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PART I FERTILITY DETERMINANTS AT THE NATIONAL LEVEL CHAPTER 1 THE PROXIMATE DETERMINANTS OF E ERTILITY The objective of this chapter is to analyze Brazil's accelerated fertility decline in demographic terms. Demographic theory indicates that two sets of variables are important: one is population composition, particu- larly age structure and marriage patterns, both of which mediate the relation between individual reproductive behavior and birth rates observed in a population; the other is comprised of the Davis-Blake (1956) ~ intermedi- ate variables, ~ such as frequency of intercourse, fertility control, breastfeeding, and abortion, which d irectly affect reproductive outcome. This chapter uses a standardization approach to identify compositional effects, and Bongaarts ' (1980) method for decomposing natural fertility into its proximate determinants to identify intermediate variables. This chapter is based on the available data for Brazil, which are fragmentary in both regional and time coverage. The approach is therefore essential detective work, piec- ing together clues from a variety of sources in an attempt to draw a picture at the national level. Changes In mar- r iage patterns and age structure are always prime suspects in declining birth rates; therefore, the discussion begins by assessing changes in the distribution of women by mar- ital status and in mean age at marriage, and then applies standardization techniques to check whether these changes and those in age structure played a major role in Brazil's fertility decline. The available evidence suggests that they did not. This suggests in turn that the primary factor in the decline was one of the intermediate vari- ables affecting marital fertility. The Bongaarts frame- work is then used to explore this possibility. There are three potential factors responsible--breastfeeding, contraception, and abortion. Among these, the limited 29

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3a Degree to which the f irst is practiced in Brazil is sufficient to eliminate it as a primary influence. The evidence implicating the second is stronger, though admittedly fragmentary. Finally, although the evidence is clearly circumstantial, i t is strong enough to implicate abortion as an important, though necessar fly indeterminate, influence on Brazil' s fertility decline. MARITAL STATUS AND MEAN AGE AT MARRIAGE As noted above, the reporting of marital status in Brazilian data is problematic. The reported percentage distribution of Brazilian women aged 15-49 by marital status in the 1950, 1960, and 1970 censuses and in the 1976 PNAD survey are presented in Table 5; preliminary results of the 1980 census are also reported. Four marital status categories are shown--married, divorced and separated, widowed, and single. Each of these categories presents its own set of problems. First, in the married category, there is a problem in the reporting of women in consensual unions. According to Henriques (1980), women in consensual unions account for an important share of Brazilian births, though Brazil has a lower proportion of such births than a number of other Latin American countries However, although Brazilian data include women in consensual unions as a subcategory of married women, there is strong evidence that a number of those who report themselves as single may in fact be in "=nsensual unions {Si}va, 1979:14). This is suggested by data in Table 6, which shows the percent of women in the single category who reported having had a birth from age 15-19 to 40O49 in the censuses and P=D survey. Brazilian census authorities have attempted to improve on the reporting of consensual unions by broadening the number of categories of mar ital status to include the type of union. In 1950, when there was no subcategory for consensual unions, nearly four out of ten single women reported a birth by the end of their reproductive years, suggesting that most of these unions were grouped in the single category (Al~'nann and Wong, 1981a:3561. This contrasts with 1960, when the consensual union category was introduced and the proportion of single women reporting a birth dropped Deco 11 percent. It should be recalled that tabulation of the 1960 census was delayed until the late 1970s because of administrative

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31 TABLE 5 Reported Percent Distr ibution of Women by Marital Status and Age, 1950-80: Brazil Divorced, Age Marr ieda Separated Widowed S ingle Total 1950 15-19 14 ~ 8 0 0 ~ 0 0 1 85 ~ 1 100 20-24 51.9 ~ ~ O 0 0 7 410 4 100013 25-29 70~4 001 lc8 27~7 100~0 30-39 7tje3 002 501 18~4 100~0 40~49 7102 Oa3 1401 1404 . 1Ot)~0 1960 15-19 14~0 (1~3) 007 0~1 8502 100~0 20-24 53~3 (3~6) 2~6 004 43~7 10000 25-29 7400 (5~1) 304 101 2105 - 10000 30~39 80~9 (504) 3~9 3~1 12~1 10000 40~49 76~2 t409) 408 1001 8~9 100~0 1970 15-19 12~0 (1~4) 0~5 0.1 87.4 100~0 20-24 46~9 (3~9) 2~0 0~3 50~8 10t)~0 25-29 71~3 (5~4) 3~0 009 24~8 100~0 30~39 80 ~ 2 (5 ~ 7) 4 ~ 1 2.8 12.9 1000 ~ 40~49 `6~2 (4~9) 5~6 8~9 9~3 100~0 1976 lS-19 11~2 (109) 0.6 001 88.1 10000 20-24 46~2 (504) 2~0 002 51~6 100~0 2S-29 69~8 (6~8) 3~0 0~8 26~. 100~0 30~39 19~5 (7.4) 4O9 2~6 13~0 10000 40-49 77.7 (6.6) 5.9 804 800 100.0 lg80 15-19 16~3 {3~5) 0~5 OoO 83c2 100~0 20-24 53~2 (8~0) 2.a 0~3 44~5 100~0 25-29 72e 6 ( 9. l) 3.2 0 0 7 23 ~ 5 100 ~ 0 30_39 79, 9 ( 9 ~ -2 ) 4 ~ 5 2.3 13 ~ 3 100 ~ 0 40~49 77~0 (7~7) 6~3 7~7 9~0 100~0 aFigures in parentheses represents when in consensual unzoned as a percent of all women, when reported. bThe total excludes women who did not report marital status. Sources: 1950-80 from population censuses' 1976 from PLED survey. breakdowns, and that procedures used in reconstructing it may have biased the results. The repot ted trend from 1960 to 1976 is puzzling, since it suggests that births to single women increased. It is possible that PEAS interviewers, who were more highly trained than census interviewers, were more careful in identify sng single mothers.

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32 TABLE 6 Percent of Single Women Who Report Having Had a Child, by Age, 1950-76: Brazil Age Group 1950 1960 1970 1976 15-19 1~7 0~4 0~7 1~5 20 24 10~0 2~4 3~8 6~0 25—29 22 0 3 5 e 5 8. 7 10 . 2 3~)~39 34O3 8~8 14~6 17~9 40 49 363 0 7 10 ~ 9 16 0 3 23 ~ 5 Source: Published tabulations of census and survey data. The impact of misreporting of women in consensual unions appears to be greatest among younger women. For women aged 20-24, the proportion reported as married increases from 51.9 percent in 1950, when consensual unions were not included as a subcategory, to 53. 3 percent in 1960 ~ when the subcategory was introduced. To illustrate the possible influence of consensual unions on reporting, the percentage of women in the consensual union subcategory is indicated in parentheses in Table 5 next to the percent married after 1960 (the basis of this percentage is all women in the age category). The proportion of women aged 20-24 reported as married decreases from 1960 to 1976 0 then increases sharply to S3O 2 percent (about equal to 1960) in the 1980 results. At the same time, the percent of women in consensual unions increases, particularly ire 1980, when the f igure is 8 percent of all women ( IS percent of marr fed women) . Published tabulations of the preliminary 1980 results do not supply enough information to determine whether, in editing, single women with births may have been reclassi- fied as being in consensual unions. The evidence suggests either that consensual unions have been increas ing or that reporting of such unions has improved. In all likelihood, results for earlier periods understate the proportion of younger women reported as married. Such underreporting would bias the age-specific marital fertility rate for these women upward if that proportion were used in the calculation of the rate; it would also add a further bias to the extent that consensual unions were recognized when a woman gave birth to a child.

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33 Although the impact of the underreporting of consens~al unions is reduced by grouping all single women with births in the married category, it is not eliminated. One is still left with the problem of women in informal unions who have no children, but should be included in the denominator when fertility rates are calculated. Thi omission could bias calculation of rates for younger women, particularly when the beginning of an informal union is not clearly demarcated and the birth of a child leads to recognition (or admission) of the union. Including in the married category only those Musingly women who had births will lead to overstatement of marital fertility rates. One way to compensate for this is to assume that the proportion of single women sat risk. Is equal to that of married women; that is, if SO percent of married women aged 20-24 report a birth, then assume that the single women aged 20024 reporting a birth represent 50 percent of the single women at risk. This at-risk group can then be added to the married category. s _. . . . . . This procedure will be employed later in calculating the denominators for marital fertility rates. The issue of type of union and its relationship to fertility at the local level is explored in detail in Part II of this report. A second problem of consistency in the Brazilian data on marital status relates to the reporting of separated and divorced women. Because Brazil legalized divorce only in 1977, its effects cannot be observed directly even in the 1976 survey. However, reporting of foreign divorces, legal separations, and a special Brazilian legal substitute for pre-1977 divorces (desquites) was increasing in the years prior to actual legalization. The contrast is sharpest between 1950, when practically no divorces and separations were reported, and the other data points. Because divorce was not legally recognized, it was fairly common practice for women who had entered a second union after separation to be declared as separated rather than married, leading to further underreporting of the proportion of women in unions. Such problems with the reliability of marital status data suggest that considerable caution is required in the calculation and interpretation of measures incorporating those data. This applies not only to the proportion of women in unions, but also to measures of the average age at marriage and marital fertility rates. Table 7 sum- mar izes the results of calculations of the singulate mean age at marriage (SMAM), which is based on the proportion

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34 TABLE 7 Singulate Mean Age at Marriage (SMAM), by Region, 1950-76: Brazil PNAD Reg ion 1960 1970 1976 1. Rio de Janeiro 22.92 23.17 23.93 2 0 Sao Paula 22.25 23.30 23 0 47 30 Southern States 21.66 22.17 22.80 4. Hinas/13spirito Santa 22 0 36 23. 36 23 ~ 66 50 Northeast Stabs 22.lB 22 23013 6. Brasilia 20.4S 23.38 23.73 7. 1?~tier States =.~] 22.04 °- Brazi.1 Marriage First Birth 22 .1l 22. 91 23.3 3a 22.42 23.28 23.84a aThe Brazil f igure for 1976 excludes rural areas of Reg ion 7, which was not included in the PNAD survey. Source: SMa~ calculated from census and survey distribu~cions of women by marital status considering single women who reported having had children as married. First-birth measure based on same computation as SMAM, but substituting the proportion of women reported as childless. of women reported as single at different ages. In order to reduce the impact of underreporting of consensual unions, single women reporting a birth were considered mart fed . SMAMs were calculated for the PNAD reg ions and Brazil as a whole ire 1960 Of 1970, and 1976. For Brazil as a whole, the data indicate a comparatively late average age at marriage and suggest that this average increased by more ~chan one year between 1960 and 1976. Most of this increase came between 1960 and 1970, and resulted from a more than 6 percentage point rise in the propor- tzan reported as single between the two dates. It was Dot Audible tc' include single women with births in the <:a'=ulati~ of t~ SW~£ for 1980; nevertheless, with the

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35 decreased proportion reported as single in the prelimi- nary results, the average age at mart iage dropped back to the 1960 level of 22.1 years. It should also be noted that the preliminary 1980 results are not fully comparable to those for earlier dates since it was necessary to use 10-year age groups for women over age 30. The breakdown of SMAlls by region indicates a fairly homogeneous pattern, with lower average ages in the Southern and Frontier states, and higher average ages in the Southeastern states (Regions 1, 2, and 4). The largest increase in average age at marriage is found In Region 6 (Brasilia); it may be observed that the compo- sition of Brasilia's population changed significantly from the 1960s, when it was being constructed, to the 1970s, when it began to function fully as the national capital. For the remaining regions, increases range from .5 to 1.0 years in 1960-70 and .2 to .6 years in 1970-76. Since there are questions about the reliability of the mar ital status data on which the SMAMs are based, another way of looking at the age at which exposure to the risk of childbear ing starts is to consider the mean age at first birth. This can be derived from data on the proportion of women who remained childless at different ages us ing the same computational procedure employed in calculating SMAMs. The resulting index, calculated only for national-level data, is shown in the second row of results for Brazil in Table 7. For 1960 and 1970, the average age at first birth is .3 years higher than the age at marriage. This increases to .5 years in 1976. The 1980 average, not shown in the table, is 22.1 years, just equal JO the average age at marriage. MARITAL FERTILITY How much did changes in the proportions married and age at marriage contribute to the acceleration of Brazil's fertility decline? Table 8 attempts to link total and age-specific fertility rates (ASFRs) to total marital fertility and age-specific marital fertility rates (ASMFRs) using the 1960, 1970, 1976 ~ and 1980 data. The f irst column of the table shows ASFRs and total fertility rates calculated for the Brazil report of the Committee on Population and Demography, National Academy of Sciences. The total fertility rates are the same as those reported in Table 2, showing declines of about 6 percent from 1960 to 1970, 24 percent from 1970 to 1976,

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36 TABLE 8 Age-Specif ~c And Total Mar ital Fertility Rate Calculations, 1960, 1970, 1976, and 1980: Brazi 1 Age Group ~sppa Percent Mar r iedb ~ a ~ ~ b ~ ASMP Rc ASMP~ 1960 15-19 e0799 14 ~ 0 15 ~ 3 ~ 354 20-24 ~ 2719 53.3 57 ~ 4; 0 472 25 29 03150 74~) 7908 0395 30~34 02615 8003 87cS .299 35 39 01935 81. `e 90 ~ 8 ~ 213 40 44 . - 08 77 O 9 910 7 ~ 099 45-49 .0239 74.3 92.7 .026 Total 6~18 58~9 65~7 9~29 1970 15-19 20-24 25-29 3 0~34 35~39 40~4 45~49 ~otal 1976 15-19 20-24 2So29 30~34 35~39 40~~. 45~49 Tota1 1980 15-19 20-24 25 -29 30~341 35-39 40—44 4 5 - 49 Pota1 .0753 2564 2971 0 2466 ol821; ~ 08S6 .0225 5~83 .0733 0 2062 0 2240 0 1814 .1292 0 OS88 oO108 ~o45 ~ 0850 4 20S. 0 2071 D ~L604 c 1030 .0Je188 ~ 0093 4.10 1200 46~9 7103 80~2 8101 77~8 741~3 55~5 11~3 46~3 69~8 7808 8003 79~d 75~7 55~2 .163 S32 .726 799 799 770 .770 S6~5 13 o7 51~6 77~6 87~3 91~0 9200 92~8 62~8 14~1 52~3 760S 8704 9106 93~7 94~2 63~3 ~ 168 .555 765 867 ~ 867 .910 .910 64!~8 . 373e .497 .383 ~ 282 0 200 .093 0024 9~27 · 295e .394 0 293 0214 o 141 eG63 ~ 011 7~06 0 278 0 370 0 271 ol8S 119 054 oO10 6~. 352e ~ 469 .384 ~ 287 .209 ~ 102 .033 .l8 . 284e ~ 379 .292 0222 ol47 a071 .015 .05 Sources s ASF8s Ag~specific fertility rates Pancl on Brazil. Cc~itte. on Population and ~raphy, Mational Acaday of Scienece. Pctcent ~rried: in coluan ta) as reported in published h^h""tione, in colu~ (b) adjusted to include all everqrried wa~n' and, except for 1980 when data not available, single wa~n ·st risk- ~ expla~d in text. ASMYRs Ag repecific earitsl fertility rates co~put.d using ASEa and percent carried, verdant (b). AS~FRs Age-specific easite1 fertility rates coo puted fro specla1 e~bolation of birthe in previous year for ever-aarried wooen, and and adjust d by P/P ratios for all wo.en tl.32 in 1970 and 1.22 in 1916). Not available for 1960 and 1980. ASMFR for 15-19 cooputed as .75 ASMFR for woann aged 20-24.

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37 0.5 0.4 LU a: a: 0.3 - - CC up Cal - C: 0.2 In Al Or 0.1 o —_ _ Santa Cruz-U rban Parnaiba-Rural /N I ~ / / \ \ >_ 1 40 45 50 1 5 20 25 30 35 AGE FIGURE 5 Age-Specif ic Fertility Rates, 1975: Brazil and about 8 percent from 1976 to 1980. As can be seen in Figure 5, the shape of the age-specific fertility rate profile became somewhat flatter with the decline, which was substantial for all age groups except the youngest. The largest absolute decline occurred at ages 25-29, with larger proportional declines among the older age categories. A first attempt was made to translate ASFRs into age-specific marital fertility rates by using data on

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38 marital status from published reports, as shown in column (a) under percent married" in Table 8. Because of the underreporting of women in consensual unions, ASMFRs appear to be biased upward, particularly for women in their twenties. In 1970, for example, the ASMF~ for the 20-24 group would be .547; this would mean that the fertility of Brazilian women exceeded that of the Hutter- ites' one of the populations on whose experience standard natural fertility schedules are based. To reduce this bias' the proportion ~married. was adjusted to include all everom~rried women, single women who reported a birth, and a prorated number of single women eat risk" based on the proportion of married women reporting a birth, as shown In column (b) under percent married. in the table. This adjustment raised the percent married by about 7 percentage points for each observation; although this did not reduce the decline of about 5 percentage points in the proportion married among women 20-24 between 1960 and 1970, it did narrow the differences between 1970, 1976, and 1980. The increase in the proportion marr fed among women in older age categor ies ar ises f rom the addition of widowed, separated, and divorced women. Even with these adjustments, the ASMFas and total marital fertility rates for 1960 and 1970 are quite hiah - nearlv 9~3 for both dates. By 1976, total marital _, ~ fertility falls to 7.06, a decline of 24 percent, with a further decline of 9 percent to 6O44 in 1980* While total marital fertility shows little change between 1960 and 1970, the rate for women aged 20-24 increases. This occurs because the decline in the ASFR for that group is less than the decline In the proportion married, even after adjustment. The rate for women aged lSol9 is similarly affected since it was calculated as .75 of the rate of those aged 20024. Because these rates are so high, total marital fertility is very sensitive to such differences, which are as likely to be the result of differences in reporting (or editing, as suggested above ) as they are to be real. Thus considerable caution is required in interpreting the 1960-70 period. Access to public use sample files for the 1970 and 1976 data made it possible to tabulate the observed nether of births by marital status in the year prior to interviews; this provided a check on the rates calculated from ASFRs. Observed births were adjusted by the IF ratios used in ad j usting A5FRs for that date. The resulting ASMF" and total marital fertility rates are shown in the last column of Table 8. These rates are not

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39 exactly comparable to those calculated directly f rom ASFRs s ince the ad j us~ment of observed births used in deriving ASFRs also included a factor to account for the one-half-year dif ference between women' s reported age and their age when births actually occurred. Because it is inappropriate to apply this factor when the denominator is limited to ever-married women, the age prof files of ASHFRs differ with the two approaches. The main d~ffer- ence is that rates based on the tabulations are lower for women under 25 and higher for women over 30. Total mar- ital fertility is slightly lower in 1970 and virtually the same in 1976 in the tabulated results O compar ison of the two sets of rates suggests that the decline in mar- ital fertility probably was close to 24 percent over the 1970-76 period; however, there is a need to be cautious about both the level and age profile of marital fertility rates . The age category most seriously affected is 20-24. Two factors could account for an overstatement of the age-specific marital fertility rate for this group. One is the underreporting of married women discussed above. The other is that the adjustment factors derived using the Brass technique may be too hzgh for this group. Estimates of ASMFRs using model marital fertility schedules suggest that this may in fact be the case (see Berquo and Leite, 1979; Altmann and Wong, 1981a; Leite, 1981~. One way to visualize the extent of possible bias is to compare observed ASMFRs to model schedules, as shown in Figure 6. Both of the 1970 ASMFR schedules from Table 8 are plotted against these model schedules. The models are based on a total marital fertility rate of 9.25, with the Coale-Trussel index of fertility control set at three levels: 0.0, the natural fertility level, and O.3 and 0.S, indicating moderate fertility control. The model schedule with the index set at 0.5 provides a very close approximation to both of the observed 1970 ASMER schedules for ages 25-29 to 40-44. The observed rates for age 20-24 exceed the model schedule, though the second schedule (estimated from births reported for ~married. women, broadly defined) is closer than the rate calculated from dividing ASFRs by the proportion married. The compar ison suggests that the 1970 base for calcu- lating declines between 1970 and 1976 among the younger age groups may be too high, resulting in an exaggeration of declines for women in these age categor ies.

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49 Abor t ion Abortion is illegal in Brazil, and the Brazilian penal code carries a sanction of several years of imprisonment at hard labor for both abortionists and women who practice it (Milanesi, 1970:12-13). However, the code is rarely invoked, except as a legal ploy in such efforts as the attempt to block the importation and use of the IUD as an ~abortifacient. n A ~ rtion is believed to be widespread; rates of mortality and hospitalization resulting from abortion-related infections are high, though not well documented. There are no reliable statistical data on abortions at the national level in Brazil, though there are reported estimates (based on some rather implausible extrapola- tions from the experience of hospitals in a few locale i ties ) . According to these estimates, the annual number of abortions runs as high as three million per year, which would mean eight abortions for every ten live births (Rodrigues et al., lB75; Carvalho et al.' 1981). The hand evidence that does exist suggests that ~ or, urban, and noncontracepting women are more likely to resort to induced abortion, and that only a fraction of there women identify themselves when the question is asked in survey interviews. Martine ( 1975) suggests that another reason for low observed abortion rates is the high mortality rate among women having abortions who, as a consequence, would not be accounted for. Questions on abortion have been asked in a number of fertility surveys conducted in Brazil since the early 1960s, including the NIER and CPS; these provide a basis for calculation of the abortion index. The way the incidence of abortion is reported varies by survey. For purposes of calculating Bongsarts' index of the effect of abortion on fertility, the ideal would be the total induced abortion rate; thin is analogous to the total fertility rate and indicates the number of abortions a woman would have during her reproductive lifetime if current rates prevailed. Either annual age-specif~c abortion rates or the total number of abortions for women who have completed their reproductive life cycle could be used to calculate such a rate. Bows ever, samples are rarely large enough to give reliable estimates by the first method, and in only a few of the Brazilian studies are rates broken down by age. Varia- bility in measures affects both the numerators and denominators of rates. In some cases, numerators refer

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so to induced abortion, in others to all abortions (spontane. ous and induced); some numerators indicate the number of abortions, others the number of women ever having had an abortion. Denominators include the number of women of reproductive age (usually restricted to women in unions) and/or the total number of pregnancies reported by these women. Table 13 summarizes available statistical information on abortion in Brazil. Hutchinson's data on Rio de Janeiro in 1963 indicate that 9 percent of married women of reproductive age had experienced an abortion, while a 1965 REWRAP study of Sao Paulo reveals that 18 percent of pregnancies ended in abortions, about one-third of which were induced. Martine's data on poor women in Rio de Janeiro in 1969 suggest a substantially higher incidence of abortion amona low-income arouDs. _ Etges' study of three municipalities in Rio Grande do Sul in 1973 shows a higher rate of induced abortions as a percent of all pregnancies in Porto Alegre than in two smaller municioal° ities that he sampled. Questions on abortion have been included in all six of the CPSs for which tabulations are available. Women were asked how many abortions (spontane- ous and induced} they had experienced, and whether their last abortion was spontaneous or induced. The proportion of induced abortions in the ~978 Sao Paulo survey was much lower (closer to one ninth) than the one°third figure of ache 1965 Sao Paulo survey: this suggests (l) that induced abortion is underreported in the CPS data, and/or (2) that a higher level of contraceptive use in 1978 Nay have resulted in a substitution of contraception for abortion (Nakamura et ale, 1979:17). The proportion of women reporting having had an induced abortion was hither in urban areas of Sao Paulo. In other CPSs, the propor- tion of women reporting that they had ever had an abortion was higher in rural areas, but the proportion of preq- nancies ending in abortion was higher in urban areas. CPS abortion data have been tabulated by women's age; this permitted a rough approximation of the total abortion rate, which was calculated as the proportion of the difference between the total pregnancy rate and the total fertility rate that could be attributed to induced abortion. This difference averaged . S7 per woman in the Northeast, where the total fertility rate was 6. 3 per woman. If the reported 10-}5 percent share of induced abortion were accepted, the total abortion rate would be a very low .06 to .08 per woman; if all reported termina- tions of pregnancy were attributed to induced abortion,

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51 then the total induced abortion rate would be .57 per woman. Berquo {1980) has calculated total abortion rates for the nine localities included in the NIHR survey. These range from .068 abortions per woman in Santa Cruz-Urban in the state of Rio Grande do Sul to .735 in Parnaiba- Rural in the state of Piaui. There is no consistent rura1-urban pattern, though there is a suggestion that abortion rates are higher in larger cities and in poorer reg ions . I ~ is also pass ible to speculate on total abortion rates using CPS data on the proportion of pregnancies ending in abortion. In Salvador, Bahia, for example, assuming that one-third of reported abortions are induced and the total fer tility rate is about 4, the total induced abor tion rate would be about 0 2 per woman, for Bahia-RuraL, with a total fertility rate of 7, the total abortion rate is about the same. For Recife, calculation based on a total fer tility rate of 4 yields an abor tion rate of . 25 per woman, about half of the rate indicated in the NIHR data; this is again consistent with the interpretation that tl) the CPSs underreport abortion more than does the NIMR survey, and/or ( 2 ) increased contraceptive use is being substituted for abor tion. The Bongaarts index for measuring the effect of abortion on- the fertility rate is defined by the expression Ten C_ ~ ~ a ~ TFR ~ 0.4 {Lou) TAR _, where "u. is the parameter already estimated when calcu- lating the contraception rate. Ca becomes zero if all pregnant yes are abor ted, and is equal to 1 if all at e successful. In applying this index to recent Brazilian fertility trends, one can at best speculate on orders of magnitude suggested by these survey results for the total induced abor tion rate. There are several qualif ications to be noted here. First, it is very likely that the survey data presented above greatly understate the abor- tion rate. Second, in addition to showing the prevalence of abortion, war iation in 80ngsarts ' abortion index also reflects the level of fertility and of contraceptive use ( to the extent that both, in turn, are related to the potential number of pregnancies to be abor ted) . Thus abor tzon, contraception, and fertility must be balanced in any calculations. Finally, uncer tainty about the level of the abor tion rate also relates to the impact of

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52 - o U] _t N ·o C) L. U] o a 3 U] o o I' lo: ~ _ _ o' ~n ~ ~ CS: .. .. 1— ·e a ~ _ _ —_. O 0C V 5: · U' — _ · - ·. ·. U~ U~ U~ _ _ _ O O :' ~ ·-o ~r Ll Ld J ~ ~ v ~ m x: ~ ~ c o - ~5 o o U' 1 o r~ 3 n ·. ·— _ _ 0° E v a' Z ,. 3 y 2 Cl _ u' ~ ,n ~n ~o ~ ~ `xs ·....... E~ ~ U U U ·- a, co ~ a' o~ ~ ~4 ~ ~4 _. - · JJ ~ ~ a~ oo a' ,6 _ ~ ~ ~o Y ~ Q ~ ~ 2 e; ~ D; C' E- E~ ~ ~ ~ ~4 #~ a~ ~ a~ _ _ _ _ · · · · ~ —~ d _I _ 18 .o ~ (0 ~ 0 ~ :3 ~ ~ ~ :5 ~ ~ 0, _ - 4 _ _ _ 0~] C ~ ~ ~ 0 O ~ ~ ~ ~ ~ —~ ~ _ _ _ U O ~ U U c a~ c~ c c c ~ ~ ~ ~ ~ 0 0 ~ q~ t,O {Q C ~ ~ ~ ~ ~ ~r ~r ~ ~ ~ ~ ~r a' ~ c ~ ~ ~ c c I ~ I t I ~ _ I I . - -4 h4 ~ V ~ ~ ~ ~ U~ U~ U~ ~ U U ~ ~ t) m ~ ~ ~: 3 ~ ~ ~— ~: ~::~— C C 0 `4 ~ h4 ~a ~ ~ a, o, C ~ ~ a, ~ C C C C C ~ C C C C :: `` m`~` ~ ~ Ql :, · - ~ · ~ - ~ £ ~ ~ ~ ~ ~ ~ E ~ ~ ~ ~ ~ ~ ~ JJ O O O O O ~o ~ O O ~ L l~l Q ~ ~ ~ 3 o Q << ~ << `~` ~ o ~ ~ ~ o ~ ~ ~ o o ~ ~ ~ ’ ’ ~ ~ ~ 4J ~ ~ 4J' - ~ 4~ ~ 4 'C Ll ~ h4 ~ ~d ~o Ll ~ ~ )d O ~ ~ O =~ ~ 0 0 0 O ~ O n ~ 0 0 83 ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ Zi v U U -: U u~ U U ~: ~ ~ ·: ~ ~ ’ ~ Q ~ ~ ~ ~ ~ ~ ~ _1 A _~ —~ _~ ~ ~ —~ d e ~:~4 c c e C~ ~ A e ~ ~ ~ ~ ~ ~ ~ ’ ’ ’ ~ ~ ~ ~ -: ’ ’ ~c ~' 43 X . . ~ eo a~ a~ m. ~ ~ ~. 0 0 JJ ~ \0 10 ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ r~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ cr' ~ ~ ~ ~ cr, a ~ .- ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ r~ ~ u' ~ ~ C~ ~ ~ ~ ~ ~ ~ ~ ~ 0 u' ~p · · · · · · · · · ~ o o c ~ . . o ~ lom ~ - ~ ~ - ~ to ~ ~ ~ ~ ~ co cr ~ ~ ~ ~o ~ ~ ~ ~ ~ - :' ~n o cn - = o o ~ ~ ~ ~ ~ ~ ~ 1 ~ ~S - - ~ o ~ ~ ~ ~ - eQ ~ ~ ~ ~ 3 ~ ~ ~ ~ ~ ~ ~ o ~ 3 ~ ~ ~ ~— V o o o o ~ o X o o o o tn a: u: ~ Pt O0 ~ tn ~n ~ P S: ~ e A ~ ~ 0 L~ ~ h4 ~ ~: 1 1 1 1 O O O O 0 Z ~ Z Z ~ O O O O _ tO ~ ~a I iV '~ C C 1 _ _ C, C, ~ V :3 :, O O O O _ _—~ _— _ P4 ~ ~ o: ~ ~

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53 be:] D ~ "a D D a' a, En EN En ~ En he ae ·e ~ ·- oe D D D. D S: D ~ ID ~ (D ~ ~ o`m mm mm _ _ _ _ _ _ _ _ _ _ _ _ ~ ~ ~ ~ ~ ~ c ~ ~ ~ ~ ~ D D ~ D 0 E~ E~ E E 4J ~ ~ ~ 4J ~ ~ ~ ~ ~ ~ - 4 ~ ~ ~ ~ ~ m0' ~ ~ o`m 0 al ~ ~o ~ ~ ~ ~ ~ ~o ~ o9 ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ 0 ~ ~ ~ ~ ~ 0 0 —————— 3 :~ ~ :~ ~ ~ 3 ~ :~ :~ :~ ~ m. mm mm m. mm - m O O O O O O _ ~ _ _ _ ~ _— ~ —_ :, _ :, :~ :, :, ~o ~ ~ ~o = - ~ ~ ~ ~ =~= ~ ~ ~ ~ ~ O ~ Q ~ ~ ~: ~ ~ P a: a: ~ ~ c:: ~ ~ ~ m m m ~ ~ ~ ~ ~ ~ q, - - - 4 ~ ~ ~ ~1 D n ~ ~ D ~ ~ 41 ~ ~ 41 E~ ~ E E" E~ ~ ~ e~ ·e == D 3 D ~ —~ _1 ~ _1 ~ ~ _ a~ - ~D ~ ~ a, ~ ~ ~ ~ - - ~ ~ o' ~ Ch ~ ~ ~ ~ ~ ~ ~ 0 ~D D E~ ~ E~ o' _ _ _ O O O :, q, mm ~ 4~ ~ 4 ~ ~ ~ ~ ~ OQ ~ ~ ~ ~ ~ ~ C t:: C C: ~ C ~ C ~ - ~r ~ ~ ~ ~ - ~ - ~ ~ ~ 0 0 0 0 ~ 0 0 0 0 1 1 1 _ _ _ 1 1 1 _ ~ _. _ _ _ _ —_. _ _ — U~ U~ ~ U U U ~ U~= U U U C C C ~ ~ ~ C: C C ~ ~o ~ ~ ~ ~ 0 a 0 C, 0 a 0 0 0 c c e ~ c e c e c c e c~ ~ D~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ m O O 0 4 ~ ~ O O O ~ ~ ~ =~= ~ == ~= ~ :~ ~ 04 ~ ~ ~ ~ ~ ~ D' p. `~` `~` U U U ~ U ~ U · e ~ O e e ~ e e e ~ e :~ ~ :~ ~ ~ ~ :~ ~ dJ ~ ~ ~ ~ dJ ~ ~ ^) ~ q:~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ 4 ~ 4 ~ ~ ~ ~ ~ hd ~ t: ~ C ~ e ~ e ~ c g ~ ~ ~ ~ g g h ~ ~ ~ ~ _~ _~ —~ A _I ~ _1 _1 ~ _~ _I _~ ~ V ~ ~ ~ JJ ~ ~ ~ ~ ~ ~ e ~C ~C e ~ E°~ e° ~° ~ ~° ~ r. ~o 0 ~o r~ ~ ~ c~ ~ 0 ~ ~ ~ ~ · e 0 0 ~ e e ~ e e e e e e e e O e O 0 - 1 Y, ~ ~ ~ O— ~ I ~ ~ c~ ~ 4~ ~ EO. ~ ~o \0 C~ `0 e ~ e O o O o O O O O O O O O ~ U1 u~ ~n u~ u~ ~ u (D ~ ~ ~ ~ ~ ~ ~ ~ ~ r. ~ ~ ~ ~ r. 0101 0\ °\ 01 ~ mm 01 ~ ~ ~ ~ 01 CR ~ ~ 0 _1 ~ ~ ~ _t e c Q 9 64 Ll :D :D ~ 64 _ ~ ~ _ U ,` Le 0= U O U D De C P P _ ~ _ ~Q ~ ~ _ ~ ~ o0 U) ~ ~ _ _ ~ ~ _ _ .. .. S:: C — U, ~ — ~ ~ C~ — _ _ Q 9 ’: ~ 41 ~ ~ ~ us ~ ~ ~ ~ ~ an ~ e :'—~ `:— ,, O ~ 0 a ,5~ ~ ,,, Ll ~ O c .e ~ ~ :' U U U—~ ~C ~ _. S ~ ~ ~ :3 1 C ~ O— ~ 1 :' ~ :, ~ ~ ~ ~ 4` :' ~ ~ ~ ~ _ i~ 5m °= mO' ~ 8 ou ° ° I —~ == ~o ~ ~ ~ ~ ~ ~ W ~ ~ ~ ~ C ~ C— —— ~— ~ ~ ~ ~ ~ U 3 C f:: S~ ~ S C U C ~ O ~ U dJ ~ ~ 43 ~ ~ ~ 41 ~ ~ ~ ~ 18 ~ d. O o.P. ~m mm mm—o ma~ mm ~o o.P.

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54 nonmarriage. It is one thing to assume that most births accrue to women in unions; it is quite another to assume that all pregnancies, particularly those that are aborted, are within unions. In all likelihood, a significant fraction of abortions may be experienced by women who are not in unions. To the extent that these abortions are understated, the estimate of nonmarriage may be over- stated. FOE illustrative purposes, a range for the total abortion rate of 0.5 to 1.5 per women may be assumed. With an estimated 1976 fatal fertility rate of 4.4, yielding about 3.75 million births in Brazil, a range estimate of between 500, 000 and 1, 2SO, 000 annual induced abortions is implied. While these figures fall well below the 3 million annual abortions derived by extrapolation from newspaper and other reports, they seem more plaus- ible than the very low abortion rates yielded by survey data. Breastfeedinq/Postpart~m Amenorrhea Statistical data on breastfeeding and postpartum amenor- rhea in Brazil are also quite deficient. Questions on breastfeeding were included only in more recent inquiries ~ the NIBR and CPSO However, the data are more consistent for the purpose of calculating Bongaarts' index of the effect of postpartum infecundibility on fertility than was the case with abortion. Mean or median months of breastfeeding are provided in reports on the NIBR and CPS by Anderson et al. (1981) and Berquo (1980}, as shown in Table 14. Calculation of the Bongsarts index requires a transformation of mean or median months of breastfeeding to months of postpartum amenorrhea, which i s the ~ i. in the formula for the index: Ca ~ 20/18 . ~ ~ i. Anderson calculated i for Bahia, Pernambuco, Rio Grande do Nor te, and Paraiba using the Lesthaege-Page model schedules, and a formula based on this schedule was used to transform the remaining observations. While not representative of the entire Brazilian population, the data in Table 14 do span a broad enough spectrum of experience, from poorer Northeastern areas to the industrialized Southeast and the more developed rural areas of the South, to permit speculation about a plau- sible national-level index. The index values in the table, as well as the breastfeeding data on which they are based, show that the practice of breastfeeding is

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55 TABLE 14 Reported Breastfeeding, Su~ary of Survey Data: Brazil Plonthe of Breset- feeding Monthe of A~nor- rhea Index S ite of Survey Date Meen ~dian Median Ci . Sao Paulo~Urban 1978 < 1 20 0 .97 Sao Paulo~Rural 1978 7O. dO. .87 Pinui, Teresina 1979 3 0 3 2 0 7 0 94 Pieui- - st 1979 901 So3 ·84 Bahia p Salvador 1980 ~O 8 ~ ~ 2 ~ 9 . 93 Bahia-Rest 1980 9. ~ 3 0 B 4.0 .89 Paraibe-Urban 1980 4.7 <1 2. ~ .96 Paraiba-}tural 1980 5.5 10 8 3 0 2 . 92 Pern~-huco, Recife 1980 3O7 <1 2.2 .97 Pernambucs - Rest l9BO ~O ~ < 1 2 01 . 9? Rio Grande do tiorte-Urban 1980 4.2 <1 205 .95 Rio Grande do Norte-Rural 1980 5.0 <1 2.8 .g. Cachoeira-Urban (ES) 1975 8.5 5.0 .85 Santa Cruz-Urban (~;S1 1975 4.2 3OO O93 Santa Cruz-Rural (RGS) 1975 S.5 3.6 .9a Sao Jose-Urban (SP) 1975 6.0 3.8 .90 Sertaosin~Rural (SP) 1975 7.3 4. ~ .87 Recife-Urban (PB) 197S 3.3 20 7 .94 Conceicso A.-Rural (PA) 1975 8.5 5.0 .85 Parnaiba-Urban (P$) 1975 4.8 3.3 .92 Parnaiba-Rural (PI) 1975 603 3O9 .89 Sources: 1975 data froa Berquo (1980sTa:bl. II) S all otb'ar data fro. Anderson et a1. (1981:Table 5J. very lin~ited. Indeed, Brazil falls at the very low end of the spectrum of <:ountries for which breastfeeding data are available, including Latin American countries, which have low rates compared to other regions of the world (Kent, 1981~. The index values range from .84 to .97, with lower values (higher breastfeeding ~ in rural areas and higher values in the cities. Values are also higher in areas in which contraceptive use is higher, suggesting that the practice of breastfeeding decreases as contracep- tive use increases. These values are much more co~ar able to tho~e of o~er industtsalized countries than to those of developing countries' they are high even in comparison with other Latin American countries that also have higher values in comparison with other developing regions. ~For purposes of computing an index of postpartum infecundabili~cy at the national level, an initial 1970 level of 4 month e was assumed. Since there is evidence

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~6 to suggest that increased contraceptive use leads to a decrease in breastfeeding, the assumption was reduced to 3.5 months in 1976 and 3 months in 1980 in the national- level estimates of proximate determinants that follow. A Speculative Overview of Trends in the Proximate Determinants of Total Fertility Rates, 1970-80 Table 15 links estimates of the total fertility rate to the total fecundity rate (assumed to be 15.3 births per woman) ~ using the evidence on contraception, abortion, and postpartum amenorrhea presented in the previous three sections on Bongsarts' indices for each of these proximate determinants It also incorporates the information on marriage rates discussed earlier in this chapter. Two variants are preseOnted for each of the three observation points: one assumes the lower value in ache range of estimates of the total abortion rate, with higher levels of contraceptive use (lower levels of the index of non- contraception); the other assumes lower contraceptive TABLE 15 Estimates of Proximate Determinants of Total Fertility Rate, 1970-80: Braz il 1970 1976 1980 Measure and variant A B A B A B Assumptione Percent users (U) 0032 0.25 0.47 0.~l 0052 Oe`46 Effectiveness (E) 0 0 80 0 0 80 0.86 0.86 0.88 0.88 Sterilization factor lelO loll 1~125 1~125 10125 1~125 Months of infecundity 4~0 4.0 3.5 3.S 3~0 3.0 Tom abortion rate 0.5 1.5 0.5 1.5 0.5 1.5 Besultea Total fecundity rate 15.3 15.3 15.3 15.3 15.3 15.3 Infecundity index ~ .89 0.89 0.91 0.91 0. 93 0 0 93 Natural Bar ital fertility 13 0 6 13. 6 13 0 9 13. 9 14 . 2 14. 2 Abortion index Q. 96 0.88 0.94 0.84 0 O 93 0.82 Contraception fertility 0.72 0.78 0.54 0.60 0.49 0~55 Total ~aarital fertility 9.34 9. 39 7 e 04 7 0 03 6 ~ 42 Be 42 Non~rriage index 0.63 0.63 0.63 0.63 0.64 0.64 Total Fertility Rate 5.89 5.92 4.43 ~ . 43 4.11 4.11 aData in se<:ond panel have been rounded s total fertility rate based on data before rounding.

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57 use, and the higher estimate of the total abortion rate. This is only one of several tradeoffs that a range of values in the abortion rate implies. Higher abortion rates could also imply less effective contraception, as well as ~ lower impact of nonmar r iage to the extent that abortions are used to terminate the pregnancies of women outside of unions. The underlying assumptions are summarized in the first panel of the table. The contraceptive use and effective ness rates in van iant #A. are based on Table 12 0 The reduction in the contraceptive use rate in variant ABE is proportional to the increase in the abortion index implied by the higher total abortion rate. Both variants assume that there is a decline in postpartum infecundity of about 0.5 months from 1970 to 1976 that relates to increased contraceptive use, with a similar decline for 1976 to 1980. No change is assumed between 1970 and 1976 in the index of nonmarriage, which is consistent with the observed trend for that period, while a small increase is shown for 19800 In variant ~A., the main factor accounting for the decline in the total fertility rate from its level of around 5.9 in 1970 to 4.4 in 1976 is the decrease in Cc; this reflects increased contraceptive use, as well as increased effectiveness deriving from a higher propor- tion of more effective methods (the pill and steriliza- tion) among those used. To the extent that variant ~A. understates the abortion rate, this conclusion should be modified by assuming a smaller increase in contraceptive use, less improvement in contraceptive effectiveness, or a lower level of nonmarriage. variant ABE illustrates the first of these possibilities. Extrapolating to 198G, the table suggests that the pace of the decline in total fertility could be slower in the last half of the decade. This is partly a result of using levels of Cc in 1976 large enough to account for the 1970-76 decline, combined with Cc values for 1980 that are consistent with the survey results reported in Table 11. Variant ABE suggests an even slower decline in Cc, assuming that abortions played a greater role in the decline in total fertility than is implied in variant ~A. ~ It is worth noting that special tabulations of the 1977 and 1978 PNAI) survey data in fact suggest a slowing of the pace of the decline of total fertility (l~eite, 1981). An alternative hypothesis is that flange in the design of the 1976 survey produced an overstatement of the decline, a point that will prove difficult to test

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58 until data for making alternative estimates of fertility during the decade become available (ye., 1980 census data, for which the own-children method could be applied). CONCLUSIONS . The 1970s brought a significant acceleration in the decline of fertility in Brazil: the crude birth rate fell from 41 per 1~000 in the late 1960s to 34 per 1,000 in the late 1970s, the total fertility rate, a more refined measure of fertility, declined from around 508 births per l,OOO women around 1970 to around 404 births by 1976. Of the three demographic factors that could account for a decline in the birth rate (proportions married, age structure, and marital fertility), declining marital fertility was clearly responsible for the change. Assessment of the effect of nuptiality on fertility is complicated by the questionable reliability of reported marital status in the availat~le census and survey data. A number of factors suggest that the proportion of younger women (up to age 25) reported as married has been under- stated. Doubts about the proportions married remain even after adjustments to include single women reporting births and separated women who might have entered into a second union and did not report it because divorce was not legally recognized. The whole question of pregnancies to women not in unions and the termination of such preg- nancies remains a major area of doubt in examining the prox ~ te determinants of Brazil's fertility decline. Calculations of the singulate mean age at marriage (SMAM) from census and survey data indicate a rise of about 0.8 years in the mean age at marriage between 1960 and 1970, and about half that from 1970 to 1976. An alternative measure of Me age at which women begin being exposed to the risk of childbearing, the singulate mean age at first birth, reveals a similar trend. Even after adjustment of the marital status data to account for possible undero reporting of the proportions married among women in their early twenties, there is little evidence of change between 1970 and 1976; this suggests that changes in marital status had only a limited effect on fertility decline during that interval. Because of the demographic echo of increased births in the l9SOs and 1960s, the age structure of the Brazilian population had a slightly positive impact on birth rates.

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59 Thus, on the basis of an admittedly speculative recon- s traction of What could have happened. when Brazil' s accelerated fertility decline is decomposed into demo- graphic components and into the proximate determinants of fertility, it can be concluded that a decline in marital fertility was the primary factor responsible. This decline in marital fertility can in turn be traced to an increased use of effective contraception, combined with an indeterminate abortion component both within and outside of marriage. Though national-level data on the proximate variables are lacking, survey data can be used to construct a nat$onal-level index of noncontraception, which declined from . 72-0 78 in 1970 to . 54-. 60 in 1976 and ·49.O55 in 1980, suggesting that increased contracep~ tion played a major role in the decline. Survey data also indicate a very low prevalence of breastfeeding, and suggest a moderate attenuation of the fertility-reducing effect of postpartum amenorrhea as contraception increased. The major unknown variable is abortion. The more one accepts the f ragments of evidence that abortion is widespread in Brazil, particularly among low~income g roups, the more one must ad just the importance attached to increased contraception and no change in marriage r ates. Finally, it should be emphasized that doubts remain about the reliability of data on marital status, particle larly since a significant number of pregnancies mung women not in unions may be terminated by abortion, and informal unions may be formalized only after a live birth. Census and survey data on the proportion of women in unions may therefore reflect after-the-fact social adjust- ment processes more than ache exact demographic accounting needed to decompose the proximate determinants of fertility.