Well-Being Final Step . . .

10.

11.

12.

Results for step 1 in stepwise Multiple Regression on Subjective Well-Being

Results for Step 2 in Stepwise Multiple Regression on Subjective Well-Being


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CHAPTER 1

INTRODUCTION

The relationship between urbanism and mental illness

and psychological distress remains ambiguous. Four

decades ago, there was no controversy about this

relationship. Epidemiological studies consistently

showed lower rates of mental illness in rural areas

(Jaco, 1968; Flax, Wagenfeld, Ivens, and Weiss, 1979;

Cockerham, 1989). These findings were consistent with

Wirth's (1938) theory of urbanism and were considered

major support for his thesis that the stress of city life

affected the people who lived there. In 1960, then, the

fact of higher rates of mental illness in urban areas was

not only a universally accepted empirical generalization,

it had strong grounding in theory.

In the 1970s, Fischer (1972, 1973) raised serious

questions about Wirth's theory, especially the idea that

urban life is especially stressful. Fischer also

presented evidence that rural life may be more malaise

inducing than is urban life.

During the same period, the epidemiological evidence

showing lower rates of mental illness in rural areas was

brought into question (Fischer, 1973; Webb and Collette,

1

2

1977; Flax et al., 1979). Further, new theories arose

which suggest that rural life may in fact be more stress

inducing than city life. Some recent findings

(Granoveter, 1973; Garbarino, 1977) appear to support

this position.

Recent research on subjective well-being has shown

that social support, particularly when measured as social

stability, has a strong negative association with

psychological distress (eg., Hellinghausen, 1984; Kunkel,

1981). This association tends to be as strong or

stronger than socioeconomic status. Traditional wisdom

suggests that rural communities may be higher in social

support.

The question then is whether stress or social

support (or both) affects subjective well-being and the

relationship of these to place of residence. Previous

studies have dealt strictly with differences in mental

illness rates and have virtually ignored the contribution

that the subjective well-being measure is able to

provide. This thesis will attempt to answer the question

by utilizing the data available in the General Social

surveys to measure subjective well-being, social

stability, and size of place of residence.

Review of Literature

The Negative Impact of Urban Life--Greater Stress

An early comparison of rural and urban life is

Ferdinand Tennies' (1887) Community and Association.

Rather than simply comparing rural and urban life,

Tennies contrasts the traditional, preindustrial society

which is characteristic of rural areas with modern

industrial society which is generally urban. Tennies'

term Gemeinschaft, meaning community, refers to the

traditional rural society. In this type of society,

people maintain close personal relations with their

neighbors and are acquainted with almost everyone that

3

they are likely to encounter. Trust is high in this type

of community.

Tennies' term Gesellschaft, which literally means

association, refers to the modern, industrial, urban

society. Tennies says that people in urban areas are

largely driven by economic self-interests. They have a

tendency to work with their own goals in mind and are,

thus, less likely to know and care about other people.

For this reason, urban areas are characterized by a more

impersonal, isolated atmosphere.

Georg Simmel (1964) speculates that the reason for

these differences is that the city contains so many

people and situations that a single person is not able to

become familiar with everyone. To cope with this

overstimulation, Simmel says that people withdraw and

only pay attention to the things that are of personal

importance. Milgram (1970) elaborates on Simmel's

argument and states that people in cities are faced with

immense sensory and mental demands which lead to

psychological distress.

4

In "Urbanism as a Way of Life" {1938), Louis Wirth

proposes a theory of urbanism based on the negative

effect that urban life has on the individual. This is

called "determinist theory" by Fischer (1976). Wirth

defines a city as a "relatively large, dense and

permanent settlement of socially heterogenous

individuals." The heterogeneity, size, and density of

the population are central to Wirth's argument in that he

asserts that these factors contribute to the problem of

developing intimate personal relationships. According to

Wirth, these factors lead to isolation, impersonality and

superficial relationships which, in turn, contribute to

poor interpersonal relationships.

Wirth also says that while urban residents may be

acquainted with a larger group of people, they are more

likely to "have a less intensive knowledge" of these

people. Thus, urban life is characterized by "secondary

rather than primary contacts." He cites Simmel (1903)

and Weber (1925) to substantiate his argument.

Another effect that Wirth attributes to density is

that of a high division of labor. In this argument, he

cites Durkheim's The Division of Labor in Society (1933),

asserting that an increase in density produces

differentiation and specialization because this is the

only way that the greater numbers can be supported.

5

This, in turn, results in diversification among residents

and increasing complexity of the social structure which

may alienate one from fellow residents.

Another point central to Wirth's theory is that of

"nervous stimulation" or "information overload" which he

says are characteristic in urban areas because of the

increasing population size and density. This idea is

drawn largely from Simmel (1964). Thus, urban residents

are the (unwilling) recipients of increasing amounts of and increasing diversity in sensory stimuli calling for response--both physical and social: other people, public messages, pleas for attention and concern. This raises the problem of "information overload" in the urban setting: more inputs than the human organism can handle. (Fischer, 1972, p. 193).

Evidence of Mental Illness in Urban Areas

Traditional wisdom supports the belief that urban

living is more stressful than living in rural areas (Flax

et al., 1979). Jaco's (1960) conclusion of higher rates

6

of psychosis in urban areas is typical, but his findings

are based on treatment rates, resulting in methodological

problems. Many early studies of treatment rates show the

same relationships (see the more than 20 studies cited by

Dohrenwend, 1975), but they all have the same

methodological weakness. As Dohrenwend (1975) notes, the

differentials could be due to the low availability of

treatment facilities in rural areas and migration to

urban centers rather than actual mental health

differences.

Dohrenwend's 1975 study also reviews eight studies

that compare urban and rural rates of psychiatric

disorders, rather than treatment rates, and concludes

that urban residents show more disorder in all but two

cases. In one of the studies, the total rate for all

psychiatric disorders is higher for rural residents and

one study shows a tie. The differences shown, though,

are not large. Certain disorders, specifically

functional psychoses, are found to be more prevalent in

rural settings while anxiety and personality disorders

show to be more predominant in urban settings.

Dohrenwend agrees that these results are consistent with

the idea that the excess stress in urban areas may result

in higher rates of disorder, but he also proposes an

alternative explanation. He says that the added

7

attractions that cities offer may lure people from rural

areas and that, of the migrants that move to the city,

some of them must be ill.

Peek and Lowe (1977) report that alcohol use, viewed

as a means to cope with stress, increases with city size.

Although this is influenced by the greater availability

of alcohol in urban areas, it is also related to the

problems of excess nervous stimulation and the greater

difficulty in establishing primary relationships.

The Negative Impact of Rural Life--Greater Stress

As we have seen, there is a position that argues

that there is greater stress for residents of urban

areas. There is some research support for this stance.

There is a second view that argues that there is greater

stress in rural areas. As opposed to the excess sensory

stimulation that is considered to be characteristic of

urban life, rural life is seen as more socially isolated

(Taylor, 1933; Sims, 1940; Webb and Collette, 1977).

Smith and Coward (1981) report that "geographic and

social isolation are characteristic of much of rural

America." This isolation, while perhaps sheltering one

from sensory overload, limits the number of persons that

one may turn to in times of need.

Webb and Collette (1977) argue that this isolation

could lead to routinization and a lack of stimulation

which may be associated with greater amounts of stress.

They also propose that the mass media, which is

predominantly urban, promotes an ideal lifestyle that is

not readily attainable by rural residents, leading to

feelings of frustration and isolation.

8

Sorokin et al. (1931) said that in rural areas it is

"much more difficult to find other than family shelters

against isolation and loneliness." In the first half of

this century, this was due largely to poor roads and the

absence of telephones (Lowe et al, 1987). This is

congruent with recent findings that size of community of

residence is positively related to frequency of

socializing with friends who are not neighbors (Glenn and

Hill, 1977; Tsai and Sigelman, 1982). Tsai and Lai

(1988) also report that rural residents are more likely

to identify neighbors in their social network than are

urban residents.

While isolation from neighbors and the rest of the

surrounding community has been identified as a possible

factor in influencing rural stress, rural homes tend to

have more occupants than urban dwellings. It has been

proposed that crowding in the home may be a more

important factor in residents' mental health than

crowding or isolation on the macro level (Cockerham,

1989; Gave, Hughes, and Galle, 1979; Webb and Collette,

1977).

9

Family therapists, educators and researchers also

report that farm men and women are subject to stress

(Bennett, 1982; Hedlund and Berkowitz, 1979; Jurich and

Russell, 1987; Keating, 1987; Keating, Doherty, and

Munroe, 1986, 1987; Rosenblatt and Anderson, 1981; Walker

and Walker, 1987; Walker, Walker, and MacLennan, 1986).

Sources of stress which have been identified include (1)

vagaries of weather, interest rates, markets and consumer

demands (Rosenblatt and Anderson, 1981); (2) multiple

work-roles which compete for limited amounts of time and

money (Hedlund and Berkowitz, 1979; Keating et al.,

1987); ( 3) combined familial and economic roles (Bennett,

1982); and ( 4) irregular cash flow, large capital

investment and financial risk (Keating et al., 1986;

Rosenblatt and Anderson, 1981; Walker et al., 1986;

Walker and Walker, 1987). Most of these studies do not

include comparisons with stress in nonfarm or urban

areas. However, a report on occupational stress states

that farm managers ranked twelfth of 130 occupations

studied (Hedlund and Berkowitz, 1987).

There is also evidence that people in rural areas

experience higher levels of stress from sources other

10

than farming. Financial problems contribute to stress in

rural areas, too. This stress may be exhibited in

marital difficulties, depression, physical aggression

against family and friends, increased smoking and

drinking, and loss of appetite (Hargrove, 1986; Heffernan

and Heffernan, 1986). "Stress related disorders are much

more prevalent among rural than urban residents,"

according to Webb and Collette (1977, p. 706). The

factors that they attribute to producing a stressful

rural environment are "the crowding of rural housing, an

inability to escape easily to distracting amusements, and

the stifling social pressures of small towns "

Webb and Collette (1977) use the amount of stress

relieving drugs prescribed in rural and urban areas in

New Zealand as an indicator of amount of stress. They

find that the larger the locality, the lower the mean

monthly amount of prescriptions filled, with rural areas

having almost double the amount of prescriptions of the

largest cities. This leads them to the conclusion that

rural residents are a high-risk group with regard to

mental health.

The explanation offered by Webb and Collette (1977)

that overcrowding in rural housing could lead to worse

mental health is consistent with previous findings in the

area of overcrowding. Although Webb and Collette

11

concentrate on crowding in the home, there are two types

of crowding that must be considered. Krupat (1985)

identifies two different levels where overcrowding

occurs, crowding on the molar and molecular levels. From

a molar point of view, crowding occurs on a large scale,

one outside of the household. Crowding from a molecular

point of view occurs on a smaller scale, crowding on the

inside.

While Baldassare (1978) finds overcrowding on the

macro level to be detrimental to mental health, it has

also been reported (e.g., Galle and Gave, 1979) that

crowding at this level may have some minor effects but it

is not a variable of "major substantive importance."

Later, Gave et al. (1979) found that both objective

(persons per room) and subjective (excessive social

demands and lack of privacy) crowding are strongly

related to poor mental health, poor social relationships

in the home, and poor child care. Carnahan, Gave, and

Galle (1974) found serious overcrowding to be found on

farms more than other locations lending support to Webb

and Collette's explanation. As opposed to the crowding

in the home that is found in rural areas, overcrowding on

the macro level tends to be associated with city life.

After reviewing the past research, Cockerham suggests

that overcrowding in the home may be "much more

12

significant than overcrowding in the neighborhood"

(Cockerham, 1989, p. 208). There is mixed evidence as to

whether crowding on the macro or micro level is more

stressful, but there is evidence to support the fact that

both have a negative effect on mental health (Galle and

Gave, 1979; Galle, Gave, and McPherson, 1972; Mitchell,

1971; Schmitt, 1957).

Evidence of Mental Illness in Rural Areas

Fischer (1973) argues that "rural malaise," a

subjective psychological state of dissatisfaction,

unhappiness, despair and melancholy, may be predominant

worldwide. This relationship is demonstrated only after

controlling for social class, race, region, and

especially migration. Malaise in urban areas is found to

dissipate after controlling for those who move from

smaller communities to larger communities and vice versa.

He concludes that while Americans generally express a

preference for smaller communities, people in cities seem

to be more content.

Lowe and associates (1987) take issue with Fischer's

conclusion, though, arguing that he misinterprets his

data. Two of the surveys that Fischer analyzed show

rural respondents to be more satisfied than urban

residents in ten of thirteen categories. Further, two of

13

the exceptions ("your future" and "people's honesty") are

not standard indicators of mental well-being. Lowe and

his associates interpret this to mean that although they

may be more pessimistic about the future, rather than

exhibiting "rural malaise," rural residents tend to be

more satisfied than urban residents.

While Dohrenwend (1975) finds that some disorders

such as neurosis, personality disorders, and

schizophrenia are more prevalent in urban areas, he also

reports that all functional psychoses combined are more

prevalent in rural areas. This is also true for the

manic-depressive subtype. Therefore, the rural setting

may lead to higher rates of certain disorders such as

functional psychosis and manic-depression.

Webb and Collette's (1977) study compares the amount

of stress-relieving drugs that are prescribed in rural

and urban areas. Their analysis shows that people in

rural areas are prescribed almost twice the amount of

stress-relieving drugs as those in urban areas. This

provides support for the idea that rural stress is

detrimental to residents' mental health.

The Merging of Rural and Urban Life

There is the possibility of an argument somewhat

less dramatic than the two opposing views previously

presented. Srole (1972) suggests that technology has

brought the two communities together. By the use of

modern transportation, such as the automobile, the

boundary between the city and the countryside is not so

strict. It is possible for people to live in the

14

country, work in the city, and commute to suburban areas

as need for affairs such as shopping (Srole, 1972).

Srole comes to the conclusion that the impact of a

person's place of residence has little etiological impact

on one's mental health. Rather, there may be some sort

of self-selection involved in who makes the decision to

live in a certain type of environment.

In a later study, Srole (1980) finds evidence to

support his view. In an analysis of previous studies and

data collected by the National Center for Health

Statistics (NCHS), Srole determines that there is no

difference in psychiatric disorder in rural and urban

areas. Further, in review of a previous study of

"General Psychological Well-Being," Srole comes to the

conclusion that there is no significant variation in

psychological well-being among people on farms, in large

cities, or in places in between.

"The Community Question" -Urbanism and Social Networks

Much of the justification for each of the opposing

views of differentials in mental illness is based on

15

primary and secondary relationships (or the lack of such

relationships). A logical question, then, is how

urbanism actually affects these relationships.

Wellman (1979) proposes "the community question" of

whether, and if so, how the large scale division of labor

in modern urban society affects a person's primary

relationships. Wellman proposes three possibilities from

the existing literature. The first proposition, the

"community lost" position, suggests that urbanites are

members of multiple social networks, but are only

involved to a limited degree. These relationships are

characterized by "webs of secondary affiliations." Polar

to this view is that of the "community saved" argument

which sees that residents of cities are equally likely to

socialize with friends neighbors and relatives as

residents of small towns and rural areas are. The

"community liberated" perspective asserts that residents

of cities are less likely to socialize with relatives and

neighbors, but they are more likely to associate with

people outside of the neighborhood. Wellman's data

provide more support for the "liberated" perspective than

the other two.

Support for Wellman's (1979) propositions has been

mixed. Tsai and Seligman (1982) utilize national survey

data to test Wellman's propositions through use of

16

sociability questions concerning respondents' interaction

with relatives, neighbors and friends. They find strong

support for the "liberated" perspective, partial support

for the "lost" perspective, and none for the "saved"

perspective. Later, Tsai and Lai (1988) took advantage

of newly obtained network data in the General Social

Surveys to test Wellman's propositions. The new network

data fail to show more than partial support for any of

the three hypotheses, suggesting that there may be no

differentials in the amount and strength of primary ties.

Social Support In Rural Areas

The idea that there is better social support in

rural areas goes at least as far back as Tennies (1887).

This support comes from increased contact with neighbors

and family. Tennies' term Gemeinschaft refers to this

type of society where people maintain close relations

with neighbors and family members. These are potential

sources of strong social support.

Tsai and Sigelman (1982) found that rural residents

have more contact with neighbors and less interaction

with friends than urban residents, but, more importantly,

they have much more contact with relatives than with

either neighbors or friends. There is additional

evidence to support the idea of greater contact with

relatives (Straus, 1969; Mirande, 1970; Glenn and Hill,

17

1977) although it has been debated as to whether this is

more beneficial than having greater amounts of less

personal contact with non-relatives (Granovetter, 1973).

There is a body of research that contradicts this

idea of greater contact among kin in rural areas.

Bultena (1969) finds some differences between rural and

urban residents in face-to-face contact with children and

siblings, but they are more among the aged than other age

groups. Lee and Cassidy (1981) review ten studies of the

association between residence and kinship interaction and

conclude that "reported rural-urban differences in

kinship interaction are quite inconsistent, almost

uniformly small, and often attributable to factors other

than residence" (Lee and Cassidy, 1981:67).

There is also the contention that, regardless of

whether familial ties are stronger in rural areas, weak

ties are more important in this instance. Garbarino

(1977) sees these types of relationships as part of

potent support systems which are crucial to an

individual. Granovetter (1973:378) states that " weak

ties, often denounced as generative of alienation (Wirth,

1938) are ... indispensable to individuals'

integration into communities; strong ties, breeding local

cohesion, lead to overall fragmentation."

18

Problems With Previous Measurement

The focus of the literature review to this point has

been the relationship between place of residence and

mental illness. There is reason to be cautious when

reviewing the previous findings, though. The validity of

the previously reported research may be questioned.

Attempts to measure mental illness with treatment

rates have been fraught with methodological problems. It

is not possible to accurately generalize findings drawn

from treatment rates to persons not receiving psychiatric

care. Social class, location of residence, and sex all

influence the probability of seeking professional help

and may, thus, contaminate the results when analyzing

only treatment rates.

Persons of lower social class have been shown to be

more likely to become mentally ill (Hollingshead and

Redlich, 1958; Srole, Langner, Michael, Opler, and

Rennie, 1962) but are less likely to be admitted into

private treatment (Hollingshead and Redlich, 1958).

Myers and Schaffer (1954) also found that social class is

directly related to acceptance to treatment and the type

of treatment received. Race has also been found to

influence the rate of admission to treatment for

alcoholism with blacks being under-represented in the

South (Lowe and Hodges, 1972). Lowe and Hodges also

19

report that admission to treatment does not necessarily

reflect rates of illness. Both diagnosis and admission

can be affected by non-pathological personality factors

(for example, problem drinkers with an unsophisticated

concept of their illness are more likely to be diagnosed

as alcoholic), organizational needs and financial

requirements (incorrect diagnoses are sometimes used in

order to treat andjor bill), and requirements of the

community (agents of social control sometimes slant

commitment papers to influence diagnosis) (Lowe and

Hodges, 1972).

According to Cockerham (1989), social factors

(especially sex roles) may lead to greater rates of

admission to psychiatric treatment for women. In

addition, greater numbers of treatment facilities in

urban areas may contribute to the higher treatment rates

in urban areas. It is easier for urban residents to seek

treatment, and rural residents may migrate to the city in

order to pursue treatment. Flax and his associates

(1979) consider a rural subculture of poverty as one

possible explanation of the low rate of use of treatment

resources for mental illness in rural areas.

An alternative to measuring treatment rates is to

assess the true prevalence of mental illness. A good

example of this type of research is the Stirling County

study (Leighton, Harding, Macklin, Macmillan, and

Leighton, 1963). While this type of research is

efficient, using trained psychiatrists to interview a

representative sample of the population is extremely

costly and, therefore, not practical.

Subjective Well-Being as a New Approach. Many

researchers have attempted to overcome the previous

20

shortcomings by using a softer measure of mental illness,

but with larger samples. Numerous studies have used the

Global Happiness item (eg., Bradburn and Caplovitz, 1965;

Palisi and Ransford, 1987; Phillips, 1967). This

approach has been used less in recent years, partly

because the item does not differentiate well among

populations (most claim to be happy), but also because

multi-item indices appear to make better measures.

Fischer (1973) analyzed several sets of data and

focused on numerous independent items rather than

building an index. These items include such questions

as:

"Do you think that life is getting better or worse in terms of •.. ? (a) honesty, (b) morals, (c) happiness, and (d) peace of mind."

"On the whole, would you say that you are satisfied or dissatisfied with ... ? (a) your income, (b) your work, (c) children's education, (d) your future, (e) people's honesty, and (f) your housing."

Dohrenwend (1975:370) characterizes Fischer's (1973)

attempt to measure malaise as "focusing on mild forms of

psychophysiological distress and personal

dissatisfaction."

21

Rather than using treatment rates, global happiness,

or other independent items, the mental well-being measure

has been increasingly used in the mental health

literature (Beiser, 1974; Beiser, Feldman, and Egelhoff,

1972; Berkman, 1971; Bradburn and Caplowitz, 1965;

Bradburn, 1969; Gaitz and Scott, 1972; Gove, Hughes, and

Style, 1983; Gurin, Veroff, and Field, 1960; Lowe and

Smith, 1987; McLanahan and Adams, 1989; Palisi, 1984;

Phillips, 1967).

Beiser (1974) demonstrated the heuristic value in

using a multidimensional measure of psychological well

being rather than using a single global construct such as

the Global Happiness Item. By using a factor analysis of

a number of items from previously used mental health

scales, he identified three basic components of mental

well-being. Factor I, "Negative Affect," contains items

measuring boredom, unhappiness, and loneliness in the

recent past, while factor II, "Pleasurable Involvement,"

measures pride, pleasure and excitement about the recent

past. Factor III, "Long-Term Satisfaction," measures the

respondent's satisfaction with the way his/her life has

been going and perceived success in work and with family.

Beiser found that all three factors correlate well (r=.38

to .45) with the Global Happiness Item. Further, he

found that both negative affect (r=.42) and long-term

satisfaction (r=-.31) correlate highly with Psychiatric

Caseness, which was a measure of mental illness used in

the Stirling County study (Beiser, 1974). What Beiser

confirmed was that a scale of this sort is able to

provide a more reliable index than the use of a single

item such as the Global Happiness Item.

Lowe and his associates (see Hellinghausen, 1984;

22

Kunkel, 1981; Lowe and Smith, 1987; Lowe and Witt, 1978;

and Witt, 1978) have demonstrated the usefulness of a

related index of mental well-being. Lowe's measure was

developed for use with the General Social Surveys and is

based on the Global Happiness Item, together with

questions about satisfaction with family life,

friendships, health, hobbies, and place of residence.

Studies using this index produce findings consistent with

studies using other measures of mental well-being (see

Beiser, 1974). It is correlated with age (Witt, 1978),

class (Kunkel, 1980; Lowe and Witt, 1978), social stress

(Hellinghausen, 1984; Lowe and Witt, 1978), and marital

status (Lowe and Smith, 1987; Lowe and Witt, 1978).

Social Stability and Subjective Well-Being

23

There is convincing evidence to show that individual

well-being is enhanced by involvement in social

relationships (Umberson, 1987) and that lack of social

ties may contribute to poor psychological well-being and

even death (Berkman and Syme, 1979; Turner, 1981;

Williams, Ware, and Donald, 1981). The study of "social

support" became extremely popular in the 1970s (e.g.,

Caplan, 1974; Cassel, 1976; Cobb, 1976) and has grown

dramatically to the present date (e.g., Cohen and Syme,

1984; Gottlieb, 1983; House, 1981; Kahn and Antonucci,

1980; Lin, Dean, and Ensel, 1986; Thoits, 1982). Though

different definitions of social support exist, it is

generally close to the one proposed by Lin et al. (1986).

Lin and associates define social support as "the

perceived or actual instrumental andjor expressive

provisions supplied by the community, social networks,

and confiding partners (1986, p. 18).

The study of social support, although not termed

social support at the time, may date as far back as

Durkheim's study of suicide in 1897 (Durkheim, 1951).

Durkheim examined the way that social integration in

society effected suicide rates. This led to later

researchers' interest in the way that integration, in the

24

form of social networks and social support, effected such

things as psychiatric disorders (Lin et al., 1986).

Lowe (1971), attempting to index "the amount of

social support available to the individual, especially in

times of adversity," developed the concept of social

stability, which refers to social support from structural

sources. It is a foundation that is accessible for the

person to draw upon when coping with social stress. This

social support may be present in the form of ties to

family, friends, employment, or voluntary groups. There

is also an aspect of social support that is artificial in

nature. This is support available only to an individual

who is playing a client role. While treatment facilities

are sources of such support, they are primarily located

in the city. Psychologists, psychiatrists, and social

workers also tend to be concentrated in urban areas

(Rogers, Burdge, Korsching, and Donnermeyer, 1988).

Lowe (1971) says that every social system that a

person is involved in provides some amount of support.

Some groups do provide more support than others, but

rather than attempting to account for all groups that an

individual belongs to, Lowe's measure of social stability

attempts to measure "a combination of (1) the presence of

links to the social structure, (2) the strength of those

links, and (3) the amount of support available within the

group" (Lowe, 1971, p. 130). Social support and social

stability have been found to be positively correlated

with mental well-being (Hellinghausen, 1984; Kunkel,

1981; Lee, 1978; Lowe, 1971; Lowenthal et al., 1967;

Moriwaki, 1973; and Wood and Robertson, 1978).

The Research Problem

Considering the previous research on rural life,

25

urban life, and the effects on the mental state of their

residents, there are two immediate hypotheses that may be

drawn. Poor interpersonal relationships, a high division

of labor, and excess sensory stimulation may lead to

higher stress for residents of urban areas, resulting in

poor subjective well-being for urban residents. The

first hypothesis states this thesis for test.

Hypothesis I: Subjective Well-Being is better among persons residing in rural areas.

However, there is also research indicating that, due to

increased stress from sources such as social isolation

and overcrowding in the home, urban residents will have

better subjective well-being.

Hypothesis II: Subjective Well-Being is better among persons residing in urban areas.

It is possible that with the growing technology in

our society, there may not be such a strong division

between the city and the country. People are now able to

use the telephone to communicate more easily and the

26

automobile to travel away from the place of residence for

whatever reason necessary. Thus, people are not bound to

their place of residence as much as may have been the

case earlier in this century. Further, while there may

be stressful factors involved in both types of

environment, the stress may be equal, resulting in no

difference in level of subjective well-being. This leads

to Hypothesis III.

Hypothesis III. There is no difference in degree of subjective well-being in urban and rural residents.

Several variables have previously been found to

affect mental well-being and its components: social

class (Clemente and Saur, 1976; Kunkel, 1980; Lowe and

Witt, 1978), gender (Lowe and Smith, 1987), race (Alston,

Lowe, and Wrigley, 1974; Thomas and Hughes, 1986), and

age (Witt, 1978). Further, Campbell, Converse, and

Rogers (1976) report that age should be controlled when

examining mental well-being because of differentials in

health and career patterns. This analysis will control

for all four factors.

After the initial control variables have been taken

into account, social stability will be controlled. If

rural stress results in better subjective well-being in

urban areas, and social stability is higher in rural

areas, a control for social stability should increase the

27

positive association between urbanism and subjective

well-being. If social stability is higher in urban

areas, the strength of this association should decrease.

In the General Social Surveys (the data set used in

this study), there is no means of measuring artificial

social support, such as that available through treatment

facilities, which is potentially more readily available

in the city. If subjective well-being is shown to be

better in urban areas after controlling for social

stability, it will not be possible to ascertain whether

these differences are due to greater stress in rural

areas or if they are due to the greater levels of

artificial support available in cities.

If, on the other hand, rural residents are initially

shown to have better subjective well-being, and if rural

residents have higher social stability, a control for

social stability should decrease the negative

relationship between urbanism and subjective well-being.

If rural areas are lower in stress, resulting in better

subjective well-being, and urban residents have higher

social stability, controlling for social stability should

increase the negative association between urbanism and

subjective well-being.

CHAPTER II

METHODS

In this chapter, a research design will be created

in order to answer the question of whether subjective

well-being is better in rural or urban areas. The

discussion will include a description of the national

surveys which comprise the data base, operationalization

of subjective well-being, location of residence, and all

control variables.

The Sample

The data used in this analysis were taken from the

General Social Surveys (GSS), conducted by the National

Opinion Research Center (NORC) at the University of

Chicago (Davis and Smith, 1989b). The General Social

Surveys are based on a full probability sample design.

They utilize a multi-stage full probability sample to the

block or segment level. Quota sampling is used at the

block level with quotas based on sex, age, and employment

status. The Primary Sampling Units implemented are

Standard Metropolitan Statistical Areas (SMSAs) or non

metropolitan counties selected in NORC's Master Sample.

28

29

Before selection, the SMSAs and counties were stratified

by region, age, and race (for more details, see Davis and

Smith, 1989a). The universe sampled includes the total

non-institutionalized, English-speaking population of the

continental United States, 18 years of age and older.

This analysis is limited to persons residing in the

central cities of the 100 largest SMSAs and the most

rural areas in the United states. In order to control

for the effects of race, only whites are included in the

present analysis. In addition, only those respondents

who were asked the sociability items and the items

included in the Subjective Well-Being index were

included. Due to the rotation of questions across years,

the 1978, 1983, 1986, 1988, and 1989 surveys are used.

These are the years in which all of the necessary items

to build the Subjective Well-Being and Social stability

measures were included. After eliminating blacks,

respondents who do not reside in the central cities or

most rural areas, and respondents who were not asked the

necessary questions, a total of 1419 respondents

remained.

Operationalization of Variables

The Dependent Variable

The measure of Subjective Well-Being is a factor

score index in which a series of satisfaction questions

and a general happiness question are combined. General

happiness is weighted on a three-point scale.

30

Respondents were asked the question, "Taken all together,

how would you say things are these days -- would you say

that you are very happy, pretty happy, or not too happy?"

Responses ranged from (3) very happy, (2) pretty happy,

to (1) not too happy. For the satisfaction questions,

respondents were asked to indicate the amount of

satisfaction they are getting from each of the following

four areas of life: (1) "your non-working activities

hobbies and so on;" (2) "your family life;" (3) "your

friendships;" and (4) "your health and physical

condition." The item concerning satisfaction with place

of residence that is used in Lowe's measure of mental

well-being was dropped from this measure. Previous

findings (Carpenter, 1977; Fuguitt and Zuiches, 1975)

have shown that, while rural residents are satisfied with

the place in which they live, urban residents show great

desire to live elsewhere. If satisfaction with size of

place was used in this measure, it would then be biased

in favor of rural residents.

31

Responses to the satisfaction items ranged from "a

very great deal" (scored seven) to "none" (scored one).

Subjective Well-Being is the standardized factor score

based on the unrotated first principal component (see

Armor and Couch, 1972, for details). The first principal

component (Table 1) accounted for 45% of the variance in

items.

The Independent Variable

In order to adequately measure the differences

between the crowding of the city and the isolation of the

city, Urbanism utilized both the NORC size of place and

Survey Research Center, University of Michigan (SRC) New

Belt code measures. It was divided into two categories,

rural and center city. Urban was coded 2 and included

the central cities of the 100 largest SMSAs. Rural was

coded 1 and included areas of open country within larger

civil divisions (e.g., township, division) as defined by

NORC which were outside of the suburbs of the 100 largest

SMSAs as defined by SRC (see Davis and Smith, 1989a, for

description).

Control Variables

The rest of the variables used in the study will be

defined as follows. For the variable Sex, males were

32

coded as 1 and females as 2. Age was coded as to actual

age of respondent in years.

Socioeconomic status was measured by four questions.

To measure occupational prestige of the head of the

household, the occupation of the respondent was used if

it was a male or a single female; for married females,

the occupation of the spouse was used. The GSS

occupational prestige scores were used (see Davis and

Smith, 1989a, for details). For subjective social class,

respondents were asked, "If you were asked to use one of

the four names for your social class, which would you say

you belong in: the lower class, the working class, the

middle class, or the upper class?" Lower class was coded

1, working class--2, middle class--3, upper class--4.

The respondent's education was coded from zero to twenty,

reflecting the number of years of formal education

obtained. Family income was first converted into dollar

amounts, using the midpoint of each of the original

categories. In the 1977-1980 surveys, there were 16

categories for family income. The lowest category was

for family incomes under $1,000 and was coded 500. The

highest category was for family incomes $50,000 or over

and was coded 55,000. The 1982-1985 surveys included 17

categories for family income. The lowest category was

for family incomes under $1,000 and was coded 500. The

33

highest category was for family incomes $50,000 or over

and was coded 55,000. There were 20 categories included

for family income in the 1986-1989 surveys. The lowest

category was for family incomes under $1,000 and was

coded 500. The highest was for family incomes $60,000 or

over and was coded 65,000. The dollar amounts were then

standardized by using a z-transformation within each

year. Thus, all respondents' incomes were standardized

for their respective years. The final measure of SES was

a standardized factor score based on the unrotated first

principal component (see Armor and Couch, 1972, for

details). The first principal component accounted for

51.2% of the variance in items (Table 2).

The index of Social Stability used is a modification

of an earlier index developed by Lowe (1971). Both

conjugal and extended family are potential sources of

support. Sources of conjugal support are measured by

asking the respondent if sjhe is married and currently

living with the spouse. Another indication of whether

the respondent may receive support from relatives or

adults is obtained by asking whether sjhe lives with a

relative, an adult, or anyone. Further, the respondent

was asked whether social evenings spent were ever spent

with relatives, parents, siblings, friends, and

neighbors.

34

The respondent was asked questions about religious

identification and frequency of church attendance in

order to measure religious ties and the strength of those

ties.

Employment is an important means of support for an

individual. The respondent's and spouse's current

employment status were included, along with union

membership. Additionally, the respondent was questioned

about memberships in voluntary associations and the

number of such associations in which sjhe was a member.

The items included in the social stability measure are as

follows.

(1) Is the respondent married and living with hisjher spouse?

(2) Does the respondent live with any relative?

( 3) Does the respondent live with any adult?

(4) Does the respondent live with anyone?

(5) Is the respondent employed?

(6) Is the respondent's spouse employed?

(7) Is the respondent or spouse employed?

(8) Does the respondent ever spend a social evening with relatives?

(9) Does the respondent ever spend a social evening with parents?

(10) Does the respondent ever spend a social evening with siblings?

35

(11) Does the respondent ever spend a social evening with friends?

(12) Does the respondent ever spend a social evening with neighbors?

(13) Does the respondent have some religious identification?

(14) Does the respondent attend church greater than once a year?

(15) Does the respondent attend church more than once a month?

(16) Is the respondent a union member?

(17) Does the respondent claim membership in any voluntary association?

(18) Is the respondent a member of three or more voluntary association?

Each of the previous items concerning the respondent was

coded as 1 if the question was answered affirmatively,

and 0, if not. The level of social stability is the sum

of all of the items. The possible range for the social

stability variable is 0 to 18. The actual range for

respondents on this variable is also 0 to 18 with a mean

of 11.43 and standard deviation of 3.40.

TABLE 1

Principal Component Factor Analysis of Subjective Well-Being Items

36

=========================================================

Item Description Loadings

Principal Component Factor

Happiness Satisfaction from hobbies Satisfaction from family life Satisfaction from friendships Satisfaction from health Eigenvalue

.631

.654

.683

.717

.667 2.252

TABLE 2

Principal Component Factor Analysis of Socioeconomic Status Items

37

=========================================================

Item Description Loadings

Principal Component Factor

Standardized Income Prestige of Head of Household Subjective Social Class Respondent Education Eigenvalue

.691

.740

.653

.773 2.049

CHAPTER III

FINDINGS

As a preliminary step, the zero-order correlations

between subjective well-being and the independent and

control variables are examined (Table 3). These are all

correlated with subjective well-being approximately as

expected. People in rural areas have better subjective

well-being than those in urban areas (r = -.084). Age is

shown to be negatively related to subjective well-being

(r = -.074). Gender is related (r = .039) to subjective

well-being with females being slightly higher than males,

while socioeconomic status (r = .275) and social

stability (r = .321) produce positive correlations which

are by far the strongest associations with the dependent

variable. Urbanism and age are significant at the .01

level, while socioeconomic status and social stability

are significant at the .001 level.

The next step in the analysis is to examine the

relationship between urbanism and subjective well-being

before any of the controls are considered. This is the

equivalent of the zero order correlation coefficient.

The analysis of variance employed indicates that the

difference between rural residents (mean = 0.025) and

38

39

urban residents (mean = -0.148) is statistically

significant at the .01 level (see Table 4). The reader

is reminded that the subjective well-being scores are

standardized on the total white population and has mean

zero and standard deviation of one. Rural residents,

then, have above average subjective well-being and urban

residents, with a mean below zero, are below average.

This is significant at the .002 level.

The second step is to consider the influence of two

variables that influence subjective well-being, but which

do not necessarily vary between rural and urban samples-

age and gender. When the means were adjusted for the

influence of these two factors, the difference between

rural and urban residents increased slightly (Table 5).

The adjusted mean of rural residents changed to 0.031 and

urban residents changed to -0.154. This shows that, when

controlling for these two variables, the difference

between rural and urban gets even larger with rural

residents still having better well-being and is

significant at the .001 level.

The third step is to consider the influence of

socioeconomic status. Social class is strongly and

positively related to subjective well-being. Persons in

urban areas have higher socioeconomic status, on average,

than do rural residents. Further, the influence of

40

social class, whether it be the increased stress

associated with lower class life or the cushioning effect

of the higher resources associated with high

socioeconomic status, should have a suppressor effect on

the relationship between urbanism and subjective well

being. Adding socioeconomic status as a covariate showed

this to be the case (Table 6). After adjustment for

socioeconomic status in addition to age and gender, rural

residents show a mean subjective well-being score of

0.080 while urban residents dropped to -0.203.

We are now ready to consider the influence of social

stability on the relationship (Table 7). The addition of

this covariate raised the mean for urban residents to

-0.137 and lowered that of rural residents to 0.014, only

slightly above the national average for whites. Clearly,

a major factor contributing to the more favorable

subjective well-being of rural residents is their higher

level of social stability. However, just as clearly, the

stresses associated with urbanism have a significant

influence on mental health.

In the analysis of variance, urbanism was treated as

a factor of classification which, in the model utilized,

did not allow it to compete equally in the explanation of

variance. The tests are now repeated using stepwise

multiple regression.

41

As can be seen in Table 8, multiple regression shows

the same effects in a slightly different form. In the

first step, the standardized partial regression

coefficient showed urbanism to be negatively correlated

(Beta = -.084) with subjective well-being. This was

significant at a level of .002. In the second step,

gender was added to the equation. When gender was added,

the effect of urbanism remained relatively the same with

a standardized regression coefficient of -0.086 and was

significant at the .002 level. Age was added to the

equation in the third step. Here, the standardized

coefficient for urbanism rose to -0.090 with a

significance level of .001. When socioeconomic status

was added to the equation in the fourth step, the

standardized coefficient for urbanism rose to -0.137 with

a significance level of .001. In this equation, urbanism

added 1.8 percent to the variance explained by the other

variables.

In the final step (Table 9), social stability was

added to the equation, and we see that urbanism retains

statistical significance in the company of these other

powerful influences on mental health. While the

standardized partial regression coefficient for urbanism

dropped to -0.073 in this equation, it is still related

to subjective well-being at the .005 level. All of the

42

other variables other than age were significant at the

.001 level. By far, the most influential variable in the

equation was social stability, which added 4.9% to the

variance in subjective well-being explained by the other

four variables. For complete results of all five steps,

see Tables 10-14 in the Appendix.

TABLE 3

Zero-Order Correlation Coefficients for Subjective Well-Being

43

=========================================================

Variable Zero-Order Correlation Coefficient

Urbanism -0.084 ** Gender 0.039

Age -0.074 ** SES 0.275 ***

Social Stability 0.321 ***

** significance under .01

*** significance under .001

TABLE 4

Mean Level of Subjective Well-Being for Rural and Urban Residents

44

=========================================================

Mean

Effect

so

N

Rural Urban

0.025 -0.148

0.087 -0.087

0.971 1.066

639 780

Unweighted Means Analysis of Variance for Subjective Well-Being

=========================================================

Sum of Squares DF F-Test Significance

Urbanism 10.546 1 10.054 0.002

Unit 1486.366 1417 Not Tested

Total 1496.912 1418

Subjective Well-Being scores have mean zero and standard deviation one. Higher scores designate better wellbeing.

TABLE 5

Mean Level of Subjective Well-Being for Rural and Urban Residents Adjusted for Age and Gender

45

=========================================================

Rural Urban

N 639 780

Adj. Mean 0.031 -0.154

Adj. Effect 0.092 -0.092

Unweighted Means Analysis of Variance for Subjective Well-Being Adjusted

for Age and Gender

=========================================================

ss DF F-Test Significance

Urbanism 11.972 1 11.493 0.001

Covariates 12.393 2 5.948 0.003



TABLE 6

Mean Level of Subjective Well-Being for Rural and Urban Residents Adjusted for Age, Gender, and

Socioeconomic Status

46

=========================================================

Rural Urban

N 639 780

Adj. Mean 0.080 -0.203

Adj. Effect 0.142 -0.142

Unweighted Means Analysis of Variance for Subjective Well-Being Adjusted for Age, Gender,and Socioeconomic Status

=========================================================


Urbanism 27.409 1 28.805 Under 0.001

Covariates 140.888 3 49.355 Under 0.001



TABLE 7

Mean Level of Subjective Well-Being for Rural and Urban Residents Adjusted

for Age, Gender, Socioeconomic Status, and Social Stability

47

=========================================================

Rural Urban

N 639 780

Adj. Mean 0.014 -0.137

Adj. Effect 0.076 -0.076

Unweighted Means Analysis of Variance for Subjective Well-Being Adjusted for

Age, Gender, Socioeconomic Status, and Social Stability

=========================================================


Urbanism 7.238 1 8.042 0.005

Covariates 214.673 4 59.632 Under 0.001



TABLE 8

Results by Step for Urbanism in Stepwise Multiple Regression on

Subjective Well-Being

48

=========================================================

Variable Added

Step 1

Gender

Age

SES

Stability

Standardized Coefficient for Urbanism T-Test

-0.084 -3.17

-0.086 -3.23

-0.090 -3.39

-0.137 -5.37

-0.073 -2.84

Unique Variance

Sig. for Urbanism R2

.002 .007 .007

.002 .007 .009

.001 .008 .015

<.001 .018 .101

.005 .005 .150

TABLE 9

Regression Results for Subjective Well-Being

Final Step

49

=========================================================

Standardized Variable Coefficient Significance

Urbanism -0.073 .005

Gender 0.097 <.001

Age 0.037 .169

SES 0.212 <.001

Social stability 0.264 <.001

Multiple Correlation Squared = 0.150

Unique Variance

.005

.009

.001

.037

.049

CHAPTER IV

SUMMARY

A review of the literature has shown two schools of

thought concerning differentials between the size of

place of residence and mental health. Both arguments

view stress as a major factor in influencing mental

health. Proponents of the theory that urban residents

have better mental health argue that rural life causes

stress because of factors such as crowding in the home,

isolation, and factors associated with financial

hardships which are detrimental to a person's mental

state. On the other hand is the contention that urban

life is characterized by a overcrowding, high division of

labor, and excess sensory stimulation, all of which are

potential causes of stress. Advocates of this theory

assert that rural residents have better forms of support

that they can turn to in times of stress in order to cope

with this stress.

Attempts to measure the differentials between urban

and rural residents' mental health have yielded ambiguous

results. This is due to inconsistent and problematic

methods of measurement such as treatment rates for mental

illnesses and use of the Global Happiness Item.

50

51

Recently, the use of subjective well-being has helped to

alleviate such problems (Gove et al., 1983; Lowe and

Smith, 1987; Lowe and Witt, 1978; McLanahan and Adams,

1989).

Three hypotheses have been stated. Hypothesis I is

that higher stress from poor interpersonal relationships

and excess sensory stimulation in urban areas will result

in rural residents having better subjective well-being.

Hypothesis II follows the line of thinking that rural

residents will have more stress from overcrowding in the

home and social isolation and, therefore, states that

urban residents will have better subjective well-being.

There is the possibility that the technological growth of

society has reduced the differences between rural and

urban areas and that stress is equal in both areas.

Hypothesis III is that there is no difference between

urban and rural residents in subjective well-being.

This analysis has shown that, before controlling for

relevant variables, rural residents have significantly

better subjective well-being. When controlling for

gender, age, and socioeconomic status, the differences

get larger with the addition of each successive control

variable. When social stability is added as a control

variable, the differences become smaller, but there is

still a significant difference. Rural residents still

52

have better well-being. These results are consistent

when two different types of analysis are employed, those

being analysis of variance and stepwise multiple

regression.

An important finding in this analysis concerns the

effect of social stability on the relationship between

urbanism and subjective well-being. In the step where

gender, age, and socioeconomic status were added to the

regression equation, there was a strong relationship

between urbanism and well-being. When social stability

was added, the relationship was reduced, but remained

significant. At this point, it may be possible to

conclude that the differences in well-being are not large

enough to provide support for the hypothesis that stress

is greater in urban areas which results in better well

being for rural residents. However, since social

stability is believed to be an important factor in

dealing with stress, the addition of this variable should

compensate for the different means of coping that the two

groups (rural and urban residents) have available.

Social stability has a strong impact on the relationship

between urbanism and well-being due to the strong

negative relationship that it has with urbanism. Because

of the strong relationship between social stability and

well-being, the relationship between urbanism and well-

53

being weakens when social stability is controlled. This

relationship remains significant though, thus providing

support for Hypothesis I: Subjective Well-Being is

better among persons residing in rural areas.

It is possible, then, to conclude that urban life

has a more detrimental effect on its residents than rural

life. This is likely because urban residents are the

recipients of more stress than those residing in rural

areas. Rather than the overcrowding in the home and

social isolation in rural areas, it appears to be

crowding on the macro level, and stress associated with

the city that leads to poor mental health. There is a

large enough differential in mental well-being that it

remains significant even when the high levels of social

stability in rural areas are controlled.

A potential problem with the conclusion drawn in

this study is that of the many separate "communities"

that exist in the city. These communities may be seen in

the form of neighborhoods, particularly ones that are

inhabited mainly by people of the same ethnic background.

Gans (1962) refers to these neighborhoods as "urban

villages." People in these neighborhoods have

characteristics similar to small rural communities.

People in these areas tend to know everyone in the

neighborhood, or they at least know something about

54

everyone. In such areas, there is solidarity and

cohesiveness that is more typical of small rural

communities than of the large city. The isolation from

one's neighbors is not the same as it may be in other

parts of the city. Thus, city life may not affect these

residents in the same way as it affects others. One may

question the effect that city life has on these

inhabitants.

There is still the possibility that a problem that

is associated with measuring mental illness by using

treatment rates is present in this analysis. Cockerham

(1989) discusses the idea that persons with poor mental

health who live in rural areas are likely to migrate to

the city in order to receive treatment. It is not

possible to measure this type of migration in the present

study due to the unavailability of data on a person's

prior place of residence. While it is not possible to

accurately measure migration, it is a factor that should

be taken into consideration. It is possible that this

could be a reason for migration, not necessarily because

of persons seeking treatment, but rather because a person

may be dissatisfied with the course that hisjher life is

taking. There may be a large number of formerly rural

residents who have moved to the city because of problems

in the country in order to resolve these difficulties.

55

Cockerham (1989) also talks about this possibility. He

says that people are likely to move in order to seek

economic, social, and cultural opportunities somewhere

else. It is possible that these people have never been

able to find what it is that they seek. Those that

remain in the country, though, are possibly the ones who

are content with their lives.

This study has shown support for the idea of

isolation and stress that is associated with the urban

lifestyle. This is consistent with Wirth's (1938) theory

of urbanism. While it has been shown that rural

residents have better subjective well-being, it should be

noted that the possibility of migration is a potential

problem. This could be resolved by the use of data that

have a measure of the individual's previous residence.

It is also relevant to question what specific stressful

factors may lead to these differences. It would be

beneficial to isolate these factors and evaluate how

people react differently to these events in the city and

in the country. This may produce more helpful

information about why rural residents have better

subjective well-being.

REFERENCES

Alston, Jon P., George D. Lowe, and Alice Wrigley. 1974. "Socioeconomic Correlates for Four Dimensions of Self-Perceived Satisfaction." Human Organization 33:35-49.

Armor, David J. and Arthur s. Couch. 1972. Data-Text Primer. New York: Free Press.

Baldassare, Mark. 1978. America. Berkeley:

Residential Crowdina in Urban University of California Press.

Bennett, John w. 1982. Of Time and the Enterprise: North American Family Farm Management in a Context of Resource Marginality. Minneapolis, MN: University of Minnesota Press.

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APPENDIX: COMPLETE TABLES FOR STEPWISE MULTIPLE REGRESSION ON SUBJECTIVE WELL-BEING

66

TABLE 10


67

=========================================================

Variable Unstandardized Coefficient

Standardized Coefficient

Urbanism -0.1733 -0.084

R2 F p

= = =

0.007 10.05 with 1 and 1417 degrees of freedom .002

T-Test Sig.

-3.17 .002

TABLE 11


68

=========================================================

Variable

Urbanism

Gender

R2 = 0.009

Unstandardized Coefficient

-0.1766

0.0875


-0.086

0.042

F p

= =

6.31 with 2 and 1416 degrees of freedom .002

T-Test Sig.

-3.23 .002

1.60 .110

TABLE 12


69

=========================================================

Variable

Urbanism

Gender

Age

R2 = 0.015


-0.1850

0.0978

-0.0046


-0.090

0.047

-0.081

F = 7.34 with 3 and 1415 degrees of freedom p = <.001

T-Test Sig.

-3.39 .001

1.79 .074

-3.05 .003

70

TABLE 13


=========================================================

Variable

Urbanism

Gender

Age

SES

R2 = 0.101


-0.2836

0.1658

-0.0032

0.3097


-0.137

0.080

-0.057

0.300

T-Test Sig.

- 5.37 <.001

3.15 .002

- 2.24 .026

11.62 <.001


TABLE 14


71

=========================================================

Unstandardized Variable Coefficient

Urbanism -0.1515

Gender 0.2004

Age 0.0021

SES 0.2190

stability 0.0800

R2 = 0.150


-0.073

0.097

0.037

0.212

0.264

T-Test

-2.84

3.91

1.38

7.88

9.05


Sig.

.005

<.001

.169

<.001

<.001

rural-urban differences in a thesis in sociology …

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