4
Fertility

INTRODUCTION

The average growth rate of the population in sub-Saharan Africa has been around 3 percent per year since the 1960s, higher than in any other major region in the world. If these rates remain constant, the population will double in the next 23 years. The reason for Africa's rapid rate of population growth is well known: while mortality and fertility rates fell substantially in Latin America and Asia between 1965 and 1985, only mortality fell in sub-Saharan Africa; fertility remained relatively stable, well above the level required to replace the population.

The existing demographic regime in sub-Saharan Africa is unlikely to remain in effect for very long. According to data from the Demographic and Health Surveys (DHS), the level of fertility has already fallen by more than 10 percent in seven sub-Saharan African countries (Kenya, Botswana, Senegal, Zimbabwe, Zambia, Burundi, and Malawi). Not all of these fertility declines are completely plausible, but fertility certainly appears to have fallen in at least three DHS countries at the national level (Kenya, Botswana, and Zimbabwe), as well as in South Africa, for which DHS-type data suggest a substantial decline. Furthermore, fertility declines appear to have occurred in several other countries at the subnational level (e.g., southwestern Nigeria, southern Namibia, northern Tanzania). These changes were documented in a chapter on fertility trends in sub-Saharan Africa in a recent volume by the Committee on Population (see Cohen, 1993).



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Population Dynamics of Senegal 4 Fertility INTRODUCTION The average growth rate of the population in sub-Saharan Africa has been around 3 percent per year since the 1960s, higher than in any other major region in the world. If these rates remain constant, the population will double in the next 23 years. The reason for Africa's rapid rate of population growth is well known: while mortality and fertility rates fell substantially in Latin America and Asia between 1965 and 1985, only mortality fell in sub-Saharan Africa; fertility remained relatively stable, well above the level required to replace the population. The existing demographic regime in sub-Saharan Africa is unlikely to remain in effect for very long. According to data from the Demographic and Health Surveys (DHS), the level of fertility has already fallen by more than 10 percent in seven sub-Saharan African countries (Kenya, Botswana, Senegal, Zimbabwe, Zambia, Burundi, and Malawi). Not all of these fertility declines are completely plausible, but fertility certainly appears to have fallen in at least three DHS countries at the national level (Kenya, Botswana, and Zimbabwe), as well as in South Africa, for which DHS-type data suggest a substantial decline. Furthermore, fertility declines appear to have occurred in several other countries at the subnational level (e.g., southwestern Nigeria, southern Namibia, northern Tanzania). These changes were documented in a chapter on fertility trends in sub-Saharan Africa in a recent volume by the Committee on Population (see Cohen, 1993).

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Population Dynamics of Senegal This chapter examines levels, trends, and determinants of fertility in Senegal. The next section combines recent census and survey results to build a general description of the pattern of fertility in Senegal and how it has changed over the last 20 years. This is followed by a section on explanations for these patterns, focusing on marriage, breastfeeding, and contraception, some of the most important determinants of fertility change. LEVELS AND TRENDS OF FERTILITY Overall Levels and Trends The standard measure of fertility used here is the total fertility rate (TFR).1 Despite dramatic improvements in the quantity and quality of population data for Senegal since the early 1960s, our knowledge and understanding of fertility levels and trends in the country still relies mainly on findings from ad hoc single-round surveys. Since 1960, five surveys have furnished information that permits the estimation of fertility in Senegal at the national level: the Demographic Survey (DS) of 1960-1961 [1]; the National Demographic Survey (NDS) of 1970-1971 [2]; the World Fertility Survey (WFS) of 1978 [3]; and two rounds of the DHS (DHS-I, DHS-II) in 1986 [4] and 1992-1993 [7].2 The data from each of these sources are not all of comparable quality. For example, the 1960-1961 DS data are generally thought to have suffered from an underenumeration of births and deaths (Cantrelle et al., 1986) and to be of lower quality than the data from the other sources. In addition to these surveys, fertility estimates are available from two censuses, conducted in 1976 [17] and 1988 [18]. The 1976 census questionnaire did not collect information on births, so fertility estimates for 1976 have been derived from the age distribution using stable population theory. The 1988 census contained a single question on births in the last 12 months. Unfortunately, because of mistakes in the coding and processing of the data, the TFR estimates produced at the time the official report of the 1988 census was being prepared were implausibly low. Consequently, fertility estimates were not included in official reports on the 1988 census, and to this day, fertility estimates from the 1988 census remain unpublished. In this report we have remedied the situation by adopting a simple correction procedure to estimate total and age-specific fertility rates (ASFRs) for 1988 that takes these data problems into account. (See Appendix B for a detailed explanation of the procedure used.) Finally, there are a number of subnational studies [8-16] in which accurate birth registers have been maintained over several years. Although these small study areas are not representative of the entire country, they yield fertility estimates that may be more accurate than those derived from large-scale surveys and censuses. Hence, small-scale studies can provide a useful independent check on the accuracy of the other estimates.

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Population Dynamics of Senegal In all, seven observations of the national TFR are available for the period 1960-1993. In principle, by putting these observations in sequence we can observe the trends in fertility over the last 30 years. However, since the quality of the data varies among the surveys, some estimates are considerably more reliable than others. Tests of internal and external consistency show that the quality of the data from several sources is often mediocre to poor. Furthermore, the methodology used to collect the information was not the same across all surveys. For example, the WFS and the DHS collected complete birth histories from all women, while the 1988 census only asked women about births in the last 12 months. This latter method is more prone to omission of births, particularly of children who died, so that it almost invariably produces lower estimates of the TFR.3 One needs to bear in mind such issues of varying data quality and methodology when comparing across survey instruments, and to remain reasonably cautious when interpreting small fluctuations in the overall rate. Table 4-1 provides a summary of the available estimates of the TFR for the period 1960-1992 at the national level and for various subpopulations. Figure 4-1 shows national-level TFR estimates for the age range 15-34 (this age range has been used so that estimates of fertility from the three birth history surveys, WFS, DHS-I, and DHS-II can be used for periods up to 15 years prior to the survey dates) plotted against calendar time. Figure 4-2 shows the national age patterns of fertility, as the proportion of total fertility contributed by each age group. The Brass P/F ratio technique—where by current fertility rates are cumulated and compared with reported lifetime fertility—provides a check of the internal consistency of each survey and a sensitive test for changing fertility. For cross-sectional surveys where fertility rates have not changed in the recent past, average parity equivalents (F) should be roughly equivalent to reported average parities (P). If fertility is rising, lifetime fertility will be lower than cumulated current fertility, particularly at higher age groups which have had more time for differences to emerge, and P/F ratios will fall with age. If fertility is falling, on the other hand, the opposite will be the case, and P/F ratios will rise with age. Figure 4-3 shows P/F ratios for the 1960-1961, 1970-1971, 1978, 1986, and 1992-1993 surveys. The fertility estimates shown in Figure 4-1 come from different sources and data collection methodologies. The 1960-1961 DS [1] included questions on births and deaths over the preceding 12 months, as well as on live births and child survivorship during a woman's entire life. The TFR based on data for births during the preceding 12 months was estimated to be 5.4 children per woman. This figure may have underestimated the true TFR as a result of the omission of certain vital events.4 However, fertility rates and age-specific parties for the 1960-1961 DS are fairly consistent, at least above age 25 (see P/F ratios in Figure 4-3). If the P/F ratios are used to

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Population Dynamics of Senegal TABLE 4-1 Levels and Trends in the Total Fertility Rate, 1960-1992 Year Source Subgroup TFR National Level       1960-1961 DS n.a. 5.4 1970-1971 NDS n.a. 6.4 1976 Census n.a. 7.0 1975-1978 WFS n.a. 7.2 1983-1986 DHS-I n.a. 6.6 1987-1988 Census n.a. 5.9 1989-1992 DHS-II n.a. 6.1 WFS and DHS Regions       1975-1978 WFS West 7.1     Center 7.3     Northeast 7.2     South 7.4 1983-1986 DHS-I West 5.9     Center 7.1     Northeast 6.6     South 7.0 1987-1988 Census West 5.5     Center 6.0     Northeast 6.0     South 6.4 1989-1992 DHS-II West 5.6     Center 6.4     Northeast 6.6     South 6.5 Administrative Regions       1967-1971 Ferry (1976) Cap-Vert 6.6 1975-1978 WFS Dakar 6.8 1983-1986 DHS-I Dakar 5.5 1987-1988 Census Dakar 5.0     Thiès 6.2     Saint-Louis 6.2     Tambacounda 5.9     Louga 5.7     Diourbel 5.6     Fatick 6.9     Kaolack 6.1     Ziguinchor 6.8     Kolda 6.3 1989-1992 DHS-II Dakar 4.9 Small-Scale Studies [8-16]       1963-1965 Cantrelle et al. (1980) Niakhar 6.8 1984-1990 Project Niakhar (1992) Niakhar 7.8

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Population Dynamics of Senegal Year Source Subgroup TFR Small-Scale Studies [8-16]       1963-1965 Cantrelle et al. (1980) Paos Koto 6.6 1981-1991 Pison and Desgrées du Loû (1993) Bandafassi 6.2 1985-1992 Lagarde et al. (forthcoming) Mlomp 5.0 Place of Residence       1975-1978 WFS Dakar 6.8     Other urban 6.5     Rural 7.5 1983-1986 DHS-I Dakar 5.5     Other urban 5.6     Rural 7.3 1987-1988 Census Dakar 4.8     Other urban 5.6     Rural 6.4 1989-1992 DHS-II Dakar 4.9     Other urban 5.4     Rural 6.8 Ethnic Groups       1975-1978 WFS Wolof 7.2     Poular 6.9     Serer 7.9     Mandingo 8.1     Diola 6.3     Other 7.0 1983-1986 DHS-I Wolof 6.4     Poular 6.4     Serer 7.6     Mandingo 6.8     Diola 6.2     Other 6.3 1987-1988 Census Wolof 5.7     Poular 6.1     Serer 6.3     Mandingo 6.0     Diola 5.9     Other 5.7 1989-1992 DHS-II Wolof 5.6     Poular 6.4     Serer 7.2     Mandingo 5.7     Diola 5.7     Other 6.5

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Population Dynamics of Senegal Year Source Subgroup TFR Level of Education 1975-1978 WFS None 7.4     Primary 7.1     Secondary+ 3.6 1983-1986 DHS-I None 7.0     Primary 5.7     Secondary+ 3.6 1987-1988 Census None 6.2     Primary 5.7     Secondary+ 4.1 1989-1992 DHS-II None 6.6     Primary 5.7     Secondary+ 3.8 NOTES: See Appendix A for description of surveys: TFR = Total Fertility Rate, calculated for women aged 15-49. SOURCES: Cantrelle et al. (1980); Cohen (1993); Ferry (1976); Lagarde et al. (forthcoming); Project Niakhar (1992); Pison and Desgrées du Loû (1993); WFS, DHS-II data files and unpublished tabulations from the 1988 census. adjust reported TFR, the resulting estimates are 6.0 or 5.5, depending on whether the correction coefficient is derived from the group aged 20-24 or 25-29. The 1970-1971 NDS [2] was a multiround prospective survey. The data from this survey have been analyzed elsewhere and are thought to be of reasonably good quality (Cantrelle et al., 1986). However, the P/F ratios calculated from this survey decline steadily with age (see Figure 4-3) and average 1.27 for the age groups 20-24 and 25-29; if this factor is applied as an adjustment, the TFR estimated for 1970-1971 becomes an unrealistic 8.2. The 1978 WFS [3], 1986 DHS-I [4], and 1992-1993 DHS-II [7] were all ad hoc fertility surveys including birth histories. As a result of using similar methodology, the estimates should be more comparable than those from the other surveys. Birth histories are usually effective at coverage of births, but fertility estimates may be distorted by errors in reports of timing. In the DHS-I, some births were undoubtedly transferred from the 5 years before the survey to an earlier period so that interviewers could avoid asking women additional questions about their children under age 5 (Arnold, 1990). Consequently, DHS-I (and DHS-II) data underestimate fertility in the last 5 years. Table 4-1 shows estimates of TFR for the period 4 years prior to the survey dates, but these also appear to be underestimates. Questions have also been raised about the quality of the WFS data (Charbit et

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Population Dynamics of Senegal FIGURE 4-1 Total fertility rates for women aged 15-34 from national-level surveys, 1960-1993. NOTE: See Appendix A for description of surveys. al., 1985); the complex procedure for collecting birth histories in the WFS may have resulted in fertility being overestimated, particularly among women aged 25-39.5 In the 1988 census, women were asked about their births in the last 12 months. This time, the problem of identifying the correct length of the period was partly resolved by taking the census exactly 1 year after an important Muslim holiday: the end of Ramadan.6 After being adjusted (see Appendix B), the fertility estimates from the census for the period 1987-1988 are very close to those reported by the DHS-II for the period 1989-1992. On average, the ASFRs for the census are the same as those reported in the DHS-II for women under 30. On the other hand, the census estimates are slightly lower than the DHS-II estimates for women over age 30. This pattern might be explained by a relative undercount of births at all ages in the census in comparison with the DHS-II and a small fertility decline at ages under 30 during the short period between 1987-1988 and 1989-1992. Data from the 1986 and 1992-1993 DHS surveys provide a useful consistency

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Population Dynamics of Senegal FIGURE 4-2 Proportion of the total fertility rate attributable to each age group. NOTE: See Appendix A for description of surveys. check on the accuracy of the 1988 census. Dividing all the women in the sample into 5-year cohorts, and assuming that each cohort in the 1986 DHS ages to become the next cohort in the 1992-1993 survey (i.e., those aged 15-19 in 1986 become those aged 20-24 in 1992—not exact, but good enough for present purposes), allows one to compare the cumulated ASFRs based on reported births in the year preceding the 1988 census with the change in the number of children ever born between the two DHS surveys. The denominator, commonly known as the period parity distribution, is obtained by cumulating the parity increments for different cohorts. For the age groups 20-24 and 25-29, the P/F ratios are close to 1, indicating a high degree of consistency between the census and the cohort parity changes. After age 30, the P/F ratios rise somewhat, but definitely not because fertility is falling, because the effects of falling fertility are purged by the cohort increment process. The most likely explanation for this pattern of P/F ratios is that it reflects underreporting of births by older women in the census. In summary, this analysis confirms our suspicions that there was

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Population Dynamics of Senegal FIGURE 4-3 Brass P/F ratios. NOTE: See Appendix A for description of surveys. differential coverage of births in the 1988 census. Specifically, the quality of reporting deteriorated for women over the age of 30. Before age 30, the fertility rates from the two DHS surveys and the 1988 census are consistent. The fertility estimates in Table 4-1 permit different interpretations of fertility trends over the last 40 years in Senegal. The estimates for periods immediately prior to the surveys appear to show steeply rising fertility from 1960-1961 (TFR = 5.4) through 1970-1971 (TFR = 6.4) to 1975-1978 (TFR = 7.2), and then a decline from 1983-1986 (TFR = 6.6) continuing to 1989-1992 (TFR = 6.1), except for an anomalous drop to 5.9 in 1987-1988. However, when time series estimates covering the 15 years prior to the birth history surveys are considered, a different picture emerges. The estimates based on the birth history surveys show fertility (cumulated from age 15-34) declining gradually from 1960 to the late 1980s, with a few irregularities; the estimates from the 1960-1961 and 1970-1971 surveys are much lower (see Figure 4-1). The most pronounced irregularities in the birth history sequences are the points immediately preceding the DHS-I and DHS-II;

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Population Dynamics of Senegal both these points are well below the general trend, and the DHS-I point is well below the corresponding time estimate from the DHS-II. These two points appear to be affected by misplacement of births in time beyond the local shifts around age 5 mentioned above. Further analysis is required to clarify what actually happened to fertility since 1960. The P/F ratios from the 1960-1961 and 1970-1971 surveys fall smoothly with age, across all ages for 1970-1971, but to a minimum for the age group 35-39 for 1960-1961 (see Figure 4-3). The ratios from these two surveys taken together would be consistent with rising fertility affecting cohorts of women born between 1920 and 1950. However, P/F ratios from the 1978 survey show no pattern with age, showing no evidence of differences between lifetime fertility and fertility in the 5 years before the survey for cohorts born between 1930 and 1960. P/F ratios from the 1986 and 1992-1993 DHSs appear to rise with age, though not very sharply, suggesting slowly declining fertility. The 1986 and 1992-1993 series are essentially parallel, but with the 1992-1993 values slightly above the 1986 ones at all ages. Together, they suggest no major change in fertility trends between the surveys, but slightly higher overall omission of children ever born in 1992-1993. The age pattern of P/F ratios from 1960-1961 and 1970-1971 could be explained by increasing omission of children ever born as age of mother increases, as well as by rising fertility. There are large differences in average numbers of children ever born for women at the end of their reproductive life across the surveys. Women aged 45-49 report an average of 5.4 children ever born in 1960-1961, 5.6 in 1970-1971, 7.2 in 1978, 7.3 in 1986, and 7.4 in 1992-1993. These averages would clearly be consistent with rising fertility from the cohort of women born prior to 1925 (aged 45-49 in 1970-1971) to the cohorts born after 1935. However, the age detail of the data suggests some omission from the earlier surveys. The women aged 45-49 in 1978 report an average of 7.2 births each, whereas the average number of children born reported by women aged 35-44 in 1970-1971 (of whom the 45-49 year olds in 1978 would be survivors) was only 5.7. It is unlikely that these women added on average 1.5 births in 8 years at the end of their reproductive lives; more likely is that women aged 35 and over in 1970-1971 underreported their lifetime fertility by half a child or more. A comparison of children ever born by cohort between 1960-1961 and 1970-1971 suggests the same type of error in 1960-1961 also. The national-level data thus do not substantiate a large fertility increase in the 1960s and 1970s, though they do not rule out a moderate increase. Data from one of the population study areas, Niakhar, confirm a fertility increase (from a TFR of 6.8 in 1963-1965 to a TFR of 7.8 in 1984-1990) in one rural area of central Senegal. On balance, it seems likely that fertility

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Population Dynamics of Senegal did rise somewhat in the 1960s and 1970s, though not by nearly as much as the change in TFR from 1960-1961 to 1978 indicates. It is difficult to explain what caused fertility to increase in the 1960s. It is unlikely that the increase can be attributed to a general reduction in the level of primary infertility. The proportion of women aged 50 or more with no live births in the 1960-1961 DS was already quite low, only 4-7 percent. Fargues (1989) has suggested that fertility increases in North Africa may have resulted from reduced marital disruption, particularly divorce; a similar process could underlie a fertility increase in Senegal in the 1960s and 1970s. Figure 4-2 shows relative age patterns of fertility from the five surveys. Though there are differences between the surveys—the proportion of fertility contributed by the age group 40-44 in 1960-1961 is low, as is the contribution of the age groups 30-34 and 35-39 in 1970-1971, partially balanced in the latter case by a high contribution by women aged 45-49—these differences are probably the result of sampling or other errors, and no major trends are evident in the age pattern of fertility from 1960-1990. There is one minor trend visible, however: the percentage of total fertility contributed by the age group 15-19 does appear to be falling over time, from nearly 15 percent in 1960-1961 to 13 percent in 1978, to 11 percent by 1992-1993. The question of whether or not there has been a recent fertility decline also requires further elucidation. Parity-specific analysis of birth history data can be a useful way to detect small changes in fertility for a country at the beginning of a transition toward lower fertility (Brass and Juarez, 1983). Recent analysis of the DHS data using censored parity progression ratios (B60s)7 revealed that the pattern of fertility decline witnessed in Kenya, Botswana, and Zimbabwe is quite unusual in comparison with the Latin American and Asian experience (Working Group on Kenya, 1993). The typical pattern of developing countries outside Africa was for initial declines to take place primarily in the middle, and sometimes in the higher, parities. The decline among low birth orders occurred more slowly. In Africa, by contrast, where fertility reductions have occurred, they have occurred across all parities (Working Group on Kenya, 1993). The B60s for women in both the DHS-I and the DHS-II are shown in Table 4-2. To simplify the table, neighboring parity progression ratios for the same cohort have been combined by multiplying consecutive indices together.8 This procedure has the advantage of dampening fluctuations in the estimates caused by small sample size and is particularly useful because no formula exists to calculate the standard errors associated with B60s: inferences about changes in fertility behavior can be drawn only by examining general patterns in the data (Brass and Juarez, 1983). For the DHS-I data, the B60s show some weak evidence of a fertility

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Population Dynamics of Senegal TABLE 4-11 Percent Distribution of Currently Married Women by Desire for Children, According to Number of Living Children   Number of Living Children Preference 0 1 2 3 4 5 6+ Total Wants to have another child                 1986 DHS-I 97.0 97.2 94.7 88.6 80.1 66.3 34.4 79.3 1992-1993 DHS-II 89.3 91.5 89.1 80.4 74.8 58.8 34.8 69.9 Wants no more children                 1986 DHS-I 1.9 2.1 4.2 10.9 18.8 31.0 61.6 19.0 1992-1993a DHS-II 1.0 1.4 4.2 9.1 16.6 28.3 52.6 20.1 Undecided                 1986 DHS-I 0.9 0.7 1.1 0.5 0.9 2.7 3.8 1.6 1992-1993 DHS-II 2.8 3.0 4.3 8.2 6.1 9.6 9.5 6.6 Declared infecund                 1986 DHS-I — — — — — — — — 1992-1993 DHS-II 6.6 4.0 2.3 2.3 2.5 3.4 3.0 3.2 NOTE: See Appendix A for description of surveys. a Includes women who have been sterilized. SOURCES: DHS-I: Ndiaye et al. (1988:Table 5.1, p. 68); DHS-II: unpublished tables supplied by Macro International, Inc. partly the function of a change in the wording of the questionnaire, it appears to have occurred across almost all parities and all age groups (see Tables 4-11 and 4-12). Another indicator suggesting that the demand for family planning may increase in the future is the decline, since 1978, in the number of children women reported as "ideal." The ideal number of children for all women fell from 8.5 in 1978 to 6.8 in 1986, and then to 5.9 in 1992-1993. As can be seen in Figure 4-23, this trend is apparent for all age groups. However, 5.9 children per woman is still very close to the potential supply of children, so that with the trend towards later age at first marriage, the small decline in ideal family size can be realized without resorting to contraception. Abortion As in most developing countries, there are few firm statistics on the extent of abortion in Senegal. Although reliable statistics are unavailable,

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Population Dynamics of Senegal TABLE 4-12 Proportion of Currently Married Women Aged 15-49 by Desire for Another Child, According to Age of Woman   Age of Woman Preferences 15-19 20-24 25-29 30-34 35-39 40-44 45-49 Total Wants to have another child                 1986 DHS-I 98.5 98.2 91.8 78.1 61.7 45.8 33.9 79.3 1992-1993 DHS-II 94.2 93.7 86.1 72.7 57.6 34.8 20.2 69.9 Wants no more children                 1986 DHS-I 1.2 1.7 7.6 19.4 36.5 50.5 59.0 19.0 1992-1993a DHS-II 1.8 1.7 7.3 17.6 33.0 47.8 52.1 20.1 Undecided                 1986 DHS-I — 0.1 0.6 2.3 1.6 3.7 7.1 1.6 1992-1993 DHS-II 3.8 4.0 5.4 8.5 7.2 8.5 10.8 6.6 Declared infecund                 1986 DHS-I — — — — — — — — 1992-1993 DHS-II 0.2 0.4 1.2 1.3 2.0 8.8 17.0 3.2 NOTES: Totals by age for each year may not equal 100; in both years, 0.1 percent of cases were missing. See Appendix A for description of surveys. a Includes women who have been sterilized. SOURCES: DHS-I: Ndiaye et al. (1988:Table 5.2, p. 68); DHS-II: unpublished tables supplied by Macro International, Inc.

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Population Dynamics of Senegal FIGURE 4-23 Variations in ideal family size over time. NOTE: See Appendix A for description of surveys. SOURCES: Standard data files from WFS, DHS-I, and DHS-II. illegal abortion is generally considered to be an increasingly serious problem, especially in urban areas (Ferry, 1981; Pillsbury, 1990; Diouf, 1994). Because abortion can carry a fine that ranges from 20,000-50,000 CFA (US$40 to US$100) and 6-10 months in prison, both for the woman undergoing the abortion and for the performer, abortions are often carried out clandestinely. Botched abortions are a major cause of all hospital admissions for women of reproductive age. In 1988, abortion complications were one of the two major reasons for the emergency transfer of women from Pikine to Dakar (Guèye et al., 1989, cited in Pillsbury, 1990). Limited data on abortions are available from several sources. Information on abortion from the WFS is limited because the relevant questions did not distinguish between spontaneous and induced abortions, but it appears that between 10-12 percent of women reported having had an abortion (Diouf, 1994). Sow (1985) estimates that at the time of the WFS, women had, on

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Population Dynamics of Senegal average, 0.3 abortions over their lives, although the basis for this estimate is unclear. Because of the moral and religious sensitivity surrounding the issue, no questions on abortion were asked in the 1986 DHS-I, but there was a rather roundabout attempt to measure the abortion experience of women in Senegal in the 1992-1993 DHS-II. In DHS-II, women were asked whether they had ever had an unwanted pregnancy, and, if so, what they had done about this pregnancy. Out of 6,299 women, 1,131 admitted that they had had an unwanted pregnancy. Of these women, 1,058 carried the pregnancy to term and 37 were currently pregnant. Only 19 women admitted that the pregnancy was terminated, either spontaneously or by induced abortion, although a further 15 women admitted that they had attempted to induce an abortion but had failed.* The prevalence of abortion in the WFS survey appears to be in reasonably close agreement with a survey undertaken in 1986 in Pikine. Out of 9,196 pregnancies, 804 or 8.7 percent of them resulted in spontaneous or induced abortions (Antoine and Diouf, 1989:507). The frequency of abortion varied by age of women, marital status, ethnic group, level of instruction, and number of children ever born. Abortion in Pikine appeared to be particularly frequent among 15-19 year olds and among unmarried women (Diouf, 1994). However, abortions were also fairly common among women over age 30 and among married women. In the Bongaarts model presented above, the index measuring the effect of abortion on fertility is set to 1 for the WFS and the DHS-I. The assumption is that, given the general high demand for children, deliberate abortion is not important in determining final fertility outcomes. This assumption almost certainly leads to a serious underestimation of the extent of abortion among adolescent schoolgirls. Taking the DHS-II figures at face value implies an index of Ca of .999, an unsatisfactory result and no improvement over the basic (poor) assumption of zero abortion. Clearly, much more research on abortion is needed, especially among young women, although the effect of abortion on total fertility is probably of little importance.30 Sterility For pathological or other reasons, some couples will never bear children (primary infertility). Others lose the ability to bear children following an earlier birth (secondary infertility). Sterility can occur either naturally, primarily by aging, or pathologically, primarily by complications resulting *   Two women failed to answer the follow-up part of the question.

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Population Dynamics of Senegal from infection with a sexually transmitted disease, which in Africa is most frequently gonorrhea. In the absence of fertility regulation, a reasonable estimate of the level of infertility is given by the proportion of women aged 40-49 who have never had a live birth. In a population with a ''normal" level of sterility, one would expect around 5 percent of women to be nulliparous (Frank, 1983), although the level depends strongly on the age pattern of first births. In Senegal, the figure ranges from 2.7 to 4.6 percent across the last three national-level surveys, WFS, DHS-I, and DHS-II. The small number of nulliparous women in each sample does not permit us to establish a trend between surveys. Other local studies confirm the general level of sterility (Ferry, 1981) or indicate slightly higher levels, possibly reaching 8 percent, as in Bandafassi (Pison and Desgrées du Loû, forthcoming). In summary, the prevalence of primary sterility in Senegal appears rather normal, and sterility scarcely diminishes the reproductive potential of Senegalese women. SUMMARY AND CONCLUSIONS The 1978 WFS established that fertility in Senegal was very high in the mid-1970s—7.2 children per woman. There are some indications that fertility may have been lower two or three decades earlier and increased in the preceding years. Fertility declined by around one child per woman between the mid-1970s and the beginning of the 1980s, and the differences in the fertility levels among various regions and socio-cultural subgroups have increased. The decline has occurred almost exclusively among women under age 30. A comparison of ASFRs between 1975-1978 and 1989-1992 reveals that the decline in fertility among women aged 15-19 is approximately twice as large as that among women aged 20-29, which, in turn, is almost twice as large as that among women over age 30. After age 30, fertility has remained much the same. The driving force behind these changes has been a trend towards later marriage. In some areas of Senegal, for example in Casamance, women have always married relatively late. However, the larger trend towards later marriage probably began in Dakar in the early 1980s and has been spreading to other urban areas ever since. The pattern of later marriage is closely linked to formal education, although signs of change are emerging even among women who have never attended school. Little of the fertility decline appears to be attributable to either a decrease in ideal family size or an increase in the use of modern contraception. Nationally, use of modern contraception has enjoyed only modest success. Contraceptive use among currently married women increased from 1 percent in 1978 to 5 percent in

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Population Dynamics of Senegal 1992-1993. However only certain subgroups of the population use modern contraception, so that the absolute number of users is still very low. In summary, these features indicate that Senegal's small fertility decline is unlike those that have occurred recently in other sub-Saharan African countries. In Botswana, Kenya, and Zimbabwe—usually considered the three countries in the vanguard of an African fertility transition—fertility declines are associated with increased use of modern contraception. In Senegal, the decline is associated with a trend toward later marriage. In addition, although Botswana, Kenya, and, to a lesser extent, Senegal and Zimbabwe have all experienced a decline in teenage marriages, Senegal has not experienced such a dramatic separation of teenage marriage and teenage fertility. Consequently, Senegal has not seen the same increase in premarital fertility as these other countries. The Senegalese pattern matches more closely, but not exactly, the pattern found in certain Northern African countries during the first phase of their fertility declines. For example, most of the first decreases in-fertility observed in countries such as Algeria, Egypt, and Tunisia can be attributed to later age at first marriage (Fargues, 1989; National Research Council, 1982). It is interesting to note that in these countries, the initial phase of fertility decline was followed immediately by a second phase linked to a substantial decline in the demand for children and a corresponding increase in modern contraceptive use among married women. Whether Senegal follows this pattern and experiences a second phase of fertility decline immediately following the first remains to be seen.31 Much will depend on what happens to the demand for children. There has been a trend towards wanting fewer children that extends across all parities and all age groups of women. However, current preferences still lie very close to the physiological maximum, assuming a continued regime of delayed marriage and long birth intervals. If the education sector can overcome its fiscal constraint and continue to make advances in primary and secondary school enrollment for women, further declines in fertility can be expected in the near future. In rural areas, a further reduction in fertility can be achieved solely by later marriage. Urban areas, particularly Dakar, have already experienced most of the decline in actual fertility that is achievable solely by an increase in the age at marriage. Future fertility reductions will have to await greater coverage of modern contraception. If the government of Senegal wishes to influence the timing and shape of the fertility decline, it must implement strong policies that target both girls and women of reproductive age. For girls, policy should be aimed at increasing formal education. For women, action should be taken to promote the availability of contraception while increasing women's functional literacy and reducing their domestic burden. When combined with interventions

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Population Dynamics of Senegal aimed at improving maternal and child health, such policies should have a good chance of making women more receptive to the use of modern contraception. NOTES 1.   The TFR expresses the total number of children a woman would have if she experienced the same level and pattern of fertility throughout her reproductive life as those in effect at the time of the survey. 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. 2.   See Appendix A for a complete list and brief description of all the major surveys used in this report. 3.   Apart from not reporting children that died, respondents frequently are unable to identify the beginning of the reference period, and this can also lead to systematic bias. Fortunately, this was probably not a serious problem in the 1988 census (see endnote 6). 4.   For example, the infant mortality rate based on data for deaths occurring during the preceding 12 months was estimated to be 93 deaths per 1,000 live births, or approximately half the presumed actual rate. 5.   There was also a tendency in the WFS to shift the dates of births towards the survey date, and there were a number of omissions of births for more remote time periods (Guèye, 1984; van de Walle and Foster, 1990). 6.   The 1988 census was conducted between May 20 and June 3, but May 27, 1988, was adopted as the official reference date. The holiday of "Korité," which marks the end of Ramadan and is widely celebrated in Senegal, fell on May 29 the year before, nearly 12 months to the day before the census reference date. Conse­quently, the holiday was used as a reference point to identify any births and deaths that occurred in the 12 months preceding the census. 7.   B60s measure the proportion of women in an age cohort (a group of women defined by 5-year age groups at the time of the survey) who, having attained an nth birth, go on to an (n + 1)th birth within 60 months. Thus B60s are a form of censored parity progression ratios (CPPRs). B60s have been designed to correct for an inherent bias in the usual calculation of CPPR suggested by Rodriguez and Hobcraft (1980) that results from systematically excluding women with long birth intervals (see Brass and Juarez, 1983)- 8.   That is, we report the probabilities that a woman in a particular cohort who has had her nth birth goes on to have an (n + 1)th birth within 60 months of her nth birth, and subsequently goes on to have an (n + 2)th birth within 60 months of her (n + 1)th birth. 9.   The term "grand region" is used throughout this report in reference to the four WFS and DHS regions, as opposed to the ten administrative regions. 10.   Other data from local studies in the Sine-Saloum region are not presented here because of the small population size from which they are taken, their poor quality that is acknowledged by those responsible for their collection, and the lack of published data.

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Population Dynamics of Senegal 11.   See Pison et al. (1991), Pison and Desgrées du Loû (forthcoming), and Appendix A for additional information. 12.   See Pison et al. (1991), Lagarde et al. (forthcoming), and Appendix A for additional information. 13.   Note that given the longitudinal nature of the survey, the omission of births in recent periods is probably not a large problem. For the most recent period, 1985-1992, the estimates of the fertility rate are based on the number of recorded events between multiple rounds of the survey. Thus the most recent estimates take advantage of the longitudinal nature of the survey. Fertility estimates for the earlier periods are from retrospective biographical data. 14.   The census did not include an additional question on the number of chil­dren a women had ever borne, which would have enabled us to use indirect estima­tion techniques to correct for underreporting of births, nor did it ask one further question, on the number of children that had died, which would have provided information for the estimation of child mortality. 15.   Briefly, this neoclassical model holds that households decide on the num­ber of children to have by attempting to maximize household utility subject to time and income constraints. Children, both in quantity and quality, enter the problem in exactly the same way as other goods. Together with other competing sources of satisfaction, they create household demand, which can be satisfied by a combination of (1) income from either a household's wealth or the labor-force participation of its members, and (2) time. Because the bearing and rearing of children is an extremely time-intensive activity, especially for women, having children competes with other activities, such as working in the labor force. Hence, women are forced to trade off their time among (1) working in the labor force so that they can purchase additional goods and services, (2) bearing and raising children, and (3) doing other things. The problem is further complicated by the fact that the wages and opportunities for women are likely to be functions of previous labor-market experience, which in turn depends on the timing and frequency of earlier children in a woman's early working life (Willis, 1973; Becker, 1981; Schultz, 1981). Note, however, that this demand-side approach is often viewed as being overly simplistic in developing countries because it largely ignores the economic contribution of children through farm work and child-minding activities—which can be considerable—and the role of children as care providers for their parents in old age (Anker and Knowles, 1982). These factors provide an important incentive for high fertility. Finally, the neoclassical model assumes that individual households act alone and ignores the role extended families play as decision makers and, in some cases, as child rearers. 16.   Ferry (1981) observes that fertility rates in Dakar were at least as high as, if not higher than, those in rural areas in the late 1960s. 17.   See, for example, Lacombe (1972) who provides estimates of fertility rates by ethnic group from as early as 1957. 18.   Comparisons among ethnic groups, and in particular between the Serer and the other groups, are made difficult because of a tendency for Serer women to declare themselves to be Wolof in surveys. This practice, which has been termed "Wolofization" (Ferry, 1977), is more prevalent in urban than in rural areas. Thus the Serer ethnic group disproportionately comprises women who remain in rural areas, which introduces an important selection bias into the data.

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Population Dynamics of Senegal 19.   Secondary education of women is also likely to be correlated to the prob­ability that the husband works in the formal sector, which itself can have an inde­pendent effect on fertility outcomes (see Mboup, 1993). 20.   See Chapter 2 for a description of each of the socioeconomic indicators. 21.   TFR = total fertility rate; Cm = index of marital fertility calculated using the formula Cm = TFR/TMFR, where TMFR is the total marital fertility rate. (Both rates are estimated for the 4 years prior to the survey.) Cc= index of contraception, calculated as Cc = 1-1.08ue, where u is the current contraceptive use prevalence rate among women in sexual unions, and e is the average effectiveness of the chosen contraceptive methods, calculated as the weighted average of the proportion of women using each method times the effectiveness of the method. Following Jolly and Gribble (1993), we have divided other methods into other traditional methods and other modern methods. The following effectiveness levels have been assigned to specific methods: sterilization = 1.0; IUD, Depo-Provera, Norplant = .95; pill = .90; other modern methods = .70; traditional methods = .30. Breastfeeding and postpar­tum abstinence are not included in contraception, since they are not parity-specific practices and are adopted to protect maternal and child health, rather than as a means to limit family size. Furthermore, there is substantial variation among sur­veys in the proportion of women practicing abstinence as a method of contraception, which probably has more to do with differences in definitions and interviewers' instructions than with changes in women’s behavior. Finally, traditional methods, such as the use of ritual charms or potions (gris-gris), have been excluded; in essence, these methods are equated with using no contraception. Ci= index of postpartum infecund interval, calculated using the formula Ci = 20/(18.5 + i), where i is the mean number of months of postpartum infecundability (estimated as the mean number of months of postpartum amenorrhea or abstinence, whichever is longer) for women in union. Ca = index of induced abortion, taken to be 1.00 in the absence of additional information; and Ip = index of sterility calculated as Ip = (7.63 - .11s)/7.3, where s is the proportion of women aged 40-49 who have never had any children. 22.   It would be a mistake to read too much into the differences in the Ci index among surveys. The WFS did not ask women whether they were currently amenorrheic, so the Ci index for the WFS was imputed using a formula provided by Bongaarts and Potter (1983), based on the duration of breastfeeding. 23.   When examining age at first marriage in any African setting, it is impor­tant to remember that marriage in Africa may be better described as a process than an event (van de Walle, 1968, 1993; Lesthaeghe et al., 1989; Pison, 1989; Meekers, 1992; Working Group on the Social Dynamics of Adolescent Fertility, 1993). Un­like births or deaths, entry into marriage may take place over an extended period of time. Consequently, the date on which a marriage occurs is subject to several interpretations. First, marriages are usually marked by a ceremony and the transfer of a bridewealth that can range from symbolic tokens to large transfers of cash or goods spanning several years. However, the payment of bridewealth, the ceremony, the cohabitation of spouses, and the consummation of the marriage often occur several months apart and not necessarily in the same order (Meekers, 1992). Among the Poular, for example, consummation of marriage may occur several years after a marriage cer-

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Population Dynamics of Senegal     emony. This traditional waiting period (known as "le jebalé") is often decided mutually among the parents of the newly married couple and helps explain the paradoxically low levels of fertility in the first years of marriage among the Poular (République du Sénégal, 1981:97). Different members of society may also give full recognition to the union at different stages of the process, perhaps depending on the ethnic group(s) involved, the degree of personal involvement, or simply individual interpretation. The practice of dating marriage by date of cohabitation was aban­doned in the DHS-I for Senegal and was replaced with date of consummation. Furthermore, there are multiple forms of marriage in Senegal, so that as an institution, marriage is not always easy to measure. Customary marriage practices in Senegal include monogamy, polygyny, and a wide range of consensual unions such as "sugar daddies" and "outside wives." Unfortunately, the need for survey and census takers to categorize and reduce the various forms of marriage into a small number of discrete units means that much of this diversity in marriage pat­terns is lost. In the 1988 census, information on marriage was collected for all persons aged 6 and over. Marriage was defined to include both civic and traditional marriages, but excluded conjugal unions (i.e., unsanctioned unions), a more restric­tive definition than that used in either the DHS-I or the DHS-II. Marriage was defined quite loosely in both the DHS surveys, and a series of questions was used to identify such possibilities as a couple living together but not in a sanctioned union and a "visiting relationship." In the 1988 census, these variants of marriage were probably captured in the category "autres cas," which was left suitably ambiguous. Confusion surrounding the definition of marriage extends far beyond researchers in their efforts to categorize people as being either married or unmarried in the West­ern tradition. Couples in apparently identical situations may describe their condi­tion in quite different ways, and in some instances, even the partners in the same union may not agree on their marital status (Locoh, 1988, cited in Working Group on the Social Dynamics of Adolescent Fertility, 1993). Van de Walle (1993) suggests that the processional nature of marriage in Africa presents an inherent ambiguity to respondents that could introduce systematic biases into their responses. For example, some unions that have only partially completed the process of marriage may be reported as marriages at the time of a survey, but may appear never to have taken place if the union dissolves. At the same time, other partial unions that prove successful may not have been reported as "mar­riages'' in their earlier stages, but with the benefit of hindsight appear to have started at a time when their status was actually quite uncertain (van de Walle, 1993). This ambiguity also makes it difficult to define what constitutes a premarital birth, since in some instances the birth of a child is actually part of a longer marriage process (Working Group on the Social Dynamics of Adolescent Fertility, 1993). 24.   In fact, Guèye and Ferry (1985) and Ndiaye (1985) note that there is an inverse relation between age at marriage and the length of the interval between marriage and first birth in Senegal. 25.   A similar finding has emerged from many other DHS studies in Africa (see Working Group on the Social Dynamics of Adolescent Fertility, 1993; Diop, 1993), but the extent of the rise in premarital adolescent childbearing in Senegal is rela­tively small in comparison with the experience of several other sub-Saharan Africa countries (e.g., Kenya and Botswana).

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Population Dynamics of Senegal 26.   The Malinké belong to the Mandingo group, and the Bedik a small group also called the Tenda, are close to the Bassari. 27.   "Polygyny is often perceived by more educated women as being a type of union that is incompatible with their social aspirations" (République du Sénégal, 1981:81). 28.   The calculation of Ci can be done directly on the basis of the duration of postpartum amenorrhea or indirectly on the basis of a model linking the duration of amenorrhea to that of breastfeeding. On the basis of data from the DHS-I, compari­son of direct and indirect results shows that the period of infecundability is longer if one considers declarations of postpartum amenorrhea than if one infers the length of amenorrhea indirectly from the duration of breastfeeding (Jolly and Gribble, 1993). 29.   We have no data on the intensity of breastfeeding over time. 30.   An alternative approach is to calculate Ca indirectly from Table 4-5. As­suming a level of total fecundity of 15.3 children per woman (Bongaarts and Potter, 1983) and applying the formula TFR = Cm x Cc x Ci x Ca x Ip × 15.3, implies levels of Ca between .82 and .88 across the three surveys. 31.   An important element in these other countries' fertility decline is that as women’s educational status has improved, the gain due to more widespread contra­ception and the loss due to shorter breastfeeding—the most important determinant of amenorrhea—have practically canceled each other out (Fargues, 1989). In con­trast, recent data from the DHS-II do not indicate that the average length of breastfeeding is decreasing in Senegal.