Public Disclosure Authorized. PEN Technical Note FERTILITY IN SUB-SAHARAN AFRICA: LEVELS AND THEIR EXPLANATION. Public Disclosure Authorized

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1 Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized PEN Technical Note FERTILITY IN SUB-SAHARAN AFRICA: LEVELS AND THEIR EXPLANATION by Susan H. Gochrane and Samir N. Farid Reissued April 1986 Population, Health and Nutrition Department World Bank The W4orld Bank does not accept responsibility for the views expressed herein which are those of the author(s) and should not be attributed to the World Bank or to its affiliated organizations. The findings, interpretations, and conclusions are the results of research supported by the Bank; they do not necessarily represent official policy of the Bank. The designations employed, the presentation of material, and any maps used in this document are solely for the convenience of the reader and do not imply the expression of any opinion whatsover on the part of the World Bank or its affiliates concerning the legal status of any country, territory, city area, or of its authorities, or concerning the delimitations of its boundaries, or national affiliation.

2 PHN Technical Note FERTILITY IN SUB-SAHARAN AFRICA: LEVELS AN] THEIR ATION A B S T R A C T This paper presents a detailed analysis of fertility in 10 sub-saharan African countries for which World Fertility Survey da;a are available. These data and similar data from other developing countries allow the exploration of fertility levels, determinants and differentials and comparisons of these with similar measures in other regions. The analysis indicates that fertility is higher in sub-saharan Africa than in other regions of the world and that in 7 of the 10 countries it has been rising to some extent over the last 20 years whereas in other parts of the world it has been falling. The high current level of fertility results from a pattern of early and universal marriage and very little use of contraception. Fertility would be even higher if it were not for prolonged and near universal breastfeeding. Low usage of contraception arises from relatively poorer contraceptive knowledge and higher family size preferences and higher infant and child mortality than is generally true in other regions. Sub-Saharan Africa is both like other regions in that socioeconomic differentials in fertility and its proximate determinants do exist and unlike other regions in the size and pattern of those differentials. For example there seem to be three patterns of socioeconomic differentials in fertility. Sub-Saharan African has high base levels of fertility and relatively small differentials. Asia has low base levels and small differentials and Latin America has high base levels and large differentials. Therefore it is necessary to use care in generalizing from the fertility experience of other parts of the world in determining the probable trends of fertility in sub-saharan Africa. * ** * ** *** * Prepared by: Susan H. Cochrane and Samir M. Farid Reissued April 1986

3 SUMMARY AND CONCLUSIONS In this paper we have attempted to provide a detailed analysis of the fertility levels, trends and determinants in the 10 sub-saharan Africa countries for which WFS surveys have been conducted. One of the excellent feature of WFS 1s that the surveys were conducted in such a way that although surveys differ in some respects and the quality of the data are not equally high in all countries, the data are broadly comparable. This enables us to make comparisons not only among the countries of sub-saharan Africa, but between sub-saharan Africa and other regions of the developing world. In addition, WFS staff have executed a wide range of sophisticated analysis on a wide range of countries that could be drawn on with minor adjustments to enrich the analysis of the present paper. Our findings on the levels and trends in actual fertility are quite similar to those documented elsewhere. Current fertility is higher in sub-saharan Africa than in all other regions except the Middle East, but this has not always been the case. Africa included here the majority (7) In the 10 countries of sub-saharan have shown some fertility increase in the last 20 years and only Ghana has shown some small decline. So for the whole, fertility appears to have risen while in other regions fertility has been declining with the largest declines in Latin America, followed by Asia and thea North Africa; even in the Middle East there has been some fertility decline. The high current levels of fertility in sub-saharan Africa result from patterns of early and universal marriage and very little use of contraception. The main factor which can be documented in this analysis

4 that has kept fertility below a biological maximum has been prolonged and near universal breastfeeding. The low level of contraceptive use in sub-saharan Africa arises in part from poor co.traceptive knowledge, relative to other regions, much higher family size preferences and higher infant and particularly child mortality. The pattern of fertility in sub-saharan Africa, however, does not appear to be fully explained by the proximate determinants of marriage, post-partum infecundity (breastfeeding) and contraceptive use. Either abortion, sterility, sub-fecundity or spousal separation appear to suppress the "maximum' fertility below that observed in other regions and this suggests that more work on other biological determinants of fertility is needed to understand current levels and probably future trends in sub-saharan Africa. The high levels of fertility and the patterns of marriage, breastfeeding and contraceptive behavior that lead to these levels arise in part from the fact that sub-saharan Africa is highly rural and still has relatively few well educated individuals who have adopted modern fertility aspirations. Urbanization and education do not explain everything, however. Generally in sub-saharan Africa, those in urban and rural areas, educated and uneducated are not identical among themselves or to those with the same characteristics elsewhere. Both the urban and rural, educated and uneducated in sub-saharan Africa have and want more children than their counterparts in other regions. This is not to say that education and urbanization do not play an important role in determining fertility, but that differentials in fertility behavior and aspirations, patterns of marriage, breastfeeding and contraception are different in sub-saharan Africa than elsewhere,

5 In general fertility in sub-saharan Africa tends to be higher among the rural and uneducated than elsewhere and fertility falls less with increases in urban residence and education. In Latin America, relatively high levels among the uneducated and the rural are in sharp contrast to those among the urban and educated. Asia by contrast has lower levels of fertility among its rural and uneducated than do sub-saharan Africa or Latin America and also has smaller differentials than does Latin America (slightly larger differentials than sub-saharan Africa). This pattern of high base fertility and small differentials reflects patterns in socio-economic differentials in marriage, breastfeeding and contraception. In general in sub-saharan Africa there are relatively small urban-rural differentials in marriage patterns, but large educational differentials. Thne large educational differentials in age at marriage are not reflected, however, in large educational differences in fertility. Looking at contraceptive use we find that the educational differentials are as expected which would tend to reinforce the fertility differences that should arise from differences in age of marriage, but the overall usage of contraception is generally very low in sub-saharan Africa only reaching about 20% among the most educated. Therefore the small educational differentials in fertility must be explained by some other factor. One explanation frequently given for the small differentials in fertility across socio-economic groups in sub-saharan Africa is that as women become more educated and modern they tend to abandon traditional methods of fertility control such as breastfeeding without compensating by adoption of modern methods of contraception. A detailed, quantitative

6 analysis of the proximate determinants of fertility in different socio-economic groups could not be carried out with this data at this time. Simple analysis of differentials in sub-saharan Africa relative to other regions however does not support this view. There are very high levels of use of breastfeeding among the least educated in sub-saharan Africa, and breastfeeding does not drop rapidly with education. The most educated in sub-saharan Africa have durations of breastfeeding which greatly exceed those in Latin America and considerably exceed those in Asia. This suggests that more exploratory work is needed to explain the differentials in fertility in sub-saharan Africa. This reinforces what has frequently been stated that more African specific models are needed. This should not be interpreted as a defeatist version of what we know about fertility and its determinants in sub-saharan Africa. These data indicate that family size preferences, contraceptive use and marriage patterns do change with education in ways which will ultimately lower fertility and infant and child mortality. In addition, there is not the great cause for alarm frequently cited of widespread abandonment of lactation with urbanization and education. While this is found in Latin America where breastfeeding is of very short duration among the most educated and the urban, this pattern is not yet found in these 10 sub-saharan Africa countries. This reinforces the importance of not generalizing from other regions in analyzing sub-saharan Africa. Sub-Saharan Africa is both like other regions in that differentials do exist and unlike other regions in the size of those differentials and the pattern of those differentials vis-a-vis the proximate determinants of fertility. Thus we know a considerable amount about fertility and its determinants in sub-saharan Africa, but there is a need to know more.

7 INTRODUCTION In Africa as elsewhere, fertility forms the basis of, and is itself a product of, social and economic organization. The number, and the timing of births determine the future potential human resources, to be realized according to the availability of nurturing services, health, education, housing, etc. This, however, entails diverse results in respect of the number, nature and demands of the human resources supplied thereby. On the one hand is the traditional scenario whereby a wiomen spends most of her reproductive years in childbearing and childrearing, a crucial part of which is a struggle to provide the physical bare necessities for survival. Aside from domestic work or work in the family enterprise, her pre-reproductive life may also have included the child-care of younger siblings. Similariy, her post-reproductive years may involve her in the rearing of her children's children. On the other hand there is a scenario featuring low fertility, a high standard of living and raised expectations. In this case less physical energy is channelled into childbearing and the mere struggle for survival of the smaller number of children. However, other aspects of social and economic survival may prove at least as demanding of both physical and emotional input. An emphasis on the realization of the child's full, potential for example, or the standards set among the offspring's peer group, in conjunction with additional extra roles for the parents in society all represent stressful demands. Such over-simplified family stereotypes have importantly different implications not only for the size of the future population, and the nature of the human resources that may be available, but also on the demands placed on the

8 - vi - family, the organizatilyc and location of family units, and on the time spent on reproduction, on women's status and the nature of their lives. Other papers in this series have documented the high level and variation in levels of fertility in sub-saharan Africa. The paper by Hill, et.al., on the demographic situation in sub-saharan Africa documented several important points: (1) current fertility (TFR's) is unquestionably very high in sub-saharan Africa by world standards although in t:he Middle East and parts of Central and Andean America have fertility as high; (2) "...there is a distinct regional pattern, with fertility distinctly higher in Eastern than in Western Africa" (Hill, et.al., p 55); (3) "... there is a very marked area of relatively low fertility in Central Africia, where the TFR's have been generally rising in recent years to more normal levels" (Hill, et.al, p 55); (4) "...there has been no documented decline in fertility anywhere in sub-saharan Africa in the post-world War II period" (Hill, et.al., p 55). The excellent descriptive analysis of the Hill, et.al. paper does not allow one to explore the causes of these fertility patterns in detail. Recently available WFS data on 10 sub-saharan Africa countries does provide some insight into these causes. In addition the Bongaarts, et.al. paper and that by Acsadi and Johnson-Acsadi have documented the supply and demand factors which contribute to high fertility in sub-saharan Africa. In the present paper, we hope to examine the fertility of sub-saharan Africa in a comparative context, studying differences between sub-saharan Africa and other developing countries, differences between sub-saharan Africa countries for which data are available and differences between groups within sub-saharan Africa

9 - vii - countries. Thus this paper will provide details on fertility determinants, botth proximate and socio-economic that were not available previously. The data for this paper come from detailed tabulations of 10 WFS surveys in sub-saharan Africa as well as published from WFS surveys in other parts of the developing world. The paper is divided into sections. In Part 1 the data and methodology of the study are discussed. In Part 2 the fertility levels of the 10 WFS countries in sub-saharan Africa will be compared with other regions of the world. Part 3 of the paper attempts to explain these patterns by examining the proximate determinants of fertility, marriage, post-partum infecundity and contraceptive use. Parts 4 through 6 will examine the proximate determinants in more detail. Part 7 will explain low contraceptive use by examining both family size preferences and child survival. After reviewing the proximate determinants, we shall then explore the socio-economic determinants. Part 8 will examine the socio-economic differences in fertility in sub-saharan Africa and compare those with other parts of the world. Parts 9 to 11 wil l, examine socio-economic differentials in proximate determinants in sub-saharan Africa. Part 12 will review the socio-economic differences in desired family size and infant and child mortality. The logic of this structure is that fertility is determined by several different kinds of factors. The most immediate determinants are the proximate determinants of marriage, breastfeeding and other biological factors as well as contraceptive use. These proximate determinants are determined by human decision making to a large degree and those decisions,

10 - viii - particularly with respect to contraceptive uisage, are in turn determined by family size aspirations and infant and child mortality. All these factors and the decisions they imply are in turn a function of the socio-economic circumstances of individuals. Therefore a different way of explainiing fertility is by explaining how it varies across socio-economic groups. This form of explanation is particularly of interest to those who wish to hypothesize about how fertility will change with socio-economic development. A thorough analysis of explanations of fertility levels requires all types of explanation both singly and in combination. This is what we shall attempt in this paper.

11 Table of Contents Page No. S ummary and Conclusions i-iv Introduction *.... O v-viii I. The WFS African Surveys MaJor Characteristics... I...-.o Descriptior. of the Explanatory Variables... 2 II. Fertility Achieved Fertility e Current Fertility Levels Fertility Trends... e * o... 7 III. Proximate Determinants IV. Marriage Patterns... e * Introducton Proportions Ever Married Transitions in Cohort Nuptiality n. e V. Breastfeeding Introduction Proportion of Children Ever Breastfed Duration of Breastfeeding e Overall Mean Duration... o Maternal Age and Parity VI. Contraceptive Knowledge and Use Introductio-a Contraceptive Awareness Levels of Use Differentials in Contraceptive Use by Age and Family Size VII. Motivation for High Mortality in Sub-Saharan Africa Fertility Preferences Infant and Child Mortality in Sub-Saharan Africa Levels and Trends in Infant and Child Mortality Comparisons of Infant and Child Mortality in Sub-Saharan Africa and other Developing Regions..... *

12 Table of Contents (Cont.) Page No, 7.5 Family Building Correlates of Infant and Child Mortality...* Maternal Age Birth Order Birth Spacing VIII. Socio-Economic Differentials in Fertility Urban-Rural Differentials Educational Differentials Differentials According to Husband's Occupation Differentials by Wife's Work Status IX. Socio-Economic Differentials in Age at Marriage X. Socio-Economid Differentials in Breastfeeding Introduction Urban-Rural Differentials Educational Differentials XI. Socio-Economic Differentials in Contraceptive Use Urban-Rural Differentials Educational Differentials XII. Socio-Economic Differentials in Desired F.imily Size and Infant and Child Mortality Urban-Rural Differentials in Family Size Preferences Urban-Rural Differentials in Infant and Child Mortality Educational Differentials in Family Size Preferences Educational Differentials in Infant and Child Mortality Bibliography Tables... 73

13 I. THE WFS AFRICAN SURVEYS 1.1 Major Characteristics The 10 African countries included in this study conducted national fertility surveys from 1978 through Table 1.1 sunmmarizes the major characteristics of these surveys. The survey in the Sudan was originally designed as a two-phase survey covering the 12 provinces in the northern part of the country, and the six provinces in the southern part. For operational reasons, the survey in the Sudan was conducted only in the northern provinces. Essentially, the sample for each survey was designed as a multistage probability sample of households, each of which was interviewed with a household schedule. Within these households, a sub-sample of individuals, women of childbearing age, were selected for interview with the Individual Questionnarie. Seven countries (Benin, Cameroon, Ghana, Ivory Coast, Kenya, Nigeria and Senegal) included all women, i.e., single and ever-married samples in their individual surveys. The other three included only ever-married women. The Individual Questionnaire consisted of the WFS Core Questionnaire and incorporated the WFS Module on "Factors Other Than Contraception Affecting Fertility". The Ivory Coast survey also utilized an individual questionnaire for husbands. The standard WFS Individual Questionnaire was produced in four languages: English, French, Spanish and Arabic. In some sub-saharan countries scores of different languages are spoken. The WFS policy of conducting interviews in the local languages on the basis of a verbatim

14 -2- version of the questionnaire in these languages, resulted in 8 out of the 10 WFS African surveys using more than one language version of the questionnaire. The situation is summarized in Table 1.2 (for further details see Vassen, et.al., 1984). 1.2 Description of the Explanatory Variables The main findings of the WFS African surveys are analysed in this report not only at the national level but also in terms of different subgroups. These subgroups are defined by four variables which represent the major dimensions normally considered in the investigation of socio-economic determinants of fertility. The four variables are: type of place of current residence, respondent's level of education, respondent's work status, and husband's occupation. In this study, we follow the definitions used by WFS in its Cross National Summaries series for these four variables. Further details on these variables are found in Singh (1984). Type of Place of Residence Type of place of current residence is represented by a trichotomy: major urban areas, other urban areas, and rural areas. Major urban areas include cities, urban agglomerations with populations exceeding one million, and also include the capital city, regardless of size. The remaining urban areas fall into the "other urban" category. In Lesotho, the number of urban respondents is too small to support the distinction between the two types of urban areas, and the respondents are classified as simply urban and rural. It should be pointed out, however, that, in most developing countries, the continuum from rural to major urban places encompasses variation in socio-economic and other variables which affect reproductive behaviour (Alam and Casterline, 1984).

15 -3- Level of Education The respondents completed years of schooling are grouped into four categories: no schooling, 1-3 years, 4-6 years and 7+ years. Work Status Each of the WFS surveys collected respondent's employment histories both before marriage and for current or most recent work since marriage. In this report we utilize only information on work since marriage as that is thought to be more pertinent (see Rodriguez and Cleland, 1980). The work status distinction is made between women who did not work and those who worked. Of the latter group, an important demarcation is made between those who worked primarily in the informal sector, i.e. for themselves or their family, and those who worked for non-relatives who are presumably more likely to be paid in cash and to work away from home. Thus the three categories used for this varible are: did not work; family or self-employed; and worked for others. Husband's Occupation A four-category classification of the respondent's husband's current or most recent occupation is derived by collapsing the WFS nine-category scheme available for most countries. The professional, administrative and managerial group and the clerical workers are combined to form one category of white collar workers. Also combined are the skilled and unskilled manual workers, and the sales and service groups. The fourth category consists of agricultural workers (including those engaged in fishing or forestry), represented by two separate categories: self-employed and non-self-employed.

16 -4- II. FERTILITY This section is concerned with fertility patterns in Africa. While information on fertility among couples in Africa has been sparse until recently, the general impression has been one of pro-natalist societies in which the average number of births per women has been and remains high. The WFS African surveys allow the validation or otherwise of this general statement and also the quantification of the rather vague expression "high fertility". 2.1 Achieved Fertility Our measure of achieved fertility will be the accumulated number of live births that each women has had up to the date of the survey. This number is referred to as the women's "current parity". The data on current parity or the number of children ever-born from the African surveys are cross-sectional and do not refer to the reproductive behaviour of a cohort of women as it grows older. Thus, for the younger women current parity will reflect their fertility during a limited period only, while for the older women this measure comes close to their life-time fertility. The mean numbers of children ever-born to ever-married and to all women, by current age, are shown in Tables 2.1 and 2.2. The reported completed fertility of all ever-married women ranges from: -- over 5 children in Cameroon and Lesotho; -- about 6 children in Benin, Mauritania, Nigeria, and Sudan; to -- about 7 children in three countries; Ghana, Ivory Coast, and Senegal -- almost 8 children in Kenya

17 -5- These figure give an average of 6.36 in sub-saharan Africa which compares with 7.00 in 3 North Africa countries, 6.30 in 10 countries of Asia and 6.65 for 8 countries of Latin America. Thus among these older women, sub-saharan Africa is not abnormally high in its fertility. The parity distribution for women (Table 2.3) shows considerable dispersion, with a skew toward the high parities in all the countries, with the exception of Cameroon. Thus, in 9 of the 10 countries included here, more than half of the women aged have had seven or more children. The data on achieved fertility by current age also show high levels of fertility by women of all ages in all the countries considered. Among ever-married women the mean number of births is in excess of three children in all but 2 countries. The mean is also around two children to women in 6 of the 10 countries included. Detailed tabulations show that as age increases, the distribution of women by current parity becomes more dispersed. It is when we look at children ever born by these younger women in Table 2.1 that we see that it is here that the fertility of sub-saharan Africa is abnormally high by world standards. One finds for all women that children ever born in sub-saharan Africa exceeds that for women in Asia, Latin America and North Africa from the youngest age up through the age group Among 35-39, fertility of women in sub-saharan Africa is slightly below that in North Africa and for women over 40 it is slightly below that in Latin America slightly above that in Asia and very much below that in North Africa.

18 Current Fertility Levels For all of the 10 African countries included here, current fertility levels far exceed those required to attain moderate population growth, let alone bring about an eventual end to such growth. In fact, current fertility levels in Africa are as much as twice to three times the replacement level fertility. in these countries, fertility would have to be substained at the "replacement level of births per women for up to 60 years before annual births and deaths would come into balance. The 'replacement level fertility" depends, of course, on current mortality levels, which are higher in Africa than in most other developing regions and developed countries. In developed countries, current replacement level fertility is 2.1 births per woman. We may compare the level of fertility across African countries using the total fertility rate (TFR). This is the number of children a woman would bear in her lifetime, were she to experience, at each age of her reproductive life, the current prevalent rate of childbearing among women of her age. Age-specific fertilty rates and total fertility rates, averages over the five years prior to each survey, are.hown in Table 2.4. The level of current fertility measured in this way is highest in Kenya (8.3 children per woman) and lowest in Lesotho (5.8 children). The region shows quite a wide range in TFR's. The total fertility rate is less than 6 children only in Lesotho; between 6 and 7 children in 5 countries (Cameroon, Ghana, Mauritania, Nigeria and Sudan); between 7 and 8 children in 3 countries (Benin, Ivory Coast and Senegal); and over 8 children in Kenya. These figures compare with TFR's in North Africa which average 5.82, 5.00 in Asia and 4.84 in Latin America. Only 4 countries of the

19 -7- Middle East where TFR's average 6.99 exceed the sub-saharan Africa average of 6.71 (see middle column of Table 2.6). There are interesting intercountry differences in the timing of childbearing which are not mirrored in the current level of fertility. Fertility rates are markedly high for women aged 15-19, in sub-saharan Africa (Table 2.5). Overall, the fertility of women is generally about 100 births per 1000 women in North Africa, but between 150 and 200 in most sub-saharan countries. Almost all of the 10 countries have high fertility rates over a broad age range extending over ages with peak fertility occurring at ages in Cameroon, Ivory Coast, Lesotho and Nigeria, and at ages in the remaining countries. In the latter group, the fertility rates in the age group rank second to those in the peak group. 2.3 Fertility Trends Changes in fertility can be inferred by comparing the completed fertility of women aged at the time of the survey, with the level of current fertility as measured by the total fertility rate. Alternatively, by combining data from the birth histories of the women interviewed and basic information obtained in the household interview, age-specific fertility rates and total fertility rates can be derived for intervals of time receding from the survey date in 5-year blocks. Only Ghana shows a very small decline in fertility. In another two countries, Senegal and Sudan, lifetime fertility is more or less equal to current fertility level. In the remaining seven sub-saharan countries, current fertility levels are higher than the reported completed fertility of women aged 45-49, by about one child in Benin and Cameroon and about 0.4 children in the remaining countries. (See Table 2.6)

20 -8- One useful summary index of fertility change may be obtained by dividing the cumulative fertility (P) of the oldest age-cohort, i.e. women years, by the level of period fertility (F) in the most recent five-year period. The resulting ratio is known as the P/F ratio. It was originally proposed as a means of identifying reporting errors, but this is appropriate only in situations where fertility has remained constant. The P/F ratio will, however, reflect real changes also, either of declines in fertility, when the ratio is greater than unity, or of rises in fertility, when the ratio is under 1.00, The P/F ratio can, therefore, equally be treated as an indicator of fertility change, as well as a measure of reportiav error. In Table 2.6 the P/F ratios for age group are shown for the 10 countries included here. Ghana shows a very small decline of 4 percent, while Senegal and Sudan show almost no change. Six sub-saharan African countries (Kenya, Mauritania, Ivory Coast, Lesotho, Nigeria and Benin) show moderate rises in fertility of 4-11 percent. A very large rise in fertility of as much as 19 percent is shown for Cameroon.l/ The situation of rising fertility an average for the 10 sub-saharan African countries should be compared with the rest of the world. On average every other region has experienced fertility declines (see column 3 of Table 2.6). The largest decline has been in Latin America followed by Asia and then North Africa. Even the Middle East, in contrast to sub-saharan Africa; has experienced some fertility decline. Before we examine recent fertility trends using the birth histories data, it should be pointed out that these histories are in fact 1/ These fertility increases could be due to either real increase in the fertility of younger cohorts, or to date misreporting and omission of births on the part of older women, or to an unknown mixture of both.

21 -9- incomplete. Due to the restriction of the surveys to women below age 50 years at the time of the interview, the sets of age-specific fertility rates become progressively truncated from above as they apply further back in time. For example, for the period years before the survey, only births to women who were then aged less than 35 years may be considered. The usual total fertility rate, therefore, cannot be calculated because of the truncation of the set of age-specific fertility rates. Instead, they are constructed by assigning the values of the adjacent period to the missing fertility rates. For a country with declining fertility, the total fertility rates calculated in this way will tend to understate the scale of fertility change. Table 2.4 gives the estimated total fertility rates for five-year periods prior to each survey. A detailed examination and evaluation of the data quality of these rates revealed that fertility has declined recently by about 0.5 child in Ghana, Kenya, Senegal and Sudan, In the remaining six sub-saharan African countries (Benin, Cameroon, Ivory Coast, Lesotho, Mauritania and Nigeria) little, if any, real change in fertility appears to have taken place in the recent past. In Cameroon, however, the data shows a continuous rise in fertility.

22 10 - III. PROXIMATE DETERMINANTS The evidence in the preceding section has documented the very high current fertility in sub-saharan Africa which results from high levels among older women and increases in fertility in recent years in 7 of the 10 countries. There are very great differences within sub-saharan Africa as well. Kenya has the highest fertility and Lesotho the lowest. Ghana, Cameroon, Mauritania, Nigeria and Sudan have the next lowest and Benin, Ivory Coast and Senegal have current fertility about one child less than Kenya. These current patterns arise from different combinations of initial levels of fertility and recent trends. Ghana is the only country which appears to have had a modest fertility decline while fertility has been approximately constant in Senegal and Sudan, The other countries have experienced fertility increases. The differences in fertility among sub-saharan African countries and the rest of the world arise from patterns of marriage, contraception and post-partum infecundability (mainly a function of breastfeeding). Abortion and sterility also play a role in determining fertility among some groups, but their roles are much more difficult to document. In this section we shall document the extent to which marriage patterns, contraceptive use and post-partum infecundability suppress fertility below its biological maximum in sub-saharan Africa and compare these findings with those for other geographical regions. This section is heavily depednent on methodological developments and comparative analysis outlined in a recent WFS paper by Casterline, Singh, Cleland and Ashurst. In their paper, however, data were available on only 5 sub-saharan African

23 countries and none of the North African countries. Therefore, we shall expand the evidence on which they based their analysis and in sections which follow we will analyze African patterns of marriage, contraceptive use and breatfeeding in more detail. In this section a multiplicative model of fertility is used by Bongaarts, 1978 and "expresses the actual level of fertility (the Total Fertility Rate, TFR) as the outcome of the fertility reducing effects of the four main proximate determinants on a maximal Total Fecundity Rate (TF): TFR = cm X cc X Ca X ci X TF (i) Where cm is the index of nuptiality, Cc is the index of contraception, ca is the index of abortion and ci is the index of postpartum infecundability. The index of abortion is omitted from the application due to lack of data for all countries (Casterline, et.al, 1983, p 1-2). cm is defined as the weighted average of time spent in a union in the 5 years prior to the survey (the same reference period as the TFR). cc is defined as one minus the proportion using contraception at the time of the survey with adjustment made to reflect the efficiency of the contraceptive method mix. ci is calculated on the basis of the length of breastfeeding and assumptions about the effect of breastfeeding on amenorrhea. Table 3.1 sutmmarizes these indices for the 10 sub-saharan African countries and regional averages for 10 Asians, 2 Middle Eastern, 3 North African and 12 Latin American and Caribbean countries. It should be noted

24 that the TFRs reported here are not identical to those shown elsewhere in every case because these TFRfs are based only on fertility within marriage. The deviation from earlier rates is very large for Kenya (7.4 versus 8.25) and Lesotho 5.27 versus 5.76 and are smaller but substantial in Ghana (6.22 versus 6.47) and Senegal (6.90 versus 7.15). Thus the average TFR for legitimate fertility in sub-saharan Africa is only 6.52 compared with 6.71 for all fertility. Patterns of total legitimate fertility in Table 3.1 mirror those for all fertility with fertility in sub-saharan Africa only exceeded by that in the Middle East. The high fertility in sub-saharan Africa results in part from a pattern of marriage which achieves martial exposure for 80% of the time available compared with about 70% in Asia and North Africa and 66% in Latin America. The Middle East has intermediate values of cm. With respect to contraceptive behaviour Africa can be distinguished from all other regions including the Middle East. Although there are differences among other regions, on the average they lose about 20% of reproductive capacity because of contraceptive use (21% in North Africa and 18% in the Middle East) while Latin America loses 35% and sub-saharan Africa loses less than 5%. Thus sub-saharan Africa's fertility is abnormally high relative to the rest of the developing world because of early and universal marriage and very little use of efficient contraception. Fertility in sub-saharan Africa would be much greater if it were not for the very high prevalence and long duration of breastfeeding. Post-partum infecundability is more important absolutely (and relatively) in sub-saharan Africa than elsewhere

25 accounting for 59% of the reduction in fertility from biological maximum (see Table 3.2). On average fertility in sub-saharan Africa is only 67% of what it would be in the absence of breastfeeding. This is close to the 68% found in Asia (It is the long breastfeeding in Nepal, Bangladesh and Indonesia which make Asia as low as it is.) and the approximately 70% in North Africa, but far below the 80% found in the Middle East and the 84% found in Latin America. It is the low usage of breastfeeding in the Middle East with its relatively high prevalence of marriage which accounts for its high fertility. Multiplying these factors we find that the total fecundity rate in sub-saharan Africa is This is substantially below that found in the Middle East (15.50) and North Africa (14.57) and considerably below Asia (13.19) but close to that found in Latin America (12.80), This difference probably arises from factors not included in the model abortion, infertility (primary and secondary) and low coital frequency due to spousal separation not accounted for by post-partum abstinence and incorporated in ci. These regional patterns disguise some variation among the countries of sub-saharan Africa. The marriage index ranges from a low of.741 in Lesotho to a high of.862 in Nigeria being well above average in Benin, Ivory Coast and Senegal, the 3 countries with fertility close to the high level of Kenya and well below average in Sudan and Mauritania. cc shows a variation of about 11 percentage points as well from a high of 99 in Mauritania to a low of 88 in Benin, but there is little correspondence between TFR's and cc and cc's are very close for Kenya (94) the highest and Lesotho (96) the lowest fertility country in the region because usage is just too low to have substantial impacts on fertility.

26 - 14 Variation in breastfeeding (ci) is somewhat less, only 6 percentage points, with a low of 64 in Benin and Nigeria and a high of 70 in Mauritania. Overall variation in fertility in sub-saharan Africa is not completely explained by the three measures included here. This fact is reflected by high illegitimate fertility in some countries mentioned previously and by the very wide differences in the Total Fecundability Rate. Benin. This ranges from a low of in Lesotho to a high of in In addition to Lesotho, TFR below 12 are also observed in Mauritania, Nigeria and Sudan while the rate of 15 is uniquely high with the next closest value being i.n Kenya. Ivory Coast follows with a TR of and Cameroon, Ghana and Senegal have rates between 12 and Thus the overall sub-saharan Africa average of which is very low by world standards is in fact elevated by extreme values for sub-saharan Africa found in only 3 countries (Benin, Ivory Coast and Kenya). This suggests that more work is needed on other factors which in fact suppress fertility in sub-saharan Africa before we can understand the sub-saharan Africa pattern well enough to understand what future trends are likely to be.

27 IV. MARRIAGE PATTERNS 4.1 Introduction In all the African countries in the study virtually everyone ultimately marries, but there are wide variations in the timing of marriage between and within these countries. There are differences by urban residence and across levels of educational achievement (see Section 9). The change from early to later ages at marriage is generally seen as a response to the modernization process in a society. Socio-economic differentials in the age at first marriage are known to constitute one of the intermediate variables which account for fertility differentials. In the African socio-economic context, shifts in the age pattern of first marriage assume special demograpic significance. Patterns of nuptiality were a major concern of all the WFS surveys, including the African fertility surveys. The WFS used a wide definition of "marriage" to include all unions with a recognized social status. This meant that "amitie" or "union libre" in French speaking African countries were covered and recognized as reproductive unions. 4.2 Proportions Ever Married By way of general introduction to the analys e of African nuptiality patterns, data on the proportion ever married by five year age groups, together with estimates of the singulate mean age of marriage (SMAM) are shown in Table 4.1. The proportion ever married (PEM) among men and women show that marriage is almost universal in Africa. The youngest female nuptiality pattern is Ivory Coast and Senegal, and the oldest for Sudan. shown for Cameroon, Senegal has the highest

28 proportion ever married in the age group About 59% of these teenagers are married. Cameroon has 53% and Ivory Coast 56% married in this age group. This high level of teenage marriages in these societies is an important factor in their high fertility levels, since they also have low contraceptive use. The proportion ever married at is also over 40% in Benin, Mauritania and Nigeria; over 30% in Ghana and Lesotho; and over 20% in Kenya and Sudan. The average for sub-saharan Africa is 40% which compares with 17% in North Africa, 32% in the Middle East, 26% in Asia and 20% in Latin America and the Caribbean. (Annex Table WFS Conference 1984) The proportion of wom!n who ever married exceeds 75% in 9 sub-saharan African countries, only in Sudan is it lower. In general, we find that the northern African countries have older marriage patterns than the sub-saharan African countries. The singulate age at first marriage ranges between 17.5 in Cameroon and 21.3 in Sudan, averaging This compares with 22.2 in North Africa, 20.3 in the Middle East, 21.3 in Asia and 21.5 in Latin America. (Annex Table WFS Conference 1984) Men show a much older age pattern of marriage than women. The SMAM for males, however, varies within a narrower range than for females, and ranges from 25.4 years in Lesotho to 28 years in Senegal The mean age difference at union between partners is 8-10 years in most sub-saharan African countries. 4.3 Transitions in Cohort Nuptiality Nuptiality as a demographic event may be characterized by its age pattern or tempo and by its ultimate level. These two aspects of

29 nuptiality are not necessarily interdependent. Thus, while first marriage in Africa has remained virtually universal, some changes have taken place in the tempo of nuptiality in the recent past. Trends in the tempo of female nuptiality may be analyzed by linking data on date of first marriage obtained in the individual survey of women with data on current marital status from the household survey. This enables us to study the age patterns of cumulative proportions married for successive age cohorts, using the life table approach (Ebanks and Singh, 1984; Farid, 1979; Smith, 1980). Table 4.2 shows the cumulative proportions of women ever married before attaining specified ages for recent five-year age cohorts under 30 years. The table brings out in sharper focus the prevalence of a very early marriage pattern in sub-saharan Africa and a relatively late marriage pattern in North Africa. Among women currently 25-29, the proportion ever married before reaching age 25 ranges from 87 to 97% in sub-saharan African countrfes, ccapared with 81% in Egypt, 84% in Morocco and 75Z,' in Tunisia, while this proportion in Tunisia does not exceed 75%. The figures in Table 4.2 also show a clear trend towards later marriage in Africa as evidenced by the decreases in the proportions of young marriages. The change appears to have been in the direction of delaying first marriage as follows: -- from the early teens (under 15) to the middle teens in: Cameroon, Mauritania, Nigeria and Senegal; -- from the middle teens to the late teens in: Benin, Kenya and Sudan; and Only three of the 10 countries covered in sub-saharan Africa do not show any significant changes in their nuptiality patterns: Ivory Coast

30 with its early-teens marriage pattern, and Ghana and Lesotho which have a middle teens pattern. The upward shift in the age pattern of first marriage at the teenages reflects, of course, an upward trend in age at first marriage. This may be illustrated by an examination of trends in the median age at first marriage, i.e. the age by which 50% of the women of any given cohort had entered into a first marriage. Table 4.3 shows that among the cohorts of ages up to 45-49, the median age at first marriage in all the African countries covered, has always been achieved before the age of 20 years. It is interesting to note that in Kenya, and Sudan, women currently at years have not attained the 50 percentile ever in a union. In contrast, and as we go from the older to the younger cohorts, little if any, change is shown for Ivory Coast and Lesotho, while very small increases in the median age at first marriage are shown for the remaining sub-saharan African countries. But larger increases of 2 to 3 years are shown for Sudan.

31 V. BREASTFEEDING 5.1 Introduction We turn next to investigate patterns of breastfeeding and their potential fertility implications in sub-saharan Africa. Though the principal interest in breastfeeding is usually its effect on child health, there are also physiological effects on the mother. In particular breastfeeding a child is associated with a delay in the return of ovulation and hence in the biological capacity to conceive. In the absence of any other form of family planning, therefore, breastfeeding may extend the interval to the next conception and ultimately affect a woman's total fertility. Breastfeeding also represents one of the mechanisms through which mortality may influence fertility, since the effect of an infant death before it is weaned may be a reduction in the period of non-susceptibility to conception. In the traditional fertility context, featuring the absence of modern methods of contraception, birth spacing is largely a function of the norms governing behaviour after birth. Most important of these is the non-susceptible period associated with lactation. Among those groups of women who do not practise any form of contraception, breastfeeding is one of the most important volitional factors that affect birth spacing and hence ultimate family size. To the extent that women have adopted modern methods of family planning, breastfeeding has less impact on the overall level of fertility. It has been observed in many societies that among those women who innovate in respect of family planning, notably in the modern urban sector, there

32 has coincidentally been a decline in the proportion of children who are breastfed and in the number who are breastfed for extended periods. This trend in breastfeeding is, however, usually prompted by considerations quite apart from family planning and it often takes place in the absence of any significant change in contraceptive use. While on average breastfeeding postpones the return of ovulation, individual experience varies quite considerably. The effect is non-linear, diminishing with the age of the child, so that breastfeeding is neither perceived to be, nor is it in reality a very effective method of contraception. In practice when the period of post-partum abstinence is short it may often be the advent of the next pregnancy that prompts weaning, in the belief that continued breastfeeding would be harmful to the foetus or to the living child. The child health and fertility effects of breastfeeding are clearly not independent of one another, The cessation of breastfeeding induced by an early infant death may hasten the return of ovulation and reduce the interval to the next conception. Short birth intervals are themselves associated with higher mortality risks for both children, especially the child born at the end of the interval. When an infant is not breastfed, or is weaned when it is very young, both higher mortality and shorter birth intervals are indicated. In the WFS African surveys, the questions on breastfeeding applied to the last two children born to a woman, whether or not they were still alive and even if one or both of them lived only for a short time. The results presented here refer to breastfeeding status at the time of the interview. The breastfeeding rates derived from status at interview are called 'current status, rates, (Ferry and Smith, 1983).