• TABLE OF CONTENTS
HIDE
 Front Cover
 Title Page
 Acknowledgement
 Table of Contents
 Abbreviations
 Map of Sub-Saharan Africa
 Chapter 1: Introduction
 Chapter 2: Sources of data
 Chapter 3: Population distribution...
 Chapter 4: Literacy and educat...
 Chapter 5: Women in economic...
 Chapter 6: Marital status and living...
 Chapter 7: Fertility and the status...
 Chapter 8: Mortality and the status...
 Chapter 9: Conclusions: National...
 Appendix A: References
 Appendix B: Tables in the women...
 Appendix C: Population by age,...
 Back Cover














Group Title: WID ; 2
Title: Women of the world
CITATION THUMBNAILS PAGE IMAGE ZOOMABLE
Full Citation
STANDARD VIEW MARC VIEW
Permanent Link: http://ufdc.ufl.edu/UF00080503/00001
 Material Information
Title: Women of the world Sub-Saharan Africa
Series Title: WID
Physical Description: viii, 200 p. : col. ill., 1 col. map ; 28 cm.
Language: English
Creator: Newman, Jeanne S
United States -- Bureau of the Census
United States -- Agency for International Development. -- Office of Women in Development
Publisher: U.S. Dept. of Commerce, Bureau of Census
Place of Publication: Washington D.C
Publication Date: [1984]
 Subjects
Subject: Women -- Social conditions -- Statistics -- Africa, Sub-Saharan   ( lcsh )
Women -- Employment -- Statistics -- Africa, Sub-Saharan   ( lcsh )
Women -- Developing countries   ( lcsh )
Genre: federal government publication   ( marcgt )
bibliography   ( marcgt )
statistics   ( marcgt )
non-fiction   ( marcgt )
 Notes
Bibliography: Bibliography: p. 165-174.
Statement of Responsibility: by Jeanne S. Newman.
General Note: "Prepared under a Resources Support Services agreement with the Office of Women in Development, Bureau for Program and Policy Coordination, U.S. Agency for International Development."
General Note: "Issued August 1984."
Funding: Women in development (Washington, D.C) ;
 Record Information
Bibliographic ID: UF00080503
Volume ID: VID00001
Source Institution: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
Resource Identifier: aleph - 001292548
oclc - 11257057
notis - AGE3230

Table of Contents
    Front Cover
        Front Cover
    Title Page
        Page i
    Acknowledgement
        Page ii
    Table of Contents
        Page iii
        Page iv
        Page v
        Page vi
    Abbreviations
        Page vii
    Map of Sub-Saharan Africa
        Page viii
    Chapter 1: Introduction
        Page 1
        Page 2
        Page 3
        Page 4
        Page 5
        Page 6
    Chapter 2: Sources of data
        Page 7
        Page 8
        Page 9
        Page 10
        Page 11
        Page 12
        Page 13
        Page 14
    Chapter 3: Population distribution and change
        Page 15
        Page 16
        Page 17
        Page 18
        Page 19
        Page 20
        Page 21
        Page 22
        Page 23
        Page 24
        Page 25
        Page 26
        Page 27
        Page 28
        Page 29
        Page 30
        Page 31
        Page 32
        Page 33
        Page 34
        Page 35
        Page 36
        Page 37
        Page 38
        Page 39
        Page 40
        Page 41
        Page 42
        Page 43
        Page 44
        Page 45
        Page 46
        Page 47
        Page 48
        Page 49
        Page 50
    Chapter 4: Literacy and education
        Page 51
        Page 52
        Page 53
        Page 54
        Page 55
        Page 56
        Page 57
        Page 58
        Page 59
        Page 60
        Page 61
        Page 62
        Page 63
        Page 64
        Page 65
        Page 66
        Page 67
        Page 68
        Page 69
        Page 70
        Page 71
        Page 72
        Page 73
        Page 74
        Page 75
        Page 76
    Chapter 5: Women in economic activity
        Page 77
        Page 78
        Page 79
        Page 80
        Page 81
        Page 82
        Page 83
        Page 84
        Page 85
        Page 86
        Page 87
        Page 88
        Page 89
        Page 90
        Page 91
        Page 92
        Page 93
        Page 94
        Page 95
        Page 96
        Page 97
        Page 98
        Page 99
        Page 100
        Page 101
        Page 102
        Page 103
        Page 104
        Page 105
        Page 106
        Page 107
        Page 108
    Chapter 6: Marital status and living arrangements
        Page 109
        Page 110
        Page 111
        Page 112
        Page 113
        Page 114
        Page 115
        Page 116
        Page 117
        Page 118
        Page 119
        Page 120
        Page 121
        Page 122
        Page 123
        Page 124
        Page 125
        Page 126
        Page 127
        Page 128
        Page 129
        Page 130
        Page 131
        Page 132
    Chapter 7: Fertility and the status of women
        Page 133
        Page 134
        Page 135
        Page 136
        Page 137
        Page 138
        Page 139
        Page 140
        Page 141
        Page 142
        Page 143
        Page 144
        Page 145
        Page 146
    Chapter 8: Mortality and the status of women
        Page 147
        Page 148
        Page 149
        Page 150
        Page 151
        Page 152
        Page 153
        Page 154
        Page 155
        Page 156
        Page 157
        Page 158
        Page 159
        Page 160
    Chapter 9: Conclusions: National level data and the situation of women
        Page 161
        Page 162
        Page 163
        Page 164
    Appendix A: References
        Page 165
        Page 166
        Page 167
        Page 168
        Page 169
        Page 170
        Page 171
        Page 172
        Page 173
        Page 174
    Appendix B: Tables in the women in development database
        Page 175
        Page 176
    Appendix C: Population by age, sex, and rural/urban residence
        Page 177
        Page 178
        Page 179
        Page 180
        Page 181
        Page 182
        Page 183
        Page 184
        Page 185
        Page 186
        Page 187
        Page 188
        Page 189
        Page 190
        Page 191
        Page 192
        Page 193
        Page 194
        Page 195
        Page 196
        Page 197
        Page 198
        Page 199
        Page 200
    Back Cover
        Page 201
Full Text

WID-2


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U.S. Department of Commerce
BUREAU OF THE CENSUS


U.S. Agency for International Development
OFFICE OF WOMEN IN DEVELOPMENT


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WID-2


Sub-Saharan

Africa

byJeanne S. Newman








This report was prepared under a Resources
Support Services Agreement with the Office of
Women in Development, Bureau for Program
and Policy Coordination, U.S. Agency
for International Development.


Issued August 1984

O-F. %C


94TES O0 '

U.S. Department of Commerce
Malcolm Baldrige, Secretary
Clarence J. Brown, Deputy Secretary
Sidney Jones, Under Secretary for
Economic Affairs
BUREAU OF THE CENSUS
John G. Keane,
Director














BUREAU OF THE CENSUS
C.L. Kincannon, Deputy Director
Robert O. Bartram, Assistant Director for
International Programs

CENTER FOR INTERNATIONAL RESEARCH
Samuel Baum, Chief







Acknowledgments


This report on Sub-Saharan Africa was prepared under con-
tract with the U.S. Bureau of the Census. It is one of four regional
handbooks in the Women of the World series prepared under
a Resources Support Services Agreement with the Office of
Women in Development, Bureau for Program and Policy Coor-
dination, U.S. Agency for International Development,Sarah
Tinsley, Director. Thanks are due to present and former staff
members of the Agency for International Development for their
contributions to the various stages of the Census Bureau's
Women In Development project. In particular, Jane Jaquette and
Paula O. Goddard, formerly of the Office of Women in Develop-
ment, and Lois Godiksen, formerly of the Economic and Social
Data Services, provided useful guidance in establishing the Cen-
sus Bureau's Women in Development Data Base, upon which
these handbooks are based. Jean Ellickson and John Hourihan
of the Office of Women in Development and Annette
Binnendijk of the Economic and Social Data Services provided
support at subsequent stages of the project.
Within the Bureau of the Census, Ellen Jamison, Staff
Assistant to the Chief, Center for International Research,
prepared the overall outline for the content and format of the
world handbook series, monitored the contracts, prepared
chapter 2, and served as reviewer and coordinator of the publica-
tion preparation activities. For this report on Sub-Saharan Africa,
valuable assistance was provided by other staff members of the
Center for International Research: Kevin G. Kinsella assisted with
countless details to ensure the accuracy of the tables and charts;


Peter 0. Way offered useful guidance on the material to be in-
cluded, provided supervisory assistance in the verification of
tables, and prepared appendix C; Eduardo E. Arriaga and
Sylvia D. Quick provided useful review comments; Joseph R.
Cooper computerized the graphics; John R. Gibson, Vera V.
Harris-Bourne, Eleanor M. Matthews, and Margaret A. Squires
provided statistical assistance in verifying the tables; and
Donna M. Dove and Janet M. Sales took charge of the typing,
with the assistance of Jacqueline R. Harrison and Carolyn King.
All demographic analysts in the Center for International Research
were involved in the compilation and evaluation of statistics for
the Women In Development Data Base upon which this hand-
book is based. The map was prepared in the Geography Divi-
sion under the direction of Betty L. Adamek in cooperation with
Geography Branch, Data Preparation Division. Editorial services
were provided by Gail R. Farren and artwork was prepared under
the supervision of Nicholas Preftakes, Publication Services
Division.
The author extends a special word of appreciation to Mary
Tadesse and her colleagues at the African Training and Research
Center for Women, Economic Commission for Africa, Addis
Ababa, and particularly to Nancy Halfkin, for hours spent in
stimulating discussion and for access to the Center's documents
library.


Library of Congress Card Number 84-601086


For Sale by Data User Services Division, Customer Services (Publications), Bureau of the Census, Washington, D.C. 20233, or any U.S. Department
of Commerce district office. Postage stamps not acceptable; currency submitted at sender's risk. Remittances from foreign countries must be by
international money order or by a draft on a U.S. bank. $5.50 per copy.





Women of the World





Contents







Page

Abbreviations Used in This Report ................................ v

M ap .. . . . . ....... .. .. . . .. .. ... V Ill

Chapter 1. Introduction ......................................... 1

Chapter 2. Sources of Data ...................................... 7

Tables

2.1. Number of Tables in WID Data Base, by Country and Category .................. 10
2.2. Availability and Recency of Statistics, by Country and Subject ................... 12

Chapter 3. Population Distribution and Change ........................ 15

Figures

3.1. Sub-Saharan Africa: Estimated and Projected Population Size and Components
of Change: 1960 to 2025 .................................. .......... 21
3.2. Estimated and Projected Population: 1960, 1970, and 1985 ................... 22
3.3. Population Distribution of Sub-Saharan African Countries: 1983 .................. 24
3.4. Sex Ratios of the Total Population ....................................... 25
3.5. Percent of All Women in Selected Age Groups ............................... 26
3.6. Percent of Women Living in Urban Areas, Latest Two Censuses .................. 27
3.7. Female/Male Ratio of Percent Urban ...................................... 29
3.8. Sex Ratio of the Population in Two Age Groups, by Rural/Urban Residence ......... 30
3.9. In-Movers to Province of Current Residence, by Sex .......................... 31

Tables

3.1. Total Population, by Sex, Sex Ratio, and Percent Female ................ ...... 32
3.2. Total Population: 1960 to 1985 ................................... ... 34
3.3. Percent of Female Population in Selected Age Groups ................. ......... 36
3.4. Percent of Male Population in Selected Age Groups ........................... 38
3.5. Sex Ratios of Rural Population in Selected Age Groups ................. ...... 40
3.6. Sex Ratios of Urban Population in Selected Age Groups ........................ 41
3.7. Percent of Population Residing in Urban Areas, by Sex, and Female/Male
Ratio of Percent Urban: Latest Two Censuses .............................. 42
3.8. Percent Distribution of Women Residing in Rural and Urban Areas, by
Selected Age Groups ............................................... 44
3.9. Percent of Migrants Among Native-Born Population, by Sex, and Female/Male
Ratio of Percent of Migrants .......................................... 46
3.10. Percent of Population Foreign Born, by Sex, and Female/Male Ratio of Percent
Foreign Born ...................................... ................ 47
3.11. Percent of In-Movers, by Sex, and Female/Male Ratio of Percent of In-Movers ....... 48
3.12. Percent of Urban Population Foreign Born .................................. 49










Chapter 4. Literacy and Education ................................. 51

Figures

4.1. Percent Literate Among Women and Men 10 Years of Age and Over .............. 58
4.2. Percent Literate Among Women and Men 10 Years of Age and Over, by
Rural/Urban Residence .. ............................................ 59
4.3. Percent Literate for Women and Men by Age ................................ 60
4.4. Female/Male Ratio of Percent Literate in Rural Areas, for Selected Age Groups ....... 62
4.5. Female/Male Ratio of Percent Literate in Urban Areas, for Selected Age Groups ...... 63
4.6. Percent Enrolled in School Among Girls and Boys 10 to 14 Years of Age ........... 64
4.7. Female/Male Ratio of Percent Enrolled in School in Rural Areas, for Selected
Age Groups ............................... ....... ................. 65
4.8. Female/Male Ratio of Percent Enrolled in School in Urban Areas, for Selected
Age Groups ................................ ...... ................. 66

Tables

4.1. Percent Literate Among Total Population Age 10 Years and Over, by Sex,
and Female/Male Ratio of Percent Literate ................................. 67
4.2. Percent Literate.Among Rural Population Age 10 Years and Over, by Sex,
and Female/Male Ratio of Percent Literate ................................. 68
4.3. Percent Literate Among Urban Population Age 10 Years and Over, by Sex,
and Female/Male Ratio of Percent Literate ................................. 69
4.4. Percent Literate Among Women and Men, by Age ............................ 70
4.5. Percent of Population Enrolled in School, by Age and Sex ...................... 71
4.6. Percent of Population Enrolled in School, by Age and Sex, for Rural Areas .......... 72
4.7. Percent of Population Enrolled in School, by Age and Sex, for Urban Areas ......... 73
4.8. Female/Male Ratio of Percent Enrolled for Selected Age Groups, by
Rural/Urban Residence ............................................... 74



Chapter 5. Women in Economic Activity ............................ 77

Figures

5.1. Labor Force Participation Rates for the Population 10 Years of Age and
Over, by Sex ............................. ......... ................ 84
5.2. Female/Male Ratio of Labor Force Participation Rates .......................... 85
5.3. Labor Force Participation Rates for Women, by Rural/Urban Residence ............. 86
5.4. Female/Male Ratio of Labor Force Participation Rates, by Rural/Urban Residence...... 87
5.5. Female/Male Ratio of Percent of Labor Force in Agriculture ..................... 88
5.6. Female/Male Ratio of Percent of Unpaid Family Workers ....................... 89

Tables
5.1. Number and Percent Economically Active Among Population Age 10 Years
and Over, by Sex, and Female/Male Ratio of Percent Active .................... 90
5.2. Number and Percent Economically Active Among Rural Population Age
10 Years and Over, by Sex, and Female/Male Ratio of Percent Active ............ 92
5.3. Number and Percent Economically Active Among Urban Population Age
10 Years and Over, by Sex, and Female/Male Ratio of Percent Active ............ 93
5.4. Labor Force Participation Rates, by Age and Sex ............................. 94
5.5. Labor Force Participation Rates, by Age and Sex, for Rural Areas ................. 96
5.6. Labor Force Participation Rates, by Age and Sex, for Urban Areas ................ 98
5.7. Female Share of Rural and Urban Labor Force, by Age ......................... 100
5.8. Female/Male Ratios of Percent in Rural and Urban Labor Force, by Age ............ 102


Women of the World


IV Contents







Women of the World Contents V


5.9. Percent of Labor Force in Agriculture, by Sex ............................... 104
5.10. Percent of Unpaid Family Workers in Labor Force Age 10 Years and Over,
by Sex and Rural/Urban Residence .................................... 105



Chapter 6. Marital Status and Living Arrangements .................... 109

Figures

6.1. Age by Which 50 Percent of Women and Men Have Ever Been Married ............ 115
6.2. Proportion of Women 10 Years of Age and Over in Categories of Marital Status...... 116
6.3. Percent Single Among Women in Two Age Groups, by Rural/Urban Residence ....... 117
6.4. Median Number of Persons per Household, by Rural/Urban Residence .............. 118
6.5. Percent of Households Headed by Women .................................. 119

Tables

6.1. Minimum Legal Age at Marriage for Women and Men ................. ...... 120
6.2. Age by Which 50 Percent of Women and Men Have Ever Been Married,
by Rural/Urban Residence ............................................. 121
6.3. Percent Distribution of Population Age 10 Years and Over, by Marital Status
and Sex ......................................................... 122
6.4. Percent Distribution of Rural Population Age 10 Years and Over, by Marital
Status and Sex ..................................................... 124
6.5. Percent Distribution of Urban Population Age 10 Years and Over, by Marital
Status and Sex ..................................................... 126
6.6. Percent Single Among Women and Men Age 20 to 24 Years and 45 to 49
Years ............................................................ 128
6.7. Percent Single Among Women and Men Age 20 to 24 Years and 45 to 49
Years, by Rural/Urban Residence ........................................ 129
6.8. Selected Measures of Polygamy ......................................... 130
6.9. Median Number of Persons per Household, by Rural/Urban Residence .............. 131
6.10. Selected Household Measures ........................................... 132



Chapter 7. Fertility and the Status of Women ........................ 133

Figures

7.1. Crude Birth Rate ..................................................... 137
7.2. Total Fertility Rate ............. ............................. ..... .138
7.3. Gross and Net Reproduction Rates ....................................... 139
7.4. Distribution of Lifetime Fertility, by Age of Mother ............................ 140

Tables

7.1. Number of Countries With Data on Fertility, by Type of Fertility Measure
and Recency of Data................................................. 141
7.2. Crude Birth Rate, Total Fertility Rate, Gross Reproduction Rate, and Net
Reproduction Rate ................................................... 142
7.3. Total Fertility Rate and Crude Birth Rate for Rural and Urban Areas ............... 144
7.4. Percent Distribution of Lifetime Fertility, by Age of Mother. ................... .. 145
7.5. Percent Distribution of Lifetime Fertility, by Age of Mother, for Rural and
Urban Areas ................. .. ................................... 146


Women of the World


Contents V






Vi Contents Women of the World


Chapter 8. Mortality and the Status of Women ................. ..... 147

Figures

8.1. Life Expectancy at Birth for Women and Men ............................... 151
8.2. Infant Mortality Rates ................. ............................... 152
8.3. Female/Male Ratio of Infant Mortality Rates ................................. 153
8.4. Proportion of Children Dying Before Their Fifth Birthday, by Sex .................. 154

Tables

8.1. Number of Countries With Data on Mortality, by Type of Mortality Measure
and Recency of Data........................ ............. ........... 155
8.2. Life Expectancy at Birth and at Age 1 Year for Women and Men, and
Female/Male Ratio of Life Expectancies ................................... 156
8.3. Number of Years Women May Expect to Outlive Men at Birth and at Age 1
Year, and Male Gains in Life Expectancy Between Birth and Age 1 Year ........... 157
8.4. Infant Mortality Rates, by Sex, and Female/Male Ratio of Infant Mortality Rates ...... 158
8.5. Percent of Children Dying Before Their Fifth Birthday, by Sex, and Female/Male
Ratio of Percent Dying .................................... ......... 159



Chapter 9. Conclusions: National Level Data and the Situation of Women .... 161

Appendixes

A References ......................................................... 16 5
B. Tables in the Women in Development Data Base ............................. 175
C. Population by Age, Sex, and Rural/Urban Residence ........................... 177


Vi Contents


Women of the World







Women of the World Abbreviations Vii


Abbreviations Used in This Report


ASFR: Age specific fertility rate (the average annual number of
births to women in a given age group during a specified period
of time per 1,000 women in the same age group, based on
midperiod population).

ATRCW: African Training and Research Centre for Women,
United Nations Economic Commission for Africa. Addis
Ababa.

CBR: Crude birth rate (the average annual number of births dur-
ing a specified period of time per 1,000 persons, based on
midperiod population).

CIR: Center for International Research, U.S. Bureau of the
Census. Washington, D.C.

DUALabs: Data Use and Access Laboratories. Arlington, Virginia.

FAO: Food and Agriculture Organization, United Nations. Rome.

F/M ratio: Ratio of the female value to the male value for a given
characteristic (for example, the ratio of the female percent
literate to the male percent literate).

GDP: Gross domestic product (the total value of all final goods
and services produced in an economy during a specified period
of time, excluding net factor income from abroad).

GNP: Gross national product (the total value of all final goods
and services produced in an economy during a specified period
of time, including net factor income from abroad).

GRR: Gross reproduction rate (the average number of daughters
born per woman in a group of women passing through the
childbearing years and experiencing a given set of age-specific
fertility rates. This rate implicitly assumes that all the women
live to the end of the childbearing years. See also NRR).

ILO: International Labour Office, United Nations. Geneva.

JASPA: Jobs and Skills Program for Africa, International Labour
Office.


NA: Data not available.


NRR: Net reproduction rate (a refinement of the gross reproduc-
tion rate that allows for mortality of women from birth to the
end of their reproductive years).

OECD: Organization for Economic Co-operation and Develop-
ment. Paris.


TFR: Total fertility rate (the average number of children that
would be born per woman if all women lived to the end of
their childbearing years and bore children according to a given
set of age-specific fertility rates).

U.N.: United Nations.

UNDP: United Nations Development Program.

UNECA: United Nations Economic Commission for Africa.
Addis Ababa.

UNECOSOC: United Nations Economic and Social Council. New
York.

UNESA: United Nations Department of International Economic
and Social Affairs. New York.

UNESCO: United Nations Educational, Scientific, and Cultural
Organization. Paris.

UNIDO: United Nations Industrial Development Office.

USAID: United States Agency for International Devleopment.
Washington, D.C.

WHO: World Health Organization, United Nations. Geneva.

WID: Women in Development.

WID Data Base: Women In Development Data Base (a project
of the U.S. Bureau of the Census).


WID Office: Office of Women In Development, Bureau for Pro-
gram and Policy Coordination, U.S. Agency for International
Development.


Women of the World


Abbreviations Vii





viii Women of the World


Sub-Saharan Africa


Liberia %L. Tog. ca eroon
.i 0 Kenya
.,,,oTorn.te ( 0,0i, .", Uganda
Rwanda ,-
Etoria. ui Buund
Zaire
Tanzania t ;OenL.



0 .: .. ". ":" Zam bia

\ S. ,.000, ZId*3%.....::. .
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!at


Note: Countries named in black are included in the analysis of this handbook.






Women of the World 1


Chapter 1





Elt fodui@n


Constituting just over 10 percent of the population of the
developing world in 1980, the people of the Sub-Saharan Africa
region are by almost any measure of economic and social
development among the least advantaged. Largely agricultural
in economic base and dependent upon the export of primary
products and labor, most countries are characterized by low per
capital gross domestic product, low per capital energy consump-
tion, undeveloped financial institutions, inadequate adult literacy,
short life expectancies, high rates of disease and malnutrition,
high infant and childhood mortality, and high fertility.' Daily life
for the vast majority of the people of the region is a constant
struggle against poverty, ignorance, and disease.
It is in this context that the question of the status of women
must be considered. Although the question of women's access
to the resources of a society also is one of social justice and
human rights, in the context of Sub-Saharan Africa it is perhaps
of greater relevance to point out that it is one which is critical
to the development process itself. As the primary food producers
in the region, Africa's women play an indispensable role in the
economy, for the achievement of regional food self-sufficiency
will depend upon their increased productivity. In many African
countries, women are also responsible for the distribution and
marketing of basic food supplies and other household goods,
both wholesale and retail. Again, unless women have access
to training and to modern financial tools, the small business
sector cannot make its maximum contribution to development.
Moreover, inasmuch as in African society and particularly in
polygamous households women are often both economically and
personally responsible for the care and early education of their
own children, failure to afford women full access to educational
and economic resources will have a direct and limiting impact
on the welfare and opportunities available to their children, boys

'National level statistics on a variety of economic and social characteristics
may be found in Population Reference Bureau (1980), U.S. Bureau of the
Census (1980 and 1983c), and World Bank (1980c, 1981, and 1982).


as well as girls. For these reasons, the status of women in Sub-
Saharan Africa is an important development issue.2
The national governments of the region, often with interna-
tional assistance, have been making strenuous efforts to mobilize
their peoples and resources for economic and social develop-
ment, and gains in many of the indicators have been registered
for both women and men in most countries since national in-
dependence. Change is underway in Africa, and with it inevitable
dislocation as well as opportunity. Many observers who have
examined the benefits and costs of economic development have
concluded that women have often borne a disproportionate share
of the costs while men have more often received the benefits
of these changes.3 Some innovations have made life easier for
all: improved water supplies, health services, and all-weather
roads have been of benefit to women as well as men. Despite
women's key roles in food production and commerce, however,
most of the programs designed to improve productivity in
agriculture and business have been directed toward men's
activities; few women have felt the benefits of these programs.
Moreover, because of the traditional division of labor in
agriculture, many development projects have simply increased
the amount of work which women must do. For example, ex-
panded acreage must be weeded, and more water carried for
additional livestock. When men leave the farm for wage employ-
ment, women are frequently left behind to manage alone, often
without adequate resources or decision-making authority.
Women's traditional income-generating activities are some-
times unintentionally curtailed by development projects, as, for
example, when the introduction of a cattle ranching scheme,
by moving families several kilometers away from the nearest

'The literature discussing African women's economic roles, particularly
in agriculture, is extensive. See Anker and Knowles (1978), Benerfa (1981),
Boserup (1970), Bryson (1981), BuviniC and Youssef (1980), Halfkin and
Bay (1976), Nelson (1981), Pala (1975), Paulme (1963), and UNECA (1974a,
1974b, 1978a, 1978d, 1978e, 1981a, and 1982b).
'For information concerning the impact of development programs on
women, see footnote 2.







2 Introduction Women of the World


town, deprives women of their traditional market for milk and
milk products. The loss of income is a serious matter for African
women because the traditional gender division of labor assigns
them economic responsibility for an important share of household
expenses. When a woman also is the head of a household, as
increasing numbers are, an adequate income becomes even more
critical for both herself and her family. Although educated
women have little difficulty finding employment in the modern
sector, albeit rarely at the upper levels of management, most
women have had relatively few opportunities for education or
training. Therefore, when women who are burdened with addi-
tional work on the farm or squeezed out of traditional occupa-
tions seek employment in the modern wage sector, their lack
of education forces them into the lowest paid, least skilled, and
least secure jobs.
Women's disadvantaged position as development proceeds
is not the result of national policy; indeed, most African govern-
ments have made full policy commitments to narrow the educa-
tional gaps between girls and boys, especially at the primary
school level. Rather, it is in large part the consequence of beliefs
and attitudes, both traditional and imported from the West, that
women's activities are primarily domestic and of secondary im-
portance. Such attitudes are both reflected in, and in turn rein-
forced by, the absence of information about women's situation
and their economic activities. And under conditions of economic
scarcity, failure to recognize and to measure the economic
significance of women's activities tends to undervalue their work
and to limit their access to national resources.
The United Nations International Decade for Women has
brought the need for information about women's contribution
to development into sharp focus, and it is now widely recog-
nized that existing statistical systems have failed to fully measure
women's productive roles as distinct from their reproductive
roles in society. Moreover, as a result of the work of Powers
(1983), UNESA (1980), Youssef (1980b and 1983), and others,4
there is growing agreement about a set of potentially useful in-
dicators for monitoring the situation of women and their par-
ticipation in the development process. Although different con-
cepts and operational definitions of economic activity and greater
sensitivity to sex biases in data collection and presentation are
both needed in order to adequately monitor changes in the con-
dition of women, careful analysis of data from existing national
statistical systems can highlight important aspects of their situa-
tion while simultaneously identifying informational and con-
ceptual inadequacies.
In recognition of the need for national-level data disaggregated
by sex, the Office of Women in Development (WID Office) of
the U.S. Agency for International Development (USAID) in 1978
requested the Center for International Research (CIR), U.S.
Bureau of the Census, to establish a Women In Development
Data Base (referred to hereafter as the WID Data Base) of
demographic and socioeconomic statistics, disaggregated by sex
and, wherever possible, also by age and by rural/urban residence.
A search was conducted on 19 variables, including demographic,


4See Benerfa (1981), DUALabs (1980 and 1981), Population Council.
(1979), UNDP (1981), and UNECA (1974a, 1976, and 1981).


educational, household and marital arrangements, and labor force
topics. Each variable was chosen because of its key importance
as an indicator of women's status and because these particular
variables appeared to be the ones that would be most readily
available in census publications. Special runs of census files were
not contemplated because of the high cost.
The first data search included only the 69 countries where
USAID had active programs. It was planned that after the initial
search was completed, more countries would be added for pur-
poses of comparison, and more variables if the initial search
determined that sufficient information was available on other
aspects of women's situation and activities. Subsequently, the
WID Data Base was expanded to include all countries with
populations of 5 million or more. Over 2,600 tables have been
compiled on the 19 indicators. Statistics come principally from
the 1970 census round; in some cases, 1960 round data are
included.5 Some information from the 1980 round censuses is
available at this time, and this also has been included whenever
possible. To supplement the census data, the results of national
surveys are also used for some topics. Detailed characteristics
of the WID Data Base are presented in chapter 2.
Analysis of these data for a large number of developing coun-
tries is presented in handbooks for Asia and the Pacific, Latin
America and the Caribbean, Near East and North Africa, and Sub-
Saharan Africa. Although these handbooks were originally con-
ceived as a tool for the development community in planning and
assessing its programs, it was decided to make them available
to a wider community of users both to demonstrate what the
data reveal about the present-day situation of women and to
serve as a benchmark against which to measure change as more
information becomes available in the future.
This handbook for Sub-Saharan Africa covers 40 developing
countries of the region-those with populations of 5 million or
more plus selected smaller countries. On the tables and charts,
countries are grouped into the subregions of Sahel West Africa,
Coastal West Africa, Central Africa, Eastern Africa, and Southern
Africa. These subregions are illustrated on the accompanying
map.
The objectives of this manual are three: (1) to present data
on the situation of women for as many developing countries in
Sub-Saharan Africa as have published national-level data con-
sidered by the Bureau of the Census to be of reasonable
quality; (2) to interpret the data in light of information from other
sources, in order to describe the situation of women in the region;
and (3) to consider the strengths and limitations of national-level
data as planning tools for monitoring changes in the status of
women and for facilitating their full participation in national
development.
It is not possible to characterize the status of the women of
Africa by means of a single statistic. Because women's roles
are many, the status of women is multidimensional, and those
dimensions-personal, familial, social, ethnic, cultural, religious,
political, and economic-vary widely across the continent. The

"A census round refers to a decade during which the various countries
conduct their censuses; 1960 round censuses were taken during the period
1955 to 1964, 1970 round during 1965 to 1974. The 1980 round is still
underway, referring to censuses taken during 1975 to 1984.


2 Introduction


Women of the World






Women of the World Introduction 3


set of indicators offered in this handbook, coming as they do
from national censuses, surveys, and vital registration systems,
can measure a number of those dimensions, but will leave largely
unexplored the equally critical cultural, social, and political
aspects of women's status. Nor, with the single exception of
rural/urban residence, do these data permit an examination of
the status of women by ethnic or other social subgroups within
a country. They can, however, afford the investigator a broad
view of the condition of women across the continent as
measured by some of the key indicators of women's status.


Analytical Summary

The remaining chapters of this handbook analyze the statistics
from the WID Data Base. Chapter 2 discusses the availability,
quality, and selection of data. Chapter 3 describes the popula-
tion of the Sub-Saharan Africa region (excluding South Africa)-
its size, growth, composition, geographic distribution, and
change. Migration and its impact on women is considered in this
chapter, but detailed discussion of both fertility and mortality
is left for chapters 7 and 8. Chapter 4 presents data on adult
literacy and on educational enrollment among children and youth.
In chapter 5, the critical issues surrounding women's economic
roles are discussed, and data on labor force participation are
presented. Marital status and household characteristics are the
focuses of chapter 6, and are followed by consideration of fer-
tility in chapter 7 and mortality in chapter 8 as they relate to
the status of women. The handbook closes in chapter 9 with
a discussion of the advantages and limitations of national-level
data in planning for a development strategy which includes
women.

Population Distribution and Change. Except in Nigeria, the
populations of Sub-Saharan African countries are not large, and
rural densities are not usually high. However, the population of
the region is growing rapidly at about 3 percent per year, and
it is a young population with considerable potential for continued
growth. The median proportion under age 15 is approximately
45 percent; at 87 young people per 100 adults (ages 15 to 64
years), the youth dependency burden is a heavy one. Most of
the population continues to reside in the rural areas, and the dif-
ferences in urbanization between women and men are rela-
tively small; the median percent urban at the most recent
national census or survey was 17 percent for women and 20
percent for men. Urban growth in the region since the early
1960's has averaged about 5.5 percent per year, although there
is considerable variation among countries. Because urban and
rural rates of natural increase are similar, only part of the urban
growth may be attributed to migration. Migration is predomi-
nantly a male phenomenon, but women also have participated.
In each of the countries for which migration data are available,
women constitute at least 40 percent, and in a few cases, more
than 50 percent of the in-movers.
For both sexes, the population age distribution in the cities
differs from that in the rural areas. Although the data refer to
varying years among countries, unweighted averages of the per-
cent in broad age groups may be taken as an approximation of
the overall age distribution by rural/urban residence. The urban


data for each sex show relatively more adults in the prime work-
ing ages (15 to 49 years), relatively fewer under age 15, and
still fewer at ages 50 and over than do the rural:

Urban (percent) Rural (percent)
Age
Women Men Women Men

All ages ........ 100 100 100 100
0 to 14 years ..... 43 40 44 47
15 to 49 years .... 49 53 46 41
50 years and over 8 7 10 12

The proportion of women in the working ages is lower in the
urban and higher in the rural areas than is that of men, differences
which probably reflect higher male than female rural-to-urban
migration.

Literacy and Education. Both the absolute level and the
female/male ratio of adult literacy vary widely among the coun-
tries. In most countries, more men than women are literate in
any language, but there is evidence of considerable improvement
in female literacy since the 1960's. A higher proportion of
women is literate and the female disadvantage is smaller in each
successively younger age group. Moreover, although urban
literacy is higher than rural, the same pattern of improvement
is shown in both urban and rural areas. There appear to be
subregional differences in female literacy: rates tend to be higher
in the Eastern and Southern regions than in West Africa, and
the female disadvantage relative to males is smaller. Indeed, in
Botswana, Lesotho, and Swaziland, it is the men who are more
often illiterate. The pattern of subregional differentials is similar
in both rural and urban areas.
In school enrollment, as in literacy, the countries of the Sub-
Saharan Africa region show wide variation. The pattern of educa-
tional differentials is similar to that for literacy: enrollment rates
for each sex are higher in urban than rural areas; relatively more
boys than girls are enrolled at each educational level; and West
African enrollment lags behind that of Eastern and Southern
Africa for each sex. Female/male differentials are lower in the
cities and in the Eastern and Southern subregions; again, in
Botswana, Lesotho, and Swaziland, it is the boys and men who
are relatively disadvantaged except at the older ages.
Opportunities for formal schooling are limited for both sexes
and decrease with each succeeding age beyond 10 to 14 years.
The female/male ratio of total enrollment also is smaller at each
successive age. Median values calculated based on the available
data are as follows:

Percent enrolled 5 to 9 10 to 14 15 to 19 20 to 24
years years years years

Female ...... 22 37 15 1
Male ....... 31 51 33 8
F/M ratio .... 0.82 0.70 0.40 0.18

Information from other sources indicates that female enrollment,
especially at the primary level, has improved since the 1960's.

Women in Economic Activity. Male labor force participation is
uniformly high in the region, while female participation is lower
and highly variable. Although social and ecological factors may


Introduction 3


Women of the World






4 Introduction Women of the World


account for some of this variability, its magnitude suggests that
the measure has a low reliability for women. For both women
and men, labor force participation is greater in the rural areas;
moreover, for both sexes but especially for women, economic
activity rates are negatively associated with the country's level
of urbanization. It is suggested in chapter 5 that this negative
association might in part be an artifact of the way in which the
rural labor force is defined in many of the countries. A greater
share of the subsistence and part-time workers in agriculture may
have been counted in the labor force, often as unpaid family
workers, than of those working in the informal sector which
dominates the economic activity of marginal workers in urban
areas.
The age pattern of participation for men shows high and
fairly uniform rates for ages 20 through 49 years and only a slight
decline after age 50. Participation rates for women, on the other
hand, show two different age patterns: one, similar to that of
the male although usually at a lower level of economic activity,
is characterized by fairly flat rates for ages 20 through 49 years.
The other, more common, pattern shows activity rates rising
with each 10 years of age to a peak for women in their forties;
in both patterns, there is a decline after age 50. Adult male par-
ticipation tends to be higher than female at every age and in both
rural and urban areas. For those under age 20, however, urban
female participation rates are often higher than male rates. There
is some evidence of an effect of the potential pool of male
workers on female participation. Female economic activity in
ages 30 to 49 years tends to be higher where there is a relative
deficiency of men in the same age, that is, where sex ratios are
low. Finally, there appear to be subregional differences in female
labor force participation, with two broad bands of low participa-
tion, one stretching across the Sahel into Sudan, and the
second stretching across south central Africa from Angola to
Mozambique.

Marital Status and Living Arrangements. Although virtually all
adults in Sub-Saharan Africa eventually marry at least once,
women marry at much younger ages than men do, with a modal
minimum legal age at marriage of 16 years for women and 18
years for men. Examination of available data on marital status
show the following values, based on information for the vary-
ing dates:

Median percent ever married Women Men

Ages 20 to 24 years ......... 85 26
Ages 45 to 49 years ......... 98 96

Both women and men marry at younger ages in rural than
urban areas. For both sexes, the age by which 50 percent have
ever been married is about 2 years higher in the cities. In most
countries, the age difference between husband and wife is 5
to 10 years; the median is about 6 years. Plural marriage is still
common in many countries of the region; in 10 of the 12 coun-
tries with data on polygamy, one-fifth to one-third of the mar-
ried men had two or more wives. The median number of wives
in these marriages is a little over two.
The distribution of the population by current marital status dif-
fers considerably among the countries and between the sexes.


Few persons of either sex report themselves as legally separated
or divorced, and although four times as many women as men
are currently widowed, these groups still represent a relatively
small proportion of the population. Divorce and death are not
uncommon, but from other information it is known that remar-
riage rates among the divorced are high. The sexes differ pri-
marily in the proportions single and currently married, with nearly
twice as many men as women reported as single. Median percen-
tages based on the available information on current marital status
for varying dates are as follows:


Marital status category Women Men

Single .................. .. 24 43
Married ................... 62 52
Separated/divorced .......... 3 2
W idowed ................. 9 2

In the cities, the percent currently single for both sexes and the
percent of separated or divorced women are higher; con-
versely, in the rural areas for both sexes, the percentages cur-
rently married and currently widowed are higher. The latter
observation suggests that women household heads in urban and
rural areas are likely to be of different marital status categories
and face somewhat different problems beyond those associated
merely with their urban and rural residence.
The countries differ considerably in the proportion of
households reported to be headed by women; the median is
only 15 percent. In most women-headed households, the woman
is between ages 30 and 45, the ages at which both work and
family responsibilities are heavy. Household sizes are large in
both rural and urban areas, although the rural household is
likely to be somewhat larger.

Fertility and the Status of Women. By all measures, fertility is
high in the countries of Sub-Saharan Africa. All but four coun-
tries (Cape Verde, Mauritius, Seychelles, and Lesotho) have
crude birth rates of about 40 per 1,000 population or higher, and
nearly half the countries have rates close to 50 per 1,000 popula-
tion or higher. The median total fertility rate is 6.6 children per
woman, and the median net reproduction rate is two surviving
daughters per woman. Fertility tends to be distributed across
the full span of reproductive ages. In most countries, although
the largest share of fertility is contributed by women ages 25
to 34 years, younger women account for at least 30 percent
and older women for another 20 percent. In four countries, the
distribution is shifted somewhat toward younger women, and
in five countries toward older women. In the few countries with
data to examine rural/urban fertility differentials, rural fertility
tends to be higher than urban, but the differences are not large.
Other sources confirm the impression that there is as yet little
relationship between indicators of modern (as distinct from tradi-
tional) female status and fertility, with the possible exception
of a shift toward an older age pattern due to an older age at
marriage.

Mortality and the Status of Women. In Sub-Saharan Africa as
elsewhere, girls and women experience lower mortality than
boys and men do. Except in Ethiopia and Upper Volta, the ex-


4 Introduction


Women of the World





Women of the World


Introduction 5


pectation of life at birth for women is greater than that for men
by 2 to 6 years; the median expectation of life is 46 years for
women and 42 years for men. Moreover, a median 27 percent
of boys but only 24 percent of girls die before their fifth birth-
day. However, most of the female mortality advantage has disap-
peared by the end of the first year of life; median expectation
of life at age I is 51 years for women, and 50 years for men.
For those who reach age 5, the median expectation of life for
women is 53 years and for men, 52 years. This convergence
implies that much of the difference in life expectancy at birth
and in survival to age 5 is due to differential infant mortality;
the median infant mortality rate for boys is 152 deaths per 1,000
live births, for girls, 132. A convergence in the pre-school years


is in marked contrast to the pattern in low mortality countries,
where women retain a considerable mortality advantage
throughout life, and implies that Sub-Saharan African women
are experiencing higher mortality relative to men at older ages
than they would under a low mortality schedule.
Regional differences in mortality are evident. For both women
and men, mortality is higher in Western and Central Africa than
in the Eastern and Southern subregions, and female/male ratios
tend also to be more favorable to women in the latter two
subregions. Simple correlational analyses of national level data
find female literacy and/or education negatively associated with
the mortality measures, associations that do not disappear when
per capital GNP is statistically controlled.









Women of the World 7


Chapter 2


The primary source of the statistical data analyzed in this hand-
book is the WID Data Base created by the Center for Interna-
tional Research, U.S. Bureau of the Census, under the auspices
of the U.S. Agency for International Development. The data file,
including statistics for 120 countries worldwide, is contained
on a computer tape. The capability also exists for selecting and
printing tables in a standardized format. A list of table titles for
which data were compiled by sex and rural/urban residence may
be found in appendix B.
The same factors which are responsible for the
underdeveloped status of most of the countries in the Sub-
Saharan Africa region also are responsible for their relatively
underdeveloped statistical systems. During the period 1955 to
1974, 15 of the 40 countries included in this analysis did not
conduct a single national census, while five others took only one.
Even for countries that did achieve national enumerations, the
data are often incomplete or of uncertain quality. Fortunately,
the situation has improved considerably during the 1980 cen-
sus round. To date, only three countries (Chad, Ethiopia, and
Zaire) have never taken a national census.
For most of the countries, the basic population data presented
in chapter 3 were gathered during the 1970 round of popula-
tion censuses. For eight of the countries, data from an earlier
census have been taken as the basic set, either because they
provide more complete breakdowns by age, sex, and rural/
urban residence, or because none other are available. For nine
countries, the population data come from the 1980 round of cen-
suses. In some countries, demographic sample surveys provide
a basis upon which to estimate national population parameters.
However, in a continent with high rates of labor migration and
many nomadic and refugee peoples, survey data often pertain
only to the de jure and settled population, and may not cover
the entire country. In all cases, choice of the reference data set
has been based on the availability of population data by age,


sex, and rural/urban residence, and of data for approximately
the same period on labor force, education, marital and household
status, fertility, and mortality. The population data therefore are
intended to provide a proper context for the discussions in
chapters 4 to 8 of the situation of women with respect to educa-
tion, economic activity, and the like. Thus, for a number of coun-
tries, the population statistics appearing in chapter 3 do not
represent the most recent data available but rather the most com-
plete data available with respect to those indicators of women's
status which are the subject of this handbook. Where more re-
cent (but usually more limited) population data are available, that
has been noted and important differences pointed out in text,
tables, or chapter notes.


Selection and Quality of Data

As is well known, there are vast differences in both the quan-
tity and the quality of statistics reported by the various coun-
tries. Furthermore, in spite of international recommendations,
such as those provided by the United Nations, for the standardi-
zation of concepts and definitions pertaining to data collected
in censuses and surveys, there continue to be wide discrepan-
cies in data collection practices due to legitimate differences of
what is appropriate in the varying cultural contexts. As a result,
any attempt to compile standard data across countries, such as
those in the WID Data Base, requires some decisions about
whether and how the reported data should be manipulated so
as to provide comparability. Certainly there is not a single right
solution to this problem, but it is essential to set rules from the
start so that consistent decisions are made whenever similar data
situations are encountered among countries.
The standards used in selecting and evaluating the data for
inclusion in the data base depend to some extent on the type
of data being considered. For the demographic subjects, only






8 Sources of Data Women of the World


data of benchmark quality are included. The concept of
benchmark data refers to statistics (as reported by the country,
as adjusted by researchers, or as derived by applying demo-
graphic techniques to incomplete data) which have been
evaluated by the Census Bureau analysts and judged to be as
representative as possible of the true situation. These data are
internally consistent for a given country (for example, birth rates,
death rates, international migration rates, population growth
rates, and age/sex composition all fit together in a logical
demographic pattern) and are consistent with other facts that
are known about the country (for example, fertility levels are
consistent with family planning practices and goals, and mor-
tality levels are consistent with known health indexes).
These data also have been checked for external consistency.
They have been compared to data for other countries in the same
region or subregion and to those elsewhere at approximately the
same level of economic and social development to ensure that
they are not out of line.
These benchmark data refer to the date on which the census
or survey was taken, that is, no projections beyond the reference
date are included among them. Demographic data that do not
conform to these rigid benchmark requirements are generally not
included in the data base. The source and method of derivation
of the estimates are explained in the notes accompanying each
table.
For socioeconomic variables (data on households, marital
status, education, and economic activity), less rigid requirements
were placed on the accuracy of the data. No techniques have
been applied to evaluate the quality of the data in the socio-
economic tables, and most of these statistics are presented as
they appear in the original sources. Nevertheless, the same care
has been taken to annotate the sources and to explain any
discrepancies in totals or deviations from standard international
practices.


Concepts and Definitions

Concepts and definitions usually are not standardized among
countries beyond what has already been done by the countries
themselves for two reasons: first, the information is usually not
available to manipulate the data to conform to standard con-
cepts, and second, the differing concepts or definitions are often
deliberately developed for reasons relating to each country's par-
ticular situation. For example, a country with only a few small
urban centers needs a different definition of urban than a coun-
try that is already predominantly urban. On the other hand, nearly
all countries define literacy as the ability to read and write,
although some countries include additional requirements such
as the ability to write a simple statement about everyday life
or the ability to read and write a specific language.
Although in the WID Data Base no attempt has been made
to standardize the definitions of concepts such as urban, literacy,
or economic activity, and such data are presented as reported
by the country, all tables are nevertheless annotated, specify-
ing the definition used by the country for these concepts and
others such as nationality, household, and school enrollment.
Thus in all cases the user has the opportunity to examine a


fairly substantial set of notes that may help to explain any ap-
parent discrepancies in the statistics from one country to
another.


Time Period

For the basic distribution of the population by age and sex,
data are presented for the latest 2 census years. Most of the
tables present data for the latest year available at the time of
compilation. For countries whose data were compiled at an early
stage of the project, updated tables presenting later statistics
have been added to the file.
Some tables, for which a measure of change is most relevant
and most readily available, present a time series of data. This
is done for the various measures of mortality and fertility, where
all available benchmark data since 1970 are presented; in a few
cases where no post-1970 data are available, the latest
post-1960 estimate is given for these measures.


Auxiliary Measures

Users may choose to manipulate the data to derive additional
rates and ratios to measure the status of women in the various
subject areas covered in the data base, and this has sometimes
been done in the analytical portions of this handbook. These
measures may be designed to compare the position of women
versus men with respect to a particular topic, or they may relate
women in a particular category to all persons in the same
category.
For example, the percent literate is shown in the data base
for women and men; another measure may be derived to pre-
sent the female/male ratio of the percent literate. A similar ratio
can be devised for other topics such as the female/male ratio
of the percent urban, the female/male ratio of the labor force
participation rate, and so on.
In the other instance, to analyze women's share in a particular
category or activity, the data can be used to calculate the per-
cent of all persons with a given characteristic who are women.
For example, it may be useful to calculate the female share of
the rural labor force in a developing country. This measure would
be derived using the number of economically active rural women
as the numerator and the number of economically active rural
persons of both sexes as the denominator. Such a measure might
also be derived separately for various age groups or for any other
characteristic.
Of course, more conventional percent distributions also are
useful in many instances, such as a percent distribution of
women by marital status. Sometimes, just one percentage is a
useful measure across countries, such as the percent single
among women ages 20 to 24 years. Many of these derived
measures lend themselves easily to graphic presentation as well.


Data Availability

Given the criteria established for the selection of statistics for
the WID Data Base, it is not surprising that not all data were
available for all countries. In many cases, even when data of
appropriate quality were available, they often did not fit the


8 Sources of Data


Women of the World







Women of the World Sources of Data 9


established categories exactly. In order to provide a summary
of the amount and standardized nature of the statistics in the
data base, a tally was made of the number of rows and columns
of data in each table, and these results were compared to the
number of rows and columns in each standard table outline. The
tally is summarized in table 2.1.
Ordinarily, a country should have 31 tables of data. (It will
be noted from the list in appendix B that there are 19 table
numbers, but several tables have parts A, B, and C, totalling 31
tables.) If updated information has been added, certain table
numbers appear more than once, giving some countries more
than 31 tables. A standard table is one whose number of rows
and columns conforms to the outline.-An actual table may be
nonstandard for trivial reasons, for example, because a single
age category was different from the outline; or it may be
nonstandard in significant ways, for example, because data for
only a total row were available when considerably more detail
was intended. A frequent reason for a classification as non-
standard is the lack of a rural/urban breakdown of the data.
Sometimes no data at all were found on a particular topic for
a given country, as represented by the number of blank tables
indicated on table 2.1. For only a few countries, data were found
on most topics for which a search was made (only four or five
blank tables for Mali and Tanzania, for example), while for
Guinea-Bissau, Djibouti, and Somalia nearly all the tables are
blank for lack of reliable data.
Table 2.2 presents information on the availability of data by
topic for the various countries. Among the topics shown, the
ones on which the most countries report data are economic
activity and fertility; these are also the topics for which the data
are the most recent. Only in Eastern Africa, where five of the
ten countries fail to report data on economic activity, is there
a substantial lack of information on that subject. In the other
subregions, such data are missing for The Gambia and Guinea-
Bissau in the Sahel, Nigeria in Coastal West Africa, and Sao Tome
and Principe in Southern Africa. Most of these countries are lack-
ing data on many of the other topics as well. For fertility, only
one or two countries in each subregion are lacking data, while
more than half the countries have fertility statistics pertaining
to the 1970's and two to the 1980's.
The poorest showing overall is in data pertaining to household
headship, for which 27 of the 40 countries are lacking informa-
tion. This is especially true in Central Africa, where no country
reports such data, and in Southern Africa, where headship is
reported only for Malawi. This lack of information is particularly
unfortunate for the analysis of household structure in the coun-
tries of Southern Africa, where many men are absent for long
periods to work in the mines in the Republic of South Africa,
as will be noted in subsequent chapters of this handbook.
For internal migration as well, there is a considerable lack of
information. In the WID Data Base, internal migration is measured
as the percent of population living in each province on the cen-
sus date who were born in a different province. Among the 40
countries under study, 23 do not report this information. Par-
ticularly notable again is the Central Africa subregion, where only


Rwanda reports data from which such estimates of internal
migration can be made, and Southern Africa, where only
Swaziland and Zimbabwe have these data.
From a perspective of the country rather than the topic, Ghana
and the Sudan appear to have the most complete data for a fairly
recent year. Both countries have some information pertaining
to the 1970's on all the topics covered in table 2.2. Mali and
Mauritius also have no missing topics, but some of the informa-
tion relates to the early 1960's (for Mauritius, only the data on
literacy pertain to the 1960's, while a crude birth rate for that
country is available for 1981). Some other countries have
nearly complete data. In particular, Liberia covers all topics
except internal migration, and Togo all except household head-
ship. Statistics on most remaining subjects are fairly recent for
both countries. Benin and Upper Volta are missing only one topic
(life expectancy and school enrollment, respectively), but data
on some or all of the other variables are not so recent.
At the other extreme, the data situation for some countries
is so poor as to virtually exclude them from the analysis. This
is true for at least one country in each of the subregions. No
basic information at all was found on any of the topics for
Guinea-Bissau in Sahel West Africa nor for Djibouti and Somalia
in Eastern Africa. In Madagascar in the latter region, data are
missing on all topics except fertility. Statistics are available on
four or five of the eight topics for Guinea in Coastal West Africa
and for Zaire in Central Africa, but for both countries these data
relate only to the mid 1950's. Also in Central Africa, Sao Tome
and Principe has data on only one of the topics (fertility).
Finally, in Southern Africa, Angola covers only economic activity
among the subjects under study.
A further discussion of the availability and quality of data on
each topic analyzed in the handbook is included in the appropriate
chapter. All tables and charts presented in the handbook are
derived from the WID Data Base unless stated otherwise. When
no data were available on a particular topic for a given country,
that country is omitted from the table in the handbook. As noted
above, for Africa it is especially important to consider not only
the quality but also the recency of the data on the various topics
because some of the statistics are quite old. In order to present
all of the available information while at the same time making
a distinction between reliable recent data and benchmark
statistics that are now quite outdated, all pertinent data from
the WID Data Base, regardless of their time reference, are
presented in the tables while information in the charts is
restricted to countries whose most recent data refer to 1970
or later. In some instances, a country is included in a chart even
though its data are incomplete. For example, if certain data are
being presented in a bar chart for the "latest two censuses"
and the country has had only one census reporting that infor-
mation, only the one bar will be shown for that country.
Further information on the Women In Development Data Base,
including how to access the computer file or obtain hard copy
printouts, may be obtained by addressing the Chief, Center for
International Research, U.S. Bureau of the Census, Washington,
D.C. 20233.


Sources of Data 9


Women of the World









Table 2.1. Number of Tables in WID Data Base, by Country and Category


Region and country Total Standard Nonstandard Blank


SAHEL WEST AFRICA

Cape Verde............... 31 2 16 13
Chad..................... 31 5 17 9
The Gambia............... 31 0 15 16
Guinea-Bissau............ 33 0 5 28
Mali ..................... 41 8 29 4
Mauritania............... 32 5 19 8
Niger.................... 37 2 27 8
Senegal.................. 31 5 12 14
Upper Volta.............. 31 4 15 12

COASTAL WEST AFRICA

Benin .................... 31 4 21 6
Ghana.................... 31 5 19 7
Guinea................... 31 3 13 15
Ivory Coast.............. 31 1 13 17
Liberia.................. 31 15 8 8
Nigeria.................. 31 1 6 24
Sierra Leone............. 38 1 27 10
Togo..................... 31 5 18 8

CENTRAL AFRICA

Burundi .................. 32 1 15 16
Cameroon................. 31 3 20 8
Rwanda................... 35 5 18 12
Sao Tome and Principe.... 31 0 6 25
Zaire.................... 31 0 16 15

EASTERN AFRICA

Djibouti................. 32 0 4 28
Ethiopia................. 31 4 13 14
Kenya.................... 35 1 20 14
Madagascar.............. 31 1 9 21
Mauritius................ 31 3 20 8
Seychelles............... 31 1 20 10
Somalia.................. 31 0 3 28
Sudan.................... 31 4 21 6
Tanzania................. 32 12 15 5
Uganda .................. 31 1 13 17


10 Sources of Data


Women of the World




Women of the World


Sources of Data 11


Table 2.1. Number of Tables in WID Data Base, by Country and Category-Continued


Region and country Total Standard Nonstandard Blank


SOUTHERN AFRICA

Angola................... 31 0 6 25
Botswana................. 33 3 19 11
Lesotho.................. 31 0 19 12
Malawi................... 39 10 21 8
Mozambique............... 32 2 15 15
Swaziland................ 35 2 18 15
Zambia ................... 33 1 27 5
Zimbabwe................. 31 5 13 13








Table 2.2. Availability and Recency of Statistics, by Country and Subject


Li fe
Internal Head of expec-
Region and country Enroll- migra- Economic Marital house- Fer- tancy
Literacy ment tion activity status hold utility at birth

SAHEL WEST AFRICA

Cape Verde............... 1960 (NA) (NA) 1960 1960 (NA) 1976 (NA)
Chad..................... 1964 1964 (NA) 1964 1964 (NA) 1963-64 1964
The Gambia............... (NA) 1973 1973 (NA) (NA) (NA) 1973 1973
Guinea-Bissau............. (NA) (NA) (NA) (NA) (NA) (NA) (NA) (NA)
Mali...................... 1960-61 1976 1976 1976 1976 1976 1960-61 1960-61
Mauritania............... 1977 (NA) (NA) 1965 (NA) 1965 1965 1965
Niger..................... 1977 (NA) (NA) 1977 1977 1960 1960 1960
Senegal.................. (NA) (NA) 1971 1970 1970 (NA) 1973-78 1970-71
Upper Volta.............. 1975 (NA) 1975 1975 1975 1975 1960-61 1960-61

COASTAL WEST AFRICA

Benin..................... 1961 1961 1961 1961 1961 1961 1961 (NA)
Ghana.................... 1971 1970 1970 1970 1971 1970 1970 1970
Guinea................... (NA) 1954-55 (NA) 1954-55 1954-55 1954-55 (NA) (NA)
Ivory Coast.............. 1975 (NA) 1975 1975 (NA) (NA) (NA) (NA)
Liberia .................. 1974 1974 (NA) 1974 1974 1974 1970-71 1970-71
Nigeria.................. 1971-73 (NA) (NA) (NA) (NA) (NA) 1971-73 1971-73
Sierra Leone............. 1963 1963 1963 1963 (NA) (NA) 1974 1974
Togo..................... 1970 1970 1970 1970 1970 (NA) 1970 1961

CENTRAL AFRICA

Burundi.................. 1970-71 1970-71 (NA) 1970-71 1970-71 (NA) 1970-71 1970-71
Cameroon................. 1976 1976 (NA) 1976 1976 (NA) 1976 1976
Rwanda.................. 1970 (NA) 1970 1970 1970 (NA) 1970 1970
Sao Tome and Principe.... (NA) (NA) (NA) (NA) (NA) (NA) 1973-79 (NA)
Zaire ................... 1955-57 1955-57 (NA) 1955-57 1955-57 (NA) 1955-57 (NA)

EASTERN AFRICA

Djibouti................. (NA) (NA) (NA) (NA) (NA) (NA) (NA) (NA)
Ethiopia.................. 1970 (NA) (NA) 1970 (NA) 1970 1968-71 (NA)
Kenya.................... (NA) (NA) 1969 (NA) 1969 1961 1977 1977
Madagascar................ (NA) (NA) (NA) (NA) (NA) (NA) 1975 (NA)
Mauritius................. 1962 1972 1972 1972 1972 1972 1981 1971-73
Seychelles............... 1960 (NA) (NA) 1977 1960 (NA) 1980 1974-78
Somalia .................. (NA) (NA) (NA) (NA) (NA) (NA) (NA) (NA)
Sudan................... 1973 1973 1973 1973 1973 1973 1972-73 1968-73
Tanzania................. 1967 1967 1967 1967 1967 (NA) 1973 (NA)
Uganda................... (NA) 1969 1969 (NA) 1969 (NA) 1969 1969


Women of the World


12 Sources of Data








Table 2.2. Availability and Recency of Statistics, by Country and Subject-Continued


Life
Internal Head of expec-
Region and country Enroll- migra- Economic Marital house- Fer- tancy
Literacy ment tion activity status hold utility atbirth

SOUTHERN AFRICA

Angola (NA) (NA) (NA) 1970 (NA) (NA) (NA) (NA)
Botswana 1964 1971 (NA) 1971 1971 (NA) 1971 1964-71
Lesotho 1966 1966 (NA) 1966 1966 (NA) 1971 (NA)
Malawi (NA) 1977 (NA) 1977 1977 1970-72 1977 (NA)
Mozambique 1970 (NA) (NA) 1970 1970 (NA) 1970 (NA)
Swaziland (NA) 1976 1966 1976 (NA) (NA) 1976 1966-76
Zambia 1969 1969 (NA) 1969 1969 (NA) 1969 1969
Zimbabwe (NA) 1969 1969 1969 (NA) (NA) 1969 (NA)

Note: Reference years shown in this table usually refer to national-level data that are avail-
able in sufficient detail to be included in the tables of this handbook. On the rural/urban level,
considerably less information is available on most topics.


Women of the World


Sources of Data 13








Women of the World 15


Chapter 3











Ch@ n )g@


Because the changing situation of women must be seen in its
sociodemographic context, the analysis of data from the WID
Data Base begins with a description of the population of the Sub-
Saharan Africa region (excluding South Africa)-its size, growth,
composition, geographic distribution, change over time, and the
population processes responsible for those changes. After a
review of data availablility, chapter 3 characterizes the region's
population, drawing upon data from a number of sources.
Presentation of data describing the reference population of each
of the 40 individual countries follows. The data are illustrated
in tables and figures, and are discussed in the light of regional
trends. In considering components of population change, atten-
tion is given in this chapter to migration and its impact on the
situation of women, but detailed discussion of both fertility and
mortality is left for chapters 7 and 8.


Data Availability

The data presented in this chapter were selected on the basis
of the availability of detailed population counts by sex, age, and
rural/urban residence and of data on indicators of the status of
women, that is, education/literacy, employment, mortality, and
so forth, for approximately the same time period. Thus they serve
as a set of reference populations for subsequent analysis. Most
come from the 1970 round of censuses and/or surveys, and
represent the most complete, but not necessarily the most-
recent data. For the discussion of population growth and rates
of urbanization, however, data are presented from the two most
recent censuses or surveys.
Population totals are available for each of the 40 countries,
and totals by sex for all but two. Nearly all countries have data
by sex and age for at least one time period; many have such
data for two dates, and a few for three. Close to two-thirds of
the countries have tabulated data by age and sex separately for


rural and urban areas. Beyond these basic tabulations, however,
the countries differ considerably in the availability of detailed
population data. More than a third of the countries have not
published information on the composition of the population with
respect to race or ethnic group, nationality, language, or religion,
and almost none have information on income.


Overview

The Sub-Saharan Africa region contains 16 percent of the
world's continental land mass but, in 1983, only 8 percent of
its population, an observation which has led some to conclude
that the region is too sparsely populated for optimum economic
development (Okediji and Bahri, 1974). However, such a con-
clusion would seem to discount the region's extraordinary varia-
tion in climate, terrain, and ecology, and its potentially rich
resource base. Population density varies widely with the land
and the climate, ranging from nearly 500 persons per square mile
in agriculturally fertile Rwanda and Burundi to fewer than 4 in
arid or semiarid Botswana and Mauritania, where livestock forms
the basis of the economy.' Population growth rates in the region
are almost uniformly high. Recent estimates place the 1982-83
growth rate for the world at 1.8 percent, and at 2.1 percent for
the developing countries as a group, while for the same period
the growth rate for all of Africa is estimated at 3.0 percent. For
the population residing in the 40 Sub-Saharan African countries
of this study, the rate was higher still, 3.1 percent. Of these, Chad
and Kenya are estimated to have current population growth rates
of more than 4 percent, among the highest in the world (U.S.
Bureau of the Census, 1983).

'Statistics presented in this overview of the Sub-Saharan Africa region
as a whole and its place in the developing world have come from statistical
series prepared by the Population Reference Bureau (1980); the U.S. Bureau
of the Census (1977, 1978, 1979, 19,81, 1982, and 1983c; and the World
Bank (1980a, 1980c, 1981, and 1982).






1 6 Population Distribution and Change Women of the World


These high growth rates are the combined result of continu-
ing high fertility in most countries and relatively high but falling
mortality in virtually all. With the exception of the island coun-
tries of Cape Verde, Mauritius, and the Seychelles, all the study
countries continue to have crude birth rates at or above 40 per
1,000 population, and close to one-half have rates of 48 and
over. Most show current crude death rates in the range of 18
to 22 per 1,000 population, down roughly 7 to 8 points since
1960. With the exception again of the island countries and a
few others, estimated infant mortality rates are greater than 100
deaths per 1,000 live births, and life expectancies at birth are
under 50 years. Such a demographic pattern means that the
population of Sub-Saharan Africa is a young one; approxi-
mately 45 percent are under 15 years of age, 52 percent are
between ages 15 and 64 years, and only 3 percent are age 65
years or over (United Nations, 1982).
The population of the continent is also a diverse one, and
relatively few of the countries are homogeneous with respect
to ethnicity, language, culture, or religion. During its long period
of development, Africa has generated a very large number of
language groups and nationalities, each with its own culture and
way of life. Onto these, as a result of influences coming from
both the Arab world and the West, additional religious, linguistic,
and cultural differences have been grafted.
When the colonial powers carved up the continent, they did
so with little reference to the existing distribution of nationalities
or of religious or linguistic communities. At independence, the
new nation states maintained the former colonial boundaries in
most cases, and as a consequence some nationalities have been
divided among several countries, while most countries try to
reconcile the conflicting interests of a number of distinctly dif-
ferent micronations into a single national identity. Conflict and
tension have been the inevitable result and have on occasion
erupted into civil war.
Most of the countries are heavily rural, but urban populations
are growing rapidly. Urban dwellers in Sub-Saharan Africa in-
creased their share of the estimated population from only 18 per-
cent in 1970 to 24 percent by 1980. This percentage is smaller
than the 31 percent which is the 1980 average for the develop-
ing countries taken as a group; nevertheless Sub-Saharan Africa
is rapidly closing the gap with a 1970-80 annual rate of urban
growth of 5.5 percent, a rate 1.4 times the average for all
developing countries during the same period (United Nations,
1982).
Much of this growth must be attributed to natural increase.
The World Fertility Survey, although limited to a very few coun-
tries in the region,2 has confirmed the impression from other
studies that urban fertility, particularly among younger women,
is nearly as high as that in the rural areas, while urban infant
and child mortality rates tend to be lower. However, migration
from the smaller towns and the rural areas also is responsible
for much of the rapid increase in urbanization seen over the past
two decades, especially in West Africa where population


2Sub-Saharan African countries for which reports are available from the
World Fertility Survey are Kenya, Lesotho, Senegal, and Sudan (see World
Fertility Survey, 1981a, 1981b, 1981c, and 1982).


mobility is particularly high and there is a long-standing urban
tradition.
The temporary migration of labor, both internal and inter-
national, particularly in West Africa and in Southern Africa, is
a second major component in a continuous redistribution of
population in the region.3 A third, the unfortunate result of severe
and persistent drought, in some cases combined with civil con-
flict, is the flight and resettlement of refugees and the homeless
in the Sahel, in the Horn of Africa,4 and in parts of Southern
Africa. Finally, there are the movements of the nomadic peoples
of the arid and semiarid zones who traverse the region, often
crossing national boundaries on seasonal or longer cycles.
Women are affected by all this movement in two ways. There
is first the impact upon the women who move, whether in search
of better opportunities or in flight from disaster. And there is
the impact of male labor migration upon the women who are
left behind to cope however they can with the family farm and
the children, often with few resources and no decision-making
authority. Both kinds of mobility tend to result in households
which are headed by women. In the countries of Sub-Saharan
Africa, as elsewhere, such households tend to be more
vulnerable to economic hardship.5
As a consequence of this continual shifting of populations,
most African countries are more concerned about issues of
population distribution than of population size or national rates
of growth, and nearly all have instituted policies designed to slow
or to redirect these movements. All have policies and programs
to reduce mortality, particularly that of infants and young
children. Only about one-fourth of the governments have taken
any action designed specifically to reduce fertility, although in
most countries family planning, particularly for child spacing,
may be included among the services offered to women in both
private and government health centers. Rates of contraceptive
use are extremely low, generally under 8 percent at the national
level; urban rates are somewhat higher (Nortman, 1982). It is
reasonable to assume, therefore, that the regional population
trends of the past two decades will continue with relatively
little change through the 1980's. However, as the governments
of the region come under increasing pressure from the develop-
ment implications of a rapidly growing number of children to be
educated and youth to be employed, more of them may begin
to institute policies designed to retard the pace of childbearing.
Nevertheless, it would be unrealistic to expect dramatic shifts
during the current decade in the population processes and
national priorities reviewed above. Estimates and projections of
the population size and components of change for the region
as prepared by the United Nations for the period 1960 to 2025
are illustrated in figure 3.1.



3For discussions of labor migration in Sub-Saharan Africa, see Caldwell
(1969), Carter and O'Meara (1977), Gordon (1981), Grundy (1973), Hance
(1971 and 1975), Little (1973), Smith, Khoo, and Fawcett (1983), Wilson
(1972), and World Bank (1980a and 1980b).
'The Sahel includes Cape Verde, Chad, The Gambia, Guinea-Bissau, Mali,
Mauritania, Niger, Senegal, and Upper Volta; the Horn of Africa includes
Djibouti, Ethiopia, and Somalia.
'For discussions of the impact of migration on women, see Caldwell (1969),
Caplan (1981), Gordon (1981), Little (1973), and World Bank (1980b).


16 Population Distribution and Change


Women of the World







Woman of the World Population Distribution and Change 1 7


Population Size

The 40 countries in this study range in size from the
Seychelles, with an estimated population of 65,000, to Nigeria,
with an estimated 85 million inhabitants in 1983. In table 3.1,
population estimates from the reference data set are presented
for each country, for the total country and separately by sex,
together with the corresponding sex ratio (males per 100
females) and the female share of the population, that is, the per-
cent female. Table 3.2 and figure 3.2 show the latest midyear
population estimates for the 40 countries for the period 1960
to 1985 (U.S. Bureau of the Census, 1983c). In these and in
all subsequent tables and figures, the countries are grouped by
geographic subregion and listed alphabetically within subregions
(except in figure 3.3, where countries are ranked by population
size). The subregional classification is that used by the U.S.
Agency for International Development and reflects a reasonable
degree of both cultural and ecological homogeneity. The distribu-
tion of the subregional populations is shown graphically in figure
3.3.


Composition by Sex

Sex ratios show considerable intercountry variation. Estimates
of males and females (U.S. Bureau of the Census, 1979) yield
sex ratios of 99.9 for the world, 93.7 for the more developed
countries, 102.4 for the less developed countries, and 99.0 for
the continent of Africa. Sex ratios in the reference data of this
study range from a low of 76.1 in Lesotho in 1966, to a high
of 108.3 in Somalia in 1975. The Lesotho figure reflects the high
male labor migration to the Republic of South Africa, estimated
at 12 percent of the male population, as do the relatively low
ratios of Botswana and Swaziland. The ratio of 86.5 for Cape
Verde too is probably due to male labor emigration. Con-
versely, the high ratio in the Ivory Coast in 1975 reflects the
effect of high male labor immigration; labor was drawn to that
country during its rapid economic expansion in the 1970's.
Specific reasons for high sex ratios in Somalia and Angola are
unknown; they may reflect data collection problems under con-
ditions of civil instability. Estimates by sex are unavailable for
Djibouti, and available only for the rural population of Mauritania.
Sex ratios for the remaining countries are in the more common
range of 90 to 103. Ratios for the individual countries with
fairly recent data are illustrated in figure 3.4.


Composition by Age

As noted, the regional population is young with an average
of 44.5 percent under 15 years of age, 52 percent in the work-
ing ages of 15 to 64 years, and only 3.5 percent are 65 years
or over. There is some variability in these proportions. The pro-
portion of children ranges from a low of 37 percent in Sierra
Leone (1963) to a high of 51 percent in Rwanda (1970); of the
working ages from 46 percent in Togo (1970) to 58 percent in
Sierra Leone (1963); of the elderly from 1.5 percent in Rwanda
(1970) to 7 percent in Lesotho (1966).
From the standpoint of development planning, proportions of
the elderly do not constitute a major constraint in any of the 40


countries. Rather, it is the relative proportions of the young and
those of working age in these countries that are likely to have
an impact upon development prospects, and the African regional
youth-dependency burden is a relatively unfavorable one. Within
the region, there are slight differences in age distribution, with
over three-fourths of the countries falling into one of two age
patterns. In the first, the proportion under age 15 is below the
average of about 44.5 percent, while the proportion of working
age is average or above, that is, 52 percent or higher. The
second pattern is the obverse of the first; the proportion under
age 15 is average or above, while the proportion of working age
is below average. The 14 countries with the first pattern, show-
ing a lower youth-dependency burden, have an age distribution
which is relatively more favorable for economic development.
The 14 countries with the second pattern are at a relative
disadvantage.


Low percentage of
population under 15
years, high percent-
age 15 to 64
years


Cape Verde
The Gambia
Mali
Senegal
Guinea
Liberia
Nigeria
Sierra Leone
Burundi
Cameroon
Zaire
Madagascar
Mauritius
Seychelles


High percentage of
population under 15
years, low percent-
age 15 to 64
years

Chad
Upper Volta
Benin
Ghana
Togo
Rwanda
Kenya
Sudan
Uganda
Botswana
Malawi
Swaziland
Zambia
Zimbabwe


Seven countries fall outside the two modal groups. In three,
Sao Tome and Principe, Tanzania, and Lesotho, the proportions
of children and of the working age population are both below
average, while the percentages of elderly (4.6, 5.6, and 6.6 per-
cent, respectively) are well above. And in four, Niger, Ivory
Coast, Angola, and Mozambique, proportions under 15 years
and 15 to 64 years are both above average; percentages of
elderly (2.9, 2.0, 2.6, and 2.0 percent, respectively) are of
course smaller than average. Data by age are unavailable for the
remaining countries.


Distribution by Age and Sex

When age distributions are computed separately by sex, for
most countries overall patterns remain the same for the three
broad age groups considered in the previous section; a few dif-
ferences emerge, due perhaps to imbalances introduced into the
sex ratios of the population of working age by male labor migra-
tion across national boundaries, as well as to problems within
the data.
More detailed age breakdowns can be useful in identifying the
age/sex pool of potential candidates for important life stage
activities. In tables 3.3 and 3.4, percentages of the population
in selected age groups are presented separately for women and
men. For men, tabulation of reproductive age is omitted. Figure


Women of the World


Population Distribution and Change 17





Women of the World


18 PoDulation Distribution and Change


3.5 illustrates these age distributions for women; in examining
this figure, reference should be made to the data and notes of
table 3.3 for identification of those countries using nonstandard
age groups.
Although data by age and sex are available for most of the
40 countries, comparability is difficult because not all have
tabulated the data by standard 5-year age groups. Moreover,
the degree of uncertainty in the reporting of ages and the
extent of undercounting, particularly of young females, in the
different countries is unknown, although it is likely to vary con-
siderably. Such data problems show very quickly in aberrant per-
cent distributions of age by sex, and particularly when sex ratios,
that is, measures of the relative numbers of each sex, for the
different age groups are examined.
For most countries, these age distributions by sex follow a
common pattern in which higher proportions of males than
females are found in the younger age groups and to some
extent among the elderly, while higher proportions of the female
population are in the working ages. Where the age distribution
by sex departs from the expected pattern, it may reflect the
presence of a large number of male working age immigrants
which shifts the male age distribution toward the middle years.
Sex ratios for each of the selected age groups are highly
variable, due in large part to differential undercounting by sex
and to age misreporting. To the extent that the variability in sex
ratios of the working age population reflects real differences,
it is probably due primarily to higher male labor migration; inter-
country differentials in mortality by sex are likely to be of only
secondary importance.


Cultural Diversity

In nearly two thirds of the countries, total counts have been
tabulated for the many ethnic groups which make up their
population. For the former Portuguese dependencies, counts are
made for blacks, whites, mixed and others. In Eastern and
Southern Africa, counts are made for Africans, sometimes by
specific ethnic group, and Europeans, Arabs, and Asians, also
sometimes by specific origin. In the countries of Central and
West Africa, more detailed tabulation of African ethnic groups
are common; the number of separate groups identified may be
as few as two (Djibouti, 1967), or as many as 36 (Togo, 1970).
In most countries, substantial fractions of the population
subscribe to each of the three major religious traditions of the
region: Islam, Christianity, and the several forms of traditional
religion, sometimes referred to as Animism. Data on religious
affiliation are found in the WID Data Base for 11 of the 40 coun-
tries. In only four of these are the populations religiously
homogeneous: Cape Verde and Lesotho (Christian), and
Mauritania and Rwanda (Muslim). In the remaining seven, the
three major groups are represented in substantial numbers. Of
the total population represented by these 11 countries, 32 per-
cent are Muslim, 29 percent are Christian, 20 percent follow one
of the traditional religions, and 19 percent report another or no
religious affiliation. Although religious differences have been
divisive in the region in the past, they are not generally a major


problem now except where they have also taken on an ethnic
character.6
Eight countries report data on nationality. Most of the foreign
nationals are urban residents; in these data they constitute
anywhere from 2 percent (Benin, 1961) to 34 percent (Ivory
Coast, 1975) of the urban population. Periodically, a wave of
national chauvinism may break out, as in the case of Nigeria in
early 1983, sending foreign nationals back to their countries of
origin. Usually, however, the immigrants play an important role
in the national economy and their presence is tolerated without
major incident.
Only five of the countries have published data on primary
language group; as many as 14 different African languages or
dialects may be tabulated for a single country. Other languages
recorded include English, French, Portuguese, Arabic, Chinese,
and six different languages from the Indian subcontinent.7 These
data are of interest in illustrating the diversity which can be found
in Sub-Saharan African countries, but they are of little use in
indicating the extent to which the population, especially the
female population, is fluent in one or more of the languages of
government and commerce.


Rural/Urban Differences in Distribution by
Age and Sex

Rural and urban populations differ considerably in their com-
position by age and sex. Tables 3.5 and 3.6 show sex ratios
for the selected age groups separately for rural and urban areas,
for the 26 countries for which such data are available in the
reference data set. In the rural areas, pre-school age girls out-
number boys in 55 percent of the countries; in urban areas in
only 40 percent. In rural areas, primary school-age girls (5 to
9 years) outnumber boys in only 20 percent of the countries;
in urban areas in 60 percent of the countries.
In none of the countries do older rural school-age girls (10 to
14 years) outnumber boys; however, the number of rural young
women of 15 to 19 years exceeds that of young men in two-
thirds of the countries. Such a wide swing is probably the result
of age misreporting among women, reflecting the common
tendency in rural areas to ascribe older ages to young married
women. In contrast, in urban areas the number of girls and young
women exceeds that of boys and young men in both of these
age groups in one half or more of the countries: for the 10 to
14 year olds, in 65 percent of the countries, and for the 15 to
19 year olds, in 50 percent of the countries.
In rural areas, the number of women of working age exceeds
that of men in virtually all countries, while in urban areas women
outnumber men in only 10 of the 26 countries, again probably
the result of higher male rural-to-urban migration. Finally, among
the elderly, in rural areas women outnumber men in one-fifth
of the countries; in urban areas, in two-fifths of the countries.

6Many observers attribute the current struggle in Chad to the combined
result of religious and ethnic divisions between the Arab and Islamic north
and the largely black and Animist south. Since, however, these religions co-
exist in reasonable harmony across the rest of Africa, it may be reasonable
to infer that the difficulties arise primarily from ethno-political factors which
religious differences may exacerbate but do not create.
7For an account of the practical difficulties which this language diversity
can create for data gatherers, see Ware (1977).








Women of the World Population Distribution and Change 19


To summarize, in most countries elderly men outnumber
elderly women in both rural and urban areas. For ages under 65
years, rural females outnumber rural males in most countries
except during the school ages (5 to 14 years); conversely,
urban males outnumber urban females except during the school
ages (5 to 14 years), and during the late teens (15 to 19 years)
when the number of urban young men exceeds that of urban
young women in one-half of the countries.



Urbanization

Although the urban areas are growing rapidly, the population
of Sub-Saharan Africa is still primarily rural. Only 28 of the
world's cities of more than 500,000 population can be found
in the region, and a mere 17 percent of the estimated 1980
population was living in urban areas of any size (World Bank,
1982). There is considerable variation among the countries in
percent urban. Table 3.7 presents the percent of the population
residing in urban areas, by sex, for the two most recent cen-
suses or surveys, and the female/male ratio of those percentages
for each date.
At the earlier time, the proportion urban ranged from a low
of 1.1 percent in Niger (1960) to a high of 32.9 percent in
Mauritius (1962). At the later time, the range was from 3.2 per-
cent in Mozambique (1970) to 42.9 percent in Mauritius (1972).
Africa has some very old cities, many of which have been
inhabited continuously; among these, Timbuktu in Mali and Kano
in Nigeria are perhaps the best known (see Bovill, 1968; David-
son, 1959; and Hull, 1976). However, the more recent explosive
growth has come primarily in the capital cities such as Lagos,
Kinshasa, and Nairobi.
Men have contributed disproportionately to that growth;
nevertheless the data indicate that, with the exception of
Zimbabwe, for which data are incomplete, many women have
participated in the urbanization process. Most of the female/male
ratios of the percent urban are 0.90 or above, and in several
countries the ratio is greater than 1.00. Figure 3.6 illustrates the
percent of women living in urban areas at the time of the two
most recent censuses, and figure 3.7 shows the female/male
ratio of the percent urban for the latest available year.
As noted, women in cities have an age distribution which dif-
fers from that of men, with relatively higher proportions of
women than men in the working ages. Sex ratios for the work-
ing ages and the elderly, by rural/urban residence, are illustrated
in figure 3.8.
Women in the cities also have an age distribution which dif-
fers from that in the rural areas, although the pattern varies
somewhat by geographic subregion. Table 3.8 shows the per-
cent distribution of women in the reference populations by age
group, separately by rural and urban residence. In West and Cen-
tral Africa, the proportion of females under age 15 is generally
slightly higher in the cities than in the rural areas, while in Eastern
and Southern Africa it is usually lower. The proportion age 50
and over tends to be higher in the rural areas in all subregions.
And except in the Sahel, the proportion in the active ages (15
to 49 years) tends to be somewhat higher in the urban areas
than in the rural. On balance, therefore, the female age distribu-


tion in the cities is a younger one than that in the rural areas,
although it is older than that of urban males.


Migration

In describing the population of Sub-Saharan Africa in a
preceding section, the important role of population redistribu-
tion in shaping the policy concerns of the governments in the
region was stressed. There have been a number of case studies
documenting the extent of population mobility in and among
several countries of the region, the most notable of which are
the studies of the South African labor market with its flow of
working-age men from the surrounding countries, and the 1979
extensive World Bank sponsored review of migration in West
Africa.8 As already noted, there have been a few studies of
women migrants to urban areas and of the impact of male labor
migration in Southern Africa on the women left behind. Other
studies have focused on the nomadic populations or on refugees.
For discussions of pastoralism in Africa, see Hance (1971 and
1975); for an historical account of traders and nomads in the
Sahel, see Bovill (1968).
Yet, despite its importance, none of the countries in the region
has routinely published data on population mobility, whether
internal or international. At most, some of the countries have
made available data concerning the population currently residing
outside the province or country of birth, and/or data on nation-
ality. Table 3.9 presents the percent of the native population
who were residing outside the province of birth at the reference
date, table 3.10 shows the percent foreign born, and table 3.11
gives the overall percentage of in-movers (whether native or
foreign born) to the province of residence at the same date.
Figure 3.9 illustrates the percent of native and foreign-born
in-movers to the province of residence at the reference date.
The proportion of both female and male migrants among the
native population varies considerably from one country to
another. The female/male ratios of these proportions range from
a low of 0.66 in the Sudan to a high of 1.35 in Mauritius,
although 12 of the 16 countries with data show ratios greater
than 0.80. Female/male ratios among the foreign born are con-
siderably lower; 10 of the 18 countries with such data show
ratios smaller than 0.80. On balance, female/male ratios of per-
cent in-movers to the province of current residence at the
reference date confirm the impression from other studies that
migration is predominantly a male phenomenon. Nevertheless,
it is not overwhelmingly so; in all countries with such data,
women constitute at least 40 percent of all in-movers, and in
some cases there are more women than men among the
migrants.9
National boundaries, carved out by colonial rulers with little
regard to existing ethnic groups and patterns of population move-
ment, have for the most part had the effect of merely slowing
but neither stopping nor radically shifting the direction of Africa's
traditional mobility. In recent years, however, much of this move-
ment has been to the urban areas. To capture some measure

8See sources cited in footnote 3.
'For an example of a study which documents a recent increase in the flow
of women to the city of Dar-es-Salaam, see World Bank (1980b).


Women of the World


Population Distribution and Change 19






20 Population Distribution and Change


Women of the World


of the movement, table 3.12 shows the percent of the urban
population which was foreign born at the reference date, both
for the total population and separately by sex, for the eight coun-
tries with such data. While in most cases these data show that
larger proportions of urban men than women are foreign-born,


the differences are not large. Most female/male ratios of these
proportions are over 0.80. Only in Benin, however, is the pro-
portion of foreign-born women higher than that of foreign-born
men.







Women of the World Population Distribution and Change 21


Figure 3.1. Sub-Saharan Africa: Estimated and Projected Population
Size and Components of Change: 1960 to 2025


Population in
millions
1300


1200


1100


1000


900 -


800 -


700 -


600 -


500 -


400 -

Populatio
300 -


200


100


0
1960 1970


Rates per
thousand
population


1980 1990 2000 2010 2020
Year


Source: United Nations, 1982, pp. 64-175.


Birth rate


Death rate


Women of the World


Population Distribution and Change 21


in





Women of the World


22 Population Distribution and Change


Figure 3.2. Estimated and Projected Population:
1960, 1970, and 1985

1960 1970 1985


Millions


Millions
20



10



0
Cameroon Ivory Zimbabwe Angola Mali
Coast


Millions


Malawi Upper Zambia Senegal Somalia
Volta


Nigeria Zaire Ethiopia Tanzania Sudan Kenya Uganda Ghana Mozam- Mada-
bique gascar


80 o


40 I-






Women of the World Population Distribution and Change 23


Figure 3.2.


Estimated and Projected Population:
1960, 1970, and 1985--Continued

1960 1970 1985
1960 1970 1985


Millions


Niger Rwanda Guinea


Chad Burundi Benin


Sierra Togo Liberia Mauri-
Leone tania


Millions


Millions


Lesotho Botswana Mauri-
tius


Millions


Swazi- Cape
land Verde


Djibouti Sao TomeSeychelles
& Principe


Note: Countries are presented in rank order by population size in 1985.
Source: U.S. Bureau of the Census, 1983.


Guinea-
Bissau


Gambia


- I I I I I


Women of the World


Population Distribution and Change 23






24 Population Distribution and Change Women of the World


Figure 3.3. Population Distribution of Sub-Saharan African
Countries: 1983








8 percent in
9 countries
of Sahel
West Africa





9 percent
in countries
not included
in the analysis






11 percent in 8
countries of
Southern Africa




















* Handbook excludes 9 percent of the population of Sub-Saharan Africa. Of this,
7 percent refers to South Africa, which was excluded from the analysis, and
2 percent refers to eight countries not presently in the WID data base.


Source: U.S. Bureau of the Census, 1983.


Women of the World


24 Population Distribution and Change






Women of the World Population Distribution and Change 25


Figure 3.4. Sex Ratios of Total Population





Males per
100 females


Sahel West Africa


130

120

110

*100

90

80

70

60

50

40

30

20

10

0


Mali Niger Senegal Upper
1976 1977 1970 Volta
1975


Coastal West Africa


Ghana Ivory
1970 Coast
1975


Males per
100 females


Eastern Africa Southern Africa


Burundi Came- Rwanda Sao Tome Made- Mauri- Say- Somalia Sudan Angola Botswana Malawi Mozam- Swazi-
1970-71 roon 1970 & Principa gaacar tiua challes 1975 1973 1970 1971 1977 bique land
1976 1970 1975 1972 1977 1970 1976


* Number of males equals number of females.


Gambia Guinea-
1973 Bissau
1970


Liberia
1974


Togo
1970


130

120

110

*100

90

80

70

60

50

40

30

20

10

0


Women of the World


Population Distribution and Change 25










Figure 3.5. Percent of All Women in Selected Age Groups




0-14 15-49 50-64 65+
0-14 15-49 50-64 65+


Percent


Sahel West Africa


Coastal West Africa


Central Africa


Gambia Mali Niger Senegal Upper Ghana Ivory Liberia T ogo Burundi Came-
1973 1976 1977 1970 Volta 1970 Coast 1974 1970 1970-71 roon
1976 1975 1976


Rwanda Sao T ome
1970 & Principe
1970


Percent


Eastern Africa


Madagascar Mauritius Seychelles Sudan
1975 1972 1977 1973


L


Southern Africa


h


h


Angola Botswana Malawi Mozambique Swaziland
1970 1971 1977 1970 1976


40 F


50 -


26 Population Distribution and Change


Women of the World






WIe fteWrdPpltonDsrbto n hne2


Figure 3.6. Percent of Women Living in Urban Areas,
Latest Two Censuses


Earlier Later
census census


Percent
100 r


Sahel West Africa


Mali Niger
1960-61/76 1977


Coastal West Africa


m


Benin Ghana Guinea Ivory
1961 1960/70 1954-55 Coast
1975


Liberia
1962/74


i1 I
Nigeria Sierra
1963 Leone
1963


90-

80-

70-

60-

50

40

30-


Chad
1964


Gambia
1963/73


Percent


Senegal
1970


80 -


Upper
Volta
1975


60 -

50

40 -

30

20


Togo
1961/70


Women of the World


Population Distribution and Change 27


la





28 Population Distribution and Change Women of the World


Figure 3.6. Percent of Women Living in Urban Areas,
Latest Two Censuses--Continued


Earlier Later
census census


Percent


Central Africa


Eastern Africa


_1I


Burundi Cameroon Rwanda
1965 1976 1970


MI.


Sao Tome Zaire
& Principe 1955-57
1970


. I


Ethiopia Kenya
1968 1969


Masda Mauri- Sey-
Gascar tius Chelles
1975 1972 1971/77


IJmL
Sudan Tanzania Uganda
1973 1967 /78 1969


Percent
100 r


Southern Africa


Malawi Zambia
1977 1974


60 -
50
40
30
20


90 -
80 -
70 -
60 -
50 -
40


Botswana
1971


Zimbabwe
1969


28 Population Distribution and Change


Women of the World







Women of the World Population Distribution and Change 29


Figure 3.7. Female/Male Ratio of Percent Urban


Sahel West Africa


1.3

1.2

1.1

1.0

0:9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0.0


Coastal West Africa


Ghana Ivory
1970 Coast
1975


Liberia Togo
1974 1970


F/M ratio
(male=1.0)


Central Africa


Eastern Africa


Southern Africa


0.0 '
Came- Rwanda Sao Tome Mada-
roon 1970 & Principe gascar
1976 1970 1975
* Female percent equals male percent.


Mauri- Sey- Sudan Tanzania Bot- Malawi Zambia
tius chelles 1973 1978 swana 1977 1974
1972 1977 1971


F/M ratio
(male=1.0)


Niger Senegal Upper
1977 1970 Volta
1975


Gambia
1973


Mali
1976


1.3

1.2

1.1

*1.0

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1


Women of the World


Population Distribution and Change 29












Figure 3.8. Sex Ratio of the Population in Two Age Groups,
by Rural/Urban Residence


Rural Urban Rural Urban
15-64 65+


Men per
100 women
160 r-


Sahel West Africa


Coastal West Africa


Mali Senegal
1976 1970


140 h-


Central Africa


120-

*100

80

60

40

20

0
Cameroon
1976


Eastern Africa


Rwanda Madagascar Mauritius
1970 1975 1972


Southern Africa


Sudan Botswana
1973 1971


* Number of men equals number of women.
'See footnotes to table 3.5 for nonstandard age groups.


140

120


*100

80

60

40

20

0


Gambia
1973


Ivory
Coast
1975


Upper
Volta'
1975


Men per
100 women


Ghana
1970


Liberia
1974


Togo
1970


Malawi
1977


30 Population Distribution and Change


Women of the World





Population Distribution and Change 31


Figure 3.9. In-Movers to Province of Current Residence, by Sex



Native-born Female Male


Percent
50 r Sahel
West Africa
45


Coastal
West Africa


Gambia Mali Upper
1973 1976 Volta
1975


Ghana Ivory
1970 Coast
1975


ULIL
Togo Rwanda Mauritius
1970 1970 1972


Foreign-born


Sahel
West Africa V












Gambia Mali Ghana
1973 1976 1970


Coastal
lest Africa


Central
Africa


Eastern
Africa


Southern
Africa


Ivory Liberia Cameroon Rwanda Seychelles Malawi
Coast 1974 1976 1970 1977 1977
1975


40 F


30 [


Central
Africa


Eastern
Africa


Percent


Sudan
1973


40 [


20


Women of the World









Table 3.1. Total Population, by Sex, Sex Ratio, and Percent Female
(Population in thousands)


Sex Percent
Region and country Year Total Female Male ratio female


SAHEL WEST AFRICA

Cape1Verde.............. 1960 200 107 93 86.5 53.6
Chad ................... 1964 2,524 1,326 1,198 90.3 52.5
The Gambia.............. 1973 494 243 250 103.0 49.3
Guinea-Bissau........... 1970 487 250 237 94.8 51.3
Mali.................... 1976 6,395 3,271 3,124 95.5 51.2
Mauritania ............. 1965 1,050 (NA) (NA) (NA) (NA)
Niger................... 1977 5,098 2,584 2,514 97.3 50.7
Senegal................. 1970 3,957 2,008 1,949 97.0 50.8
Upper Volta............. 1975 5,638 2,811 2,827 100.6 49.9

COASTAL WEST AFRICA

Benin .................. 1961 2,082 1,062 1,021 96.1 51.0
Ghana................. 1970 8,697 4,312 4,385 101.7 49.6
Guinea................. 1954-55 2,570 1,347 1,223 90.8 52.4
Ivory Coast............. 1975 6,714 3,229 3,485 107.9 48.1
Liberia................. 1974 1,556 769 787 102.3 49.4
Nigeria.................. 1963 55,670 27,558 28,112 102.0 49.5
Sierra Leone............ 1963 2,180 1,099 1,081 98.4 50.4
Togo.................... 1970 1,950 1,012 937 92.5 51.9

CENTRAL AFRICA

Burundi................. 1970-71 3,400 1,782 1,618 90.8 52.4
Cameroon................ 1976 7,661 3,840 3,821 99.5 50.1
Rwanda.................. 1970 3,573 1,815 1,757 96.8 50.8
Sao Tome and Principe... 1970 74 37 37 101.1 49.7
Zaire.................... 1955-57 12,734 6,551 6,182 94.4 51.4

EASTERN AFRICA

Djibouti................. 1970-71 164 (NA) (NA) (NA) (NA)
Ethiopia................. 1968 23,662 11,665 11,997 102.8 49.3
Kenya................... 1969 10,943 5,537 5,406 97.6 50.6
Madagascar.............. 1975 7,569 3,823 3,745 98.0 50.5
Mauritius............... 1972 851 425 426 100.2 50.0
Seychelles.............. 1977 62 31 31 101.6 49.6
Somalia................. 1975 3,494 1,677 1,817 108.3 48.0
Sudan................... 1973 14,114 6,976 7,138 102.3 49.4
Tanzania................ 1967 12,306 6,290 6,016 95.6 51.1
Uganda.................. 1969 9,549 4,730 4,818 101.9 49.5


See footnotes at end of table.


32 Population Distribution and Change


Women of the World









Table 3.1. Total Population, by Sex, Sex Ratio, and Percent Female-Continued
(Population in thousands)


Sex Percent
Region and country Year Total Female Male ratio female


SOUTHERN AFRICA

Angola................ 1970 5,250 2,526 2,724 107.8 48.1
Botswana.............. 1971 603 326 277 85.1 54.0
Lesotho2.............. 1966 852 484 368 76.1 56.8
Malawi................ 1977 5,548 2,874 2,674 93.0 51.8
Mozambique............ 1970 8,169 4,130 4,038 97.8 50.6
Swaziland............. 1976 494 263 232 88.3 53.1
Zambia................ 1969 4,057 2,070 1,987 96.0 51.0
Zimbabwe.............. 1969 5,099 2,532 2,567 101.4 49.7


Note: Data for Botswana, Cameroon, Ghana, Ivory Coast, Kenya, and Liberia represent adjusted
census/survey information. All other figures are unadjusted. The sex ratio in this table refers to
the number of males per 100 females.

1Excludes persons not covered by respective national demographic surveys. Estimated total numbers
of excluded persons are 730,000 in Chad, 88,000 in Mauritania, and 23,000 in Benin.
2Excludes absentee workers estimated to comprise 12 percent of Lesotho's total population.


Women of the World


Population Distribution and Change 33






34 Population Distribution and change Women of the World


Table 3.2. Total Population: 1960 to 1985
(Midyear population in thousands)


Annual
rate of
growth,
Region and country 1980
to 1985
1960 1965 1970 1975 1980 1985 (percent)


AHEL WEST AFRICA

Cape Verde................ 197 232 269 280 289 304 1.0
Chad...................... 3,014 3,338 3,707 4,134 4,416 5,246 3.4
The Gambia ................ 357 404 458 521 591 672 2.6
Guinea-Bissau............. 617 604 620 681 784 858 1.8
Mali....................... 4,559 5,035 5,578 6,200 6,914 7,735 2.3
Mauritania................ 1,066 1,155 1,254 1,369 1,502 1,656 1.9
Niger...................... 3,105 3,561 4,100 4,741 5,528 6,495 3.2
Senegal................... 3,270 3,744 4,318 4,989 5,765 6,755 3.2
Upper Volta............... 4,430 4,762 5,163 5,597 6,138 6,907 2.4

COASTAL WEST AFRICA

Benin..................... 2,055 2,311 2,623 3,002 3,465 4,033 3.0
Ghana..................... 6,958 8,010 8,789 10,308 12,130 14,254 3.2
Guinea................... 3,213 3,519 3,921 4,416 5,014 5,734 2.7
Ivory Coast............... 3,565 4,290 5,427 6,758 8,054 9,472 3.2
Liberia................... 1,055 1,209 1,397 1,624 1,898 2,232 3.2
Nigeria................... 42,367 48,676 56,346 65,663 77,082 91,178 3.4
Sierra Leone.............. 2,290 2,484 2,727 3,041 3,429 3,909 2.6
Togo...................... 1,456 1,648 1,964 2,247 2,580 3,003 3.0

CENTRAL AFRICA

Burundi................... 2,864 3,221 3,589 3,744 4,204 4,826 2.8
Cameroon.................. 5,609 6,104 6,727 7,522 8,582 9,770 2.6
Rwanda................... 3,037 3,269 3,785 4.367 5,114 6,036 3.3
Sao Tome and Principe..... 63 69 74 79 85 90 1.1
Zaire..................... 16,151 18,651 21,638 25,009 28,624 33,092 2.9

EASTERN AFRICA

Djibouti.................. 78 111 158 208 279 293 1.0
Ethiopia.................. 20,093 22,550 25,299 28,210 29,790 32,716 1.9
Kenya ..................... 8,157 9,549 11,256 13,481 16,431 20,177 4.1
Madagascar................ 5,482 6,070 6,766 7,604 8,665 9,909 2.7
Mauritius................. 663 756 830 883 957 1,034 1.5
Seychelles................ 42 47 53 59 63 67 1.1
Somalia................. 2,701 2,941 3,231 3,583 5,373 6,542 3.9
Sudan..................... 10,589 12,086 13,788 16,002 18,745 21,682 2.9
Tanzania.................. 10,328 11,673 13,446 15,850 18,618 21,902 3.2
Uganda.................... 7,286 8,432 9,806 11,080 12,806 14,732 2.8


34 Population Distribution and Change


Women of the World






Women of the World Population Distribution and change 35


Table 3.2. Total Population: 1960 to 1985-Continued
(Midyear population in thousands)


Annual
rate of
growth,
Region and country 1980
to 1985
1960 1965 1970 1975 1980 1985 (percent)


SOUTHERN AFRICA

Angola................... 4,797 5,125 5,573 5,951 6,979 7,981 2.7
Botswana.................. 552 587 650 754 899 1,075 3.6
Lesotho................... 859 952 1,067 1,195 1,339 1,512 2.4
Malawi.................... 3,450 3,914 4,449 5,162 6,021 7,056 3.2
Mozambique................ 7,584 8,428 9,442 10,553 12,103 13,994 2.9
Swaziland................ 340 386 440 504 579 671 2.9
Zambia................... 3,254 3,694 4,247 4,952 5,771 6,770 3.2
Zimbabwe .................. 4,011 4,685 5,546 6,554 7,556 8,952 3.4

Note: Slight discrepancies between the population totals shown in this table and those in table
3.3 are explained primarily by the different dates during the year to which the data refer. Figures
in table 3.1 refer to the respective census dates for each country, while those in table 3.2 all
refer to July 1.


Source: U.S. Bureau of the Census, 1983.


Population Distribution and Change 35


Women of the World









Table 3.3. Percent of Female Population in Selected Age Groups
(Percentages do not add to 100.0 because of overlapping categories)


Pre- Repro-
school School age ductive Working Elderly
age age age
Region and country ----
Oto4 5to9 10to14 15tol9 15to49 15to64 65years
Year years years years years years years andover


SAHEL WEST AFRICA

Cape Verde................ 1960 17.9 14.4 7.8 7.0 42.4 53.2 5.9
Chadl..................... 1964 18.4 16.3 6.8 7.1 50.5 55.1 3.4
The Gambia................ 1973 17.1 13.5 11.8 10.8 248.4 55.2 2.4
Mali....................... 1976 18.0 14.8 9.8 10.2 46.0 53.6 3.8
Niger...................... 1977 18.9 14.9 8.5 11.7 49.2 54.6 2.7
Senegal................... 1970 15.9 14.4 10.9 10.3 48.2 55.6 3.2
Uppper Volta.............. 1975 18.2 14.3 11.4 9.0 45.7 352.7 43.4

COASTAL WEST AFRICA

Benin..................... 1961 19.4 15.8 8.4 7.1 46.4 53.1 3.3
Ghana..................... 1970 19.2 15.0 12.0 10.1 44.1 50.9 2.9
Guinea................... 1954-55 17.5 14.5 6.8 9.5 51.8 58.1 3.0
Ivory Coast............... 1975 19.1 14.7 11.1 9.9 47.4 52.3 1.9
Liberia................... 1974 17.7 14.4 11.8 10.0 45.4 52.5 3.8
Nigeria................... 1963 17.6 14.8 9.7 10.0 52.3 56.2 1.7
Sierra Leone............... 1963 17.3 12.3 6.0 10.1 53.0 59.7 4.7
Togo...................... 1970 20.3 17.6 8.5 6.8 44.1 49.5 4.0

CENTRAL AFRICA

Burundi................... 1970-71 15.7 14.0 12.6 10.5 47.0 55.4 2.3
Cameroon.................. 1976 16.7 13.5 11.7 10.1 46.6 54.6 3.5
Rwanda.................... 1970 18.4 16.7 14.5 8.3 43.1 49.1 1.3
Sao Tome and Principe..... 1970 16.5 16.1 12.7 9.0 42.3 50.0 4.9
Zaire..................... 1955-57 16.8 12.8 8.2 7.2 248.9 562.2 (NA)

EASTERN AFRICA

Ethiopia.................. 1968 18.6 (NA) 627.4 (NA) 243.0 554.0 (NA)
Kenya ..................... 1969 18.5 16.1 12.9 9.9 42.9 49.7 2.8
Madagascar................ 1975 17.4 14.7 11.5 11.3 46.1 53.5 3.0
Mauritius................. 1972 12.3 14.3 13.3 12.1 47.1 55.6 4.3
Seychelles................ 1977 13.1 13.0 13.7 11.6 42.5 52.4 7.6
Sudan..................... 1973 17.1 17.0 10.6 8.8 47.1 52.6 2.6
Tanzania.................. 1967 17.7 15.4 9.4 9.1 45.9 52.4 5.1
Uganda................... 1969 19.6 15.5 11.1 8.8 43.6 50.3 3.4


See footnotes at end of table.


36 Population Distribution and Change


Women of the World










Table 3.3. Percent of Female Population in Selected Age Groups-Continued
(Percentages do not add to 100.0 because of overlapping categories)


Pre- Repro-
school School age ductive Working Elderly
age age age
Region and country -------
Oto4 5to9 10tol4 15to19 15to49 15to64 65years
Year years years years years years years and over


SOUTHERN AFRICA

Angola................... 1970 17.4 15.6 11.3 8.5 47.0 53.7 2.0
Botswana.................. 1971 17.6 14.4 12.2 10.1 42.8 50.2 5.5
Lesotho7.................. 1966 12.7 13.0 12.6 10.0 44.7 54.0 7.3
Malawi.................... 1977 19.2 14.5 9.6 9.7 45.1 52.1 4.4
Mozambique................. 1970 17.5 16.1 9.9 6.3 47.0 54.6 1.9
Swaziland................. 1976 17.2 15.2 12.9 10.9 44.7 50.7 3.7
Zambia................... 1969 18.4 15.8 10.7 8.9 46.3 52.1 1.9
Zimbabwe.................. 1969 16.8 17.1 13.4 10.1 45.1 49.9 2.1

Note: Data for Botswana, Cameroon, The Gambia, Ivory Coast, Kenya, Liberia, and Upper Volta are
based on adjusted or smoothed census/survey information. All other figures are based on unadjusted
data.

1Excludes consideration of persons not covered by respective national demographic surveys.
Estimated total numbers of excluded persons are 730,000 in Chad and 23,000 in Benin.
3Refers to ages 15 to 44 years.
4Refers to ages 15 to 60 years.
Refers to ages 60 years and over.
6Refers to ages 15 years and over.
Refers to ages 5 to 14 years.
Excludes consideration of absentee workers, estimated to comprise 12 percent of Lesotho's total
population.


Women of the World


Population Distribution and Change 37









Table 3.4. Percent of Male Population in Selected Age Groups
(Percentages do not add to 100.0 because of overlapping categories)


Preschool Worki ng
age School age age Elderly
Region and country
0 to 4 5 to 9 10 to 14 15 to 19 15 to 64 65 years
Year years years years years years and over


SAHEL WEST AFRICA

Cape Verde............ 1960 20.5 16.6 8.9 7.4 50.2 3.2
Chad1.................. 1964 20.5 19.6 10.1 6.3 46.1 0.4
The Gambia............. 1973 16.5 12.8 11.2 10.3 57.4 2.1
Mali................... 1976 18.8 15.8 11.0 9.9 50.7 3.8
Niger................... 1977 19.7 17.2 10.9 8.1 49.0 3.1
Senegal............... 1970 16.5 15.6 11.6 9.8 51.9 4.4
Upper Volta........... 1975 19.3 15.2 13.0 9.5 48.5 3.9

COASTAL WEST AFRICA

Benin1 ................. 1961 20.1 17.8 10.5 6.8 47.3 4.3
Ghana.................. 1970 19.1 14.8 11.8 9.9 51.7 2.6
Guinea................. 1954-55 19.0 17.2 9.4 8.3 50.6 3.7
Ivory Coast............ 1975 17.8 14.5 11.3 9.4 53.6 2.0
Liberi a................ 1974 17.5 14.2 11.6 9.8 53.5 3.0
Nigeria................ 1963 16.8 15.5 11.6 8.9 53.8 2.4
Sierra Leone........... 1963 17.3 13.5 7.0 7.7 56.7 5.5
Togo................... 1970 21.8 20.4 11.2 7.5 42.2 4.4

CENTRAL AFRICA

Burundi................ 1970-71 17.9 14.5 13.8 10.9 52.0 1.9
Cameroon................ 1976 17.0 13.7 11.8 10.3 54.6 2.9
Rwanda................. 1970 19.5 17.0 15.7 9.6 46.2 1.7
Sao Tome and Principe.. 1970 16.0 15.3 11.9 8.8 52.5 4.4
Zaire................... 1955-57 17.0 13.0 11.0 6.5 459.0 (NA)

EASTERN AFRICA

Ethiopia............... 1968 18.4 (NA) 526.5 (NA) 442.3 (NA)
Kenya ................ 1969 19.1 16.4 13.0 9.9 49.1 2.4
Madagascar............. 1975 18.0 14.3 12.3 10.7 51.7 3.6
Mauritius.............. 1972 12.6 14.6 13.6 12.1 56.2 3.0
Seychelles ........... 1977 13.2 13.1 13.2 12.4 55.0 5.3
Sudan.................. 1973 17.5 17.9 11.5 8.5 49.8 3.0
Tanzania............... 1967 18.1 16.2 10.9 8.5 48.6 6.1
Uganda................. 1969 18.9 15.3 11.9 8.6 49.6 4.3


See footnotes at end of table.


38 Population Distribution and Change


Women of the World










Table 3.4. Percent of Male Population in Selected Age Groups-Continued
(Percentages do not add to 100.0 because of overlapping categories)


Preschool Working
age School age age Elderly
Region and country
0 to 4 5 to 9 10 to 14 15 to 19 15 to 64 65 years
Year years years years years years and over


SOUTHERN AFRICA

Angola................. 1970 16.3 16.2 12.6 9.1 52.0 2.9
Botswana................ 1971 20.9 16.9 13.5 9.8 43.5 5.2
Lesotho6............... 1966 16.4 17.2 16.6 10.8 44.2 5.2
Malawi................. 1977 19.8 15.3 11.0 9.8 49.2 4.6
Mozambique............. 1970 17.3 17.5 12.3 7.7 50.9 2.0
Swaziland.............. 1976 18.6 17.0 14.3 10.2 46.6 3.2
Zambia................. 1969 18.5 16.3 11.9 8.7 49.7 2.5
Zimbabwe............... 1969 15.9 17.0 13.4 10.1 50.6 2.3


Note: Data for Botswana, Cameroon, The Gambia, Ivory Coast, Kenya, Liberia,
based on adjusted or smoothed census/survey information. All other figures are
data.


and Upper Volta are
based on unadjusted


1Excludes consideration of persons not covered by respective national demographic surveys.
Estimated total numbers of excluded persons are 730,000 in Chad and 23,000 in Benin.
2Refers to ages 15 to 60 years.
3Refers to ages 60 years and over.
4Refers to ages 15 years and over.
5Refers to ages 5 to 14 years.
6Excludes consideration of absentee workers, estimated to comprise 12 percent of Lesotho's total
population.


Population Distribution and Change 39


Women of the World









Table 3.5. Sex Ratios of Rural Population in Selected Age Groups


Pre- Repro-
school School age ductive Working Elderly
age age age
Region and country
0 to4 5to9 10tol4 15to 19 15 to 49 15to64 65years
Year years years years years years years and over


SAHEL WEST AFRICA

Chad................... 1964 100.4 109.2 133.4 77.5 72.5 74.7 101.9
The Gambia............. 1973 98.8 102.6 114.3 93.2 192.3 98.9 130.5
Mali................... 1976 99.3 102.8 109.8 91.6 86.6 89.2 96.8
Mauritania............. 1965 119.3 111.1 111.3 132.0 107.9 107.0 84.0
Senegal................ 1970 100.0 108.1 108.4 96.0 85.9 89.4 139.9
Upper Volta............ 1975 103.9 109.3 118.2 106.7 88.6 290.9 3117.3

COASTAL WEST AFRICA

Benin.................. 1961 98.6 108.8 118.7 91.5 82.6 86.0 128.3
Ghana.................. 1970 99.1 104.5 115.2 109.0 88.3 91.0 109.2
Guinea................. 1954-55 98.6 108.7 125.8 78.9 73.2 77.9 115.0
Ivory Coast............ 1975 99.0 108.6 122.9 82.3 93.1 97.2 114.9
Liberia................ 1974 101.8 106.8 115.3 88.4 82.0 88.2 145.7
Nigeria................ 1963 97.0 108.0 121.6 86.3 90.0 93.0 145.9
Togo................... 1970 99.1 109.6 129.3 99.6 73.4 76.6 104.0

CENTRAL AFRICA

Cameroon............... 1976 100.7 102.9 112.4 87.5 78.5 81.5 100.1
Rwanda................. 1970 102.5 98.0 105.0 112.3 87.6 90.8 121.3
Zaire.................. 1955-57 95.2 96.0 126.5 85.6 178.9 486.1 (NA)

EASTERN AFRICA

Ethiopia................ 1968 101.8 100.0 100.0 100.2 103.4 104.5 182.4
Kenya.................. 1969 (NA) 5101.8 108.2 102.5 88.0 288.8 3108.9
Madagascar............. 1975 100.8 94.9 106.3 92.5 91.0 94.9 124.6
Mauritius.............. 1972 102.2 102.9 101.2 100.0 102.7 103.4 76.6
Sudan.................. 1973 105.3 109.0 112.9 94.6 88.5 91.6 122.9
Tanzania............... 1967 97.8 101.2 111.5 88.9 85.0 86.5 113.8
Uganda................. 1969 97.8 100.9 110.6 100.4 95.1 96.8 129.0

SOUTHERN AFRICA

Botswana............... 1971 97.0 99.6 185.4 81.2 65.3 68.5 79.2
Malawi................. 1977 95.5 98.4 108.2 92.2 83.6 83.9 96.3
Zimbabwe............... 1969 94.6 101.0 101.1 96.9 85.9 89.8 115.7

Note: Sex ratios in this table refer to the number of males per 100 females.

1Refers to ages 15 to 44 years. 4Refers to ages 15 years and over.
2Refers to ages 15 to 60 years. 5Refers to ages 0 to 9 years.
3Refers to ages 60 years and over.


40 Population Distribution and Change


Women of the World









Table 3.6. Sex Ratios of Urban Population in Selected Age Groups


Pre- Repro-
school School age ductive Working Elderly
age age age
Region and country
Oto4 5to9 10to14 15to19 15to49 15to64 65years
Year years years years years years years andover


SAHEL WEST AFRICA

Chad................. 1964 102.1 99.9 137.2 108.8 87.2 87.9 85.6
The Gambia........... 1973 98.3 91.6 78.9 81.8 1120.9 123.8 103.1
Mali................. 1976 100.9 97.8 93.2 96.5 95.1 96.5 80.0
Senegal.............. 1970 102.7 99.0 92.4 84.3 90.7 93.6 106.4
Upper Volta.......... 1975 103.7 104.0 101.4 112.7 104.7 2106.1 391.7

COASTAL WEST AFRICA

Benin................ 1961 108.3 105.5 128.7 94.7 78.9 81.7 96.9
Ghana................ 1970 99.1 91.5 85.7 98.0 107.1 107.1 78.9
Guinea............... 1954-55 99.4 95.0 122.1 80.0 90.6 92.9 100.0
Ivory Coast.......... 1975 103.4 97.8 104.9 110.4 135.5 137.0 118.0
Liberia.............. 1974 104.2 100.0 116.0 95.0 116.0 118.9 130.4
Nigeria.............. 1963 99.1 100.2 119.7 117.9 121.3 121.6 117.5
Togo................. 1970 99.1 90.7 89.5 112.8 94.2 94.1 71.6

CENTRAL AFRICA

Cameroon............. 1976 101.9 99.5 109.5 110.8 111.6 112.2 83.4
Rwanda............... 1970 102.0 100.3 102.5 120.1 105.9 104.5 113.9
Zaire................ 1955-57 99.0 94.7 126.1 84.7 123.6 129.5 (NA)

EASTERN AFRICA

Ethiopia............. 1968 101.3 (NA) 596.0 (NA) 187.1 485.6 (NA)
Kenya................ 1969 (NA) 6101.4 100.2 105.2 166.1 2167.3 3146.2
Madagascar........... 1975 102.8 100.8 99.9 94.9 92.8 94.0 94.2
Mauritius............ 1972 101.6 101.4 102.9 98.9 98.7 98.5 63.5
Seychelles ........... 1977 (NA) (NA) (NA) (NA) (NA) 98.3 (NA)
Sudan................ 1973 102.7 100.8 107.8 113.2 121.8 121.3 110.6
Tanzania............. 1967 98.3 92.1 106.2 104.8 127.3 128.0 110.3
Uganda............... 1969 97.3 89.6 97.3 97.8 136.5 137.2 129.7

SOUTHERN AFRICA

Botswana............. 1971 95.1 88.1 67.1 65.5 101.4 105.2 98.9
Malawi............... 1977 99.5 94.5 86.5 102.9 134.9 136.3 120.0
Zimbabwe............. 1969 102.2 98.4 100.1 126.7 170.9 171.2 92.9

Note: Sex ratios in this table refer to the number of males per 100 females.

1Refers to ages 15 to 44 years. 4Refers to ages 15 years and over.
2Refers to ages 15 to 60 years. 5Refers to ages 5 to 14 years.
3Refers to ages 60 years and over. 6Refers to ages 0 to 9 years.


Population Distribution and Change 41


Women of the World









Table 3.7. Percent of Population Residing in Urban Areas, by Sex, and Female/Male Ratio
of Percent Urban: Latest Two Censuses


Earlier Census Later Census

F/M F/M
Region and country ratio ratio
Both (male= Both (male=
Years sexes Female Male 1.00) sexes Female Male 1.00)


SAHEL WEST AFRICA


Chad....................
The Gambia .............
Mali....................
Mauritania .............
Niger...................
Senegal.................
Upper Volta............


1964
1963/73
1960-61/76
1965/77
1960/77
1970
1960-61/75


COASTAL WEST AFRICA


Benin..................
Ghana ..................
Guinea..................
Ivory Coast.............
Liberia...............
Nigeria.................
Sierra Leone...........
Togo....................


1961
1960/70
1954-55
1975
1962/74
1963
1963
1961/70


CENTRAL AFRICA


Burundi ................
Cameroon...............
Rwanda..................
Sao Tome and Principe...
Zaire...................


EASTERN AFRICA


Ethiopia................
Kenya...................
Madagascar..............
Mauritius..............
Seychelles..............
Sudan...................
Tanzania................
Uganda..................


1965
1976
1970
1970
1955-57/70



1968
1969
1975
1962/72
1971/77
1955-56/73
1967/78
1969


6.9
12.7
11.9
8.4
1.1
(NA)
2.8



9.3
23.1
8.3
(NA)
19.8
16.1
13.0
14.7



(NA)
(NA)
(NA)
(NA)
9.5



(NA)
(NA)
(NA)
32.9
26.1
8.3
5.5
(NA)


6.6
12.3
12.3
(NA)
(NA)
(NA)
(NA)



9.3
22.6
8.0
(NA)
16.9
15.1
12.2
14.6



(NA)
(NA)
(NA)
(NA)
8.5



(NA)
(NA)
(NA)
(NA)
27.2
(NA)
4.9
(NA)


7.1
13.0
11.5
(NA)
(NA)
(NA)
(NA)



9.3
23.5
8.6
(NA)
22.7
17.1
13.8
14.8



(NA)
(NA)
(NA)
(NA)
10.6



(NA)
(NA)
(NA)
(NA)
25.0
(NA)
6.0
(NA)


0.93
0.95
1.07
(NA)
(NA)
(NA)
(NA)



1.00
0.96
0.93
(NA)
0.74
0.88
0.88
0.99



(NA)
(NA)
(NA)
(NA)
0.80



(NA)
(NA)
(NA)
(NA)
1.09
(NA)
0.82
(NA)


(NA)
15.9
16.8
23.0
11.8
30.2
6.4



(NA)
28.9
(NA)
32.4
29.1
(NA)
(NA)
13.0



2.2
28.1
3.2
23.6
21.6



8.6
9.9
16.4
42.9
37.2
18.5
13.3
7.7


(NA)
15.5
16.7
(NA)
11.7
30.3
6.3



(NA)
28.7
(NA)
30.5
27.6
(NA)
(NA)
13.0



2.1
26.5
3.1
23.4
(NA)



9.2
8.3
16.5
43.3
37.8
17.5
12.6
7.1


(NA)
16.4
16.9
(NA)
12.0
30.1
6.5



(NA)
29.0
(NA)
34.2
30.7
(NA)
(NA)
13.1



2.3
29.8
3.3
23.8
(NA)



8.1
11.4
16.3
42.4
36.6
19.4
14.0
8.3


(NA)
0.94
0.99
(NA)
.98
1.01
0.97



(NA)
0.99
(NA)
0.89
0.90
(NA)
(NA)
0.99



0.91
0.89
0.94
0.98
(NA)



1.14
0.73
1.01
1.02
1.03
0.90
0.90
0.86


42 Population Distribution and Change


Women of the World









Table 3.7. Percent of Population Residing in Urban Areas, by Sex, and Female/Male Ratio
of Percent Urban: Latest Two Censuses-Continued


Earlier Census Later Census

F/M F/M
Region and country ratio ratio
Both (male= Both (male=
Years sexes Female Male 1.00) sexes Female Male 1.00)

SOUTHERN AFRICA

Angola................... 1960 10.6 (NA) (NA) (NA) (NA) (NA) (NA) (NA)
Botswana................. 1971 (NA) (NA) (NA) (NA) 10.2 9.5 11.1 0.86
Malawi.................. 1966/77 5.0 (NA) (NA) (NA) 8.5 7.6 9.5 0.80
Mozambique.............. 1970 (NA) (NA) (NA) (NA) 3.2 (NA) (NA) (NA)
Swaziland............... 1966/76 7.1 (NA) (NA) (NA) 15.2 (NA) (NA) (NA)
Zambia.................. 1969/74 29.4 (NA) (NA) (NA) 35.6 33.6 37.7 0.89
Zimbabwe................ 1969 (NA) (NA) (NA) (NA) 16.8 14.0 19.6 0.71


Women of the World


Population Distribution and Change 43










Table 3.8. Percent Distribution of Women Residing in Rural and Urban Areas, by Selected
Age Groups
(Numbers in thousands)
Percent

Total Oto14 15 to 49 50 years
Region and country Year women years years and over


Rural

SAHEL WEST AFRICA

Chad ...................... 1964 1,238 41.5 50.4 8.1
The Gambia.................. 1973 206 41.5 245.6 312.6
Mali....................... 1976 2,724 42.1 46.0 11.9
Mauritania.................. 1965 461 43.0 46.1 10.5
Senegal ..................... 1970 1,399 39.8 48.8 11.4
Upper Volta.................. 1975 2,633 43.3 45.8 10.9

COASTAL WEST AFRICA

Benin ...................... 1961 963 43.4 46.4 10.2
Ghana.................. ... 1970 3,073 46.3 43.7 10.1
Guinea.................... 1954-55 1,239 38.8 51.6 9.4
Ivory Coast.................. 1975 2,245 44.9 46.6 8.5
Liberia................. ... 1974 539 39.0 50.0 11.0
Nigeria ..................... 1963 23,384 42.6 51.8 5.6
Togo....................... 1970 881 46.3 43.8 9.8

CENTRAL AFRICA

Cameroon.................... 1976 2,675 40.9 46.0 13.0
Rwanda..................... 1970 1,759 49.7 43.1 7.3
Zaire ...................... 1955-57 5,993 37.2 248.7 314.1

EASTERN AFRICA

Ethiopia.................... 1968 10,592 46.8 45.4 7.8
Kenya....................... 1969 5,008 48.1 42.0 9.9
Madagascar.................. 1975 3,194 43.9 45.6 10.5
Mauritius.................. 1972 241 42.6 45.5 11.8
Sudan...................... 1973 5,753 44.6 47.0 8.2
Tanzania.................... 1967 5,979 42.7 45.5 11.7
Uganda ........... .......... 1969 4,396 46.5 43.1 10.5

SOUTHERN AFRICA

Botswana................... 1971 282 43.4 40.4 13.2
Malawi...................... 1977 2,657 43.0 44.9 12.0
Zimbabwe.................... 1969 2,178 48.6 44.0 6.7


See footnotes at end of table.


Women of the World


44 Population Distribution and Change









Table 3.8. Percent Distribution of Women Residing in Rural and Urban Areas, by Selected
Age Groups-Continued
(Numbers in thousands)

Percent

Total 0 to14 15 to 49 50years
Region and country Year women years years and over


Urban

SAHEL WEST AFRICA

Chadl...................... 1964 88 41.1 52.6 6.3
The Gambia................. 1973 38 41.8 245.2 312.1
Mali....................... 1976 548 45.1 46.2 8.7
Mauritania4................ 1965 (NA) (NA) (NA) (NA)
Senegal .................... 1970 609 44.5 46.8 8.7
Upper Volta................. 1975 177 47.2 45.6 6.8

COASTAL WEST AFRICA

Benini..................... 1961 99 46.2 45.8 8.0
Ghana.................... .. 1970 1,239 46.2 46.2 7.6
Guinea.................. .. 1954-55 108 39.2 53.4 7.4
Ivory Coast................. 1975 985 45.5 51.0 3.4
Liberia................... 1974 205 42.5 52.5 5.0
Nigeria.................... 1963 4,174 39.1 55.4 5.5
Togo....................... 1970 132 47.3 45.5 7.2

CENTRAL AFRICA

Cameroon.................... 1976 966 43.8 49.5 6.6
Rwanda..................... 1970 56 47.7 44.4 8.0
Zaire ....................... 1955-57 558 43.9 250.8 35.3

EASTERN AFRICA

Ethiopia................... 1968 1,073 37.8 251.4 310.7
Kenya..................... 1969 453 43.4 51.4 5.2
Madagascar.................. 1975 629 41.8 48.9 9.3
Mauritius................... 1972 184 36.5 49.3 14.2
Sudan..................... 1973 1,223 44.9 47.3 7.8
Tanzania.................... 1967 311 38.3 54.1 7.6
Uganda..................... 1969 335 42.4 52.4 4.9

SOUTHERN AFRICA

Botswana..................... 1971 30 38.6 51.7 6.5
Malawi....................... 1977 217 47.0 47.8 -5.0
Zimbabwe ..................... 1969 354 39.5 52.1 7.5

1Excludes persons not covered by respective national demographic surveys. Estimated total
numbers of excluded persons are 730,000 in Chad and 23,000 in Benin.
2Refers to ages 15 to 44 years.
3Refers to ages 45 years and over.
4The 1965 Demographic Survey of Mauritania did not cover urban areas, where 88,000 persons were
estimated to reside.


Women of the World


Population Distribution and Change 45









Table 3.9. Percent of Migrants Among Native-Born Population, by Sex, and Female/Male
Ratio of Percent of Migrants


F/M ratio
Region and country Year Total Female Male (male=1.00)


SAHEL WEST AFRICA

The Gambia.................... 1973 19.5 18.1 20.9 0.87
Mali.......................... 1976 8.1 7.9 8.4 0.94
Senegal....................... 1970 15.0 (NA) (NA) (NA)
Upper Volta.................... 1975 4.8 5.2 4.5 1.16

COASTAL WEST AFRICA

Benin ......................... 1961 3.9 4.3 3.3 1.23
Ghana ......................... 1970 18.8 16.9 20.8 0.81
Ivory Coast.................... 1975 40.9 41.8 39.9 1.05
Sierra Leone.................. 1963 17.7 15.0 20.5 0.73
Togo.................. ........ 1970 9.3 9.1 9.6 0.95

CENTRAL AFRICA

Rwanda........................ 1970 5.4 6.0 4.9 1.22

EASTERN AFRICA

Kenya ......................... 1969 12.4 10.7 14.0 0.76
Mauritius..................... 1972 25.2 28.9 21.4 1.35
Sudan......................... 1973 10.6 8.4 12.7 0.66
Tanzania...................... 1967 9.1 7.5 10.7 0.70
Uganda........................ 1969 12.7 11.8 13.7 0.86

SOUTHERN AFRICA

Swaziland..................... 1976 14.0 13.2 14.8 0.89
Zimbabwe ....................... 1969 25.3 23.3 27.3 0.85

Note: Migrants are defined as persons born in a province other than that in which they lived at
the time of enumeration in the census or survey.


46 Population Distribution and Change


Women of the World









Table 3.10. Percent of Population Foreign Born, by Sex, and Female/Male Ratio of Percent
Foreign Born


F/M ratio
Region and country Year Total Female Male (male=1.00)


SAHEL WEST AFRICA

Cape Verde.................... 1960 1.1 1.0 1.2 0.83
The Gambia.................... 1973 10.5 8.3 12.7 0.65
Mali .......................... 1976 1.2 1.2 1.3 0.92
Niger.......................... 1977 1.6 (NA) (NA) (NA)

COASTAL WEST AFRICA

Benin......................... 1961 1.3 1.2 1.4 0.86
Ghana......................... 1970 6.6 5.5 7.6 0.72
Ivory Coast.................... 1975 22.2 18.9 25.2 0.75
Liberia....................... 1974 4.0 3.2 4.7 0.68
Nigeria....................... 1963 0.3 (NA) (NA) (NA)
Sierra Leone.................. 1963 2.7 2.0 3.4 0.59

CENTRAL AFRICA

Cameroon...................... 1976 3.1 2.7 3.5 0.77
Rwanda........................ 1970 0.6 0.6 0.6 1.00

EASTERN AFRICA

Kenya......................... 1969 2.5 2.3 2.6 0.88
Seychelles .................... 1977 3.1 2.4 3.8 0.63
Sudan ......................... 1973 2.0 (NA) (NA) (NA)
Tanzania...................... 1967 2.0 1.6 2.3 0.70
Uganda........................ 1969 5.7 4.4 7.0 0.63

SOUTHERN AFRICA

Botswana...................... 1971 2.0 (NA) (NA) (NA)
Malawi ........................ 1977 7.3 7.1 7.5 0.95
Mozambique.................... 1970 0.1 0.1 0.1 1.00
Zambia........................ 1969 4.6 4.2 5.0 0.84
Zimbabwe...................... 1969 9.9 7.1 12.6 0.56


Population Distribution and Change 47


Women of the World









Table 3.11. Percent of In-Movers, by Sex, and Female/Male Ratio of Percent of In-Movers



F/M ratio
Region and country Year Total Female Male (male=1.00)


SAHEL WEST AFRICA

The Gambia.................... 1973 28.0 24.9 31.0 0.80
Mali.......................... 1976 9.2 9.0 9.6 0.94

COASTAL WEST AFRICA

Benin......................... 1961 5.1 5.5 4.8 1.15
Ghana ......................... 1970 24.1 21.5 26.8 0.80
Ivory Coast.................... 1975 54.0 52.8 55.0 0.96
Sierra Leone.................. 1963 19.9 16.7 23.2 0.72

CENTRAL AFRICA

Rwanda ....................... 1970 6.0 6.6 5.5 1.20

EASTERN AFRICA

Kenya ......................... 1969 14.0 12.8 16.3 0.79
Tanzania ...................... 1967 10.9 9.0 12.8 0.70
Uganda ........................ 1969 17.7 15.7 19.8 0.79

SOUTHERN AFRICA

Zimbabwe ....................... 1969 32.7 28.8 36.4 0.79

Note: In-movers are defined as the sum of foreign-born and native-born persons who were born in
a province other than that in which they lived at the time of enumeration in the census.


48 Population Distribution and Change


Women of the World









Table 3.12. Percent of Urban Population Foreign Born


F/M ratio
Region and country Year Total Female Male (male=1.00)


SAHEL WEST AFRICA

The Gambia ..................
Mali ................ ........

COASTAL WEST AFRICA

Benin...............................
Ghana............... .....
Ivory Coast..................
Liberia.............. .....

CENTRAL AFRICA

Cameroon....................

EASTERN AFRICA

Tanzania ....................


1973
1976



1961
1970
1975
1974



1976


16.8
3.1



2.3
7.7
33.6
8.7


15.4
2.8



2.5
6.2
30.5
7.8


18.0
3.4



2.1
9.2
36.1
9.5


0.86
0.82



1.19
0.67
0.84
0.82



0.70


7.8 8.3 0.94


Women of the World


Population Distribution and Change 49


1967 8.1








Women of the World 51


Chapter 4






[l-edl Tc




II~o][U](g~ifnl


Because literacy and education are prerequisite to full participa-
tion in a modern society, the relative extent to which girls and
women have access to programs of literacy, education, and
vocational/technical training is one of the most important
indicators of the current and potential status of women in a given
country.
Education not only provides women with knowledge and an
opportunity for employment in the skilled and higher status
occupations of the modern sector, but also improves their
access to all the resources of the society. Moreover, it alters
their family and social situation in many subtle and not yet well-
understood ways. Formal schooling takes women out of the
home and away from traditional female activities for some por-
tion of each day over several years; it exposes them to new ways
of thinking about the world and themselves; it tends to delay
their entry into the world of marriage and childbearing, and often
makes them more desirable marriage partners for young men of
higher status. It appears to have an effect, independent of either
family income or husband's education, on their fertility and on
the life chances of their children, both in higher survival rates
and in the educational achievement of sons and daughters alike.'
Education for women is therefore both an indicator and an agent
of change.
There are a number of different ways to measure the relative
access to education and training of women and men:
female/male ratios for literacy, school enrollment, educational
attainment, dropouts and repeaters, and participation in non-
formal training; the content of programs and curricula available
to the two sexes; and government policies and expenditures for
education of the two sexes. Of these, the data in the WID Data
Base permit detailed consideration in this chapter only of literacy

'For discussions of the effect of women's education on fertility and on
their children's mortality, see Caldwell (1979) and Cochrane (1979); on the
education of their children, see Smock (1981) and UNECA (1978d).


and school enrollment. Because of their importance, however,
some of the other educational indicators mentioned above will
also be discussed, drawing on information from other sources.2


Literacy
Overview and Data Sources. Literacy is a minimum require-
ment for participation in modern society. It is defined variously
in the several countries but its essence is the ability to read,
write, and comprehend a simple paragraph in any language.
Unlike school enrollment figures, which may come from
administrative records, data on literacy must be obtained from
the individuals themselves. Sometimes a test is given to each
respondent; often it is simply presumed that anyone who has
completed at least 4 years of formal schooling is literate, and
only those completing fewer than 4 years are given a literacy
test. In other cases, a household respondent is simply queried
about the literacy status of household members.
The functional meaning of figures on literacy is not everywhere
and always the same. Those who have left school after com-
pleting 4 years and have not continued to use their reading and
writing skills often find them gone after several years. Moreover,
the language of literacy also affects its function. Because the
legacy of colonialism and the requirements of nation-building in
Sub-Saharan Africa have resulted in the adoption of one of the
European languages in business and government, those who are
literate only in a language other than that used in the modern
sector are at a functional disadvantage. Women, who frequently
know only the local language, are more likely to face this
problem than men are. For example, in Cape Verde, the 1960
census reported that 29 percent of men but only 13 percent of

2The most complete compilations of educational statistics are the UNESCO
Statistical Yearbooks; other useful statistical series may be found in Population
Reference Bureau (1980) and World Bank (1980c, 1981, and 1982).







52 Literacy and Education Women of the World


women knew Portuguese. Although none of the other Sub-
Saharan African countries in the WID Data Base publish such
data, these figures are probably not atypical.
Female literacy rates in the region are generally much lower
than male rates. The 1982 UNESCO Statistical Yearbook, con-
taining the most recent estimates available for a variety of educa-
tional indicators, lists only 12 Sub-Saharan African countries in
which 30 percent or more of the women age 15 and over are
literate, whereas for men, no more than 30 percent are illiterate
in all but 13 countries. Notable exceptions to the typical pat-
tern of high female illiteracy relative to male are Botswana,
Lesotho, and the Seychelles, where percent literate is greater
among women than men.

County Data. Data on adult literacy in the WID Data Base are
limited. Literacy rates for the entire country are available for only
26 of the 40 countries, and separately by sex for only 24.
Estimates of rural literacy can be found for 12 countries only,
separately by sex for 11, and by age and sex for 8; for urban
literacy, comparable numbers are 11, 10, and 8. In most cases,
the estimates refer to approximately the same dates as the
population figures of chapter 3.
Literacy data from the WID Data Base are presented in tables
4.1 to 4.3, together with the appropriate female/male ratios of
percent literate, and illustrated in figures 4.1 and 4.2. These
tables and figures demonstrate the wide variability to be found
among the countries of the region in adult female literacy, from
less than 1 percent in Chad (1964) and Ethiopia (1970) to 67
percent in Lesotho (1966). They also show an equally wide
variability in the extent of relative female disadvantage; female
rates range from 10 percent or less of the male rate in Chad,
Ethiopia, and Zaire (1955-57), to more than 100 percent in
Botswana (1964), the Seychelles (1960), and Lesotho noted
above. In Ethiopia, it should be noted, during the past 3 years
the revolutionary government has mounted a major campaign
in both rural and urban areas to improve literacy, particularly
among women; consequently, the 1970 estimates in these
tables may not reflect the current situation, for which figures
are not yet available.
Subregional differences are apparent, with West African
women relatively less and Eastern and Southern African women
relatively more advantaged than the regional average. The
subregional pattern remains similar for both rural and urban
residents; however, as expected, the available data show that
urban levels of literacy are everywhere considerably higher for
both sexes than are rural levels.
Literacy rates for women and men are shown for three broad
age groups (15 to 24 years, 25 to 34 years, and 35 years and
over) in table 4.4 and are illustrated in figure 4.3. Female/male
ratios of literacy rates for these age groups are shown for rural
and urban populations in figures 4.4 and 4.5. Comparison among
the three age groups indicates major improvement in literacy
since independence in the 1960's, presumably reflecting the
large investment in education made by most of the governments
of the region, especially at the primary school level. (Central
government expenditures are discussed in the final section of
this chapter.) Both in absolute levels of literacy and in
female/male literacy ratios, women have registered important


gains in all the countries for which data are available by age and
sex. With few exceptions, each successively younger age group
shows a higher female literacy rate, as expected, and a higher
female/male ratio of percent literate. Except for Botswana,
Lesotho, and the Seychelles, where literacy rates among women
35 years and over were already among the highest in the region,
progress in reducing both absolute and relative female illiteracy
is most evident among the youngest age group. Although
illiteracy among women in rural areas remains high, the pattern
of improvement indicated by these data is similar in both rural
and urban areas.


Formal Schooling: Enrollment and Achievement

Overview and Data Sources. A second set of indicators measures
access to formal schooling. The most common measure is school
enrollment, expressed as a percent of those of the appropriate
age groups who are enrolled in school. The data are usually
available separately by sex, but where population estimates by
age and sex are highly uncertain, or the ages of the enrollees
are variable, female enrollment may be expressed merely as a
percent of the total enrollment in a given program or grade level.
Data may come from the administrative records of educational
institutions, usually compiled at the national level by the Ministry
of Education or other official body and are readily available,
although often with some time lag. They also come from popula-
tion censuses, which have been the major source of enrollment
data in the WID Data Base. Because of the high proportion of
children who drop out during the school year, enrollment figures
will vary according to the time of year they are collected.
Measures of educational attainment such as years of school
or grade completed, rather than of enrollment, are preferable for
some purposes but are not as widely available. For the current
school age population, these figures may be inferred from
official data on school enrollment by grade level, but for the adult
population they must be obtained from household surveys or
censuses.
Many students repeat 1 or more years, particularly Standard
7 when a number of students, usually boys, sit more than once
for the examination for admission to secondary school. Two
measures of attainment which try to capture dropouts and
repeaters have been suggested. One, analogous to person-years
in a life table, computes the number of student-years in school
required to produce one graduate (UNESCO, 1975). The second
is simply the percentage of those enrolling who complete a given
program. Pupil wastage can be inferred from school enrollment
data by grade, but data on repeaters must usually come from
special studies based on school records; such data have been
published for only a few countries in the region.
Opportunities for education at any level in the region are
limited, despite the fact that many countries have invested
important fractions of their gross domestic product (GDP) in a
push to achieve universal primary education. Historically, schools
in Africa were established by missionaries for the training of
catechists and by colonial administrators in order to provide
themselves with an army of clerks and junior officers, virtually
all male. Initially, the majority of schools were for boys alone;


Women of the World


52 Literacy and Education






Women of the World Literacy and Education 53


most girls' schools and co-educational institutions came
somewhat later and in smaller numbers. Among the pioneering
efforts in the struggle for equality for women in education was
the establishment of Ghana's distinguished Achimota School in
1924 on a co-educational basis, considered by many at the time
to be a revolutionary and highly risky step.3 It has been only since
the achievement of national independence that a concerted
effort has been made in most of the countries of the region to
provide educational opportunities for both girls and boys, young
women and young men.

School Enrollment. Despite a national policy commitment to pro-
viding formal schooling for both sexes, in most countries female
educational opportunities continue to lag behind those for males.
In 1980, girls constituted only 43 percent of those enrolled in
primary school in the region (UNESCO, 1982), again, as with
literacy, with the exception of a few countries, primarily in
Southern Africa. In Botswana, Cameroon, Lesotho, Mauritius,
and Swaziland, girls make up 50 percent or more of total primary
school enrollment.
The rate of improvement in school enrollment for girls,
however, has often exceeded that for boys, particularly during
the 1960's when serious efforts to narrow the gap were made
in a number of countries. UNESCO's estimates for primary school
enrollment in Sub-Saharan Africa for 1960, 1970, and the late
1970's demonstrate this pattern; from 1960 to 1970 the per-
cent of girls ages 6 to 11 years enrolled in primary school
doubled, from only 17 to 35 percent, while comparable figures
for boys rose from 46 to 63 percent. During the 1970's, rates
of improvement for both sexes were approximately equal and
considerably slower; for girls, primary school enrollment
increased only to 44 percent, and for boys to 74 percent,
representing annual rates of increase of only 1 to 2 percent for
each sex.
Neither sex has had many opportunities for secondary educa-
tion in most of the countries of Sub-Saharan Africa, although
important gains have been made since the mid-1960's. UNESCO
(1982) estimates that for all of Africa, secondary school enroll-
ment increased its share of total enrollment from 10 percent in
1975 to 15 percent in 1980. Girls in Sub-Saharan Africa have
done less well in catching up with their brothers at the
secondary school level. From a mere 0.7 percent in 1960, girls
increased their enrollment to 3 percent by 1970 and to 4.6 per-
cent at the most recent estimate; this represents a large per-
cent increase, but touches only a tiny fraction of girls of the
appropriate ages. The comparable figures for boys are 3, 9, and
12 percent, still a very small fraction of the relevant male popula-
tion. At each time period, the female share of the secondary
school population was under 30 percent.
Still fewer young Africans have had the chance for post-
secondary education. UNESCO estimates that during the period
from 1965 to 1980, less than 1 percent of total enrollment in
Africa was at this level; currently only a little more than one-
fourth of these students are women.
Data on school enrollment by age in the WID Data Base are
even more limited than those on literacy. Enrollment rates by

3For an interesting if congratulatory account, see Setse (1974).


sex are available for the entire country for children and youth,
ages 5 to 19 years, for only 22 of the 40 countries in the data
base; rural and urban enrollment rates for the same groups are
found for only 12 countries. Comparable numbers for countries
with enrollment data for young adults, ages 20 to 24, are 16
and 8. As with literacy data, in most cases the enrollment data
refer to approximately the same dates as the population figures
of chapter 3. An additional complication in these data lies in the
use by many countries of noncomparable age groups in tabula-
tions; the particular age groups employed by the specific coun-
tries must be kept in mind in making any intercounty com-
parisons. Reference should be made to the notes to the tables
of chapter 4 for a listing of countries tabulating by nonstandard
age groups.
Enrollment rates by age and sex, calculated from data in the
WID Data Base, are presented in tables 4.5 to 4.7, and
female/male ratios of these rates in table 4.8. Enrollment rates
for a key age group, 10 to 14 years, are shown by sex in figure
4.6, and female/male ratios by age for rural and urban areas are
illustrated in figures 4.7 and 4.8. Again, as with literacy, the
tables and figures indicate wide variation in enrollment rates
among countries in the region. For example, in the age group
10 to 14 years, values for girls range from 12 percent in The
Gambia (27 percent for boys, 1973), to 81 percent in Lesotho
(only 49 percent for boys, 1966); among boys of the same ages,
values range from 24 percent in Mali (15 percent among girls,
1976) to 75 percent in Ghana (62 percent among girls, 1970).
In Chad, only 8 percent of girls in the age group 6 to 14 years
were enrolled in school (36 percent of boys, 1964).
There appear to be subregional differences in enrollment by
age, although the relative scarcity of data and the different ages
and time periods to which the data refer make such generaliza-
tions problematic. At each age level and for both sexes, the coun-
tries of the Sahel register lower proportions enrolled in school
than do the other subregions, while Southern Africa excels in
the proportions enrolled at ages 10 to 14 years and 15 to 19
years for both sexes. Liberia (1974) in Coastal West Africa
reports the highest rate (30 percent) of young men ages 20 to
24 years enrolled in school, presumably in post-secondary
institutions, but this percentage is not characteristic of the
subregion, and only 5 percent of women in this age group are
enrolled. In tables 4.6 and 4.7, each successively younger age
group shows a higher female enrollment rate, in both rural and
urban areas, except for ages 5 to 9 years, where many children
have not yet started school. Each also shows a higher
female/male ratio of percent enrolled, (table 4.8 and figures 4.7
and 4.8) but with some exceptions the differences between the
ratios for ages 5 to 9 and 10 to 14 years are not large. Such
a pattern is the combined result of increasingly greater propor-
tions of girls entering primary school and a dropout rate for girls
which, like that for boys, increases with each higher grade in
school and is increasingly larger than that for boys at each suc-
cessive grade in school. Nevertheless, the dropout rate for girls
is gradually coming closer to the boys' rate for a given grade,
as more girls are encouraged to stay in school.
Sex differentials in enrollment are most pronounced at age 15
years and above, the ages of higher secondary, vocational, and
post-secondary education. It is the latter differential in enroll-


Women of the World


Literacy and Education 53






54 Literacy and Education Women of the World


ment which the countries of Sub-Saharan Africa must now
address if women are to be able to acquire the skills needed for
productive employment in a modernizing economy.
Enrollment levels are much lower in rural than in urban areas
for both sexes and among all age groups, as are female/male
ratios of percent enrolled for each age group; patterns of sex
differences in enrollment by age, however, are similar in rural
and urban areas.

Educational Attainment. With respect to educational attainment,
the figures are equally discouraging. UNESCO (1982) reports
only five countries in Sub-Saharan Africa (Ghana, Mauritius,
Seychelles, Swaziland, and Zimbabwe) in which the fraction of
adults age 25 years and over who have completed primary school
is 9 percent or more; the highest fraction reported is that for
Seychelles at 21.5 percent. Among these five, the proportion
of girls completing primary school varies from a low of 4 per-
cent in Zimbabwe to 23 percent in the Seychelles, where
women's achievement in fact exceeds that of men. At the
highest levels of education, in only two Sub-Saharan African
countries do those who have completed at least 1 year of post-
secondary education constitute more than 1 percent of the
adults: Mauritius at 1.2 percent, and the Seychelles at 2.6 per-
cent. Even in these two, the comparable proportions for women
are only 0.5 percent and 1.7 percent, respectively.

Educational Wastage. An analysis of the sex composition of
enrollment by grade level shows a high degree of educational
wastage in the region. Figures from Malawi in the mid-1 970's
are illustrative. Only 35 percent of females over age 5 had ever
been to school; 26 percent of the total had attended but
dropped out after completing only 4 years; another 8 percent
had attended but dropped out before secondary school; fewer
than 1 percent attended but failed to reach the final year of
secondary school; and the remaining 0.2 percent terminated
formal education but did not continue on to post-secondary pro-
grams (UNECA, 1982d). At each successive level, girls drop out
at an increasingly greater rate than boys do. In Kenya in 1976,
the female share of total enrollment decreased from 47 percent
in Standard I to 40 percent in Standard VII, to 26 percent in Form
VI, and to only 18 percent at the university undergraduate level
(Kenya Central Bureau of Statistics, 1978).
UNESCO has estimated the extent of school wastage for a
number of countries, using the life table person-years concept.
In 1975, it was estimated that it takes an average of 14.7 years
of female schooling and 16.7 years of male schooling to graduate
one individual from a 7-year primary school program in Lesotho,
one of the countries in the region with relatively high levels of
educational attainment as indicated by other measures. In
Malawi, where illiteracy is higher and enrollment considerably
lower, educational wastage is much higher, particular among
the girls; the comparable figures are 23.8 female and 17.7 male
school years to produce one graduate of a 6-year primary
program.
The traditional division of labor based upon sex accounts in
large measure for the higher rates of educational wastage among
girls. Young girls are expected to assist their mothers at home


and on the farm. They take care of younger children; carry
firewood and water, sometimes for many kilometers; assist in
food processing and meal preparation; and carry meals to those
in the fields. This added work load may cause girls to drop out
altogether, or may depress performance and retard their
progress. Low occupational expectations lead many into
pregnancy or early marriage. When money for school fees is
scarce, girls are expected to sacrifice for the sake of their
brothers. These attitudes are slowly changing, and in at least
one survey of Ghanaian secondary school students, girls
expressed an interest in continuing their education and a set of
occupational objectives, whether realistic or not, which were
as high as those of boys (Smock, 1981; and UNECA, 1979e).
Botswana, Lesotho, and Swaziland, as well as the island coun-
tries of Mauritius and the Seychelles, are consistent exceptions
to the African pattern of low educational attainment for women
as compared to men. Among the former, an economy based on
cattle raising, mining (in Botswana), and the export of labor to
the mines of South Africa has placed boys and young men at
a relative disadvantage with respect to education. At an early
age, boys are sent off to work at the family cattle posts; when
their younger brothers have become old enough to relieve them,
the young men then leave for a period of work in the mines. In
neither situation is there much opportunity for either formal or
informal education, and when the young men return most find
it is too late to begin a protracted period of formal training. As
a consequence, men in these countries have lower literacy,
school enrollment, and educational attainment rates than those
of women (Gay, 1982).


Educational Performance. A comparison by sex of the results
of the Cambridge School Certificate or.other examinations of
academic performance can provide another measure of relative
educational aspiration and achievement among young women
and men. These data, usually available from national education
officials, generally show a pattern of female performance which
is somewhat lower than that of males. The source of these
discrepancies lies in the same set of factors which tend to keep
the dropout rate for girls higher than that for boys: the lower
expectations and aspirations which families tend to have for girls,
and the consequent demands placed on them for assistance at
home. In Malawi in 1979-80, girls made up 23 percent of those
taking the Primary School Certificate examination but only 20
percent of those who passed (UNECA, 1982d). In Ethiopia in
1978, girls constituted 38 percent of those sitting for the grade
six examination but only 36 percent of those passing; for the
grade eight examination, the comparable figures were 38 per-
cent and 35 percent, respectively (UNECA, 1981e).
In Kenya, since 1960, the ratio of girls to boys taking the
examination for the Certificate of Primary Education has risen
from 23 percent to 69 percent; in most areas boys have tended
to outperform girls, but the differences have been narrower in
districts in which a relatively high proportion of girls have elected
to take the examination. In those districts, families tend to be
better off economically; parents were therefore less dependent
upon the labor of their daughters and were better able to afford
school fees. But the higher performance of girls in these districts


Women of the World


54 Literacy and Education





Women of the World


Literacy and Education 55


suggests in addition that where girls are encouraged to attend
school, they also are motivated to higher performance. Girls
generally did well on the examination for the East African
Certificate of Education, taken after Form IV. It is probable that
this represents the combined result of higher dropout rates
among girls and of repeaters among boys, both of which would
tend to result in greater selectivity among female candidates at
the upper grades (Kenya Central Bureau of Statistics, 1978).



Other Indicators of Female Access to Education

Nonformal Education. Given relatively low enrollment rates and
high rates of attrition, most of the countries of Sub-Saharan
Africa are facing a major problem in the large and growing
number of out-of-school youth and young adults, most of whom
are inadequately trained for productive employment in modern
agriculture, business, industry, or government. They swell the
ranks of the unemployed and the underemployed, and unless
they can be provided with access to further vocational training,
they appear destined for marginality. Recognizing the
seriousness of the problem, all the governments of the region,
with assistance of a large number of nongovernmental organiza-
tions, have instituted programs of nonformal vocational and
technical education, aimed specifically at school leavers.4
Accordingly, a third set of indicators of relative female/male
access to education and training describes the availability of such
nonformal educational and training programs, especially those
in commercial, technical, and agricultural subjects. Because
these programs are offered by a wide variety of institutions and
are in their very nature short term and somewhat ephemeral,
data on female access are fragmentary at best. Nevertheless,
a number of regularities are readily apparent from examination
of several of the many case studies which describe individual
programs.
Literacy programs are widely available for both women and
men. While literacy skills are basic, experience has shown that
without substantive training as well, they have not generally
resulted in productive employment. Other nonformal and exten-
sion programs for women tend to focus on homemaking, nutri-
tion, and health. As with literacy, these are subjects which, while
valuable in themselves, do not often lead to gainful employment.
Most of the remainder teach dressmaking, hairdressing, or the
less skilled commercial subjects, training which can increase
employability and earning capacity but only in the marginal
occupations traditionally open to women. These skills do not help
women qualify for participation in modern agriculture or industry,
except possibly at the very lowest levels. Nevertheless, in areas
of high unemployment, such skills can make the difference for
many women between dependency and self-sufficiency.
Meanwhile, men are recruited into courses in farm manage-
ment and innovation, areas in which many have had little


"For a discussion of the role of nonformal education in development, see
Clignet (1974), Coombs and Ahmed (1974), and Kindervatter (1980). For
Africa, see Elias (1981), Smock (1981), and UNECA (1978e, 1981a, and
1 982b). Nonformal training programs in specific countries are described in
Gay (1982), Kenya Central Bureau of Statistics (1978), Smock (1981), and
UNECA (1975a, 1979e, 1981c, 1981d, 1981e, 1982b, and 1982d).


experience, as well as those in woodworking, automotive
mechanics, and the like. Increasingly, the latter type of training
is being offered by employers in the form of apprenticeships and
on-the-job training, and therefore is available only to those who
have already entered the modern wage economy. Women can-
not benefit from such programs if they are not part of the
industrial and commercial labor force. Consequently, it is even
more critical that out-of-school women be able to obtain train-
ing in nonformal programs for the skills which they need to
obtain employment and to qualify for advancement.
Examples of programs for women in tie-dyeing, sewing, soap-
making, typing and the like are too numerous to catalog.
However, one of the more innovative examples of a nonformal
course is a 4-year apprentice program for training both women
and men in technical skills, offered by the national workshop
in Freetown, Sierra Leone (UNECA, 1981c). The objective of the
workshop is to train school leavers in mathematics, general
science, engineering drawing, workshop practice, and one of 16
areas of specialization, including metal fabrication, welding,
vehicle maintenance and repair, electricity, carpentry, and the
like. Those completing the program will be expected to take a
trade test under Sierra Leone regulations; some may then go on
for more specialized technical training. At completion, the
apprentices are bonded to remain working at the national
workshop for a period of time equivalent to the total time of their
training. Eventually, most are expected to work in industry or
to become self-employed. Although open to both sexes, out of
144 participants there are only 12 female apprentices in the pro-
gram. This is hardly a typical program, and without adequate
encouragement and social support, women training for fields
which are normally not open to them may find it difficult to
persevere; nevertheless, their success may open the way for
others.
A second innovative program in nonformal education is under-
way at the Eastern and Southern Africa Management Institute
(Arusha, Tanzania), where women who hold senior and middle-
level administrative and professional posts in the public sector
can improve their skills in planning and management on the job,
and where both men and women are trained in policy analysis
and the implementation of strategies to integrate women's pro-
ductive contribution into the national development planning
process. This program serves the 18 countries of the Economic
Commission for Africa's Eastern and Southern Africa regions
(Elias, 1981).


Programs, Institutions, and Curricula. Although school enroll-
ment, educational attainment, and informal course attendance
form the basic data in an assessment of female educational
opportunities and of women's situation relative to men's, it is
important to note that a year of school completed at a given
grade level or a nonformal course attended by women and men
may not represent the same educational experience. Programs
offered to women and men are often very different in content
and orientation. To understand the full pattern of sex biases,
therefore, it also is necessary to examine the kinds of institu-
tions, programs, and curricula available to (or taken advantage
of by) each sex.






56 Literacy and Education Women of the World


Single-sex institutions and separate tracking at the secondary
and post-secondary level are common, and scientific and
technical subjects are often found only in educational institu-
tions for boys and men. For example, in Sudan, the 974 second-
ary schools in 1974 were distributed as follows (UNECA,
1975a):

Schools Female Male

General secondary ........... 250 609
Academic higher ............ 32 67
Commercial ................ 0 3
Technical ................. 0 11
Agricultural higher technical. 0 2
Total ................... 282 692

In Kenya as of 1978, none of the secondary vocational and
technical schools admitted female students, while of the 21
secondary schools offering advanced mathematics, only 3 were
for girls, another 3 were coeducational, and 15 were for boys.
In 1976, there were approximately 900 places for girls in arts
and only about 400 places in science programs compared to
1,000 in arts and 2,000 in science for boys. Despite the fact
that 80 to 90 percent of women in rural areas are engaged in
producing, processing, and marketing food, their access to
technical education in agriculture is very limited; in 1975, there
were only 30 openings for girls at the Bukura Institute of
Agriculture compared to 270 for boys (Kenya Central Bureau
of Statistics, 1978).
Even when technical programs are offered to girls and women,
the proportion electing to enroll in them is small. In part, this
is the result of the absence of strong science programs for girls
in the lower grades. For example, in Kenya, it has been difficult
to fill all of the places available to women in science, especially
in physics, in higher secondary school because of inadequate
preparation. In certain countries like.Chad and Togo, where
relatively few girls complete primary school, there are only a few
female entrants to vocational and technical schools because
most do not meet the minimum requirements for entrance
(UNECA, 1978e).
In Lesotho in 1979, although girls constituted 58 percent of
students enrolled in technical and vocational schools, most were
studying domestic arts, bookkeeping, and typing. Few graduated
equipped with the technical skills for modern rural development
or with adequate foundations in math and science for higher
technical training (UNECA, 1978e). In the higher specialized
institutes of Sudan in 1973-74, where women constituted 16
percent of the enrollment, they made up only 8 percent of those
enrolled in such subjects as agriculture, business, engineering,
or architecture, and 74 percent of those enrolled in nursing,
secretarial studies, or teaching (UNECA, 1975a).
The pattern may continue at the university level. In Ghana,
women make up only 7 percent of those enrolled at the Univer-
sity of Science and Technology at Kumasi, compared to just over
15 percent at the University of Ghana (Legon) and at the Univer-
sity of Cape Coast. Most of the Ghanaian university women are
concentrated in the faculty of arts; even at Kumasi where the
arts faculty is not a strong one, 20 percent of the women are
in arts programs. Many are in teacher training programs (Smock,
1981; and UNECA, 1979e and 1981a). On the other hand,


access to university education can permit a greater range of
options for women. At the University of Khartoum, where
women were 10 percent of the student body, they represented
fully 8.5 percent of those enrolled in the combined science
faculties of agriculture, engineering, medicine, science,
veterinary science, and pharmacy (UNECA, 1975a and 1978e).
Examples could be multiplied, as the pattern of sex bias in pro-
gram and curriculum, particularly at the secondary level, is a
general one. Indeed, the Economic Commission for Africa
(1978e) has suggested that secondary education may even
depress women's options, as it equips them to move into the
modern sector without providing them with sufficient under-
standing of science and technology to be able to move into the
more highly skilled occupations. Furthermore, the introduction
of a wider range of secondary school programs, under the guise
of reforming the curriculum to make it less academic and more
relevant to the vocational needs of the students, has intro-
duced even more gender differentiation. For example, the cur-
riculum prescribed for a new junior secondary course intro-
duced in Ghana in the mid-1970's segregated girls into home
science and pre-nursing, while offering agricultural science to
boys. Electives for girls included beauty culture, tailoring,
dressmaking, and catering, and for boys woodworking, masonry,
technical drawing, and automotive practice (UNECA, 1979e).
It should be pointed out that this pattern of bias does not follow
the traditional African division of labor; traditionally, Africa's
agriculture has been in the hands of women, as has much of
its commerce. Were women to be trained for the traditional
African economic pattern, far more of them would be in
agricultural and commercial programs. Apparently many of the
sex biases in African education have been imported from the
West, along with its technology.


Level of Commitment. Finally, a very important indicator of the
status of women in a given country is the commitment of that
society to their education and training. Most important are the
attitudes of parents. Where parents encourage the educational
aspirations of their daughters, female achievement levels reflect
this concern, and because women who have been educated also
tend to have higher expectations for their children, the effect
is cumulative. Nevertheless, most of the gains made during the
1970's have come from the interest and the willingness of
increasing numbers of ordinary workers and farmers to support
female education, either through the payment of school fees
themselves for their daughters, or through government revenues.
In most of the poorer developing countries, the national govern-
ment has accepted the primary responsibility for education. Con-
sequently, except where education is constitutionally a private,
local, or as in Nigeria, a regional function, the policies and ex-
penditures for female education and training made by the cen-
tral government are important indicators of a society's
commitment.

Information on per capital central government expenditures for
education is generally available in annual financial reports and
other official documents. By this measure, the commitment of
the countries of Sub-Saharan Africa is impressive. Excluding
China and India, the per capital government expenditure for


56 Literacy and Education


Women of the World





Women of the World


Literacy and Education 57


education in developing countries averaged only $3 in 1975 U.S.
dollars during the 1970's. But for the same period, per capital
expenditure in Sub-Saharan Africa ranged from $2 (Somalia,
1972; Ethiopia, 1979) to $20 (Ghana, 1972) and $33 (Zambia,
1979). Two thirds of the countries reported per capital expend-
itures above the developing country average; the median figure
reported was $5 (World Bank, 1981).
Expenditure data are not usually available separately by sex,
but sometimes close examination of the national education
budget can be illuminating. In Malawi in 1979, for example, the


Ministry of Education proposed to improve and expand seven
girls' secondary boarding schools, and to provide assistance to
three or four home economics units, whereas it proposed building
a large number of new hostels for secondary school boys (one
per 120 pupils) (UNECA, 1982d). Although budget figures for
any given year are subject to considerable risk of misinterpreta-
tion, analyses of annual expenditures over time can indicate
trends in the pattern of resources allocated to the education of
the two sexes.






58 Literacy and Education Women of the World


Figure 4.1. Percent Literate Among Women and Men
10 Years of Age and Over


Women


Men


Percent
literate
80 r
Sahel West Africa

70


60 -

50

40 -

30


20 -


0

Niger Upper
1977 Volta
1975


Ghana
1971


Coastal West Africa


Ivory
Coast
1975


Liberia
1974


Percent
literate
80 r


Central Africa


Eastern Africa


60 -

50 -

40


-






Burundi
1970-71


Cameroon
1976


Rwanda
1970


Ethiopia
1970


Sudan
1973


Mozambique
1970


Note: See footndtes to table 4.1 for nonstandard age groups.
Literacy rate for women in Ethiopia is 0.2 percent.


Togo
1970


Southern
Africa


30

20


58 Literacy and Education


Women of the World





Literacy and Education 59


Figure 4.2. Percent Literate Among Women and Men 10 Years
of Age and Over, by Rural/Urban Residence




Women Men Women Men
Rural Urban


Percent
literate


Coastal West Africa


Ivory
Coast
1975


Liberia
1974


Togo
1970


Central
Africa
















Cameroon
1976


Eastern Africa


Kenya
1976


Sudan
1973


Note: See footnotes to tables 4.2 and 4.3 for nonstandard age groups.


Upper
Volta
1975


Women of the World






60 Literacy and Education Women of the World


Figure 4.3. Percent Literate for Women and Men, by Age





Sahel West Africa and Coastal West Africa


Women


Percent


0
15-24


Men


Percent


0 -
15-24


25-34

Age


25-34

Age


35+


60 Literacy and Education


Women of the World






Women of the World Literacy and Education 61


Figure 4.3. Percent Literate for Women and Men, by Age--Continued





Central, Eastern and Southern Africa


Women


Percent


01-
15-24


Men


Percent


0o
15-24


25-34

Age


25-34

Age


Literacy and Education 61


Women of the World






62 Literacy and Education Women of the World


Figure 4.4 Female/Male Ratio of Percent Literate
in Rural Areas, for Selected Age Groups



15-24 25-34 35+
F/M ratio
(male=1.0)
1.3-
1.2
Sahel West Central Eastern
1.1 Africa Coastal West Africa Africa Africa
*1.0
*11.0 ------------------------------------------------------------

0.9
0.8
0.7
0.6
0.5
0.4 -

0.3
0.2

0.1
0.0 __ _
Upper Ivory Liberia Togo Cameroon Sudan
Volta Coast 1974 1970 1976 1973
1975 1975


*Female percent equals male percent.


62 Literacy and Education


Women of the World






Women of the World Literacy and Education 63


Figure 4.5. Female/Male Ratio of Percent Literate
in Urban Areas, for Selected Age Groups


15-24


25-34 35+


F/M ratio
(male=1.0)
1.3 r
1.2
Sahel West
1.1 Africa
1.0 ----------
0.9 -


Upper
Volta
1975


Ivory
Coast
1975


Coastal West Africa


Liberia
1974


Togo
1970


*Female percent equals male percent.


Central
Africa


















Cameroon
1976


Eastern
Africa


Sudan
1973


Women of the World


Literacy and Education 63






64 Literacy and Education Women of the World


Figure 4.6. Percent Enrolled in School Among Girls and Boys


Figure 4.6. Percent Enrolled in School Among Girls and Boys
10 to 14 Years of Age


Girls


Boys


Percent
enrolled


Sahel West Africa


L-
Gambia
1973


i
Mali
1976


Coastal West Africa


Ghana Liberia
1970 1974


Percent
enrolled


Central Africa


Burundi'
1970-71


Cameroon
1976


Eastern Africa


Mauritius
1972


Sudan
1973


Southern Africa


Botswana
1971


Malawi
1977


SSee footnotes to Table 4.5 for nonstandard age groups.


90

80 -

70

60 -

50

40 -


Togo
1970


90

80

70

60 -

50

40

30

20 -

10 -


Swaziland
1976


64 Literacy and Education


Women of the World


0 L






Women of the World Literacy and Education 65


Figure 4.7.


Female/Male Ratio of Percent Enrolled in School
in Rural Areas, for Selected Age Groups


5-9 10-14 15-19


F/M ratio
(male=1.0)


-Sahel West Africa


Gambia Mali
1973 1976


Coastal West Africa


Central Africa


1.5
1.4
1.3
1.2
1.1
S1.0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0


Eastern
Africa


Sudan
1973


* Female percent equals male percent.
See footnotes to table 4.8 for nonstandard age groups.


Ghana Liberia Togo Burundi Cameroon
1970 1974 1970 1970-71 1976


Literacy and Education 65


Women of the World










Figure 4.8. Female/Male Ratio of Percent Enrolled in School
in Urban Areas, for Selected Age Groups



5-9 10-14 15-19
F/M ratio
(male=1.0)


1.4 -Sahel West Africa
1.3-
1.2-


Coastal West Africa


Central Africa


1.0 H-


I r


Ghana
1970


Liberia
1974


Togo Burundi
1970 1970-71


Cameroon Sudan
1976 1973


* Female percent equals male percent.
Note: See footnotes to table 4.8 for nonstandard age groups.


Eastern
Africa


Gambia
1973


Mali
1976


66 Literacy and Education


Women of the World









Table 4.1. Percent Literate Among Total Population Age 10 Years and Over, by Sex, and
Female/Male Ratio of Percent Literate


Percent literate
Region and country F/M ratio
Year Total Female Male (male=1.00)


SAHEL WEST AFRICA

Cape Verde............... 1960 29.3 18.7 42.4 0.44
Chad .................... 1964 5.6 0.6 12.1 0.05
Mali.................... 1960-61 2.9 1.0 4.9 0.20
Mauritania2.............. 1977 17.4 (NA) (NA) (NA)
Niger..................... 1977 9.5 4.6 14.6 0.32
Upper Volta.............. 1975 10.0 4.4 15.7 0.28

COASTAL WEST AFRICA

Beninl................... 1961 4.6 1.8 7.7 0.23
Ghana1................... 1971 30.2 18.4 43.1 0.43
Ivory Coast.............. 1975 22.7 14.6 29.9 0.49
Liberia.................. 1974 21.0 12.2 29.6 0.41
Nigerial1................. 1971-73 37.7 (NA) (NA) (NA)
Sierra Leone............. 1963 9.8 5.1 14.7 0.35
Togo3.................... 1970 19.1 9.1 30.9 0.29

CENTRAL AFRICA

Burundi ................. 1970-71 25.0 19.0 32.0 0.59
Cameroon................. 1976 43.6 33.1 54.8 0.60
Rwanda................... 1970 23.0 14.0 33.0 0.42
Zaire.................... 1955-57 15.4 2.8 29.2 0.10

EASTERN AFRICA

Ethiopia.................. 1970 4.2 0.2 8.3 0.02
Mauritius4 ............... 1962 61.9 53.5 70.2 0.76
Seychelles .............. 1960 45.9 49.2 42.3 1.16
Sudan.................... 1973 31.3 17.9 44.7 0.40
Tanzania................. 1967 31.5 18.8 45.0 0.42

SOUTHERN AFRICA

Botswana................. 1964 34.5 37.5 30.8 1.22
Lesotho.................. 1966 56.3 67.0 40.5 1.65
Mozambique................ 1970 14.2 8.8 19.7 0.45
Zambia................... 1969 53.4 41.9 65.4 0.64

1Refers to ages 15 years and over.
2Refers to ages 6 years and over.
3Refers to ages 12 years and over.
4Refers to ages 5 years and over.


Literacy and Education 67


Women of the World









Table 4.2. Percent Literate Among Rural Population Age 10 Years and Over, by Sex, and
Female/Male Ratio of Percent Literate

Percent literate
Region and country F/M ratio
Year Total Female Male (male=1.00)


SAHEL WEST AFRICA

Chad1.................... 1964 5.0 0.4 11.0 0.04
Mali.................... 1960-61 1.0 0.2 1.9 0.10
Mauritania2.............. 1977 11.5 (NA) (NA) (NA)
Upper Volta.............. 1975 7.9 2.9 13.0 0.22

COASTAL WEST AFRICA

Benini................... 1961 2.3 0.6 4.2 0.14
Ivory Coast.............. 1975 13.0 7.8 18.1 0.43
Liberia.................. 1974 12.1 5.7 18.8 0.30
Togo3.................... 1970 14.0 5.7 23.9 0.24

CENTRAL AFRICA

Cameroon................. 1976 34.7 25.4 45.4 0.56

EASTERN AFRICA

Ethiopia................. 1970 4.7 0.4 8.9 0.04
Kenya. ................... 1976 46.0 30.0 65.0 0.46
Sudan.................... 1973 24.5 12.2 37.7 0.32
Tanzania................. 1967 29.5 17.4 42.7 0.41

1Refers to ages 15 years and over.
2Refers to ages 6 years and over.
3Refers to ages 12 years and over.


68 Literacy and Education


Women of the World









Table 4.3. Percent Literate Among Urban Population Age 10 Years and Over, by Sex, and
Female/Male Ratio of Percent Literate


Percent literate
Region and country F/M ratio
Year Total Female Male (male=1.00)


SAHEL WEST AFRICA

Chadl.................... 1964 13.1 2.2 25.4 0.09
Mali.................... 1960-61 16.5 6.5 28.0 0.23
Mauritania2.............. 1977 36.9 (NA) (NA) (NA)
Upper Volta.............. 1975 41.5 28.1 54.3 0.52

COASTAL WEST AFRICA

Benint ................... 1961 28.8 12.3 46.5 0.26
Ivory Coast.............. 1975 40.5 28.6 49.7 0.58
Liberia.................. 1974 42.5 30.0 53.0 0.57
Togo .................... 1970 49.6 30.8 69.9 0.44

CENTRAL AFRICA

Cameroon................. 1976 65.9 54.9 75.8 0.72

EASTERN AFRICA

Sudan................... 1973 53.2 38.9 65.3 0.60
Tanzania................. 1967 60.8 44.6 73.5 0.61

1Refers to ages 15 years and over.
2Refers to ages 6 years and over.
3Refers to ages 12 years and over.


Literacy and Education 69


Women of the World









Table 4.4. Percent Literate Among Women and Men, by Age


Female Male

Region and country 10tol4 15to24 25to34 35years 10 to14 15to24 25to34 35years
Year years years years and over years years years and over


SAHEL WEST AFRICA

Cape Verde......... 1960 28.8 24.4 17.4 14.0 41.4 45.9 39.5 42.6
Mali............... 1960-61 4.7 11.5 20.5 30.0 9.7 15.5 24.6 32.7
Upper Volta........ 1975 11.0 6.7 2.6 1.0 20.7 22.3 15.1 8.9

COASTAL WEST AFRICA

Benin.............. 1961 (NA) 3.9 1.5 0.6 (NA) 14.5 7.1 4.8
Ghana............... 1971 (NA) 39.6 14.3 5.0 (NA) 68.6 46.6 22.7
Ivory Coast........ 1975 40.0 21.5 5.5 2.3 60.4 43.7 21.8 10.1
Liberia............ 1974 24.0 19.4 6.9 4.7 32.7 51.7 30.7 14.2
Sierra Leone....... 1963 13.4 5.6 3.1 4.1 24.2 22.1 14.0 9.6
Togo............... 1970 31.8 16.8 5.5 2.1 60.5 48.4 28.0 14.1

CENTRAL AFRICA

Cameroon........... 1976 71.1 56.1 24.2 7.3 78.5 76.1 56.7 29.2

EASTERN AFRICA

Ethiopia5.......... 1970 1.8 0.4 0.1 0.1 11.9 11.4 8.7 6.3
Mauritius.......... 1962 62.0 65.5 49.5 38.0 667.2 80.1 70.1 65.3
Seychelles.......... 1960 (NA) 60.4 52.5 40.3 (NA) 48.8 48.5 35.5
Sudan............... 1973 44.9 27.5 9.8 4.0 64.9 55.2 41.8 30.6
Tanzania........... 1967 42.5 29.4 13.9 4.9 56.3 60.3 49.3 29.4

SOUTHERN AFRICA

Botswana ........... 1964 49.7 52.5 39.8 21.1 32.7 39.3 33.9 23.6
Lesotho............. 1966 63.9 89.1 81.3 49.7 30.2 53.4 49.7 36.8
Mozambique......... 1970 20.9 11.7 6.1 4.3 26.9 24.9 20.0 12.4
Zambia............. 1969 75.6 60.3 33.2 13.7 79.4 82.5 70.3 43.9


1Refers
2Refers
3Refers
4Refers
5Refers
6Refers
7Refers


ages 15
ages 20
ages 40


to 19 years.
to 39 years.
years and over.


to ages 12 to 14 years.
to rural areas only.
to ages 5 to 12 years.
to ages 13 to 24 years.


70 Literacy and Education


Women of the World







Women of the World Literacy and Education 71


Table 4.5. Percent of Population Enrolled in School, by Age and Sex


Female Male

Region and country 5to9 10tol4 15to19 20to 24 5to9 10to 14 15to19 20to24
Year years years years years years years years years


SAHEL WEST AFRICA

Chad............... 1964 (NA) 8.0 (NA) (NA) (NA) 135.7 (NA) (NA)
The Gambia.......... 1973 7.9 12.1 4.7 (NA) 14.3 26.9 17.3 (NA)
Mali............... 1976 212.7 14.7 5.8 1.3 220.1 24.5 14.3 5.7

COASTAL WEST AFRICA

Beni n.............. 1961 (NA) 312.9 41.6 (NA) (NA) 330.3 44.1 (NA)
Ghana............... 1970 245.6 62.4 30.7 2.6 251.5 74.9 53.4 14.4
Guinea............. 1954-55 213.4 516.2 (NA) (NA) 235.2 546.0 (NA) (NA)
Liberia............ 1974 11.4 28.7 20.4 5.3 14.0 40.2 50.7 30.0
Sierra Leone....... 1963 14.0 20.5 4.4 0.2 18.3 35.3 20.8 2.7
Togo............... 1970 20.7 29.6 11.6 1.0 36.8 56.0 31.7 6.9

CENTRAL AFRICA

Burundi............ 1970-71 (NA) 610.0 2.9 70.1 (NA) 620.8 9.8 71.5
Cameroon........... 1976 257.6 64.8 23.9 3.7 264.1 72.5 43.3 11.9
Zaire.............. 1955-57 16.6 31.5 6.5 (NA) 33.2 69.2 42.9 (NA)

EASTERN AFRICA

Mauritius.......... 1972 90.8 62.8 20.0 1.3 91.5 71.4 30.5 3.2
Sudan............... 1973 828.7 38.2 13.1 1.6 839.7 59.3 36.6 8.8
Tanzania........... 1967 12.2 35.2 10.2 1.0 15.6 48.1 27.0 5.5
Uganda............. 1969 25.9 39.0 11.0 0.9 31.6 56.2 32.2 7.4

SOUTHERN AFRICA

Botswana........... 1971 22.0 52.5 28.3 2.6 19.1 41.2 33.0 9.4
Lesotho............ 1966 41.9 80.8 47.8 4.1 25.0 49.0 40.9 15.6
Malawi............. 1977 14.6 44.8 21.0 1.6 16.1 52.4 49.0 13.4
Swaziland.......... 1976 44.1 73.4 37.2 (NA) 41.2 71.4 53.9 (NA)
Zambia............. 1969 27.2 65.1 29.2 1.5 28.2 70.5 60.1 13.8
Zimbabwe........... 1969 29.0 52.3 17.1 1.5 30.9 59.8 32.8 4.9


1Refers
2Refers
3Refers
4Refers
5Refers
6Refers
7Refers
8Refers


to ages 6
to ages 6
to ages 6


ages
ages
ages
ages
ages


14 years.
9 years.
13 years.


14 to 19 years.
10 to 13 years.
5 to 14 years.
20 to 29 years.
7 to 9 years.


Literacy and Education 71


Women of the World








Table 4.6. Percent of Population Enrolled in School, by Age and Sex, for Rural Areas


Female Male

Region and country 5 to9 10to14 15to19 20to24 5to9 10to14 15to19 20to24
Year years years years years years years years years


SAHEL WEST AFRICA

The Gambia.......... 1973 3.6 3.3 1.3 (NA) 9.5 18.9 13.1 (NA)
Mali............... 1976 17.2 6.6 1.4 0.2 114.2 15.5 6.8 1.3

COASTAL WEST AFRICA

Benin.............. 1961 (NA) 28.5 (NA) (NA) (NA) 224.8 (NA) (NA)
Ghana............... 1970 139.1 58.1 27.0 1.6 45.6 70.6 50.6 12.3
Guinea............. 1954-55 112.5 315.0 (NA) (NA) 133.5 343.8 (NA) (NA)
Liberia............ 1974 5.3 17.3 13.1 2.7 8.1 30.2 42.4 25.3
Togo................ 1970 16.6 23.4 7.4 0.3 33.7 51.8 26.5 3.2

CENTRAL AFRICA

Burundi............ 1970-71 6.8 8.8 2.5 40.2 14.8 22.9 8.5 41.1
Cameroon........... 1976 150.1 58.3 18.1 1.9 157.5 67.7 37.7 7.1
Zaire.............. 1955-57 13.4 28.6 6.4 (NA) 30.5 67.9 43.1 (NA)

EASTERN AFRICA

Sudan............... 1973 522.5 28.3 6.8 0.7 534.8 52.8 30.2 6.6
Tanzania........... 1967 10.0 33.5 9.3 0.9 14.5 46.8 26.3 5.4

1Refers to ages 6 to 9 years.
2Refers to ages 6 to 13 years.
3Refers to ages 10 to 13 years.
4Refers to ages 20 to 29 years.
5Refers to ages 7 to 9 years.


72 Literacy and Education


Women of the World









Table 4.7. Percent of Population Enrolled in School, by Age and Sex, for Urban Areas


Female Male

Region and country 5to9 lOtol4 15to19 20to24 5to9 10to14 15to19 20to24
Year years years years years years years years years


SAHEL WEST AFRICA

The Gambia......... 1973 33.9 49.2 18.6 (NA) 46.9 75.4 36.7 (NA)
Mali............... 1976 139.9 46.6 25.3 6.6 150.2 66.1 46.3 21.9

COASTAL WEST AFRICA

Benin............... 1961 (NA) 250.2 (NA) (NA) (NA) 276.3 (NA) (NA)
Ghana.............. 1970 162.2 71.2 37.9 4.5 169.2 86.3 59.6 17.7
Guinea............. 1954-55 124.0 327.1 (NA) (NA) 156.1 369.5 (NA) (NA)
Liberia............ 1974 26.7 54.6 35.2 10.1 29.9 62.7 66.1 36.2
Togo............... 1970 48.6 56.4 29.6 4.5 62.9 82.4 51.5 18.4

CENTRAL AFRICA

Burundi............ 1970-71 60.0 73.0 15.0 0.0 63.0 82.0 31.0 6.0
Cameroon........... 1976 178.6 80.9 35.8 7.3 183.3 84.7 52.3 17.9
Zaire.............. 1955-57 46.3 67.0 9.0 (NA) 60.1 86.5 49.8 (NA)

EASTERN AFRICA

Sudan............... 1973 553.2 70.5 32.6 4.5 560.8 81.8 52.6 13.1
Tanzania........... 1967 62.1 70.1 22.7 2.2 42.8 76.5 36.1 7.1


1Refers to ages
2Refers to ages
3Refers to ages
4Refers to ages
5Refers to ages


6 to 9 years.
6 to 13 years.
10 to 13 years.
20 to 29 years.
7 to 9 years.


Literacy and Education 73


Women of the World






74 Literacy and Education Women of the World





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Women of the World


Chapter 5





Wonn
O) Onn)(^[n

la Eco@oml@



ActiviKy


African women have always worked, both outside and inside
the home-in agriculture, commerce, and handicrafts. The tradi-
tional division of labor by sex in Africa has given women the
major role in agricultural production in addition to their roles of
bearing and raising children and caring for their husbands and
the elderly. Because traditionally women are responsible for pro-
viding their families with food, they control most of the food pro-
duction in the region. Across large areas of the continent, women
decide which food crops to plant, how much, when, and by what
methods, and they exercise substantial autonomy over the
disposition of the crop and the proceeds of the sale of any
surplus. Moreover, although men have been responsible for ex-
port production since such crops were introduced during the
colonial period, women have provided much of the labor for their
cultivation and harvest. It has been variously estimated that Sub-
Saharan African women produce 60 to 80 percent of all
agricultural output, and 90 percent or more of the food crops.
They also carry the major responsibility for processing, storing,
and marketing their agricultural surplus.1
Throughout the dislocations of colonialism and the social and
economic changes since national independence, strong family
and inheritance systems have continued to sustain this pattern
in the sexual division of labor.2 Initially colonial governments and
later many national governments and private corporations found
the system an advantageous one. Because women have con-
tinued to produce the food for subsistence, male labor has been
employed in the modern sector at relatively depressed wages,


'There is a large literature on women's role in agriculture in Sub-Saharan
Africa. See Boserup (1970), Bryson (1981), Halfkin and Bay (1976), Hanger
and Morris (1973), ILO (1981), Kebede (1975), Oppong (1983), Paulme
(1963), and UNECA (1974b, 1978d, 1978e, 1981a, 1981g, 1982b, and
1982c).
2For discussions of the family and social structure supporting the sexual
division of labor, see Boserup (1970), Bryson (1981), and UNECA (1982b).


releasing a surplus for investment in other activities, whether
for national development or for export overseas.3
The agricultural sector is basic to the economy of the region,
but it has been a relatively neglected one during the two decades
since independence while the governments of the region have
concentrated on building national political coherence and have
invested heavily in physical infrastructure, a nascent industrial
sector, and the development of human capital. As a conse-
quence, the productivity of both export and food crops has fallen;
food production has failed to keep pace with the growth of
population, while production for export has stagnated.
Since the late 1970's, however, most of the governments
have recognized the critical importance of agriculture in the
national economy, and have instituted policies and programs
designed to strengthen that sector. Although larger scale enter-
prises have a role to play, it has become apparent to many
African economists and officials that the region cannot hope to
achieve its goal of self-sufficiency in food unless the produc-
tivity of its small farmers is substantially increased. Economists
and planners are also giving increased attention to improving pro-
ductivity in the informal and small business sectors, where
African women play a major role, particularly in marketing and
trade.4 Nevertheless, so great has been the power of Western
presuppositions and models of development, that only in the last
few years have planners begun to recognize the key role of



3For discussions of the role of female agricultural production in the broader
political economy of Sub-Saharan Africa, see Bryson (1981) and UNECA
(1982b).
4A comprehensive review of and prognosis and recommendations for
economic development in Sub-Saharan Africa has been published by the
World Bank (1981). The Bank questions the wisdom of the regional goal of
food self-sufficiency, but highlights the importance of agriculture and the
small farmer. See also Lele (1975).


77







78 Women in Economic Activity Women of the World


women in these sectors, and the importance of facilitating their
access to the resources they need to improve their performance."
A data base on women's economic activities is essential if
planning for the more efficient utilization of the female labor force
is to be effective; without adequate information about women's
activities, those programs designed to improve the productivity
of the small farmer and trader may be targeted inappropriately
or have unexpectedly negative economic and/or social
consequences.6 Yet it is now widely recognized that existing
statistical systems, based on a labor force concept of economic
activity, have failed fully to capture women's productive role
in African society. The shortcomings of existing data on the
female labor force arise from a number of factors, three of the
more important of which are a definition of the labor force which
is based on culturally biased assumptions, derived from Western
experience, about the sexual division of labor and economic rela-
tionships within the household; the practical difficulties of
measuring part time and multiple activities, and production for
use as well as for exchange; and the costs for tabulation by sex
of existing statistical series and/or for the collection of additional
data.
Although different concepts and/or definitions of the
economically active and greater sensitivity to sex biases in data
collection and presentation will be needed to explicate the
African woman's productive roles fully, better exploitation of
data from existing statistical systems will highlight women's
economic activities while identifying data gaps and conceptual
inadequacies. In this chapter, labor force data from the WID Data
Base are presented and examined for their validity as indicators
of the level of women's economic activity in Sub-Saharan Africa.




SSee Boserup (1970) and UNECA (1974b, 1975b, 1978d, 1978e, 1981g,
and 1982c). The World Bank study (1981) makes only oblique reference to
women's key role in African agriculture and writes of "...his willingness to
produce and sell..." However, scattered through the document are specific
recommendations to help women improve productivity: (1) governments
should give proper attention to the labor of both men and women; (2) female
extension workers are needed in order not to talk "with the wrong people";
(3) application of new and appropriate technology to tasks which women
traditionally perform is needed; (4) improved water supply and energy sources
are needed to relieve women of the burden and time spent carrying water
and fuel; and (5) primary health services and family planning would improve
health. For further discussion of appropriate technology, see UNECA (1978a);
of agricultural extension credit, land, and related issues, Dadson (1981), Dey
(1981), Sebstad, et al. (1980), and Staudt (1976); and of workload and time
use, Birdsall (1980), McSweeney (1979), and Szalai (1972). For informa-
tion on women's role in small business and the informal sector, see Benerfa
(1981), Boserup (1970), Gay (1982), ILO (1981), Standing and Sheehan
(1978), UNECA (1975a, 1978e, 1979c, 1979d, 1979e, 1980a, 1980c, and
1 982b), and World Bank (1980b). For reports on women's economic activ-
ity in individual countries, see, for Cameroon, UNECA (1 982b); for Ethiopia,
Kebede (1975) and UNECA (1979d, 1980a, and 1981e); for The Gambia,
Dey (1981); for Ghana, Dadson (1981) and UNECA (1979e and 1982b); for
Ivory Coast, UNECA (1 982b); for Kenya, Kenya Central Bureau of Statistics
(1978), Hanger and Morris (1973), ILO (1981), Pala (1975), and UNECA
(1 979e and 1982b); for Lesotho, Gay (1982); for Liberia, UNECA (1979c);
for Malawi, UNECA (1982d); for Mali, Caughman (1980) and UNECA
(1981b); for Nigeria, UNECA (1981f and 1982b); for Senegal, Braun (1978)
and UNECA (1982b); for Sierra Leone, Tommy (1980) and UNECA (1981c);
for Sudan, UNECA (1975a and 1980c); for Tanzania, Caplan (1981), UNECA
(1981d), and World Bank (1980b); for Uganda, UNECA (1982b); for Upper
Volta, McSweeney (1979); for Zaire, UNECA (1982b); and for Zambia,
UNECA (1979e and 1982b).
6For an account of how a planned investment in the Liberian fishing fleet
had the unintended consequences of depriving Liberian market women of
their traditional role in fish distribution, see UNECA (1979c). For an analytical
framework and model impact study, see Palmer (1979). See also Dey (1981)
and Hanger and Morris (1973).


Data Availability


Data on the labor force come from national censuses, special
labor force surveys, and household surveys undertaken for other
purposes, such as the World Fertility Survey, that also ask about
employment and occupation. Although each source seeks infor-
mation about economic activities, differences in their objectives,
definitions, and data collection procedures mean that data from
the three types of sources may be incommensurate. Even when
data collection procedures are similar, not all the countries in
the region apply existing international definitions and standards
in a consistent fashion, thus making comparisons among the
countries of the region subject to considerable risk of misinter-
pretation. For example, some apply an operational definition of
the economically active which has the effect of including vir-
tually all adults in the tabulated labor force; others exclude nearly
all but wage labor.

Since the 1930's, when the industrial countries became con-
cerned about monitoring the level of unemployment among their
workers, economic activity has been measured by participation
in the labor force. In the years since the adoption of the initial
1938 League of Nations guidelines for labor force statistics,
however, there have been a number of modifications in the
definition of participation and in the terminology to be employed
in data collection. In 1966, the definition was expanded to
facilitate identification of the underemployed. Later modifications
extended the definition of economic activity to include persons
engaged in the subsistence production of marketable goods.
Additional revisions were adopted recently by the 1982 Thir-
teenth International Conference of Labour Statisticians, with the
intention of more clearly differentiating between paid and self
employment, and among the employed, the underemployed, and
the unemployed.7

Nevertheless, production and labor not clearly exchanged in
the market continue to be grossly underestimated. The prob-
lem is particularly severe in cases where women's unpaid family
work and much of their market-oriented activity are closely in-
tegrated with domestic activities. Moreover, as these economic
activities are commonly assumed to be secondary to women's
main occupation of housewife, they are generally excluded from
statistics on the labor force which tabulate principal occupation
only.

Quite apart from the issue of the economic valuation of
women's purely domestic duties is the difficult problem of defin-
ing what constitutes an economic as distinct from a domestic
activity. Activities such as child care or meal preparation are
clearly domestic, but how should the preparation of meals for
farm laborers be classified, or the gathering of fuel, or the
carrying of water, often over distances of several kilometers?
Carrying water, usually the job of women or children, has nor-
mally been considered a domestic activity; yet, for example, the
addition of 100 chickens to the family's livestock has been


'See Beneria (1981), UNESA (1980 and 1983), and Youssef (1980b and
1983).


78 Women in Economic Activity


Women of the World







Women of the World Women in Economic Activity 79


estimated to require the transport of an additional 25 litres of
water per day.8
The concept of the unpaid family worker represents an
attempt to include such unpaid work,,usually of women and
children, undertaken in support of the family enterprise. Many
women working in agriculture have been included in labor force
statistics under this category, as have women working in small
family shops and other informal enterprises in both rural and
urban areas. Other women who are actively engaged in such
activities as trading, handicrafts, small-scale manufacturing, or
services may be classified as self-employed. These two
classifications have not proven entirely satisfactory, however,
as they make it very difficult to distinguish between those who
choose to work for themselves and/or as unpaid family workers
and those who engage in these activities by default, during
periods of unemployment or underemployment; it therefore tends
to result in an underestimation of the extent of unemployment.
Data concerning these categories are thus difficult to inter-
pret, and may become even more so under the rules adopted
in 1 982 for their inclusion in the labor force. Under the previous
definition, to be included in the labor force, an unpaid family
worker must have worked at least one-third of the normal work-
ing hours without direct payment, in some kind of business
owned by a relative; because the one-third time requirement is
more stringent than that for inclusion as an employee or as self-
employed, it has had the effect of undercounting the many wives
and other female relatives who work in family enterprises without
pay. In an effort to correct this anomaly, the 1982 rule calls for
the inclusion in the labor force-whether as employee, unpaid
family worker, or self-employed-of anyone who can satisfy the
not very stringent requirement of a minimum of one hour's
productive work during the reference week. Although this
modification may successfully address the problem of under-
counting, it has created the possibility of a new problem; unless
it is carefully applied, it can have the effect of including in the
labor force all adults, and all children not in school, thereby
destroying much of the usefulness of the concept of the labor
force itself.
In addition to problems in the concept and definition of
economic activity and of the labor force, stereotypes about
appropriate roles for men and women and inappropriate ter-
minology can bias the data collection procedure. Different
answers about women's economic activities result when the
woman herself is the respondent, rather than her husband, or
when either is asked in some detail about the work she does
rather than about her job (see Anker, 1981; and UNESA, 1980).
Moreover, even when data have been gathered about the
activities of both women and men, national statistical offices
may not tabulate those data separately by sex, or may publish
data only for the male population. As a consequence, existing


8For discussions of the measurement problem, see Beneria (1981), Bird-
sail (1980), Boserup (1970 and 1975), Boulding (1983), Buvini6 and
Schumacher (1981), Dixon (1982), DUALabs (1980 and 1981), Halfkin and
Bay (1976), Hanger and Morris (1973), ILO (1981), Jamison and Baum
(1982), McSweeney (1979), Paulme (1963), Population Council (1979),
Recchini de Lattes and Wainerman (1982), Powers (1983), Safilios-Rothschild
(1983), Standing and Sheehan (1978), Szalai (1972), UNDP (1981), UNECA
(1975b), UNESCO (1976), UNESA (1980 and 1983), and Youssef (1980b
and 1983).


labor force statistics are grossly inadequate for assessing the
full extent of women's contribution to the national economy.
Nevertheless, because data from censuses do tend to measure
roughly comparable activities for women and men, that is, work
for a wage or salary, and are reasonably consistent across coun-
tries and over time in measuring those kinds of activities, the
use of census data to monitor women's access to employment
in the modern sector can be defended. In order to monitor
women's participation in the wage economy, some observers
have suggested using a more refined partial activity rate, which
has had several versions but in essence is defined as the per-
cent of women of particular age groups employed in certain
specified modern occupational categories.9
While demonstrably a better measure of female incorporation
into the modern wage sector, these measures require occupa-
tion and industry data which are not always available. Further-
more, the vital role which Africa's women play in agriculture and
trade would be not be captured by such measures. The
majority of women workers would remain invisible were some
version of the partial activity rate to be widely used to monitor
women's integration into the economic development process.
This would in turn thwart the policy objective of making women's
labor statistically visible (and thus more valuable) so as to
strengthen their claim on the national resources they need to
improve productivity. Thus, despite their limitations, census data
on the full labor force afford the most feasible source now
available for monitoring African women's economic activities.
Data in the WID Data Base for describing female labor force
participation in Sub-Saharan Africa are limited. Labor force data
by sex are available for only 31 of the 40 Sub-Saharan African
countries in the data base, and relatively few of the 31 have data
on all the labor force variables or categories of interest. Rural
data by sex are available for just 17 countries; urban data for
only 15. Eighteen of the 40 countries tabulate labor force by
sex and age, but only 14 countries have data by sex, age, and
rural residence, and only 13 by'sex, age, and urban residence.
Twenty-two have data on employment status for the employed
labor force by sex, but only 11 tabulate the same data for rural
and urban areas. For 26 countries, an estimate of the percent
employed in agriculture is available, but for only 21 of these is
that figure shown separately by sex. Nor does the WID Data Base
as yet contain information for the Sub-Saharan African coun-
tries on occupation, industry, and income.10
In most cases, the data in the tables and figures of this chapter
refer to the same dates as those of chapter 3, and come from


FFor discussions of the 'partial activity rate,' see Boserup (1975), Boulding
(1983), Jamison and Baum (1982), and Recchini de Lattes and Wainerman
(1982).
"1For examples of the distribution of female wage employment by industry
and/or occupation, see Gay (1982), ILO (1981 and 1982), and UNECA
(1975a, 1978e, 1979e, and 1980b). Earnings and income data for women
are scanty, but see ILO (1981 and 1982), UNECA 1978e), and World Bank
(1980b). For detailed analysis of the Kenyan Labor Enumeration Survey, see
ILO (1981). For detailed analysis of earnings of urban Tanzanian women,
see World Bank (1980b). Income distribution data for a limited number of
African countries may be found in World Bank (1981). Although some coun-
tries have enacted "equal pay for equal work" laws, women tend to learn
less; this is attributed variously to women's lower education, differential job
titles for the same work, or casual (by the day or by the job) rather than regular
employment status. Some employers cite the costs introduced by laws
requiring maternity leave and day care as reasons for hiring women pri-
marily as casual labor (UNECA, 1979e).


Women in Economic Activity 79


Women of the World







80 Women in Economic Activity Women of the World


the same source, which was often but not always the 1970 cen-
sus round. Some country data were obtained in earlier or later
censuses, while in about one-fourth of the cases, labor force
data were gathered during national demographic surveys, car-
ried out at various times. The comparability of these data, taken
at different times and using different data collection procedures,
is suspect. The analysis which follows is, therefore, limited by
data availability and comparability as well as by whatever biases
and conceptual difficulties those data reflect.



National Level Data

The number of economically active women and men age 10
years and over are presented in table 5.1 for 31 of the 40 coun-
tries, together with labor force participation rates by sex and
the ratio of female to male participation rates. Participation rates
and the female/male ratio are illustrated in figures 5.1 and 5.2
for countries with recent data. Two characteristics of participa-
tion rates are immediately apparent: (1) the almost uniformly high
levels of the male rates, and (2) the extreme variability of the
female rates. If one excludes Zimbabwe, whose statistics do not
reflect the full range of economic activity of the African popula-
tion, almost none of the countries report a male participation
rate under 60 percent, and all but 5 countries report rates of
70 percent or above; the mean is about 78 percent. In contrast,
female participation, although usually lower than male in a given
country, ranges fairly evenly from under 10 to greater than 90
percent, with a mean of only 44 percent. The standard devia-
tion for the male rate is 14, while that for the female rate is nearly
twice as great, at 26 percent (Newman, 1983).
Because of the relative lack of variability in the data for males,
the female/male ratio of percent in the labor force is highly cor-
related with the female participation rate and is also extremely
variable. In four countries-Upper Volta, Burundi, Rwanda, and
Botswana-the female/male ratio is greater than 1.00, that is,
the percent of women in the labor force is greater than that of
men.
Although African countries differ from one another in a number
of respects, it is unlikely that the reported variability in female
labor force reflects so much real variation in the extent of
women's participation in productive activities. Some of the varia-
tion in rates computed from the reported data is the result of
differences in the ages included in the country's definition of
the labor force: all of the countries include the population ages
15 and over in the denominator for calculating participation rates,
but many also include ages 10 to 14 and a few begin as low
as age 6. Some variation is due to differences in the age and
sex composition of the population, and to the extent of urbaniza-
tion and modernization among the countries. There may also be
subregional differences, reflecting both cultural and ecological
factors. Despite the effects of some of these factors, however,
it is highly probable that much of the variation in these rates is
an artifact, reflecting differences in definitions, concepts, and
data collection procedures among the several countries, which
differences are themselves, of course, not completely indepen-
dent of social and cultural biases.


Rural/Urban Differences

For both women and men, the recorded rural activity rates are
greater than urban rates in virtually all the countries. Tables 5.2
and 5.3 present labor force participation rates separately by sex
and female/male ratios of percent active for rural and urban
areas, respectively. The participation rates for women and the
female/male ratios are illustrated in figures 5.3 and 5.4. For men,
rural participation is greater than urban in all 15 countries for
which data are available by sex and rural/urban residence; for
women, rural participation is higher in all but one. Among men,
however, the differences are not large; except in Mali, where
the urban rate is only 69 percent of that in the rural areas,
urban male participation is at least 80 percent of the rural rate.
Among women workers, the countries appear to follow two
different patterns; in nine of the countries, female urban rates
are approximately one-half of the rural rates, while in the remain-
ing six countries the participation of urban women is closer to
the male pattern, with urban rates which are 80 percent or more
of the rural rates. Indeed, in Niger, urban female participation
is slightly higher than rural.
These data show a strong and consistently negative associa-
tion between the level of urbanization, total and female, and labor
force participation-total, male, female, urban, and urban female.
With every increase of 1 percent in the proportion of the popula-
tion living in urban areas, the percent of the population
economically active decreased anywhere from 0.5 percent in
the case of all males, to 1.8 percent for urban females. It is not
known the extent to which this reflects a real decrease in labor
force participation as urbanization increases, or is merely the
result of rural/urban differences in the way in which workers in
the subsistence and informal sectors are counted. These figures
also indicate that urban female participation rates show a greater
decrease with increased urbanization than do those of males
(Newman, 1983). Whether this truly represents a greater female
economic disadvantage as the country urbanizes, or simply
means that rural female workers are more likely to be counted
in the labor force is unknown; perhaps both factors are operating.
There are a number of factors which may contribute to the
rural/urban patterns which are recorded in these data. In most
rural areas, virtually everyone is engaged at some level in
agriculture, and many also work part time in off-farm activities.
In countries where national statistical offices have made
strenuous efforts to count the rural labor force, recorded par-
ticipation rates are likely to be fairly high, and where an attempt
has been made to include women working in subsistence
agriculture, the female rates approach the male rates.
Low participation rates in the cities, on the other hand, reflect
a combination of real differences among certain population
subgroups and the undercounting of those who support
themselves in the large informal sector. In urban areas, relatively
more of the young are in school and more of the elderly have
withdrawn formally from employment, while some of the wives
of the middle class are housewives in the Western style. Except
for these, however, nearly everyone in the city as in the rural
area also engages in income-generating activities, but there is
a greater variety in the things urban people do to earn the cash


80 Women in Economic Activity


Women of the World







Women of the World Women in Economic Activity 81


incomes they require in an urban setting. Their efforts make some
urban dwellers more and others less likely to be recorded in the
labor force statistics-more likely for those who have joined the
modern wage labor force, even at its lowest levels, and less likely
for the vast army of those who operate on its fringe.
Official statistics fail to capture a large proportion of the
latter-the small-scale traders and street vendors of all kinds of
legal and illegal merchandise; those who do odd jobs for
householders; neighborhood traditional healers, herbalists, and
midwives; self-employed seamstresses and off-factory
pieceworkers; caterers and beer brewers; those who do launder-
ing or perform other personal services; prostitutes;1 and so forth.
The economic activities of migrant women, particularly those
who have accompanied their husbands from farm to city, are
often underestimated, as the city offers few opportunities for
formal employment for the poorly educated and unskilled rural
migrants of either sex. In the rural areas from which they came,
the great majority of migrant women had relied upon subsistence
farming or other agricultural employment to secure the necessary
resources to meet their traditional responsibility for providing
their families with food and other household necessities. Their
traditional economic responsibilities do not cease with the move
to the city; indeed, their need for cash income increases, while
very few have the required skills for wage employment in the
modern sector. Consequently, most of these women will join
that informal urban sector whose economic activities remain
unreported or underreported. Thus, while there may in fact be
a somewhat smaller proportion of the urban population
engaged in economic activities, the rural/urban differences
reported in the official statistics are probably exaggerated.



Subregional Differences

Among the more than 50 countries on the continent of Africa,
there are wide variations in ecology, history, and culture.
Because they represent more or less homogeneous
sociogeographic areas, the five subregions of this study of Africa
south of the Sahara have been those employed by USAID: the
Sahel, Coastal West Africa, Central Africa, Eastern Africa, and
Southern Africa. Superficial examination of the data of table 5.1
suggests the presence of differences among the subregions in
reported levels of female labor force participation. Mean values
range from 28 percent in the Sahel to 76 percent in the Central
Africa subregion.
Considering the geographic distribution of female participa-
tion rates, it is clear that there are at least two centers of rela-
tively high reported female economic activity, one in Coastal
West Africa and the other in Central Africa; and two broad bands
of relatively low reported activity, one stretching across the Sahel
and into Sudan, the other from Angola across to Mozambique.


"There are many who have written on women in the informal sector in
Africa. Nearly all of the country reports referenced in footnote 5 include such
discussions. See especially Anker and Knowles (1978), Beneria (1981),
Caldwell (1969), Halfkin and Bay (1976), Little (1973), Oppong (1983),
Paulme (1963), Smith, Khoo, and Fawcett (1983), Standing and Sheehan
(1978), UNECA (1981a), World Bank (1980a and 1980b), and Young and
Moser (1981). For a discussion of prostitution as an avenue to financial
independence, see Little (1973) and UNECA (1981a and 1982b).


Some of the subregional variations may reflect real differences
in the work that women do; for example, the low reported rates
in the Sahel may result from the higher rates of seclusion among
Islamic women in these countries. Some of the differences result
from the definitions and data collection procedures employed.
The extraordinarily high female participation rates of Upper Volta,
for example, are the result of a definition of the labor force which
includes women who were classified as homemakers. Efforts
to relate these geographic patterns to other labor force deter-
minants must await further analysis; in this handbook their
presence is simply noted.



Age Composition of Labor Force


In most countries, the life pattern of work is different for the
two sexes. Most young men enter the labor force when they
leave school, usually in their late teens or early twenties;
thenceforth, until retirement they remain in the labor force, even
through substantial periods of unemployment and underemploy-
ment. The typical age pattern of male economic activity rates,
therefore, whether in urban or rural areas, begins with a relatively
low level among those under age 20 years. Participation rises
sharply among men ages 20 to 29 years, in most countries to
85 percent or more, rises still further to 95 percent or more
among men ages 30 to 39 years, remains at these levels through
the forties, and begins to fall again among men age 50 years
and over. Because the age at which young men enter the labor
force depends upon the availability of educational and training
opportunities, national service requirements, and the like, par-
ticipation rates at the earlier ages vary among countries and,
within countries, by rural and urban residence, far more than they
vary for the prime working ages 30 to 49 years. Differences in
age of withdrawal also result in somewhat more variability in
the rates among those age 50 years and over.
The life pattern of labor force participation is less uniform
among women. Relatively fewer women are formally employed
on a regular basis throughout their adult working lives, but where
educational opportunities for women are limited, they may enter
the labor force in greater numbers at the younger ages than their
brothers do. Thenceforth, women tend to move in and out of
the labor force as they marry, bear and raise children, care for
aged parents, become unemployed for any reason, help out in
the family business, and generally respond to their many family
and social responsibilities. For most of their lives, whether or
not they are in the formal labor force, a large proportion of African
women work in family farms and business enterprises at least
on a part time basis and also supplement family income and/or
provide for their needs and those of their children in the infor-
mal sector through trading, small-scale industry, catering, brew-
ing, and so forth. African women rarely withdraw totally from
economic activity and are usually engaged in more than one kind.
As a consequence of their irregular participation in the formal
labor force, the age pattern of women's economic activity is con-
siderably more variable than that of men. In some countries, the
pattern for women may resemble that for men, although the
levels of participation are lower; in these cases, the rates rise


Women in Economic Activity 81


Women of the World







82 Women in Economic Activity Women of the World


sharply among women ages 20 to 29 years, are highest and fairly
similar among the prime working ages of 20 to 49 years, and
begin to decline after age 50 years. A second common pattern
shows female participation increasing with each 10 years of age,
peaking among the age group 40 to 49 years as the demands
of childbearing and child care slack off.
Both patterns are seen in the WID Data Base. Table 5.4
presents labor force data for women and men by 10-year age
groups: under 20 (usually referring to 10 to 19 years), 20 to 29
years, 30 to 39 years, 40 to 49 years, and 50 years and over.
In seven countries (Chad, Mali, Upper Volta, Guinea, Burundi,
Rwanda, and Zimbabwe), female economic activity follows the
male pattern in which the three groups of mature adults (20 to
29 years, 30 to 39 years, and 40 to 49 years) show roughly
comparable rates; peak levels of activity in these countries vary
from 12 percent active (Zimbabwe, 1969) to nearly 100 per-
cent (Burundi, 1970-71). In 11 countries (Senegal, Ghana,
Liberia, Togo, Cameroon, Mauritius, Sudan, Tanzania, Botswana,
Lesotho, and Malawi), female activity rates rise with each suc-
cessive 10 years of age, to peak at 40 to 49 years; female par-
ticipation levels in the peak years range from 28 to 90 percent.

Although there are rural/urban differentials in levels of labor
force participation, the broad age pattern of labor force activity
is similar in the rural and urban areas of most of the countries.
Labor force participation rates by age and sex for the rural popula-
tion are presented in table 5.5, and for the urban population in
table 5.6. At all ages except the youngest, male rates are typi-
cally higher than female rates, and rural rates are higher than
urban rates. For all ages except the youngest, the usual order
of decreasing labor force participation is: rural male, urban male,
rural female, urban female.
Exceptions to this pattern, however, are found in each age
group, and five of the countries (Upper Volta, Guinea, Togo,
Rwanda, and the Sudan) deviate considerably from the modal
pattern. Upper Volta shows relatively high urban female par-
ticipation at all ages. Rural female participation is relatively high
in Guinea at ages under 50 years, while urban female activity
ranks higher at age 50 years and over (it should be noted,
however, that the only available data for Guinea refer to the
mid-1950's, while those for most other countries relate to the
1970's). In Togo, rural female participation is relatively high at
the youngest ages, while urban female activity exceeds that of
rural women at age 50 years and over. In Rwanda, rural female
participation is relatively high at all ages under 50 years, and
in the Sudan, urban male activity is relatively high during these
ages. Seven of the remaining countries depart from the modal
pattern in only one age group, usually among persons under 20
years where variability is highest; only Chad follows the pattern
in all age groups.
Two measures of women's labor force participation relative
to that of men, that is, female share and the female/male ratio
of percent economically active, are presented by age and
rural/urban residence in tables 5.7 and 5.8. For most countries,
there is a close association between the female share of the total
labor force and the share at each age. Nevertheless, in the rural
areas there is a tendency for that share to peak at ages 20 to
29 years, falling off thereafter with each successive age group.


In the urban areas, female share is likely to be greatest at the
very youngest ages, under 20 years. The peak age is lower in
the cities, in part because young men of these ages tend to
remain in school, postponing entrance into the labor force for
longer periods than young women do. Total female share of the
labor force in the rural areas ranges from 9 percent (Niger, 1977)
to 54 percent (Guinea, 1954-55), with a median of 38 percent;
the median share for rural women in the peak ages (20 to 29
years) is approximately 47 percent. In urban areas, total female
share ranges from 9 percent (Sudan, 1973) to 52 percent (Up-
per Volta, 1975), with a median of 22 percent; the median share
for urban women in the peak ages (under 20 years of age) is
close to 35 percent.
Female/male ratios of the percent economically active in the
rural areas range from 0.09 (Niger, 1977) to 1.06 (Upper Volta,
1975), with a median F/M ratio of about 0.65, that is, the female
rate is about 65 percent as high as the male rate. Comparable
female/male ratios for the urban areas are from a low of 0.12
(Sudan, 1973) to a high of 1.11 (Upper Volta, 1975), with a
median F/M ratio of 0.40. Again, the relatively higher rates of
female participation in the rural areas are evident. In both rural
and urban areas, the female disadvantage12 relative to males is
lowest among the under 20 year olds. Female/male ratios for
this age group in the rural areas range from 0.23 (Mali, 1976)
to 1.16 (Upper Volta, 1975), with a median of approximately
0.91. In urban areas, they range from 0.13 (Sudan, 1973) to
1.24 (Upper Volta, 1975), with a median of 0.49. The very high
ratios among young women in Upper Volta are not the result
of age misreporting; in that country female labor force participa-
tion is high relative to male in all age groups.
On the assumption that opportunities for female employment
are greater where the supply of male labor is relatively deficient,
the influence of the supply of potential and observed male labor
on female labor force participation was examined in an earlier
paper, employing the same data set (Newman, 1983). No signifi-
cant association was found between total female labor force par-
ticipation and female share of the population of working ages,
whether of ages 10 years and over or 15 years and over.
However, when separate analyses were made by 10-year age
groups, a significant tendency was found in the economically
important ages 30 to 39 years and 40 to 49 years for female
participation in the labor force to increase as women's propor-
tion in the population increased, that is, as the relative supply
of potential male laborers decreased. In these age groups, female
labor force participation increased by one percentage point for
each 3.5 to 4.4 point increase in female share of the popula-
tion. The association between participation and female share of
the potential labor supply was also positive in ages 20 to 29
years but did not reach significance and disappeared among the
youngest and oldest age groups.
The relatively high female share of the population in these age
groups which is observed in a number of countries is probably

'2"Disadvantage" may not be the appropriate word here. Except for those
trained at the professional level and relatively few prosperous entrepreneurs,
most women are incorporated into the modern wage sector at the lowest
levels while those who enter the labor force at young ages do so because
of restricted educational opportunities. The "advantage" of participation
under such conditions is dubious.


82 Women in Economic Activity


Women of the World







Women of the World Women in Economic Activity 83


a reflection of the high rates of male labor migration characteristic
of many parts of the Sub-Saharan Africa region, an important
demographic phenomenon with major social and economic con-
sequences for both sending and receiving countries (see chapter
3 of this handbook). Apparently one of the consequences is a
higher rate of female participation in the labor force.


Modernization: Structure of Economy and Labor
Force

Participation in the modern wage sector of the economy is an
important indicator of female integration into the development
process. Although information on employment by industry was
not available in the WID Data Base, examination of three in-
dicators of employment structure may suggest the extent to
which women are participating in economic development: the
percent of female employment in agriculture, the percent of
women employed as unpaid family workers, and the percent self-
employed.

Agricultural Employment. The relevance of percent employed
in agriculture as an indicator of the level of economic develop-
ment is well established, but the use of statistics on female
agricultural workers to assess participation in development is
subject to severe limitations. Women working in agriculture are
particularly subject to undercounting, inasmuch as agricultural
work is usually seasonal, often part time, and typically highly
integrated with domestic activities. The resulting underreporting
of female agricultural workers tends to deflate female labor force
participation in countries where a high proportion of women are
still employed in agriculture.
On the other hand, there is a growing practice among national
statistical offices in the region to include virtually all persons
working in subsistence agriculture, women as well as men, in
the labor force. Such a policy has the effect of raising the female
participation rate close to that of the male, that is, to the 80
to 90 percent range, in countries with high levels of agricultural
employment. Upper Volta is an example of a country following
this practice; the result is a reported female labor force participa-
tion rate in that country of 79 percent, three to four times higher
than the rates of other countries in the Sahel.


Countries vary in the extent of underreporting or, con-
versely, in the degree of possible overreporting of female
agricultural workers; estimates are available for neither. Conse-
quently, it is not surprising that in the WID Data Base, neither
total female labor force participation nor rural female participa-
tion is associated with the proportion of women employed in
agriculture. In table 5.9, the percent of the labor force employed
in agriculture is presented, for the whole labor force and
separately by sex; female/male ratios of percent in agriculture
are shown in figure 5.5.

Unpaid Family Workers and Self-Employed. The percent of the
female labor force employed as unpaid family workers and the
percent self-employed may also indicate the extent to which
women have been integrated into the formal labor force. Data
concerning these categories of employment are difficult to in-
terpret, and as noted earlier in this chapter, the former may
become even more so under the international rules for measur-
ing labor force participation which were adopted in 1982. That
is a problem for the future, however. In the WID Data Base, the
unpaid family worker and the self-employed are two categories
in which women whose work might otherwise have gone
unrecorded have found their way into labor force statistics, and
with the exception of a few countries, the problem generally is
one of undercounting, not overcounting.
Among the 21 countries with such data, there is a positive
but insignificant association between female labor force par-
ticipation and each of these indicators (Newman, 1983). No
significant relationship is evident between the percent of women
who were self-employed and those employed either as unpaid
family workers or in agriculture. There are, however, significant
associations between the proportion of women employed as un-
paid family workers and the percent of both the total and the
female labor force engaged in agriculture. It is a reasonable in-
ference from these data that, to the extent that women
engaged in subsistence farming are being recorded as part of
the labor force, they are being counted as unpaid family workers
and not among the self-employed. In table 5.10, the percent of
unpaid family workers among women and men is shown for the
total labor force and for rural and urban areas. Female/male ratios
of percent unpaid family workers are illustrated in figure 5.6.


Women of the World


Women in Economic Activity 83













Figure 5.1. Labor Force Participation Rates for the Population
10 Years of Age and Over, by Sex


Women Men


Sahel West Africa


Coastal West Africa


Upper Ghana
Volta 1970
1975


Ivory Liberia
Coast 1974
1975


Central Africa


Eastern Africa


Southern Africa


Percent


Burundi Came- Rwanda
1970-71 roon 1970
1976


...':.















Ethiopia Mauri- Seychelles Sudan
1970 tius 1977 1973
1972


Angola Botswana Malawi Mozam- Swaziland
1970 1971 1977 bique 1976
1970


Note: See footnotes to table 5.2 for nonstandard age groups.


Percent


Mali
1976


Senegal
1970


Niger
1977


Togo
1970


Women of the World


84 Women in Economic Activity


ii






Women of the World Women in Economic Activity 85


Figure 5.2. Female/Male Ratio of Labor Force
Participation Rates



F/M ratio
(male=1.0)


Sahel West Africa


1.3
1.2
1.1
1.0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0


Coastal West Africa


Upper
Volta
1975


Ghana
1970


Ivory
Coast
1975


Liberia
1974


F/M ratio
(male=1.0)


Burundi Came- Rwanda
1970-71 roon 1970
1976


Eastern Africa

















Ii I


Ethiopia Mauri-
1970 tius
1972


Sey-
chelles
1977


Southern Africa


Sudan Angola Bot- Malawi Mozam- Swazi-
1973 1970 swana 1977 bique land
1971 1970 1976


* Female rate equals male rate.


Mali Niger Senegal
1976 1977 1970


Togo
1970


Women of the World


Women in Economic Activity 85






86 Women in Economic Activity Women of the World


Figure 5.3. Labor Force Participation Rates for Women,
by Rural/Urban Residence


l U I
Rural Urban


Sahel West Africa


Coastal West Africa


Upper Ivory
Volta Coast
1975 1975


Liberia Togo
1974 1970


Central Africa


Cameroon
1976


Rwanda
1970


Eastern Africa


Ethiopia
1970


Sudan
1973


Percent


Mali
1976


Niger
1977


Senegal
1970


Percent


Southern
Africa


Malawi
1977


86 Women in Economic Activity


Women of the World










Figure 5.4 Female/Male Ratio of Labor Force Participation
Rates, by Rural/Urban Residence


Rural Urban


Sahel West Africa


1.3
1.2
1.1
* 1.0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0


Senegal
1970


Coastal West Africa


Upper Ivory
Volta Coast
1975 1975


Liberia Togo
1974 1970


Central Africa


Cameroon
1976


Rwanda
1970


Eastern Africa


Ethiopia
1970


Sudan
1973


* Female rate equals male rate.


F/M ratio
(male=1.0)


Niger
1977


EL
Mali
1976


F/M ratio
(male=1.0)


Southern
Africa


Malawi
1977


Women of the World


Women in Economic Activity 87







88 Women in Economic Activity Women of the World


Figure 5.5. Female/Male Ratio of Percent of Labor Force
in Agriculture


F/M ratio
(male-1.0)


- Sahel
- West Africa






-
i
-
------------




-










Mali
1976


Coastal West Africa


Ghana
1970


Ivory Liberia
Coast 1974
1975


Sierra
Leone
1973


Central Africa


1.6
1.5
1.4
1.3
1.2
1.1
*1.0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0


F/M ratio
(malel1.0)


Eastern Africa


Southern Africa


Mauritius Seychelles
1972 1977


Botswana Lesotho
1971 1976


Malawi Mozambique
1977 1970


* Female percent equals male percent.


Cameroon Rwanda
1976 1970


Ethiopia
1968-71


Women of the World


88 Women in Economic Activity








Women of the World Women in Economic Activity 89


Figure 5.6. Female/Male Ratio of Percent of Unpaid Family Workers


F/M ratio
(male=1.0)


Sahel
- West Africa


Mali
1976


Coastal West Africa


Ghana
1970


Liberia
1974


Togo
1970


Central Africa


8.0


7.0


6.0


5.0


4.0


3.0


2.0


S1.0


0.0


F/M ratio
(male=l.0)


Eastern Africa


0.0
Ethiopia Mauritius Seychelles
1970 1972 1977

* Female percent equals male percent.


Sudan
1973


Southern Africa


Botswana Malawi Mozambique
1971 1977 1970


Burundi Cameroon Rwanda
1970-71 1976 1970


8.0


7.0


6.0


5.0


4.0


3.0


2.0


*1.0


Women in Economic Activity 89


Women of the World









Table 5.1. Number and Percent Economically Active Among Population Age 10 Years and
Over, by Sex, and Female/Male Ratio of Percent Active
(Numbers in thousands)


Women Men
Region and country F/M ratio
Year Number Percent Number Percent (male=1.00)


SAHEL WEST AFRICA

Cape Verde.............. 1960 20 26.9 43 73.8 0.36
Chad1...................... 1964 216 27.8 563 94.3 0.30
Mali2..................... 1976 368 15.9 1,825 83.7 0.19
Mauritania ,3............. 1965 48 18.2 261 94.6 0.19
Niger .................... 1977 131 8.6 1,263 94.3 0.09
Senegal5.................. 1970 346 22.8 824 60.3 0.38
Upper Volta............... 1975 1,499 79.4 1,375 74.5 1.07

COASTAL WEST AFRICA

Benin1 .................... 1961 443 74.0 498 94.7 0.78
Ghanal ...................1970 1,472 34.1 1,859 43.8 0.78
Guinea ................ 1954-55 692 82.5 624 90.9 0.91
Ivory Coast5.............. 1975 969 38.9 1,932 70.4 0.55
Liberia.................... 1974 116 22.2 317 59.9 0.37
Sierra Leone.............. 1963 334 43.1 604 80.0 0.54
Togo6..................... 1970 323 54.7 405 81.7 0.67

CENTRAL AFRICA

Burundi................... 1970-71 1,112 88.7 930 84.9 1.04
Cameroon5................. 1976 1,102 37.7 1,656 60.0 0.63
Rwandal................... 1970 878 96.6 807 96.2 1.00
Zairel1.................... 1955-57 3,247 79.7 3,063 84.0 0.95

EASTERN AFRICA

Ethiopia3................. 1970 1,718 32.9 4,952 93.5 0.35
Mauritius6................ 1972 54 18.6 215 75.1 0.25
Seychelles6............... 1977 10 45.6 16 76.6 0.60
Sudan1.................... 1973 694 21.7 2779 89.6 0.24
Tanzania.................. 1967 2,758 67.0 3,076 78.9 0.85


See footnotes at end of table.


90 Women in Economic Activity


Women of the World









Table 5.1. Number and Percent Economically Active Among Population Age 10 Years and
Over, by Sex, and Female/Male Ratio of Percent Active-Continued
(Numbers in thousands)


Women Men
Region and country F/M ratio
Year Number Percent Number Percent (male=1.00)


SOUTHERN AFRICA

Angola7..................... 1970 107 19.0 601 91.2 0.21
Botswan .................... 1971 145 67.0 110 65.5 1.03
Lesotho ...................1966 228 76.5 143 78.4 0.98
Malawi...................... 1977 1,056 55.6 1,232 71.1 0.78
Mozambique.................. 1970 771 28.1 2,156 81.9 0.34
Swaziland.................. 1976 40 28.2 68 58.9 0.48
Zambial..................... 1969 344 30.2 815 77.0 0.39
Zimbabwel................... 1969 151 6.0 774 30.4 0.20


1Refers to ages 15 years and over.
2Refers to ages 8 years and over.
3Refers to rural areas only.
4Refers to ages 14 years and over.
5Refers to ages 6 years and over.
6Refers to ages 12 years and over.
7Based on data from 9 of 15 administrative districts.


Women in Economic Activity 91


Women of the World




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