geo cape handbook final

Students’

HANDBOOK

Geography

© 2009 Statistical Institute of Jamaica

Short extracts from this publication may be copied or reproduced for individual use, without permission, provided the source is fully acknowledged. More extensive reproduction or storage in a retrieval system, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise requires prior permission of the

Statistical Institute of Jamaica.

Published by

The Statistical Institute of Jamaica

7 Cecelio Avenue

Kingston 10

Jamaica

P.O. Box 643

Tel: (876) 926-5311

Fax: (876) 926-1138

e-mail: [email protected]

Website: www.statinja.gov.jm

ISBN: 978-976-8213-51-8

Printed by

The Printing Unit

Statistical Institute of Jamaica

84 Hanover Street

Kingston

Jamaica

Table of Contents

FOREWORD iii

ACKNOWLEDGEMENTS iv

INTRODUCTION v

Population Distribution............................................................................................................. 1

Population Density ..................................................................................................................... 1

Dot Distribution Map................................................................................................................ 2

Isopleth Maps ........................................................................................................................... 3

Proportional Circle..................................................................................................................... 5

Choropleth Map.......................................................................................................................... 9

Population Structure................................................................................................................10

Types of Population Pyramids ................................................................................................12

Settlement ...............................................................................................................................16

The Labour Force .....................................................................................................................21

Per Capita Income ....................................................................................................................24

Inflation .....................................................................................................................................27

Life Expectancy........................................................................................................................29

Dependency Ratios ...................................................................................................................31

Fertility ......................................................................................................................................34

Literacy ......................................................................................................................................38

Mortality ....................................................................................................................................40

Nutrition ....................................................................................................................................44

Appendices.................................................................................................................................49

Foreword

The initiative for the Students’ Handbook is the response of the Statistical Institute of Jamaica (STATIN) to the demands from students for information to complete their course requirement in various areas of study. The Handbook has the dual purpose of being a compendium on statistics as well being a guide on how to use information published by the Institute. It is our expectation that these Handbooks will be useful to both the teachers and students who are preparing for the Caribbean Advanced Proficiency Examinations (CAPE) in the areas of Economics, Sociology and Geography.

The preparation of the handbooks was done through several consultations with teachers and students and subject matter experts within the Institute. It is to be noted that the Handbooks do not cover the entire syllabus in each subject area but selected topics. Your feedback on the information presented would greatly assist us in improving the quality of the material contained in future publications.

The Statistical Institute of Jamaica (STATIN) was established under the Statistics (Amendment) Act 1984 (the Act) on April 9, 1984 has been invested with all the powers formerly vested in the Department of Statistics and previously the Bureau of Statistics (which came into existence in 1946).

The Act prescribes the role and functions of STATIN, what data are to be collected and how these data are to be released. The Act protects the individual’s right to privacy, in that data cannot be released in such a manner that will identify the individual or any specific business entity. Where those circumstances cannot be avoided, the data provider’s written consent must first be obtained before the data are released. In addition, the data collected can only be used for statistical purposes. Where breaches occur in the administration or use of data, the Act prescribes penalties. Integrity and confidentiality are at the core of operations at STATIN.

The Handbook should not be treated as a textbook and should only serve to complement the other resources available on the subject area. Additional data on Jamaica can be obtained at the Institute’s library at 7 Cecelio Ave. Kingston 10, or on our website: www.statinja.gov.jm. Students are being encouraged to use the website which provides current information on the

economy in such areas as international merchandise trade, gross domestic product (annual and quarterly), the labour force; and the population, its composition and distribution.

Acknowledgements

The Statistical Institute of Jamaica thankfully acknowledges the contribution and assistance of all persons and organizations in the development of this handbook.

STATIN recognizes the members of staff, too numerous to mention by name, who took time out from their regular work programme to facilitate the creation of another landmark in the history of the Institute.

The preparation of this handbook would not have been possible without the support, hard work and endless efforts of the subject area teachers and students from the various high schools.

Introduction

The Geography Handbook was developed as a guide for students and was specially designed to enhance their ability to interpret and analyze the complex relationships that exist between people and their environment. It is a practical guide that focuses on how maps and diagrams, rates, ratios and other statistical indicators are prepared and used to illustrate and analyze spatial patterns and trends. The text provides a step by step guide to the calculation of indicators such as fertility, mortality and unemployment rates, population density, dependency ratios, and purchasing power parity among others. It contains worked examples that illustrate their application and offers in-depth interpretation of the results. In addition, concepts are explained, helpful guidelines provided and data are included to support evidence-based reasoning.

In this edition of the Geography Handbook, two of the six modules covered in the CAPE Geography Syllabus are considered:- Module 1 (Unit 1) covering Population and Settlement and Module 3 (Unit 2) that deals with Development and Disparities in Development. In order to realize the objectives of these modules, students need to make use of statistical data and simple tools of statistical analysis to demonstrate their understanding of the issues and to support their ability to explain, interpret and analyze. The Handbook aims at providing these resources to the students.

Data presented on population, labour force, employment, inflation and gross domestic product were extracted from available datasets for Jamaica (and elsewhere) and used to prepare the relevant maps and indicators. The data for Jamaica are compiled from decennial censuses and on-going socio-demographic and economic surveys and are published in time series. Current data are therefore available to all students and academics in pursuit of their learning objectives.

The Handbook should not be relied on as a sole source or treated as a comprehensive guide on geographic information. It should rather be viewed as a supporting document designed for use by students who are striving to achieve mastery in Geography.

Students’ Handbook: Geography

The formula for calculating population density is

Total population within an area

Total area

E.g. Population of Lucea in 2001 = 6,062

Total Area of Lucea = 3.9 km²

Population density = 6,062

3.9

= 1,554 persons per km²

Population distribution refers to the way in which people and settlements are dispersed within a geographic area.

It is usually described in terms of observed patterns of settlement and reflects the concentration or spread of people living in these settlements.

Several types of population distribution patterns are observed as settlements can either be concentrated, clustered or grouped; scattered or randomly distributed; strung out along roads and waterways in linear patterns or arranged in diverging corridors from a central core as in radial distributions.

Population density is a measure of the number of people in a given area relative to the space occupied by them. It is usually expressed as the number of persons per unit of area such as “persons per square kilometer” or square mile and is an indicator of the intensity of land use.

INTERPRETATION

Lucea is a rural town and would be considered as having low population density since it has less than two thousand persons per sq km (i.e. < 20 persons/hectare)1. A density of 15.5 persons per

POPULATION DENSITY

POPULATION DISTRIBUTION

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1 There are 100 Hectares in each square Kilometer and 2.47 Acres per Hectare


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hectare (or approx. 6 persons per acre) is low when compared with urban cities like Mumbai (India) with 29,650 persons per km² (or 296.5 persons/hectare) and the Kingston Metropolitan Area (KMA), Jamaica with 4,020 persons per km² (or 40.2 persons/hectare) which are areas classified as high density.

METHODS OF DEPICTING POPULATION DISTRIBUTION AND DENSITY

Several methods exist for depicting population distribution and density and most are illustrated graphically. Listed below are some popular methods of depicting population distribution and density.

DOT DISTRIBUTION MAPS

Dot Distribution Maps utilize dots (or other symbols) to represent the numbers of population found in a particular location and is one of the most popular methods of depicting population distribution. In areas of high population concentration the dots may coalesce or, a larger dot symbol may be used to represent an increased number of population.

This method involves three (3) principal considerations:

• The selection of the dot value (i.e. the number of persons that each dot represents)

• The selection of the dot size

• The distribution of the dots so as to depict the actual distribution of population.

It is important to decide on a dot value and size which will be equally legible in areas where the population is widely dispersed as in areas where the population is more concentrated. Dot concentration should not exceed the point where the number of dots cannot be discerned. Larger dots representing larger values have a greater visual effect but make the interpretation in densely populated areas more difficult.


An example of a dot distribution map is shown in Fig.1. (Population Distribution of Jamaica)

Fig. 1

ISOPLETH MAPS

Isopleth Maps are maps that display the distribution of a phenomenon or attribute (e.g. temperature, elevation or rainfall) with the use of lines that connect points of equal value. The lines are either drawn to connect points of identical value or are interpolated proportionally between known values.

Isopleth maps generalize and simplify data with a continuous distribution. They are best suited for depicting population distributions over large geographic areas where the aim is to smooth out local variations in order to get a broad overview of the pattern of distribution. With an isopleth map, each line connects places of equal population value. An example of how an isopleth map is constructed is shown in fig. 2. The figure shows that lines are used to connect places of equal population. Layer-shading is added to each intervening area to define the bands and to add clarity to the map. Isopleth maps can also be used to illustrate population density.

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Source: Statistical Institute of Jamaica


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CONSTRUCTION OF A POPULATION ISOPLETH MAP

Fig. 2

Steps in the Construction of a Population Isopleth map (as shown in Fig. 2)

STEP 1

The population of each location identified is marked by a dot.

STEP 2

A dotted isoline is used to interpolate all locations with a population of 70 persons.

STEP 3

Isolines at 10-person intervals are similarly interpolated and mapped.

STEP 4

Shades of increasing intensity were added to provide clarity between isopleths and to illustrate the increasing population concentration from east to west.


PROPORTIONAL CIRCLE

Some map symbols if drawn to scale and accurately positioned on a map can provide quantitative as well as locational information about the phenomenon they represent.

There are four (4) basic types of proportional symbols namely:-

• Area Proportional Symbols such as circles and squares whose AREA is drawn proportional in size to the values they represent.

• Columnar Proportional Symbols in which the HEIGHT of the column is proportional to the data value.

• Flow Lines (used to illustrate any kind of movement e.g. migration, tourism, trade or liquids in pipelines). The flow line is constructed such that the WIDTH of the line is proportional to the data value.

• Prisms that are constructed by proportionally raising the HEIGHT of each mapped region to give the appearance of a 3-dimensional block or prism.

The Proportional Circle is a type of Area Proportional Symbol and is suitable for showing the distribution of population by countries particularly to demonstrate the significance of the population resources in a particular region. As the name suggests, the size of the circle must be directly proportional to the population it represents.

Procedure for Making Proportional Circles

(N.B. this method applies when making area proportional symbols of any shape)

1. The first step is to make a list of the data values and find the square root of each of these (unlike other types of proportional symbols, area symbols involve the calculation of the square root of the data values) All subsequent calculations will make use of the square roots list instead of the original data.

2. Choose a scale for the symbol sizes from whatever unit of

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measure is considered appropriate for the map (e.g. circle radius’ in millimeters; circle diameter in centimeters; column heights in inches or centimeters etc.)

3. Examine the base map and determine a maximum circle size for the largest data value that is to be mapped (e.g. For a given map, the largest circle may be set to have a diameter of 2 cm.)

4. Calculate all other proportional circles in relation to the dimension that was set for the largest symbol using the formula below:-

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9.760

9.394

Example: Procedure for making Proportional Circles (Steps 1- 4)

If the Kingston Metropolitan Area (KMA) had a 2001 population of 579,000; Portmore a population of 156,000 and Montego Bay a population of 96,000, prepare proportional circles to illustrate the relative size of the population for each urban center.

The square root of the population values are as follows:

If the maximum circle size is set at 2cm in diameter (to represent the largest population) then the other circle sizes can be computed as follows:

= 2 cm *

= 2 * 0.5189

= 1.03 cm

Location Population - 2001 Data Value

(Sq Root) Symbol Size

KMA 579,000 760.9 2.00 cm (given)

Portmore 156,000 394.9 ?

Montego Bay 96,000 309.8 ?


The computed symbol size of 1.03 cm means that the proportional circle for Portmore will be approximately 1cm in diameter. Similarly, the diameter of the circle for Montego Bay was calculated at 0.8 cm or 8 millimeters in diameter.

The final two steps involve positioning the symbols on the map and preparing the Legend for the symbols as explained below:

Draw the symbol for each data value and position it inside the boundaries of the region to which the values refer. It should be noted that with proportional symbols, there is always the danger that very large symbols may obscure smaller ones on the map. It is therefore important to select the scale of the symbols carefully and to use equal care to position the symbols on the map.

Prepare the Legend for the map by creating a scale of symbols from three or four round numbers to represent the top middle and bottom values for the legend. These can then be mapped on a linear scale with the diameter of each proportional circle positioned perpendicular to the horizontal axis of the scale line. By drawing an oblique line to connect the ends of each perpendicular, the diameter of intermediate circles can be deduced. The slope of this line will depend on how big the maximum symbol is. (See Fig. 3)

Fig.3 Legend for Proportional Circle Diagram

NOTE: It does not matter if the symbol size computed is used

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to represent the radius or the diameter of the circle, the side of a square or the side for a triangle. As long as the measurement is applied consistently to all symbols, they will be in proper proportion.

A vertical line drawn from any point along the horizontal scale line to the oblique line will give the diameter of any circle and the population value it represents can then be deduced.

While the square root is used to calculate symbol sizes for the legend, it should be noted that all labels in the legend should reflect the

original data values.

See Table 2 in the Appendix for symbol size of proportional circles for depicting Jamaica’s population distribution by parish.

CHOROPLETH MAP

Choropleth maps utilize patterns or shades of varying intensity to depict average values for designated areas. These designated areas may represent geographic areas or arbitrarily defined administrative units. Population density is best depicted by the use of a choropleth map. Choropleth maps

used to depict population density illustrate the average densities per unit area.

To produce a population density map, the densities for each geographic unit must first be calculated. The densities are then grouped into classes. The number of classes will vary depending on the number of observations, but typically, maps are designed with between four (4) to six (6) classes to facilitate ease of interpretation.

Each class is assigned a symbol, tone or colour that increases in intensity from lighter to darker to reflect successively higher densities. An example of a population density map is shown in Fig. 4.

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The density map of Montego Bay reveals a concentric pattern of population density as distance increases from the Central Business District located on the west coast (Montego Bay Central). Densities increase from between 5 and 20 persons per hectare in communities like Montego Bay Central, Red Hills/Paradise and Brandon Hill to highs of between 51 and 80 persons per hectare in communities such as Flankers, Glendevon, Rosemont, Catherine Mount and Mount Salem. After peaking, the densities decline fairly steadily outwards towards the edge of the urban fence reaching lows of less than 5 persons per hectare in communities such as Ironshore, Coral Gardens, Half Moon, Sign, Irvin, Fairfield and Freeport2.

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Fig. 4. Population Density of Montego Bay, 2001


2 To view population estimates; country area, and population densities for different coun-tries and geographic regions, visit the US Census Bureau’s International Data Base web-site at www.census.gov/ipe/www/idb/tables.html.


The population structure of a country or place describes the composition or make-up of that population in terms of age and sex. Population structure is best shown by use of a population pyramid. Population pyramids are diagrams that graphically display a population’s age and sex composition (See Fig. 5). They are made by putting two horizontal bar graphs (one for males, one for females) side by side. The male population is usually represented on the left of a central vertical axis and the female on the right. Each bar represents a different age group and the number of males or females in each age group is indicated by the length of the bar from the central axis. Ages may be represented in single years or grouped into five-year, ten-year or other combinations as desired. The youngest population is depicted at the base of the pyramid and the oldest at the apex. Pyramids may be constructed using either absolute numbers or percentage values. Percentage values (that express the number of males or females within each age group as a percentage of the total male or female population) have the advantage of facilitating realistic comparisons in the age sex variations among countries or regions.

Population pyramids are used to determine the proportion of a population that is of a particular gender and age. Age-sex pyramids constructed for different years or different locations may be superimposed to show changes in the population structure over time or to compare population differences between places.

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POPULATION STRUCTURE

Guidelines for making Density Maps

• Use four (4) or five (5) density classes.

• Classes should not overlap. This means that a set of population figures appearing in one class should not appear in another, (e.g. 0-50, 50-100: The correct class break should be 0-50, 51-100).

• To more clearly depict the change in density between areas, it is best to use one colour or shading and increase or decrease the intensity of this colour/shading.


Fig. 5: 2001 Population Pyramid for St James, JAMAICA

Interpretation of the Age-Sex Structure of St James:

The age structure of the population of St. James illustrates a typical broad based pyramid depicting high birth rates of the past and a population that remains largely youthful. The reduction observed in the population of the 0-4 age group, is a reflection of the impact of fertility controls.

The pyramid displays a bulge in age groups 20-49, depicting a large proportion of the population in the working age-groups. This pattern may be due partly to the influx of migrant workers from other parishes in search of employment opportunities in St James.

The larger numbers of females observed in the young adult population is most likely the result of a greater influx of female migrants from other parishes.

Sex selective migration is typical among young adults in developing

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countries the search for employment and educational opportunities act as major push and pull factors. When the migrant flow is dominated by one sex, distortions typically result in the age sex profile of both the sending and receiving territory. In Jamaica, (like elsewhere in the Caribbean) although females dominate the flow of out migrants, current age sex pyramids do not reflect major gender imbalances because no major outflows have occurred since the 1980s.

The narrowing of the pyramid as it approaches the apex is predominantly a reflection of the impact of mortality in the older age groups. There is however a difference between the number of males and females that survive beyond age 75 and this is due largely to the longer life expectancy of females than males in the population.

TYPES OF POPULATION PYRAMIDS

Although population pyramids differ from country to country, there are three basic types of population pyramids that can be identified, namely the Expansive, the Constrictive and the Stationary pyramids. The shape of each is influenced primarily by levels of fertility in the population but is also affected by trends in mortality and migration.

1. The Expansive Population Pyramid:

Expansive population pyramids are pyramids that depict a broad base that tapers towards the apex. They reflect large proportions of people in the younger age groups and a significantly smaller proportion in the older ages. The steady upward narrowing of the pyramid reveals that more people die with increasing age and is indicative of low life expectancies.

Expansive pyramids are usually found in populations with high birth rates, high death rates and short life expectancy. The age-sex distributions of Latin American and many Third World countries tend to display expansive population pyramids.

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This pyramid of the Philippines shows a triangle-shaped pyramid and reflects a high population growth rate of about 2.1 percent annually.

2. The Constrictive Population Pyramid

The constrictive pyramid is characterized by low birth rates and slower population growth. The base of the pyramid narrows reflecting lower numbers or percentages of population in the younger age categories and the largest proportion of the population are found in the economically active age groups.

Expansive Population Pyramid

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Source: US Census Bureau Database


Constrictive (Slow Growth) Population Pyramid

Constrictive pyramids are typical of the populations of the United States

3. The Stationary Population Pyramid

Stationary or near-stationary population pyramids display

somewhat equal population numbers or percentages for almost

all age groups although the population tapers in the oldest age

groups. The relatively stationary age categories is the result of

relatively low but constant fertility and mortality rates, and a

high quality of life that enables more persons to live to older

ages.

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Stationary (Zero Growth) Population Pyramid

The age-sex distributions of some European countries and

particularly countries of the Scandinavian region are depicted by

stationary population pyramids.

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Guidelines for Interpreting a Population Pyramid:

• Observe the date and place, (country, city or group) that the pyramid represents

• Comment on the general shape of the pyramid

• Note the proportions of male and female population in the various age groups

• Relate patterns identified to levels of fertility, mortality and/or migration in the population.




SETTLEMENT

A settlement is a general term used for a permanent or temporary community in which people live. A settlement may range in size from a single building to a large number of dwellings grouped together to form an urban or rural community. The term is used to describe villages, towns and cities of varying sizes and shapes.

Several factors impact on settlements as they evolve over time and these factors combine to determine the shape or morphology of the settlement. The physical geography of an area is one of the main influences in the location of settlements and how different types of settlements evolve over time. However environmental and cultural factors also influence settlement morphology. (See Table 1)

Settlement patterns are usually described in terms of their geometry. Settlements may develop in a regular, evenly spaced pattern; may be clustered together with little space between them, or they may have a random pattern in which the location of one building bears no obvious relationship to the location of the next. Listed below are the most common types of settlement patterns.

Isolated

This refers to a settlement pattern characterized by one or a few individual buildings located in an area of extreme physical difficulty where the natural resources are insufficient to maintain more than a few inhabitants.

Dispersed

This type of settlement is characterized by a scatter of individual farms and houses across a wide area. Either no nucleation is present or clusters of dwellings are so small that at most, they consist of two or three buildings grouped together to form a hamlet. Each farm or hamlet may then be separated from the next by several kilometers of open space or farmland. Dispersed settlements are normally found in highland or rugged terrain and in areas with poor soils, but may also be linked to prevailing cultural factors.

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Nucleated

Nucleated settlements are formed where dwellings and buildings form a compact cluster around a central organizational point such as a central market, a major cross road, near centers of industry and employment or adjacent to a bay or mouth of a river. Settlements may also cluster together because of economic, social or defense reasons. Most towns or villages that originated as nucleated settlements have a tendency to loose their compact pattern over time as the outward growth of the settlement give rise to a looser knit pattern.

Linear

Linear settlements are formed where buildings are strung out along a main line of communication or along a river valley.

Linear settlements have been found clustered along rivers, creeks and streams, or along migration routes, railroads and highways.

Radial

A radial settlement pattern results when there is a convergence of route ways at a node near the center of a settlement. The resulting settlement growth radiates outwards in concentric bands along the route ways to form a cobweb-like pattern.

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18

Notes:

1. Relationship between Settlements of Different Sizes

The relationship between settlements of different sizes can be examined statistically using the Rank Size Rule. According to the rank size rule, the size of a settlement is inversely proportional to its rank. This means that, where all settlements are rank-ordered from largest to smallest (in terms of population); the second largest settlement should be half the size of the largest settlement and the third largest settlement should be one third the size of the largest etc. The rank-size rule does not hold true in many countries where dominant primate cities have emerged as the largest city. Primate cities have populations that are far larger than any other town.

2. Distribution and Spacing of Settlements

The study of the spacing between settlements is conducted using a technique known as Nearest Neighbour Analysis. This is a technique in which the observed spacing between settlements is obtained from an actual settlement pattern and is compared with the expected spacing in a theoretical random pattern.

In nearest neighbour analysis, the straight line distance from each settlement to its nearest neighbour is measured and this is divided by the total number of settlements to give the observed mean distance between nearest neighbours. This observed mean is then compared with the average distance expected if the pattern were randomly distributed (the expected mean). The value of the expected mean is derived from the density of the settlements found in the area being studied.

The value derived from the comparison of the observed and expected means ranges from 0.00 for a totally clustered pattern, through 1.00 representing a random distribution, to a maximum value of 2.15, which is indicative of a completely regular pattern.


FACTORS THAT INFLUENCE WHERE PEOPLE LIVE

Table 1

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Factors Sparsely Populated

Areas

Densely Populated

Areas

Physical ● Rugged mountains and terrain e.g. the Blue Mountains and the Cockpit Country.

● Flat, low lands of Plains and valleys e.g. The Queen of Spain Valley in Montego Bay and the Liguanea Plain in Kingston and St. Andrew.

Climate & Vegetation ● Areas receiving very low annual rainfall (the Sahara Desert)

● Very hot or very cold areas susceptible to natural disasters.

● Forested areas such as the coniferous forests of Northern Eurasia and Northern Canada and the rainforests of the tropics.

● Areas where the rainfall is reliable and evenly distributed throughout the year; where no temperature extremes exist and where there is a lengthy growing season.

● Places with seasonal rainfall and sufficient sunshine to attract tourists.

●Areas of grassland tend to have higher population densities than places with dense forest or desert.

Soils ● The leached soils of the tropical rain forests (e.g. the Amazon Basin)

● Areas characterized by infertile soils e.g. deserts and swamp areas.

● Areas of deep humus-filled soils and especially areas with river-deposited silt.

Water Supplies ● Areas lacking a permanent supply of clean, fresh water due to insufficient or irregular rainfall or a lack of money and technology to build reservoirs and wells or to lay pipelines (e.g. Ethiopia).

● Where rainfall is evenly distributed and where there is available potable water.


Factors Sparsely Populated

Areas

Densely Populated

Areas

Disease and Pests

● Areas where insect pests and other diseases are endemic. E.g. typhoid in Westmoreland.

● Areas that are relatively disease and pest free.

Resources

● Areas devoid of minerals and other easily obtainable sources of energy.

● Areas that have large mineral deposits and/or

energy supplies e.g. oil in Trinidad.

Communications & Transportation

● Areas where it is diffi-cult to construct and main-tain transport systems e.g. the hilly terrain of the Blue Mountains, Jamaica.

● Areas where the terrain makes it easier to con-struct roads and maintain good communication net-works.

Socio-Economic

● Areas with less devel-oped subsistence-type economies usually need large areas of land to sup-port relatively few people.

● Places that provide good social services.

●Areas with developed commerce and industry to support employment.

Crime and

Violence

● Areas where there is conflict and political ten-sion may force people to migrate.

● Areas where there are hardly any conflicts will attract people to settle e.g. districts in Mandeville, Jamaica.

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Table 1 cont’d


DEVELOPMENT AND DISPARITIES IN DEVELOPMENT

THE LABOUR FORCE

Unemployment Level

The Unemployment Level or extent of unemployment is an expression of the number of unemployed persons identified within the work force.

The Unemployment Rate (used to indicate the level of unemployment in an economy) is the percentage of the total labour force that is unemployed. The unemployment rate is used for comparing unemployment levels among different countries because it expresses each country’s unemployment in standard percentage terms.

In Jamaica, the Unemployed Labour Force consists of all persons without a job who are actively looking for work and those who, although not actively looking for work, want work and are available for work (during a specified reference week).

The Employed Labour Force consists of all persons who are working (i.e. engaged in paid or unpaid economic activities), and those who have jobs but are not actively working (e.g. because of illness or absence on leave).

The Total Labour Force is the sum of all persons in the Employed Labour Force and the Unemployed Labour Force.

N.B. In most countries unemployment levels rarely fall below 3% since at all times there are people who are occasionally out of work due to job changes, residence relocation, or ill health.

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FORMULA

Unemployment Rate = x 100

EXAMPLE

Jamaican Labour Force statistics published in October 2008 showed that there were 134,600 unemployed persons within a Labour Force of 1,302,400. The unemployment rate would be computed thus:

The level of unemployment within a country is influenced by factors such as:

• The size and education of the labour force.

• The rate at which persons enter and leave the labour force: Persons enter when they graduate from school, return to the country from overseas, decide to start working again, etc. Persons leave the labour force when they stop working to go to school, migrate to another country, for reasons of health or death, etc.

• Technological changes: New technology usually affects the need for workers by requiring new skills to replace old ones. In most cases of technological change fewer workers are required to do the job, and so the number of unemployed will increase.

• High interest rates, which tend to discourage spending and encourage savings. A high interest rate regime limits the amount of money available for creating new businesses, which in turn affects how many new jobs are created.

• The regulatory framework: Investors will create more jobs in environments where there are many tax concessions and minimum interference by government and other entities e.g. labour unions.

• Social intervention: Temporary jobs are sometimes created to employ (mostly unskilled) workers to do socially beneficial work (e.g. road cleaning and beautification projects).

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Force Labour Total

Force Labour Unemployed


The Unemployment Rate = x 100

= 0.1033 x 100

= 10.3%

INTERPRETATION

An unemployment rate of 10.3% suggests that for every 100 persons in the Labour Force there were approximately 10 unemployed persons. The other 90 persons would be considered as employed, and so the employment rate would be approximately 90%.

The unemployment rate is important as a gauge of joblessness and is one of the indicators that is used to determine the economic health of a country. It is usually analyzed by industry or occupation to get an indication of those sectors in the economy that are contracting (losing jobs) over time.

Unemployment rates are most comparable when the rate for a given period is compared with that of a corresponding period (that is, when like periods are compared e.g. June quarter 2008 compared with June quarter 2009). When comparing consecutive periods, (e.g. June Quarter with September Quarter), one must be careful that the changes observed in the unemployment figures are not the result of seasonal patterns in employment. For example, the annual ending of the school year usually produces a spike in unemployment among school leavers.

1,302,400

134,600

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PER CAPITA INCOME

Per Capita Income is the amount of money “allocated” to each citizen of a country when the total income is divided by the total population.

The Total income of a country is represented by the Gross Domestic Product (GDP), which is regarded as the single, most widely used indicator of economic performance.

The GDP of an economy/country is the total unduplicated dollar value of all the goods and services produced within its geographic boundaries/borders within a specified period of time (usually one year).

(The term unduplicated dollar value highlights the fact that there should be no “double counting” or “multiple counting” in calculating GDP).

Per capita GDP is the GDP per person. It serves as an indicator of a country's living standards because it estimates the average amount of money required for each person to cover basic living expenses for one year.

The 2007 UN data listing of country GDP per capita placed Liechtenstein (in central Europe) at the top with US$118,040 and Burundi (in central Africa) at the bottom (position No. 237) with US$118. Barbados, Jamaica and Haiti were placed at positions 71 (US$12,687), 120 (US$4,147) and 205 (US$612), respectively. (See Table 1).

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FORMULA

GDP per capita =

EXAMPLE

If the GDP of country ‘A’ was US$7.0 billion in 2006, and the total population was 1,675,400 in the same year, then the per capita GDP would be:

= US$4,178.11

1,675,400

00,000US$7,000,0

Per Capita GDP at Current Prices (US$)

2007

(Ranking of selected countries)

Rank Country US$

1 Liechtenstein 118,040

66 Trinidad and Tobago 15,457

70 Antigua and Barbuda 12,799

71 Barbados 12,687

88 Montserrat 8,149

105 Saint Lucia 5,810

112 Grenada 5,081

113 Dominica 4,838

117 Suriname 4,463

118 Belize 4,429

120 Jamaica 4,147

172 Guyana 1,435

205 Haiti 612

237 Burundi 118

Source: United Nations Statistics Division

25

Table 1

Gross Domestic Product

Total Population


INTERPRETATION

In 2006, the average income “allocated” to each citizen of country ‘A’ was US $4,178.11. This is a dollar value in theory only, since not all citizens of a country are able to contribute to income generation and, within a country there are citizens who will require (and utilize) either more or less than the “allocated” per capita amount.

Per capita figures are generally accepted as reliable indicators of the relative prosperity of a country. However, when per capita estimates are compared it is necessary to consider factors such as:

• The populations of the countries: Since it is assumed that more populous countries should generate more income, then countries with small populations and high incomes indicate economic health. Countries with very large numbers of foreign workers tend to have high per capita GDP because the foreign workers (although contributing significantly to income generation) are excluded from the total population in the calculations.

• The proportion of the country’s income which belongs to its citizens: Foreign-owned enterprises generate income within a country, but the owners are citizens of other countries. Remember it is the income generated within the country which is used in the calculation of the GDP.

• The extent to which the economic activities within the country are documented. The values of economic activities such as informal trading, barter transactions (i.e. trading without money) and subsistence/ backyard farming may not be officially recorded.

• The basic needs of the country’s citizens. The standard of living of residents in a richer country may be much higher in monetary terms than that of residents in a poorer country, but this comparison does not reveal that a person in a poorer country may require far less to survive and may, in relative terms, enjoy an equally good quality of life.

26


INFLATION

Purchasing Power

Purchasing Power is the value of a currency expressed in terms of the quantity of goods and services that one unit of money can buy. The purchasing power of money is very closely linked to levels of inflation (i.e. the rise in prices of goods and services). Purchasing power falls when there is inflation because inflation decreases the quantity of goods and services one is able to purchase with the same amount of money.

For example, if last year one dollar could buy two units of a commodity, and this year one dollar can buy only one unit of the same commodity (due to inflation), then the purchasing power (at the current value) is now 50% of what it was last year. This is because the dollar can only buy half the number of commodities it was able buy last year.

Changes in prices for goods and services are indicated by the Consumer Price Index (CPI), which is a measure of how the cost of a representative “basket” of consumer goods and services has changed in comparison with the cost at a specified time in the past (i.e. the base period). Changes in the CPI are used to assess price changes and associated purchasing power of consumers.

Other inflation-related factors which affect purchasing power include:

• An increase in the demand for a particular good or service: There may be a rush by persons to obtain a new type of vehicle, clothing, appliance, etc. The sellers of these items will “cash in” on the increased demand by raising the price of the items which effectively reduces the purchasing power of the consumer until the demand goes back down.

• An increase in the average disposable income: If there are wage increases or windfalls but no corresponding

27


increase in the amount of goods and services available, then people will be willing to pay more to get these goods/services. Note that there is no real shortage in this case; only that the good/service will go to the highest bidder due to the artificial shortage created by the surplus money available.

• Unstable exchange rate: When most of the goods/services consumed within a country are imported, they will have to be purchased by an internationally accepted trading currency (e.g. the US dollar). If the local currency is converted to the trading currency at ever increasing rates, then the local prices of these goods/services will be adjusted to recover the cost of acquiring them. The consequence will be a reduction in purchasing power due to increased purchase prices for goods and services.

FORMULA

Purchasing Power is indicated by the rate of inflation, which is given by:

x 100

Where K0 = current average price index (e.g. CPI)

K-1 = previous average price index

EXAMPLE

The All Jamaica ‘All Divisions’ CPI was 116.8 in December 2007, and. 136.5 in December 2008. How was the purchasing power affected between December 2007 and December 2008?

The rate of inflation during the period Dec 2007 to Dec 2008 is given by:

x 100

= 0.1687 x 100

= 16.87%

1-

1-0K

KK −

116.8

116.8- 136.5

28


INTERPRETATION

An inflation rate of 16.87 per cent indicates a reduction in purchasing power of money since an additional 16.87 cents is required for every dollar in December 2008 to purchase the same quantity of goods and services purchased in December 2007.

LIFE EXPECTANCY

Life Expectancy or “average life span” is the average number of additional years that a person can expect to live if current mortality rates prevail for the rest of his/her life.

Life Expectancy at Birth (years) is the average number of years that a newborn is expected to live if mortality rates at the time of birth continue to apply throughout his/her life*.

Life expectancy is usually given for each year of life beginning at birth, and is dependent on factors such as health care, gender, race, poverty, occupation, geography, drug abuse, and traditional beliefs/practices. Life expectancy, therefore, does not only reflect the quality of healthcare of a country, but may also serve to guide governments in the implementation of policies and facilities for promoting human health and development.

FORMULA

The estimation of life expectancy at birth is an output of a Life Table which is a set of statistical tables that shows the death rate, the probability of dying and the life expectancy at any given age. The calculations are based on Probability Theory, which is outside the scope of this handbook.

EXAMPLE

According to data compiled by the United Nations Children’s Fund for 192 countries in 2007, life expectancy at birth ranged from 83 years in Japan to 40 years in Swaziland (southern Africa).

29


Table 2 shows that among the CARICOM countries, Barbados had the highest life expectancy at birth of 77 years and Haiti had the lowest at 61 years.

INTERPRETATION

According to Table 2, a child born in Barbados in 2007 is expected to live until the year 2084 and die naturally at age 77; while a child born in Haiti is expected to die naturally at age 61 years in 2068.

Many of the countries with low life expectancies suffer from high rates of HIV/AIDS and other infections, as well as frequent and extended periods of food shortages. Countries with high infant mortality rates (i.e. deaths among infants under 1 year of age) will also have a lower life expectancy at birth.

Table 2

Life Expectancy at Birth, 2007

Rank Country Years

1 Japan 83.0

36 Barbados 77.0

40 Belize 76.0

57 Saint Lucia 74.0

83 Jamaica 72.0

102 Suriname 70.0

104 Trinidad and Tobago 70.0

108 Grenada 69.0

124 Guyana 66.0

142 Haiti 61.0

192 Swaziland 40.0

Source: United Nations Children's Fund


30


31

DEPENDENCY RATIOS

Total Dependency Ratio is the proportion of persons in the “dependent” ages (generally under age 15 and over age 64) to those in the “economically productive” age group (i.e. 15-64 years) in a population.

Child (or Youth) Dependency Ratio is the proportion of children 0-14 years to those in the “economically productive” age group.

Aged Dependency Ratio is the proportion of adults aged 65 years and over to those in the “economically productive” age group.

Age dependency ratios serve as measures of the age structure of a population. A high child dependency ratio for example, indicates a youthful population, while a high aged dependency ratio indicates an ageing population. These ratios also bear economic significance for the economically productive who must provide for dependents (either by earning incomes or paying taxes) and for governments that must implement policies and programmes to address the social and welfare needs of the dependent population. A developing country with a high child dependency ratio (e.g. Uganda: 104%) would need to invest more in education and nutrition, while a developed country with a high aged dependency ratio (e.g. Japan: 35%) would need to concentrate more on healthcare and social security for the elderly.

N.B. Dependency ratios fail to accurately represent economic dependency at the national level since there are many persons aged 15-64 who are economically dependent who are counted among the productive population (e.g. the unemployed, disabled and mentally ill). The ratios also fail to reflect the fact that many adults over age 64 remain economically productive, and that many children under age 15 are in reality working, despite the fact that it is illegal.


1,707,266

754,427

1,707,266

225,549

FORMULA

Total Dependency Ratio = x 100

Where P0-14 = Population age 0-14 years

P15-64 = Population age 15-64 years

P65+ = Population age 65 years and over

EXAMPLE

According to STATIN’s Demographic Statistics 2008 report, the age distribution of Jamaica’s mid-year population in 2008 was as follows:

The Total Dependency Ratio = x 100

= x 100

= .57 x 100 = 57.0%

The Child Dependency Ratio = x 100

= 0.44 x 100 = 44.0%

The Aged Dependency Ratio = x 100

= 0.13 x 100 = 13.0%

Age Group Population

0-14 yrs 754,427

15-64 yrs 1,707,266

65+ yrs 225,549

All ages 2,687,242

32

64-15

6514-0P

P P ++

1,707,266

754,427

1,707,266

225,549

1,707,266

979,976

754,427 + 225,549

1,707,266


N.B. In demographic analysis, the Mid Year Population is the most convenient approximation of the population at risk and is therefore used in the denominator of the formulae for calculating most demographic rates. It represents the average number of persons present during the year and is calculated as the mean or average of the population taken at the start and end of the year. Where the mid year population is not available, the End of Year Population is used.

INTERPRETATION

According to the 2008 population figures for Jamaica, there were 57 persons in the “dependent” age groups for every 100 persons in the economically productive population (i.e. ages 15-64 yrs). The higher the ratio, is the greater the burden faced by the population of working age to support the dependent. The data calculated above reveal that, of the 57 dependents, 44 were in the youth category and 13 were in the aged category. This would suggest that policy planners would need to look seriously at developing and implementing youth-oriented programmes and facilities geared at the education and upbringing of the youth in society.

It may also be necessary to analyze what proportion of youth dependents continues to be dependent after age 15. A subsidiary programme to begin to address the social security and health needs of the elderly in the population should also be considered.

FERTILITY

The term fertility refers to the reproductive or child-bearing performance of a population and is based on the number of live births that occur in women of child bearing age (i.e. 15-49). It should not be confused with “fecundity”, which is the physiological ability of women to bear children.

The study of fertility is critical to understanding population growth and trends and for the planning and provision of social and welfare

33


services in a country. In order to measure fertility, it is necessary to have data on the number of births and the number of persons who are at risk of giving birth.

The major measures of fertility are as follows:

• The Crude Birth Rate is the simplest and most widely used measure of fertility. It is defined as the total number of live births (per thousand of population) in a given year. It requires the least amount of data for its calculation and facilitates quick comparisons of fertility between different populations. The rate is described as “crude” because the number of births is assessed in relation to the total population, which includes persons not at risk of bearing children i.e. children, men, and women who fall outside the child-bearing ages

• The General Fertility Rate (GFR) is the number of live births per 1,000 women ages 15-49 in a given year. This rate relates the number of live births in any given year to the female

Total Fertility Rates

2007


Rank Country Births per woman

1 Niger 7.2

55 Haiti 3.6

74 Belize 3.0

97 Jamaica 2.5

105 Suriname 2.4

110 Grenada 2.3

111 Guyana 2.3

120 Saint Lucia 2.2

159 Trinidad and Tobago 1.6

160 Barbados 1.5

192 Ukraine 1.2


Table 3

34


population who are at risk of giving birth. As such, the GFR addresses the primary weakness of the Crude Birth Rate.

It should be noted that the likelihood of a woman having live births during her reproductive life varies according to her age, with a gradual rise in fertility up to her twenties and thirties, followed by a rapid decline after age 35. It is therefore useful to examine fertility by age (as well as over time)

• The Age Specific Fertility Rate is the number of live births occurring to women of a particular age or age group. Many countries display a particular interest in births among teenage women as this is considered an area for national policy intervention. The Age-Specific Fertility Rate facilitates t h i s kind of analysis.

• The Total Fertility Rate (TFR) is an estimate of the total number of children that would be born per woman, assuming she lived to the end of her childbearing years and bore children according to current age specific fertility rates. Stated simply, the TFR is an estimate of the average number of children per woman. It can be derived by adding the age specific fertility rates, i.e. the fertility rates of each specific age or age group.

The TFR is a widely used indicator of fertility because it produces a single estimate of fertility for a population that is

based on the age specific fertility.

Globally, total fertility rates tend to range between one and eight children per woman. A TFR of two children per woman is considered the replacement rate for a population. Rates above two children indicate populations undergoing growth and whose median age is declining (i.e. getting younger). Higher rates may also indicate difficulties for families to feed and educate their children and for women to enter the labor force. Rates below two children indicate populations decreasing in size and or ageing.

Global fertility rates are generally declining and this trend is most

35


pronounced in industrialized countries (especially Western Europe) where populations are projected to decrease dramatically over the next 50 years.

Fertility rates tend to be higher in the less developed countries and lower in more developed countries. Some of the factors which affect fertility rates are:

• child mortality

• female life expectancy

• age of women at the first marriage/union

• accessibility, availability and use of contraception

• average number of years of education for women

• participation of women in labor the force.

Tracking trends in fertility and birth rates helps support effective social planning and the allocation of basic resources across generations. Sustained high fertility rates create large populations of young dependents, creating an increased demand for services to support the development and care of young children. These include, an adequate number of schools, and affordable child care. For example, during the Baby Boom period (1946-1964), unanticipated high fertility rates caught communities unprepared and without the school facilities needed to accommodate rapidly increasing numbers of school-age children. On the other hand, sustained low fertility rates can lead to aging populations which, in the long-run, may place a burden on the Social Security system.

36


FORMULA

General Fertility Rate = x 1000

EXAMPLE

There were 181,455 live births in country ‘A’ in 2005. The population of women ages 15-49 years was 1,675,433. The fertility rate was:

x 1000

= 0.11 x 1000

= 110.0

INTERPRETATION

The figures indicate that there were 110 births for every 1,000 women aged 15-49 years in country ‘A’ in 2005.

37

1,675,433

181,455

yrs49-15 age women of Number

births live of Number


1. UNESCO Education Sector, The Plurality of Literacy and its implications for Policies and Programs: Position Paper. Paris: United National Educational, Scientific and Cultural Organization, 2004, p. 13, citing an international expert meeting in June 2003 at UNESCO.

LITERACY

The United Nations Educational, Scientific and Cultural Organization (UNESCO) has drafted a definition of literacy as the "ability to identify, understand, interpret, create, communicate, compute and use printed and written materials associated with varying contexts. Literacy involves a continuum of learning in enabling individuals to achieve their goals, to develop their knowledge and potential, and to participate fully in their community and wider society."[1]

Most countries define Literacy in terms of the ability to read and write, with understanding, although others (e.g. Barbados) define literacy in terms of enrollment at school. School Enrollment alone however does not ensure the achievement of literacy.

The Adult literacy rate is defined as the proportion of the population aged 15 years and over who are literate.

Literacy rates can vary widely from place to pace and country to country. The literacy rate is usually related to levels of wealth and urbanization in a country, as well as the influence of social customs in a given culture (e.g. limiting the education of females, or children not attending school in order to work).

Literacy rates are important indicators of the state of a country’s human capital. This is because a literate population tends to achieve higher socio-economic status, and have the potential to enjoy better health, education and employment prospects. The combination of these factors will contribute to an increase in the wealth of a country and the well-being of its population.

There is no universal definition or standards for literacy. Information on literacy, while not a perfect measure of educational attainment, is probably the most easily available and valid for

international comparisons. Low levels of literacy (and education in

38


population Total

over and yrs15 age population Literate

general) can impede the economic development of a country in a rapidly changing, technology-driven world.

FORMULA

Adult Literacy Rate = x 100%

EXAMPLE

Data for country “A” showed that in 2007 there were 2,307,990 literate persons aged 15 years and over, and the average population was 2,625,700. The adult literacy rate in that year would have been

x 100

= 0.80 x 100

= 80%

Table 4

Adult Literacy Rates (15+ yrs)

(Selected countries)

Country Literacy rate (%)

Armenia 100.0

Belarus 100.0

Cuba 100.0

Estonia 100.0

Trinidad and Tobago 99.0

Suriname 90.0

Jamaica 86.0

Haiti 62.0

Burkina Faso 29.0

Afghanistan 28.0

Chad 26.0

Mali 23.0 * Data refer to the most recent year available during the period.


2000 - 2005*

39

2,758,124

2,203,741


INTERPRETATION

A literacy rate of 80 % indicates that there were about 80 literate persons aged 15 years and over out of every 100 persons in country “A” in 2007. If rate of at least 95% was expected, the target would not have been achieved. The results may therefore be an indication that the plans implemented to advance adult literacy were not as effective as planned or that the resources allocated were not adequate. The appropriate adjustments would then be made by providing the necessary resources and adjusting the time-line for achievement of the goal.

MORTALITY

Mortality refers to the occurrence of deaths in a population. The simplest measure of mortality is the Crude Death Rate, which measures the total number of deaths per thousand of population in a given year. Mortality rates of below 10 per 1,000 population are considered low, while rates above 20 per 1,000 are considered high.

The mortality rate is just one of the factors affecting population growth of a country or region. Other components of growth include fertility and net migration (i.e immigration – emigration). If the borders were closed (i.e. not allowing migration) and the mortality rate were higher than the fertility rate, then there would be an overall decrease in the population. Similarly, if the level of fertility exceeded the level of mortality, the outcome would be a net growth in population. Since it is unlikely that the borders will be closed, population decrease or increase is off-set by the effects of migration into, and/or out of the country or region.

Child Mortality rate is the number of deaths of children under five years of age in a given year per 1,000 live births in the same year.

Infant Mortality rate is the number of deaths of infants under one year of age in a given year per 1,000 live births in the same year.

40


A country’s mortality rate is considered a good indicator of the health status of its population. The mortality rate is influenced by one or more of the following factors:

• Age of the population

• Nutrition level

• Standard of diet and housing

• Access to clean drinking water

• Hygiene level

• Level of infectious diseases

• Conflicts and violent crime

• Amount and quality of health care

FORMULA

Infant Mortality Rate =

x 1000

EXAMPLE

There were 181,455 live births recorded in country ‘A’ in 2008, and 3,266 infants died before their first birth-date during that year. The infant mortality rate was:

x 1000

= 0.018 x 1000

= 18.0 per 1,000

INTERPRETATION

Country ‘A’ recorded an infant mortality rate of 18 (infant) deaths per thousand live births in 2008. When compared with the average rate of 8/000 for developed countries, country ‘A’ could be

181,455

3,266

yearsame the in births live Total

yearparticular a in one age under infants of deaths of No.

41


assessed to have ‘A’ relatively high rate of infant deaths. Not withstanding, this rate is well below those recorded for the least developed countries of the world, where infant mortality rates often exceed 20 deaths per thousand live births, rising to rates exceeding 100 infant deaths/000 in some countries in Africa.

Several factors could be responsible for the infant mortality rate recorded for Country A, including the quality of and access to health care, the socioeconomic wellbeing and public health conditions in the country and the age, nutrition and education of mothers. It would be necessary to analyze the leading causes of infant deaths in this county in order to determine the best strategies to be employed to reduce the current level of infant deaths.

It should be noted that infant mortality is often broken down into two components related to the timing of the infant deaths- namely:- neonatal deaths (or deaths to babies within 28 days after birth) and the post neonatal mortality (involving deaths of babies from 28 days to the end of the first year of life). The major causes of neonatal mortality are related to birth defects, premature birth, low birth weight and sudden infant death syndrome. In developed countries most infant mortality is related to these causes (neonatal mortality).

On the other hand, post neonatal mortality is most often the result of poor socio-economic and environmental conditions that result in infectious diseases such as pneumonia, gastroenteritis, tetanus and malaria. In many developing countries, these causes predominate and efforts at reducing post neonatal mortality must concentrate on improving nutrition and the quality of health care facilities.‡

42

‡ See article on Infant Mortality at http://www.deathreference.com/Me-Nu/Mortality-Infant.html


Table 5 is an extract of infant mortality rates for year 2007 for 195 countries provided by the UN Statistics Division. Highlighted are the CARICOM countries ranked in descending order (from worst -rank #46 to best -rank #144). Dominica recorded the lowest infant mortality rate (IMR), with 9 infant deaths per thousand live births while Jamaica is recorded as having an IMR of 26/‘000 and Trinidad and Tobago a rate of 31 per thousand live births. Haiti, with a rate of 57 infant deaths per thousand live births, is ranked as having the 46th highest infant mortality rate among the countries listed.§

Table 5

Infant Mortality Rates (0-1 year) per 1,000 live births

(2007)

Rank Country Deaths per 1,000

live births

1 Afghanistan 165

46 Haiti 57

62 Guyana 45

76 Trinidad and Tobago 31

85 Suriname 27

86 Jamaica 26

96 Belize 22

121 Grenada 15

124 Saint Lucia 14

137 Barbados 11

139 Antigua and Barbuda 10

144 Dominica 9

195 Singapore 2

Source: United Nations Statistics Division


§Infant mortality rates quoted from different sources for the same time period may not be

consistent since different methodologies are utilized in the estimation and calculation of these rates from country to country. Care should therefore be exercised in the use of these rates and data sources should be quoted.

43


NUTRITION

Nutritional status

Health and development are intricately interconnected because meeting the primary health care needs and the nutritional requirements of a population are fundamental to the achievement of sustainable development. The nutritional status of a population is dependent primarily on the following factors:-

Food availability – including quantity and quality of food available from local production and other sources

Access to Food Supply - determined by the capacity of the population to produce or purchase its food supply (a function of the purchasing power of money) and

Stability of Food Supply over time - relates to the population’s ability to obtain and maintain a steady flow of food over time which is facilitated by an efficient food storage and distribution system.

Health and nutritional status are commonly assessed by:- anthropometric measurement; biochemical analysis (typically of the blood and urine to determine micro nutrient deficiency) and clinical examination of patients with disorders associated with poor nutrition. Of these three methods, anthropometric measurement is considered the easiest and most practical for assessing the health and nutrition of a population. Anthropometric measurements cover the measurement of the size and proportions of the human body and typically include the measurement of body weight, height, age and sex. The indicators derived from these measurements are used to assess the extent and severity of nutritional deficiencies and serve as strong predictors of ill health, functional impairment and possible mortality, primarily among children.

Other factors contributing to the nutrition and health status of a population (especially among children under five years of age) include: living standards, water and sanitation, birth weight, birth interval, parity, sex of child, weaning practices and mother’s education.

44


Three anthropometric measurements are commonly used to assess nutritional status in children including:- Weight for Age, Height (length) for Age and Weight for Height. When these indicators are compared with a reference standard for healthy children, they reveal the magnitude, distribution and severity of nutritional problems in a country.

Weight for Age tells if a child is underweight, overweight or normal in weight

Height for Age tells if the child is the normal height for that age or is experiencing stunting, (a condition where the child has a low height for age). Stunting results from inadequate food supply and serves as a measure of poor nutrition in the past.

Weight for Height is a measure of current body mass. Low weight-for-height also termed “wasting” results from malnutrition or the effects of disease, while high weight-for-height is indicative of obesity.

Z-scores or Standard Deviation (SD) scores are used to describe how far a measurement is from the median (average) of the reference population and is indicative of the degree of severity of a nutritional deficiency.

Measurements that fall at, or below 3 standard deviations of the median or reference standard represent severe nutritional problems; those that fall between 2 and 3 standard deviations represent moderate nutritional problems and those falling between 1 and 2 standard deviations of the median value represent mild problems.

45


Table 6

Section of table of z-scores - Weight-for-age (Boys): Birth to 5 years

Source: http://www.who.int/childgrowth/standards/ft_wfa_boys_z_0_5.pdf

INTERPRETATION

Table 6 is a section of a weight for age table showing the z-scores for boys of specific age and weight. The first two columns of the table reflect age from birth (col. 1 shows age in years and months and col. 2 shows age in months only). The coloured/shaded section of the table contains weight data (in kilograms). The z-score is obtained by matching the given age with the given weight and then reading off the associated score in SDs along the top row.

EXAMPLE

According to the table, the median weight for a 3 year old boy is 14.3 kg. If a 3 year old boy was therefore weighed at 10 kg he would be considered underweight. His current weight for age of 10 kg gives him a z-score of -3 SD from the median weight. This is reflective of severe underweight for his age. Similarly, a 3 year old boy weighing 18 kg would have exceeded the median weight for his age by 3.7 kg. This would place him between 1 and 2 SD of the median weight which is indicative of moderate overweight.

46


Table 7 shows the equivalent information for girls at corresponding ages and weights.

At the level of the entire population, the information obtained from anthropometric indicators provides a basis for assessing the prevalence of unsatisfactory nutritional conditions.

In a normal population it is expected that approximately 2.3 per cent of the children will have z-scores of -2.00 (i.e. under-nutrition), and 2.3 per cent will have z-scores of +2.00 (i.e. over-nutrition)

In most countries, the prevalence of wasting or thinness (low weight for height) is usually below 5 percent (even in poor countries). Prevalence rates of 5-9 % are therefore considered high particularly because of the strong correlation between wasting and mortality. On the severity index, rates of 10-14% are regarded as serious while countries or regions with rates of 15 % and over are considered to have a critical problem.

Table 7

Section of table of z-scores - Weight-for-age (Girls): Birth to 5 years

Source: http://www.who.int/childgrowth/standards/ft_wfa_girls_z_0_5.pdf

47


48

Globally, variation in stunting (low height for age) is considerable, ranging from between 5% and 65% among less developed countries. Prevalence rates above 40% are considered as very high.

It should be noted that the nutritional status of children alone is not a sufficient measure of the nutritional status and food adequacy of a population since children under age 10 account for less than 20% of the population of developing countries as a whole and less than 11% of all countries in the developed world. Other indicators must be examined to establish the nature and extent of the nutritional status of a country’s population.



APPENDIX

SYMBOL SIZE OF PROPORTIONAL CIRCLES FOR DEPICTING

JAMAICA’S POPULATION DISTRIBUTION BY PARISH -2001

Table 2


PARISH POPULATION

2001 SQ. ROOT

SYMBOL SIZE

(Diameter (in cm ) of Circles by Parish: based on maximum diameter

of 2cm)

Kingston 96,052 309.9 0.8

St. Andrew 555,828 745.5 2.0

St. Thomas 91,604 302.6 0.8

Portland 80,205 283.2 0.7

St. Mary 111,466 333.8 0.9

St. Ann 166,762 408.3 1.0

Trelawny 73,066 270.3 0.7

St. James 175,127 418.4 1.1

Hanover 67,037 258.9 0.7

Westmoreland 138,948 372.7 0.1

St. Elizabeth 146,404 382.6 1.0

Manchester 185,801 431.0 1.2

Clarendon 237,024 486.8 1.3

St. Catherine 482,308 694.4 1.9

49


JAM

AIC

A:

Mid

Yea

r Po

pulation

by

Age

and

Sex

: 2

008

50

Table 3

Source: Demographic Statistics 2008, STATIN

(For

Con

stru

ctin

g Po

pula

tion

Pyr

amid

s an

d D

epen

denc

y R

atio

s)


JAM

AIC

A:

End

of

Yea

r Po

pulation

by

Age

and

Sex

: 1

988

51

JAM

AIC

A:

Mid

Yea

r Po

pulation

by

Age

and

Sex

: 1

998

Table 4

(For

Con

stru

ctin

g Po

pula

tion

Pyr

amid

s an

d D

epen

denc

y R

atio

s)



52

Table 5


JAM

AIC

A:

End

of

Yea

r Po

pulation

by

Age

and

Sex

: 1

988

(For

Con

stru

ctin

g Po

pula

tion

Pyr

amid

s an

d D

epen

denc

y R

atio

s)


Jamaica: Population and Area by Parish, 1988, 1998 and 2008

(for computing and comparing population densities by parish)

Parish Area

(Km2)

Population

1988

(mid year)

Population

1998

(mid year)

Population

2008

(mid year)

1 Kingston 21.8 101,260 97,692 93,812

2 St Andrew 430.7 546,740 555,207 571,104

3 St Thomas 742.8 85,400 90,148 94,066

4 Portland 814.0 76,900 79,598 82,088

5 St Mary 610.5 111,400 111,338 114,099

6 St Ann 1212.6 147,200 162,642 173,085

7 Trelawny 874.6 73,100 73,032 75,474

8 St James 594.9 151,600 169,958 184,062

9 Hanover 450.4 65,000 67,381 69,793

10 Westmore-

land 807.0 126,600 136,710 144,713

11 St Elizabeth 1212.4 144,200 147,253 150,834

12 Manchester 830.1 158,800 179,085 190,557

13 Clarendon 1196.3 214,400 231,883 246,049

14 St Catherine 1192.4 353,800 454,892 497,505

Table 6

53

geo cape handbook final

Documents

population density

population structure

types of population

dot distribution map

prior permission

choropleth map

cecelio avenue kingston

students handbook geography