2
Fertility Levels, Differentials, and Trends

Barney Cohen

INTRODUCTION

Fertility rates are higher in sub-Saharan Africa (Africa) than in any other major region of the world, and considerable controversy surrounds the likelihood of these rates declining in the near future. Although mortality and fertility rates fell substantially in Latin America and Asia between 1965 and 1985, only mortality declined in Africa; fertility remained relatively stable, well above a level required to replace the population. Consequently, the region experienced extremely rapid population growth, with rates for some populations considerably above 3 percent per year (United Nations, 1991; Freedman and Blanc, 1992). A few countries, most notably Kenya, Botswana, and Zimbabwe, have begun the transition toward lower fertility, but smaller declines in fertility have been observed recently in many other countries. Nevertheless, fertility rates generally remain above six children per woman, and the question of whether Africa is more resistant to fertility change than other regions of the world is a topic of considerable debate

   

Barney Cohen is a research associate for the Committee on Population, National Research Council. He thanks Anouch Chahnazarian, James Gribble, Carole Jolly, and the editors for helpful comments on an earlier draft. The author is also grateful to George Bicego, Bill Chu, Timothy Fowler, Ronald Freedman, Bill House, Vasantha Kandiah, Tim Miller, Sidney Moore, and Pat Rowe for their help in providing some of the data used in this report. Anne Scott assisted with the computer programming of the B60s.



The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement



Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 8
Demographic Change in Sub-Saharan Africa 2 Fertility Levels, Differentials, and Trends Barney Cohen INTRODUCTION Fertility rates are higher in sub-Saharan Africa (Africa) than in any other major region of the world, and considerable controversy surrounds the likelihood of these rates declining in the near future. Although mortality and fertility rates fell substantially in Latin America and Asia between 1965 and 1985, only mortality declined in Africa; fertility remained relatively stable, well above a level required to replace the population. Consequently, the region experienced extremely rapid population growth, with rates for some populations considerably above 3 percent per year (United Nations, 1991; Freedman and Blanc, 1992). A few countries, most notably Kenya, Botswana, and Zimbabwe, have begun the transition toward lower fertility, but smaller declines in fertility have been observed recently in many other countries. Nevertheless, fertility rates generally remain above six children per woman, and the question of whether Africa is more resistant to fertility change than other regions of the world is a topic of considerable debate     Barney Cohen is a research associate for the Committee on Population, National Research Council. He thanks Anouch Chahnazarian, James Gribble, Carole Jolly, and the editors for helpful comments on an earlier draft. The author is also grateful to George Bicego, Bill Chu, Timothy Fowler, Ronald Freedman, Bill House, Vasantha Kandiah, Tim Miller, Sidney Moore, and Pat Rowe for their help in providing some of the data used in this report. Anne Scott assisted with the computer programming of the B60s.

OCR for page 8
Demographic Change in Sub-Saharan Africa (Boserup, 1985; World Bank, 1986; Caldwell and Caldwell, 1987, 1988, 1990; Lesthaeghe, 1989; van de Walle and Foster, 1990; Caldwell et al., 1992). The level of fertility in sub-Saharan Africa, as measured by the total fertility rate (TFR),1 is approximately 6.0–6.5 births per woman. This figure masks considerable variation between regions and between individual countries. For example, the most recent estimate of the total fertility rate in Rwanda (8.5 births per woman in 1983) is almost double the most recent estimate for the population of black South Africa (4.6 births per woman in 1987–1989). More generally, fertility rates in East and West Africa are greater than those in Central Africa, in part because of the historically high prevalence of sexually transmitted diseases (STDs) in certain areas of Central Africa (Frank, 1983; Tambashe, 1992). The prevalence of STDs is associated with unusually high rates of infecundability in the region especially prior to the 1970s. Fertility was probably higher in East Africa than in West Africa during the 1970s and 1980s, although the difference appears to have lessened in the more recent past. Reported fertility rates rose in certain parts of Africa in the late 1960s and 1970s; however, it is not clear what proportion of the increase was the result of improvements in data accuracy. In addition to the regional and national variation in fertility rates, there is often considerable variation in fertility within countries. Repeatedly, fertility surveys have recorded substantial differences in rates among ethnic, geographic, and socioeconomic groups. For example, fertility rates are consistently lower among women who live in urban areas, women who have more than primary school education, and women who work in the formal labor market. In Africa, the number of women in each of these socioeconomic groups has, at least until recently, been small, and the groups overlap considerably. Consequently, lower fertility among these women has a minimal effect on national-level TFRs. The objective of this chapter is to summarize existing knowledge on levels, trends, and differentials in achieved fertility in sub-Saharan Africa. Although there have been several comprehensive reviews of fertility levels in Africa in the past (see, for example, Brass et al., 1968; Page and Coale, 1972; United Nations, 1987), new sources of data make it possible to update 1   There is no single, readily agreed upon best measure of fertility. The total fertility rate is a synthetic measure that expresses the total number of children a hypothetical woman would have if she survived to the end of her reproductive years (taken to be 49) and if she experienced the same level and pattern of fertility throughout her reproductive life as women at the time the data are collected. An advantage of using the TFR over other measures of fertility, such as the crude birth rate, is that it is independent of the age structure of the population.

OCR for page 8
Demographic Change in Sub-Saharan Africa the analysis to the early 1990s. By employing a wide variety of data sources, including some that have not been readily accessible in the past, estimates of fertility rates are presented for virtually all countries in sub-Saharan Africa. True understanding of fertility trends in Africa is clouded by the extremely variable quality of demographic data in the region. Close examination of much of the data reveals gross inconsistencies that are the result of misreporting of ages and omitting or systematically displacing vital events. In an attempt to correct for obvious data errors, a mixture of direct and indirect estimation techniques is used to determine fertility rates. The indirect techniques are based on the examination of inconsistences within the reported data or on comparisons of observed data to values expected from various demographic models. The chapter is organized as follows: Issues of data availability and quality are discussed in the following section. In the third section, four methods for estimating TFRs are presented. Characteristics of African fertility are presented in the fourth section. Next, recent data from the Demographic and Health Surveys are used to examine the possible evidence for declining fertility levels in Africa. The penultimate section compares recent fertility trends in Africa to those in other developing areas of the world. Finally, there is a summary and some concluding observations. SOURCES AND QUALITY OF DEMOGRAPHIC DATA IN AFRICA The state of demographic data collection in Africa has recently been reviewed by de Graft-Johnson (1988). Despite dramatic improvements since the 1960s, our knowledge and understanding of fertility levels and trends in Africa are still surprisingly weak. Until 1960, virtually no sub-Saharan African country had conducted a complete census. Consequently, little was known about the size or structure of the region’s population. In the few countries where censuses were undertaken, they were often unreliable and of very limited content. A fundamental problem facing researchers in Africa was that a large percentage of the adult population was unable to report its age accurately. Further, many early censuses did not include questions related to the number of children ever born and childhood mortality. In addition, vital registration data were virtually nonexistent throughout the region and, when available, were of questionable quality. Fortunately, demographic data collection in Africa has improved considerably over the last 30 years. Although vital registration is still rare, most countries have conducted one and in many cases several censuses, though quality has been uneven. In addition, many countries have supplemented efforts to collect reliable demographic data with various ad hoc

OCR for page 8
Demographic Change in Sub-Saharan Africa national and subnational household demographic surveys. Some of the most accurate information comes from these large-scale demographic surveys. In particular, the World Fertility Surveys (WFS), an international data collection effort undertaken from the mid-1970s to the early 1980s, and the ongoing Demographic and Health Surveys (DHS) begun in the mid-1980s, have generated a reasonably accurate data base for calculating fertility levels and differentials for countries in sub-Saharan Africa. The WFS carried out surveys in nine sub-Saharan African countries: To date, the DHS has published demographic reports for 13 sub-Saharan African countries and issued preliminary results for 4 others. Reports for 4 additional African countries are scheduled for release by the end of 1993. Special attention is given in this chapter to the DHS because it is the source of most of the recent demographic data on Africa. The quality of DHS data was recently analyzed by DHS staff and found to be generally acceptable. But, in cases where data problems were identified, they were determined to be most severe in sub-Saharan Africa in comparison to other regions of the developing world (Institute for Resource Development, 1990:2). For example, Arnold (1990) identified errors in the coverage and timing of births, including (1) systematic displacement of children’s birth dates, (2) disproportionate numbers of women’s ages heaped on digits ending in 0 and 5, and (3) missing or incomplete information in some birth histories. These problems were determined to be most severe in Botswana, Burundi, Liberia, Mali, and Togo. Problems in the first category arose, in part, because some interviewers appear to have deliberately altered the ages of children under 5 to avoid asking an extensive series of questions on the health and well-being of young children. A second assessment of the quality of DHS data focused on women’s age at first birth and judged that response problems were most severe in African countries, especially Mali and Liberia (Blanc and Rutenberg, 1990). The African data suggest that some women omit information about early births or displace the dates of low-parity births forward in time, making children appear younger than they really are. Finally, Rutstein and Bicego (1990) report that less than 80 percent of women interviewed in Africa provide accurate birth dates for their children. Fortunately, the effect of displacement problems on fertility levels is relatively minor. For example, Arnold and Blanc (1990) calculate that without any displacement, the total fertility rate in Liberia, the country with the most displacement, would have been 6.5 instead of 6.3 births per woman between 1983 and 1988. Nevertheless, it is important to acknowledge that there is always the danger of drawing incorrect conclusions from data collected in areas where vital events go unrecorded. Consequently, a single point estimate of fertility from Africa should be interpreted with some caution.

OCR for page 8
Demographic Change in Sub-Saharan Africa In this chapter, DHS and WFS data are supplemented by data collected in censuses and other national demographic surveys. Where no other information was available these data are augmented with findings from large-scale subnational studies. Data from small-scale studies conducted at the district or provincial level have not been used due to concerns regarding their generalizability. Naturally, censuses and surveys are carried out in different countries at different times. But, unlike the estimates presented by several organizations (including the United Nations and the U.S. Bureau of the Census), the estimates presented here are not standardized on a specific year. Rather, the current goal is to present the reader with the original data from which standardized estimates are derived. METHODS FOR ESTIMATING TOTAL FERTILITY RATES Four distinct strategies are used here to obtain independent estimates of fertility. The first strategy is to calculate fertility directly, without adjusting for any apparent inconsistencies in the data. This method requires information on the number of women of childbearing age, their ages, and the number of births to these women during a given time period, typically five years. Direct estimates of fertility are reported only when the quality of the data was thought to be adequate, for example, as in all the WFS and the DHS. In these cases, fertility estimates are derived by using retrospective birth histories. Experience has shown, however, that response errors in census and survey data can often lead to biased or inaccurate estimates of the fertility rate. Response errors in birth history data arise mainly from age misreporting and the omission or systematic displacement of vital events. For example, many women incorrectly report their own age or the ages of their children. Similarly, in the absence of written records, women often forget births that occurred in the distant past and make systematic errors when estimating the timing and spacing of events (Potter, 1977). Older women, women with little education, women who were not in sanctioned unions at the time of their first birth, and women whose children have moved away or died are particularly likely to make these types of errors. Obvious errors, such as birth intervals of less than 6 months or first births to women under 10 years of age, can often be detected by the interviewer or the researcher and perhaps corrected by cross-referencing birth dates with well-known historical events. Errors resulting from omitted births are much harder to correct. Demographers have developed alternative methods designed to improve their ability to make “indirect” inferences about fertility from poor or incomplete data (Brass et al., 1968; United Nations, 1983). Most of these methods involve the identification of internal inconsistencies in the reported

OCR for page 8
Demographic Change in Sub-Saharan Africa data or the comparison of observed data to model fertility schedules. In cases where the direct and indirect estimates of fertility are substantially different, the indirect estimates are usually preferred. Three of the four strategies used in this chapter employ indirect techniques. One strategy is based on the principle of comparing reported births in a given time period with women’s responses to questions regarding the number of children ever born. A full description of this method (commonly called the method of P/F ratios) can be found in United Nations (1983). The data requirements for this method are identical to those for direct estimation except that they include information about the number of children ever born. Where the data allowed, this technique was used to check and, if necessary, to adjust the survey or census estimates for apparent misreporting. Unfortunately, because this method relies on equating current and past experiences, it has the potential for producing biased estimates of the total fertility rate when fertility has recently declined (United Nations, 1983:32). Nonetheless, at least for the earlier time periods, this method arguably produces the most accurate estimates possible. Because early censuses often did not include specific questions on fertility, the age structure of the population may be the only information available to estimate the total fertility rate. In these cases, fertility estimates are inferred by using stable population theory, which is based on assumptions of constant fertility and mortality. The only data requirements for these estimates are the age structure of the population, the growth rate, and an estimate of the level and pattern of mortality. Because results from this estimation method are not particularly robust and are quite sensitive to different mortality assumptions, it is used only in the absence of other alternatives. In an attempt to check the robustness of these approximations, similar estimates are also derived by using a method developed by Coale (1981) and later extended by Venkatacharya (1990). This method, labeled the Coale method, also relies on stable population theory and requires an estimate of the population growth rate, the proportion of both sexes under the age of 15, and an estimate of mortality for children up to age 5. Assuming constant fertility rates for the population under consideration, Coale (1981) suggested that his method would yield reasonable estimates of the total fertility rate for 7.5 years prior to the census date, even if the census or survey was characterized by severe age misreporting.2 2   Another indirect method, the “variable-r” technique suggested by Preston (1983), was dropped after it was ascertained that age structure data in the earlier African censuses were not of sufficiently high quality to provide accurate independent estimates of the fertility rate.

OCR for page 8
Demographic Change in Sub-Saharan Africa CHARACTERISTICS OF AFRICAN FERTILITY Estimates of Total Fertility Rates Table 2–1 provides estimates of the TFR for 38 African countries for which data were available at some point during 1960–1992. For ease of comparison, all estimates were converted into point estimates of the total fertility rate. In reality, a particular figure may be the midpoint of a range of plausible estimates. Table 2–1 highlights the paucity of demographic data in many African countries. Despite considerable improvements in the availability of data during the past 10 years, 12 countries still have fewer than four data points since 1960. In other cases, although data exist, they are of extremely variable quality. Consequently, fertility trends over time may appear more erratic than they truly are. For example, in Ethiopia, the data imply a substantial increase in fertility during the 1970s followed by a rapid decline in the 1980s. Both trends are almost certainly exaggerated. Although the data are often sketchy, several important conclusions may still be drawn about fertility in Africa. Few countries in Africa have TFRs less than 6.0, and nowhere is fertility currently less than 4.0 births per women, a rate well above that required for replacement. Africans have a strong preference for large families. Children are prized not only as the means of preserving family lines, but as positive economic assets that provide labor, wealth, risk insurance, and old-age security to their parents. In the past, high fertility in Africa resulted from early and near universal marriage,3 and extremely low rates of efficient contraception. Fertility has been controlled (outside geographic areas of pathological sterility) by social pressures against premarital sex, the practice of postpartum sexual abstinence, and long breastfeeding periods that lead to lengthy lactational amenorrhea (see Chapter 3; also Caldwell and Caldwell, 1977, 1987; Page and Lesthaeghe, 1981). Bongaarts et al. (1990) recently estimated that fertility in Africa would increase by 72 percent if the fertility-inhibiting effects of breastfeeding and postpartum abstinence were removed. These fertility-reducing practices have probably evolved principally to ensure exceptionally long birth intervals in an effort to combat high rates of infant mortality. Recently there are signs that some of these cornerstones of African fertility may be weakening (see Chapter 3; also Schoenmaeckers et al., 1981; Caldwell et al., 1992; Westoff, 1992). 3   Divorce is common in Africa but so is remarriage, particularly if the woman is still in her reproductive years, so the total time lost to exposure to the risk of childbearing may be small (Smith et al., 1984). Several institutions, including polygamy and the levirate, a practice whereby a widow automatically remarries a close relative of the deceased (often his brother), facilitate quick remarriage following widowhood.

OCR for page 8
Demographic Change in Sub-Saharan Africa TABLE 2–1 Fertility Estimates for Various Sub-Saharan African Countries, 1960–1992 Country Date of Estimate TFRa,b Data and Methodologyc Reference Western Benin 1961 6.9 Demographic Survey, Dahomey Benin (1988)   1965 7.1 World Fertility Survey, 1981–1982 Cochrane and Farid (1989) 1970 7.0 World Fertility Survey, 1981–1982 Cochrane and Farid (1989) 1975 7.0 World Fertility Survey, 1981–1982 Cochrane and Farid (1989) 1979 7.3 Census; stable population theory United Nations (1984)d 1980 7.1 World Fertility Survey, 1981–1982 Cochrane and Farid (1989) Burkina Faso 1960–1961 6.2 National demographic survey Burkina Faso (n.d.)e   1960 6.6 Census; stable population theory United Nations (1979)d 1969 6.4 1975 census (Coale method) United Nations (1984)d 1973–1974 7.2 Subnational survey U.S. Department of Commerce (1979) 1976 6.7 Postenumeration survey Burkina Faso (n.d.)c 1985 7.2 Census Burkina Faso (n.d.)e Côte d’Ivoire 1963 7.5 World Fertility Survey, 1980–1981 Cochrane and Farid (1989)   1962–1964 6.4 National demographic survey U.S. Department of Commerce (1979) 1968 7.5 World Fertility Survey, 1980 Cochrane and Farid (1989) 1973 7.9 World Fertility Survey, 1980–1981 Cochrane and Farid (1989) 1975 6.9 Census; stable population theory United Nations (1990)d 1978 7.7 World Fertility Survey, 1980–1981 Cochrane and Farid (1989) 1978–1979 6.9 National survey; P/F ratios Ahonzo et al. (1984) 1981 7.4 1988 census; Coale method Lopez-Ecartin (1992e)d 1988 6.8 Census; method of estimation not stated Lopez-Escartin (1992e)f The Gambia 1973 6.4 Census; P/F ratios The Gambia (1976)   1983 6.9 Census; stable population theory United Nations (1990) 1983 6.4 Census; P/F ratios The Gambia (1987) Ghana 1960 7.2 Postenumeration survey U.S. Department of Commerce (1979)   1960–1964 7.2 World Fertility Survey, 1979–1980 Singh et al. (1985)

OCR for page 8
Demographic Change in Sub-Saharan Africa Country Date of Estimate TFRa,b Data and Methodologyc Reference Ghana 1965–1969 7.0 World Fertility Survey, 1979–1980 Singh et al. (1985)   1968–1969 7.1 National demographic survey, second round U.S. Department of Commerce (1979)f 1970 7.3 Census; stable population theory United Nations (1979) 1970–1974 6.9 World Fertility Survey, 1979–1980 Singh et al. (1985) 1978 6.2 1984 census; Coale method Ghana (n.d.)e 1975–1979 6.5 World Fertility Survey, 1979–1980 Singh et al. (1985) 1982–1984 6.6 Demographic and Health Survey, 1988 Ghana (1989) 1985–1988 6.4 Demographic and Health Survey, 1988 Ghana (1989) Liberia 1967 6.8 1974 census; Coale method United Nations (1984)d   1970–1971 6.3 Liberian population growth survey U.S. Department of Commerce (1979) 1974 6.2g Census Chieh-Johnson et al. (1988) 1977 6.6 1984 census; Coale method Liberia (n.d.)d,e 1980–1982 7.0 Demographic and Health Survey, 1986 Chieh-Johnson et al. (1988) 1983–1986 6.8 Demographic and Health Survey, 1986 Chieh-Johnson et al. (1988) Mali 1960–1961 7.4 Demographic survey Traoré et al. (1989)   1976 6.3 Census; stable population theory United Nations (1984)d 1981–1983 7.1g Demographic and Health Survey, 1987 Traoré et al. (1989) 1984–1986 6.9 Demographic and Health Survey, 1987 Traoré et al. (1989) 1987 6.8 Census; method of estimation not stated Lopez-Escartin (1992a)f Mauritania 1964–1965 5.7 Demographic survey U.S. Department of Commerce (1979)   1962–1966 6.5 World Fertility Survey, 1981 Cochrane and Farid (1989) 1967–1971 6.9 World Fertility Survey, 1981 Cochrane and Farid (1989) 1972–1976 7.2 World Fertility Survey, 1981 Cochrane and Farid (1989) 1977 7.0 Census; stable population theory United Nations (1990)d 1977–1981 6.3 World Fertility Survey, 1981 Cochrane and Farid (1989) 1988 6.3 Census; stable population theory Lopez-Escartin (1992b)d Niger 1960 6.9 Demographic survey; P/F ratios U.S. Department of Commerce (1979)f

OCR for page 8
Demographic Change in Sub-Saharan Africa   1977 7.0 Census; stable population theory United Nations (1984)d 1988 7.1 Census; P/F ratios Niger (1992a)e 1992 7.4 Demographic and Health Survey, 1992 (preliminary) Niger (1992b) Nigeria 1965 6.6 World Fertility Survey, 1981–1982 Cochrane and Farid (1989)   1970 6.5 World Fertility Survey, 1981–1982 Cochrane and Farid (1989) 1971–1973 7.3 National fertility survey; P/F ratios U.S. Department of Commerce (1979)f 1975 7.0 World Fertility Survey, 1981–1982 Cochrane and Farid (1989) 1980 6.3 World Fertility Survey, 1981–1982 Cochrane and Farid (1989) 1990 6.2 Demographic and Health Survey II, 1990 Nigeria (1992) Senegal 1960 5.4 Demographic Survey U.S. Department of Commerce (1979)   1959–1963 7.8 World Fertility Survey, 1978 Cochrane and Farid (1989) 1964–1968 7.7 World Fertility Survey, 1978 Cochrane and Farid (1989) 1969–1973 7.5 World Fertility Survey, 1978 Cochrane and Farid (1989) 1970–1971 6.4 National demographic survey U.S. Department of Commerce (1979) 1976 7.0 Census; stable population theory United Nations (1984) 1974–1978 7.2 World Fertility Survey, 1978 Cochrane and Farid (1989) 1981 7.3 Provisional 1988 census; Coale method Senegal (1988) 1986 6.6 Demographic and Health Survey, 1986 Ndiaye et al. (1988) 1988 6.3 Census (preliminary estimate based on a 10 percent sample) Senegal (1992) Sierra Leone 1967 7.2 1974 census; Coale method United Nations (1979)   1973 6.4 Pilot census; P/F ratios U.S. Department of Commerce (1979)f Togo 1961 7.0 Demographic survey U.S. Department of Commerce (1979)   1971 6.6 Census; method of estimation not stated Lopez-Escartin (1991d) 1981 6.0 Census Agounké et al. (1989) 1982–1984 6.9g Demographic and Health Survey, 1988 Agounké et al. (1989) 1985–1987 6.5g Demographic and Health Survey, 1988 Agounké et al. (1989) Middle Angola 1960 6.4 Census; stable population theory United Nations (1979)d   1970 6.7 Census; stable population theory Lopez-Escartin (1992d)d 1983–1985 8.0 Census; P/F ratios Angola (n.d.)e,f

OCR for page 8
Demographic Change in Sub-Saharan Africa Country Date of Estimate TFRa,b Data and Methodologyc Reference Cameroon 1961 5.3 World Fertility Survey, 1978 Cochrane and Farid (1989)   1960–1962 4.6 Demographic survey U.S. Department of Commerce (1979) 1964 4.9 Subnational demographic survey Cameroon (1983) 1966 5.7 World Fertility Survey, 1978 Cochrane and Farid (1989) 1969 6.4 1976 census; Coale method United Nations (1983)d 1971 6.5 World Fertility Survey, 1978 Cochrane and Farid (1989) 1974–1978 6.4 World Fertility Survey, 1978 Cochrane and Farid (1989) 1976 6.0 Census; P/F ratios Cameroon (1983)f 1980 6.3 1987 census; Coale method Lopez-Escartin (1991a)d 1987 5.7 Census; method of estimation not stated Lopez-Escartin (1991a)f 1991 5.8 Demographic and Health Survey, 1991 Cameroon (1992) Central African Republic 1959–1960 4.9 National demographic survey Central African Republic (1964)   1975 5.7 Census Central African Republic (1987) 1988 6.1 Census Lopez-Escartin (1992c) Chad Congo 1964 5.4 Subnational sample; P/F ratios U.S. Department of Commerce (1979)f   1960–1961 4.9 Survey; P/F ratios Congo (1965)f 1974 5.5 Census Congo (1978) 1977 6.5 1984 census; Coale method Lopez-Escartin (1991e)d 1984 6.6 Census; P/F ratios Congo (1987)d Equatorial Guinea 1983 5.6 Census Equitorial Guinea (1991) Gabon 1960–1961 4.1 Census and demographic survey Gabon (1965)   1969–1970 4.5 Census; stable population theory Lopez-Escartin (1991c)d Zaire 1955–1957 5.1 National demographic survey Lopez-Escartin (1992f)   1978 6.2 Census; Coale method Zaire (1991)d 1984 6.7 Census; method of estimation not stated Zaire (1991)

OCR for page 8
Demographic Change in Sub-Saharan Africa FIGURE 2–5 Total fertility rates (TFR) by gross national product (GNP) per capita. NOTE: Δ: African countries; +: other developing countries. rates across countries. Once these controls are introduced, Africa no longer exhibits a slower fertility response to changes in GNP per capita (Working Group on Factors Affecting Contraceptive Use, 1993). Overall, it is probably too early to tell whether a major decline in fertility is likely to occur more or less slowly in Africa than elsewhere. CONCLUSIONS This chapter has presented a descriptive picture of childbearing in sub-Saharan Africa. It is clear that most countries in Africa began to experience a decline in mortality in the 1950s and 1960s (see Chapter 5), but the region has yet to experience a similar general decline in fertility. Consequently, the population growth rate is high, with the population of sub-Saharan Africa expected to double within the next 22–23 years.9 One overriding ques- 9   This statement is true regardless of whether there is an immediate and sustainable drop in fertility because the young age structure of sub-Saharan African populations ensures that large numbers of potential parents will shortly enter their childbearing years. Consequently, “demographic momentum” is built into the current age structure of the population (Keyfitz, 1977).

OCR for page 8
Demographic Change in Sub-Saharan Africa tion now faces African demographers: When and through what mechanisms is a general decline in fertility likely to occur? Together, the Demographic and Health Surveys represent the biggest single data collection effort ever to be undertaken in sub-Saharan Africa, and birth histories have already been collected from more than 90,000 women. Attempting to identify the start of an African fertility transition has been one of the most important contributions of the DHS. At face value, DHS data imply that fertility is declining across much of Africa. However, this conclusion is not always supported by other related patterns of behavior (i.e., later marriage, increased contraceptive use, and lower fertility preferences) or by in-depth analysis of birth histories. Kenya, Botswana, Zimbabwe, parts of Nigeria, and, possibly, Senegal comprise the vanguard of the decline. In none of the above cases has fertility fallen to a level that would imply a zero rate of population growth (that is, a level that would just replace the existing population). Nonetheless, the reductions in fertility rates are important and may herald the onset of the fertility transition that at some point will stretch across the entire continent. What is particularly intriguing about these fertility declines, however, is not only that they are the first to have taken place, but also that they have arisen through changes in different proximate determinants. In the first four cases, fertility decline appears to be associated with an increase in the use of contraception. In Senegal, the decline appears associated with a trend toward later marriage. DHS data also indicate that there are substantial differences in fertility by urban-rural residence and level of education even in countries whose national-level statistics do not indicate that a substantial decline in fertility has occurred. However, the absolute level of fertility in urban areas and among more educated women often remains high. There is also considerable overlap between the two groups so that the total contribution to fertility decline, so far, is small. Despite the increase in information available from sample surveys and censuses, there is still a shortage of reliable data on fertility rates for many countries in Africa. There is no tradition of accurate data collection in the region, and vital registration statistics are unavailable. Given the resource constraints facing most governments, the instability of political regimes in the region, and the large-scale movements of many refugees across the continent as a result of drought, famine, or low-intensity warfare, the immediate prospects for accurate data collection are extremely poor. Censuses have provided the majority of the information on fertility rates, but censuses have been plagued frequently by problems that have resulted in incomplete or inaccurate coverage. In other cases, census counts were not published because they were politically unacceptable (the 1983 Guinea Census), too unreliable (the census of Nigeria in 1973), or simply lost due to conflict (Uganda in 1980, Liberia in 1984, and Somalia in 1986). Survey data from the region are thought to be reasonably reliable; yet despite WFS and DHS

OCR for page 8
Demographic Change in Sub-Saharan Africa efforts to ensure data quality, careful analysis has revealed significant inaccuracies. In addition, many countries in Africa have not been surveyed recently. The need for accurate and timely demographic data on fertility levels and trends for many African countries is still urgent. REFERENCES Adamchak, D.J., and P.G.Ntseane 1992 Gender, education, and fertility: A cross-national analysis of sub-Saharan African nations. Sociological Spectrum 12:167–182. Agounké, A., M.Assogba, and K.Anipah 1989 Enquête Démographique et de Santé au Togo 1988. Lomé: Unité de Recherche Démographique, Direction de la Statistique; Columbia, Md.: Institute for Resource Development/Westinghouse. Ahonzo, E., B.Barrere, and P.Kopylov 1984 Population de la Côte d’Ivoire: Analyse des Données Démographiques Disponsibles. Abijan. Ministère de l’Economic et des Finances, Direction de la Statistique. Angola No date Boletim Demográfico. No. 10. Fecundidade e Mortalidade das provincias de Cabinda e do Zaire, Censo 1984. Luanda: Instituto Nacional de Estatistica. Arnold, F. 1990 Assessment of the quality of birth history data in the Demographic and Health Surveys. Pp. 83–111 in An Assessment of DHS-I Data Quality. Demographic and Health Surveys Methodological Reports No. 1. Columbia, Md.: Institute for Resource Development/Westinghouse. Arnold, F., and A.K.Blanc 1990 Fertility trends and levels. Demographic and Health Surveys Comparative Studies 2: Fertility. Columbia, Md.: Institute for Resource Development/Westinghouse. Balepa, M., M.Fotso, and B.Barrière 1992 Demographic and Health Survey 1991. Yaoundé: National Department of the Second Population Census; Columbia, Md.: Institute for Resource Development/ Westinghouse. Barampanze, G. 1991 Population Burundaise. Cahiers demographiques du Burundi, No. 2. Bujumbura: Premier Ministère et Ministère du Plan, Secrétariat d’Etat au Plan. Benin 1988 Enquête sur la Fécondité au Benin, 1982. Rapport National. Tome I: Analyse des Principaux Résultats. Cotonou: Ministère du Plan et de la Statistique. Blacker, J., B.Zaba, and K.Moser 1979 Fertility trends in Kenya 1962–1978—A reassessment. Unpublished report, Centre for Population Studies, Lond School of Hygiene and Tropical Medicine. Blanc, A.K., and N.Rutenberg 1990 Assessment of the quality of data on age at first sexual intercourse, age at first marriage, and age at first birth in the Demographic and Health Surveys. Pp. 41–79 in An Assessment of DHS-I Data Quality. Demographic and Health Surveys Methodological Reports No. 1. Columbia, Md.: Institute for Resource Development/ Westinghouse. Bongaarts, J., and R.G.Potter 1983 Fertility, Biology, and Behavior: An Analysis of the Proximate Determinants. New York: Academic Press.

OCR for page 8
Demographic Change in Sub-Saharan Africa Bongaarts, J., O.Frank, and R.Lesthaeghe 1990 The proximate determinants of fertility. Pp. 133–143 in G.T.F.Acsadi, G.Johnson-Acsadi, and R.A.Bulatao, eds., Population Growth and Reproduction in Sub-Saharan Africa: Technical Analyses of Fertility and Its Consequences. Washington D.C.: The World Bank. Boserup, E. 1985 Economic and demographic interrerlationships in sub-Saharan Africa. Population and Development Review 11(3):383–397. Brass, W., and F.Juarez 1983 Censored cohort parity progresion ratios from birth histories. Asian and Pacific Census Forum 10(1):5–13. Brass, W., A.J. Coale, P.Demeny, D.F.Heisel, F.Lorimer, A.Romaniuk, and E.van de Walle 1968 The Demography of Tropical Africa. Princeton, N.J.: Princeton University Press Burkina Faso No date Deuxième Recensement Général de la Population du 10 au 20 Décembre, 1985. Principales Données Définitives. Ouagadougou: Ministère du Plan et de la Cooperation. Burundi 1966 Enquête Démographique, 1965. Bujumbura: Royaume du Burundi. 1972 Enquête Démographique, Burundi, 1970–71. Methodologie, Résultats Provisoires. Bujumbura: Département de Statistiques. Caldwell, J.C., and P.Caldwell 1977 The role of marital sexual abstinence in determining fertility: A study of the Yoruba in Nigeria. Population Studies 31(2):193–217. 1987 The cultural context of high fertility in sub-Saharan Africa. Population and Development Review 13(3):409–437. 1988 Is the Asian family planning program model suited to Africa? Studies in Family Planning 19(1):19–28. 1990 Cultural forces tending to sustain high fertility. Pp. 199–214 in G.T.F.Acsadi, G. Johnson-Acsadi, R.A.Bulatao, eds., Population Growth and Reproduction in Sub-Saharan Africa: Technical Analyses of Fertility and Its Consequences. Washington, D.C.: The World Bank. 1993 The South African fertility decline. Population and Development Review 19(2). Caldwell, J.C., P.Caldwell, and P.Quiggin 1989 The social context of AIDS in sub-Saharan Africa. Population and Development Review 15(2):185–234. Caldwell, J.C., I.O.Orubuloye, and P.Caldwell 1992 Fertility decline in Africa: A new type of transition. Population and Development Review 18(2):211–242. Cameroon 1983 The Cameroon Fertility Survey, 1978: A Summary of Findings. London: World Fertility Survey. Central African Republic 1964 Enquête Démographique en République Centrafricaine, 1959–1960. Résultats Définitifs. Paris: Institut National de la Statistique et des Etudes Economiques. 1987 Recensement Général de la Population—1975. Analyse Abregée. Bangui: Direction Générale de la Statistique et des Etudes Economiques. Chieh-Johnson, D., A.R.Cross, A.A.Way, and J.M.Sullivan 1988 Liberia Demographic and Health Survey, 1986. Monrovia: Bureau of Statistics, Ministry of Planning and Economic Affairs; Columbia, Md.: Institute for Resource Development/Westinghouse.

OCR for page 8
Demographic Change in Sub-Saharan Africa Chimere-Dan, O. 1993 Population policy in South Africa. Studies in Family Planning 24(1):31–39. Coale, A.J. 1981 Robust estimation of fertility by the use of model stable populations. Asian and Pacific Census Forum 8(2):5–7. Cochrane, S.H. 1979 Fertility and Education: What Do We Really Know? World Bank Staff Occasional Paper Number 26. Washington, D.C.: The World Bank. Cochrane, S.H., and S.M.Farid 1989 Fertility in Sub-Saharan Africa, Analysis and Explanation. World Bank Discussion Paper Number 43. Washington, D.C.: The World Bank. Congo 1965 Enquuête Démographique, 1960–1961. Résultats Définitifs. Paris: Institut National de la Statistique et des Etudes Economiques. 1978 Recensement Général de la Population du Congo, 1974. Tome IV: Tableaux Statistiques Détaillés . Brazzaville: Direction des Statistiques Démographiques et Sociales. 1987 Recensement Général de la Population et de l’Habitat de 1984. Tome 1: Ensemble du pays. Brazzaville: Bureau Central du Recensement. Cross, A.R., W.Obungu, and P.Kizito 1991 Evidence of a transition to lower fertility in Kenya. International Family Planning Perspectives 17(1):4–6. de Graft-Johnson, K.T. 1988 Demographic data collection in Africa. Pp. 13–28 in E.van de Walle, P.O.Ohadike, and M.D.Saka-Diakanda, eds., The State of African Demography. Liège: International Union for the Scientific Study of Population. Equatorial Guinea 1991 Censo de Guinea Ecuatorial de 1983. Analisis de la Fecundidad. Malabo: Ministerio de Economia, Comercio y Planificación. Ethiopia 1971 Population of Ethiopia: Results from the National Sample Survey 1st Round, 1964–1967. Statistical Bulletin No. 6. Addis Ababa: Central Statistical Office. 1974 The Demography of Ethiopia: Results of the National Sample Survey Second Round, Vol. 1. Statistical Bulletin No. 10. Addis Ababa: Central Statistical Office. 1991a The 1984 Population and Housing Census of Ethiopia. Analytical Report at National Level. Addis Ababa: Transitional Government of Ethiopia, Office of the Population and Census Commission. 1991b The 1990 Family and Formation Survey. Prelimary Report. Addis Ababa: Central Statistical Authority, Population Analyses and Studies Center. Ewbank, D.C. 1979 Fertility estimation. Pp. 70–93 in R.A.Henin, ed., The Demography of Tanzania: An Analysis of the 1973 National Demographic Survey of Tanzania, Vol. IV. Dar es Salaam: Bureau of Statistics, Ministry of Finance and Planning and the Demographic Unit, Bureau of Resource Assessment and Land Use Planning, Univeristy of Dar es Salaam, United Republic of Tanzania. Frank, O. 1983 Infertility in sub-Saharan Africa: Estimates and implications. Population and Development Review 9(1):137–144. 1987 The demand for fertility control in sub-Saharan Africa. Studies in Family Planning 18(4):181–201.

OCR for page 8
Demographic Change in Sub-Saharan Africa Freedman, R. 1992 Issues about fertility and family planning in South Africa. Report on a visit, October 25-November 24, 1992. Unpublished manuscript. Population Studies Center, University of Michigan, Ann Arbor. Freedman, R., and A.K.Blanc 1992 Fertility transition: An update. International Family Planning Perspectives 18(2):44– 50. Gabon 1965 Recensement et Enquête Démographiques, 1960–1961; Ensemble du Gabon. Résultats Définitifs. Paris: Institut National de la Statistique et des Etudes Economiques. Gaisie, K., A.R.Cross, and G.Nsamukila 1993 Demographic and Health Survey 1992. Lusaka: University of Zambia and Central Statistical Office; Columbia, Md.: Macro International, Inc. The Gambia 1976 Population Census, 1973. Statistics for Local Government Areas and Districts, Vol. III: General Report. Banjul: Central Statistics Division, Ministry of Economic Planning and Industrial Development. 1987 Population and Housing Census, 1983: General Report, Vol. I: Administrative and Analytical Procedures. Banjul: Central Statistics Division, Ministry of Economic Planning and Industrial Development. Ghana No date 1984 Population Census of Ghana: Demographic and Economic Characteristics. Accra: Ghana Statistical Service. 1989 Ghana Demographic and Health Survey 1988. Accra: Ghana Statistical Service; Columbia, Md.: Institute for Resource Development/Westinghouse. Haaga, J.G. 1989 Mechanisms for the association of maternal age, parity, and birth spacing with infant health. Pp. 96–139 in A.M.Parnell, ed., Contraceptive Use and Controlled Fertility: Health Issues for Women and Children: Background Papers. Washington, D.C.: National Academy Press. Hill, A.L.L. 1985 The Demography of Zambia. Population, Health and Nutrition Department Technical Note, 85–9. Washington D.C.: The World Bank. House, W.J., and G.Zimalirana 1992 Rapid population growth and poverty generation in Malawi. Journal of Modern African Studies 30(1):141–161. Institute for Resource Development 1990 An Assessment of DHS-I Data Quality. Demographic and Health Surveys Methodological Reports No. 1. Columbia, Md.: Institute for Resource Development/ Macro Systems, Inc. Kaijuka, E.M., E.Z.A.Kaija, A.R.Cross, and E.Loaiza 1989 Uganda Demographic and Health Survey, 1988/1989. Entebbe: Ministry of Health; Columbia, Md.: Institute for Resource Development/Westinghouse. Kenya 1980 Kenya Fertility Survey, 1977–78. Nairobi: Central Bureau of Statistics, Ministry of Planning and National Development. London: World Fertility Survey. 1984 Kenya Contraceptive Prevalence Survey, 1984. First Report. Nairobi: Central Bureau of Statistics, Ministry of Planning and National Development. 1989 Kenya Demographic and Health Survey 1989. Nairobi: National Council for Population and Development, Ministry of Home Affairs and National Heritage; Columbia, Md.: Institute for Resource Development/Westinghouse.

OCR for page 8
Demographic Change in Sub-Saharan Africa Keyfitz, N. 1977 Introduction to the Mathematics of Population. Reading, Mass.: Addison-Wesley Publishing Company. Kidane, A. 1990 Regional variation in fertility, mortality and population growth in Ethiopia, 1970– 1981. Genus 66(1,2):195–206. Lesetedi, L.T., G.D.Mompati, P.Khulumani, G.N.Lesetedi, and N.Rutenberg 1989 Botswana Family Health Survey II 1988. Gaborone: Central Statistics Office, Ministry of Finance and Development Planning, and Family Health Division, Ministry of Health; Columbia, Md.: Institute for Resource Development/Westinghouse. Lesotho 1991 1986 Population Census Statistical Tables, Vol. II. Maseru: Bureau of Statistics. Lesthaeghe, R.J., ed. 1989 Reproduction and Social Organization in Sub-Saharan Africa. Berkeley: University of California Press. Lesthaeghe, R.J., I.Shah, and H.Page 1981 On the compensating effects of changes in the proximate determinants of fertility. Pp. 71–94 in International Union of the Scientific Study of Population Conference Volume, Manila, 1981. Liège: International Union of the Scientific Study of Population. Liberia No date 1984 Population and Housing Census. Summary Population Results. Monrovia: Bureau of Statistics, Ministry of Planning and Economic Affairs. Lopez-Escartin, N. 1991a Données de Base sur la Population: Cameroun. CEPED working paper No. 1. Paris: Centre Français sur la Population et le Développement (CEPED). 1991b Données de Base sur la Population: Madagascar. CEPED working paper No. 2. Paris: Centre Français sur la Population et le Développement (CEPED). 1991c Données de Base sur la Population: Gabon. CEPED working paper No. 3. Paris: Centre Français sur la Population et le Développement (CEPED). 1991d Données de Base sur la Population: Togo. CEPED working paper No. 4. Paris: Centre Français sur la Population et le Développement (CEPED). 1991e Données de Base sur la Population: Congo. CEPED working paper No. 8. Paris: Centre Français sur la Population et le Développement (CEPED). 1992a Données de Base sur la Population: Mali. CEPED working paper No. 13. Paris: Centre Français sur la Population et le Développement (CEPED). 1992b Données de Base sur la Population: Mauritanie. CEPED working paper No. 14. Paris: Centre Français sur la Population et le Développement (CEPED). 1992c Données de Base sur la Population: Centrafrique. CEPED working paper No. 16—Version provisoire. Paris: Centre Français sur la Population et le Développement (CEPED). 1992d Données de Base sur la Population: Angola. CEPED working paper No. 17— Version provisoire. Paris: Centre Français sur la Population et le Développement (CEPED). 1992e Données de Base sur la Population: Cote D’Ivoire. CEPED working paper No. 18—Version provisoire. Paris: Centre Français sur la Population et le Développement (CEPED). 1992f Données de Base sur la Population: Zaire. CEPED working paper No. 19— Version provisoire. Paris: Centre Français sur la Population et le Développement (CEPED).

OCR for page 8
Demographic Change in Sub-Saharan Africa Malawi No date Malawi Population and Housing Census, 1987. Preliminary report. Zomba: National Statistical Office. 1980 Malawi Population Census, 1977. Zomba: National Statistical Office. 1987a Malawi Demographic Survey, 1982. Zomba: National Statistical Office. 1987b Malawi Family Formation Survey, 1984. Vol. II: Fertility, Family Size Preferences and Child Spacing. Zomba: Ministry of Health. 1991 Population and Housing Census, 1987: Summary of Final Results. Zomba: National Statistical Office. 1993 Malawi Demographic and Health Survey 1992: Preliminary Report. Columbia, Md.: Macro International, Inc. Manyeneng, W.G., P.Khulumani, M.K.Larson, and A.A.Way 1985 Botswana Family Health Survey 1984. Columbia, Md.: Westinghouse Public Applied Systems. Mhloyi, M.M. 1988 The determinants of fertility in Africa under modernization. Pp. 2.3.1–2.3.22 in African Population Conference, Dakar, 1988, Vol. 1. Liège: International Union for the Scientific Study of Population. Mostert, W.P. 1990 Recent trends in fertility in South Africa. Pp. 63–73 in W.P.Mostert and J.M. Lötter, eds., South Africa’s Demographic Future. Pretoria: Human Sciences Research Council. Namibia 1992 Namibia Demographic and Health Survey 1992. Preliminary Report. Niamey: Ministry of Health and Social Services, and Central Statistical Office, National Planning Commission; Columbia, Md.: Macro International, Inc. Ndiaye, S., I.Sarr, and M.Ayad 1988 Enquôte Démographique et de Santé au Sénégal 1986. Dakar: Ministère de l’Economie et des Finances, Direction de la Statistique; Columbia, Md.: Institute for Resource Development/Westinghouse. Niger 1992a Recensement Général de la Population 1988: Analyse des Données Définitives. Rapport de Synthèse. Niamey: Ministère de l’Economie et des Finances, Bureau Central du Recensement. 1992b Enquête Démographique et de Santé, Niger 1992. Rapport Préliminaire. Niamey: Direction de la Statistique et des Comptes Nationaux, Ministère des Finances et du Plan; Columbia, Md.: Macro International, Inc. Nigeria 1992 Nigeria Demographic and Health Survey 1990. Lagos: Federal Office of Statistics; Columbia, Md.: Institute for Resource Development/Westinghouse. Page, H.J. 1988 Fertility and family planning in sub-Saharan Africa. Pp. 29–45 in E.van de Walle, P.O.Ohadike, and M.D.Sala-Diakanda, eds., The State of African Demography. Liège: International Union for the Scientific Study of Population. Page, H.J., and A.J.Coale 1972 Fertility and child mortality south of the Sahara. In S.H.Ominde and C.N.Ejiogu, eds., Population Growth and Economic Development in Africa. London: Heinemann Press. Page, H.J., and R.Lesthaeghe, eds. 1981 Child-Spacing in Tropical Africa: Tradition and Change. London: Academic Press.

OCR for page 8
Demographic Change in Sub-Saharan Africa Population Reference Bureau 1992 Adolescent Women in Sub-Saharan Africa. Washington, D.C.: Population Reference Bureau. Potter, J.E. 1977 Problems in using birth-history analysis to estimate trends in fertility. Population Studies 31(2):335–364. Preston, S.H. 1983 An integrated system for demographic estimation from two age distributions. Demography 20(2):213–226. Rodriguez, G., and J.N.Hobcraft 1980 Illustrative analysis: Life table analysis of birth intervals in Columbia. In World Fertility Survey Scientific Reports. Number 16. London: International Statistical Institute. Rutenberg, N., and I.Diamond 1993 Fertility in Botswana: The recent decline and future prospects. Demography 30(2):143–157. Rutstein, S.O., and G.T.Bicego 1990 Assessment of the quality of data used to ascertain eligibility and age in the Demographic and Health Surveys. Pp. 5–37 in An Assessment of DHS-I Data. Demographic and Health Surveys Methodological Reports No. 1. Columbia, Md.: Institute for Resource Development/Macro Systems, Inc. Rwanda No date Enquête Nationale sur la Fécondité 1983. Tome I: Analyse des Résultats. Kigali: Bureau National de Recensement. 1973 Enquête Démographique, 1970. Kigali: Office Général des Statistiques. 1984 Recensement Général de la Population et de l’Habitat, 1978. Tome III: Fécondité— Mortalité. Kigali: Bureau National de Recensement. Schoenmaeckers, R., I.H.Shah, R.Lesthaeghe, and O.Tambashe 1981 The child-spacing tradition and the postpartum taboo in tropical Africa: Anthropological evidence. Pp. 25–71 in H.J.Page and R.Lesthaeghe, eds., Child-Spacing in Tropical Africa: Traditions and Change. London: Academic Press. Segamba, L., V.Ndikumasabo, C.Makinson and M.Ayad 1988 Enquête Démographique et de Santé au Burundi 1987. Gitega, Burundi: Ministère de l’Intérieur, Département de la Population; Columbia, Md.: Institute for Resource Development/Westinghouse. Senegal 1988 Situation Economique. Dakar: Republique du Sénégal. 1992 Niveaux et Tendances de la Fécondité. Dakar: Direction de la Statistique. Singh, S., J.Y.Owusu, and I.H.Shah, eds. 1985 Demographic Patterns in Ghana: Evidence from the Ghana Fertility Survey, 1979–80. London: World Fertility Survey. Smith, D.P., E.Carrasco, and P.McDonald 1984 Marriage Dissolution and Remarriage. World Fertility Survey Comparative Studies Number 34. London: World Fertility Survey. Somalia No date National Survey of Population, 1980–81: Report on Findings. Mogadishu: Central Statistical Department, Ministry of National Planning. 1984 Census of Population, 1975. Analytical Report. Mogadishu: Central Statistical Department, Ministry of National Planning. 1985 Fertility and Family Planning in Urban Somalia: Results of the Somali Family Health Survey in Five Cities, 1983. Mogadishu: Ministry of Health.

OCR for page 8
Demographic Change in Sub-Saharan Africa Tambashe, O. 1992 Infécondité et politique de population en Afrique centrale. Vie et Santé 12:3–7. Tanzania No date Provisional Estimates of Fertility, Mortality and Population Growth for Tanzania. Dar es Salaam: Bureau of Statistics. 1983 1978 Population Census, Vol. VIII. Dar es Salaam: Bureau of Statistics. 1990 Population Census National Profile. Summary. Dar es Salaam: Bureau of Statistics. 1992 Tanzania Demographic and Health Survey, 1991/92. Preliminary Report. Dar es Salaam: Bureau of Statistics, President’s Office, Planning Commission; Columbia, Md.: Macro International, Inc. Thibon, C. 1993 Evolution démographique de la population burundaise d’après les registres des missionaires et le recensement général 1990: Etude des fécondités. Départment d’historire, University of Burundi, Bujumbura. Thomas, D., and I.Muvandi 1992 The Demographic Transition in Southern Africa: Another Look at the Evidence from Botswana and Zimbabwe. Yale University Economic Growth Center Discussion Paper No. 668. New Haven, Conn.: Yale Univeristy. Traoré, B., M.Konaté, and C.Stanton 1989 Enquête Démographique et de Santé au Mali. Bamako: Centre d’Etudes et de Recherches sur la Population pour le Développement; Columbia, Md.: Institute for Resource Development/Westinghouse. Uganda 1973 Report on the 1969 Population Census. Entebbe: Statistics Division, Ministry of Finance, Planning and Economic Development. United Nations 1979 Demographic Yearbook—Special Issue: Historical Supplement. New York: United Nations. 1983 Manual X: Indirect Techniques for Demographic Estimation. Population Studies No. 81. New York: United Nations, Department of International Economic and Social Affairs. 1984 Demographic Yearbook, 1983. New York: United Nations. 1987 Fertility Behaviour in the Context of Development; Evidence from the World Fertility Study. Population Studies No. 100. New York: United Nations, Department of International Economic and Social Affairs. 1990 Demographic Yearbook, 1988. New York: United Nations. 1991 World Population Prospects 1990. Population Studies No. 120. New York: United Nations, Department of International Economic and Social Affairs. 1992 Child Mortality Since the 1960s: A Database for Developing Countries. New York: United Nations, Department of Economic and Social Development. U.S. Department of Commerce 1979 A Compilation of Age-Specific Fertility Rates for Developing Countries. International Research Document No. 7. Washington, D.C.: Bureau of the Census, van de Walle, E., and A.D.Foster 1990 Fertility Decline in Africa: Assessment and Prospects. World Bank Technical Paper Number 125, Africa Technical Department Series. Washington, D.C.: The World Bank. van de Walle, F., and K.Omideyi 1988 The cultural roots of African fertility regimes. Pp. 2.2.35–2.2.52 in African Popu

OCR for page 8
Demographic Change in Sub-Saharan Africa lation Conference, Dakar, 1988. Liège: International Union for the Scientific Study of Population. Venkatacharya, K. 1990 Simplified birth rate estimates under nonstable conditions. Demography 27(1):131– 147. Warren, C.W., J.T.Johnson, G.Gule, E.Hlophe, and D.Kraushaar 1992 The determinants of fertility in Swaziland. Population Studies 46(1):5–17. Westoff, C.F. 1992 Age at Marriage, Age at First Birth and Fertility in Africa. World Bank Technical Paper Number 169. Washington, D.C.: The World Bank. Working Group on Demographic Effects of Economic and Social Reversals 1993 Demographic Effects of Economic Reversals in Sub-Saharan Africa. K.H.Hill and L.G.Martin, eds. Panel on the Population Dynamics of Sub-Saharan Africa, Committee on Population, National Research Council. Washington, D.C.: National Academy Press. Working Group on Factors Affecting Contraceptive Use 1993 Factors Affecting Contraceptive Use in Sub-Saharan Africa. J.T.Bertrand and C.L.Jolly, eds. Panel on the Population Dynamics of Sub-Saharan Africa, Committee on Population, National Research Council. Washington, D.C.: National Academy Press. Working Group on the Social Dynamics of Adolescent Fertility 1993 The Social Dynamics of Adolescent Fertility in Sub-Saharan Africa. C.H.Bledsoe and B.Cohen, eds. Panel on the Population Dynamics of Sub-Saharan Africa, Committee on Population, National Research Council. Washington, D.C.: National Academy Press. World Bank 1986 Population Growth and Policies in Sub-Saharan Africa. A World Bank Policy Study. Washington, D.C.: The World Bank. 1988 Education in Sub-Saharan Africa. A World Bank Policy Study. Washington, D.C.: The World Bank. 1989 Sub-Saharan Africa, From Crisis to Sustainable Growth. Washington, D.C.: The World Bank. 1991 World Development Report 1991, The Challenge of Development. Washington, D.C.: The World Bank. Zaire 1991 Recensement Scientifique de la Population, 1984. Un Aperçu Démographique. Kinshasa: Institut National de la Statistique. Zambia 1985a Population and Housing Census of Zambia, 1980. Analytical Report. Volume II: Demographic and Socio-Economic Characteristics of Zambia Population. Lusaka: Central Statistical Office. 1985b Population and Housing Census of Zambia, 1980. Analytical Report Volume. Vol. IV: Fertility and Mortality Levels and Trends. Lusaka: Central Statistical Office. Zimbabwe 1989 Demographic and Health Survey 1988. Harare: Central Statistical Office, Ministry of Finance, Economic Planning, and Development; Columbia, Md.: Institute for Resource Development/Westinghouse.