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Demographic Change in Sub-Saharan Africa (1993)

Chapter: 6 Adult Mortality

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Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
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6
Adult Mortality

Ian M.Timœus

INTRODUCTION

The aim of this chapter is to provide a largely descriptive account of levels, trends, and patterns of adult mortality in sub-Saharan Africa. A very incomplete picture emerges. Both the coverage and the accuracy of the data on which the chapter draws are far more limited than those for other components of African population dynamics such as child mortality or fertility. No data at all exist for most of the population of the region, and representative information on causes of death in adulthood is available from only a handful of studies of relatively small populations. Furthermore, very little information about the effect of the AIDS epidemic on national populations is yet available.

The shortage of data on adult mortality in sub-Saharan Africa largely reflects the inadequacy of vital registration systems, combined with the technical limitations of the methods that can be used to investigate the subject retrospectively (Timæus, 1991a). In addition, a substantial proportion of what we know about the demography of Africa derives from fertility surveys or from longitudinal studies mounted to investigate child health. Both types of inquiry usually cover too small a sample to be used to mea-

Ian Timæus is at the Centre for Population Studies, London School of Hygiene and Tropical Medicine

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

sure adult mortality directly, and many of them have failed to collect data that can be used to estimate adult mortality indirectly.

Adults tend to die of different diseases from children, and evidence has accumulated that neither the level of—nor the trend in—adult mortality is closely associated with child mortality (Murray et al., 1992). Thus, it is necessary to investigate adult mortality in Africa to provide a sound basis for the population estimates and projections that underlie planning in any sector. Evidence that adult mortality has stagnated at a high level in some countries (e.g., Timæus, 1984) further suggests that adult ill health is not an issue that can be left to look after itself. Equity and efficiency in health planning require consideration of the health problems of the poor throughout their lives.

Against this background, this chapter attempts, to examine adult mortality in sub-Saharan Africa and the extent of the public health problem that such mortality poses. Given the limited knowledge of the subject, three questions seem of central interest. First, how does adult mortality in sub-Saharan Africa compare with other continents? Second, how does the mortality of adults compare with that of children? Third, are there distinctive variations in adult mortality patterns across Africa that raise issues for further investigation?

SOURCES OF DATA

The difficulties involved in measuring adult mortality in developing countries and the deficiencies of the data available on sub-Saharan Africa are well known to most demographers. The only mainland country south of the Sahara that has a civil registration system with sufficient deaths reported for it to be possible to use the national data to estimate adult mortality is South Africa. Even in this country the statistics exclude the four nominally independent “homelands” and are incomplete (though amenable to adjustment) for that part of the rest of the population that is not “White.”1 Although registration of adult deaths is more complete locally, particularly in some major cities, few such data have been published. Thus, nearly all of the estimates of adult mortality that can be made for sub-Saharan Africa derive from census or survey data.

Useful information can be culled from a variety of sources, including national censuses, the Population Growth Estimation surveys of the early 1970s, the World Fertility Surveys (WFS), and the Demographic and Health Surveys (DHS), as well as other inquiries mounted by the statistical organi-

1  

“White,” “Colored,” “Asian,” and “Black” are legal statuses defined in South African apartheid legislation and used in South African official statistics.

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

zations of particular countries. Unfortunately, there has been little growth in the availability of reasonably up-to-date information on adult mortality in sub-Saharan Africa during the last 15 years. Information from the 1980 round of censuses and from Phase I of the DHS is available for about the same number of countries as from the 1970 round of censuses and the WFS. Moreover, although the core questionnaire for Phase I of the DHS program included pertinent questions about survival of parents, these have been left out of the Phase II questionnaire. Similarly, a few countries that collected data about adult mortality in their 1980-round census failed to do so in their 1990-round census. Such decisions not to build on earlier efforts are regrettable. Even if the data on adult mortality obtained in an initial inquiry proved difficult to interpret, those on orphanhood, in particular, become much more useful once they have been collected repeatedly.

A second limitation of the available information is that even in those countries that collect adult mortality data in their censuses, processing and publication of the results often take an inordinate length of time. Almost no information is available from the 1990 round of censuses at present, and some data collected in the 1980 round of censuses, including the orphanhood data from the 1985 census of Sierra Leone and 1986 census of Lesotho, could not be obtained for this study. Thus, although data have been collected to update—by a decade—many of the estimates presented here for the mid-1970s, it may be impossible to do the actual updating for several more years.

Lack of data means that it is impossible to arrive at well-founded national estimates of adult mortality in many countries for any point during the 1970s or 1980s. All the different forms of information that can be used to measure adult mortality were considered during the preparation of this chapter, and some of the estimates presented are based on very inadequate data. Even with this catholic approach, the results cover only 24 countries and exclude several populous nations such as Nigeria, Ethiopia, and Zaire. In total, they refer to only about 40 percent of sub-Saharan Africa’s population.

METHODS OF ANALYSIS

The methods that can be used to estimate adult mortality in the absence of adequate vital registration have been reviewed in detail recently (Timæus, 1991a) and are discussed only briefly here. Examples illustrating these methods are supplied in the appendix to this chapter.

The main source of direct estimates is retrospective questions about recent deaths in the household posed in censuses and single-round surveys. Such data are the primary source of information used to produce estimates for nine of the countries listed in Table 6–1: Mali, Togo, Cameroon, Congo,

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

Madagascar, Rwanda, Tanzania, Botswana, and Lesotho. Such questions have been included in many more national inquiries, but the results have frequently been disappointing. Often it is manifest that only a small minority of deaths have been reported. The data appear complete in only a few instances. Nevertheless, a range of techniques exists that can be used to assess such data and, in favorable circumstances, to adjust them for underreporting. The crucial assumption is that the degree of underreporting is the same at all adult ages. Of these techniques, those proposed by Brass (1975), Preston et al. (1980), and Bennett and Horiuchi (1981) were used to evaluate the data presented in this chapter. On this basis, reporting is taken as complete in six countries.2 In Mali, only about half the deaths, and in Togo slightly more than half, were reported. In Congo, only about one-third of men’s deaths and one-fifth of women’s deaths seem to have been reported.

A second source of direct estimates of adult mortality is the multiround demographic surveys that have been conducted in several sub-Saharan countries. The results of many of these studies are now rather out-of-date, but they are the main sources used for three of the countries in Table 6–1—Côte d’Ivoire, Liberia, and Senegal. In all three, reporting has been accepted as complete.3

An additional source of adult mortality estimates for Africa is the information obtained from retrospective questions about the survival of respondents’ mothers, fathers (Brass and Hill, 1973), and spouses (Hill, 1977). Information on orphanhood has been collected more frequently than that on widowhood and has usually yielded better results. The estimates that result are somewhat out-of-date and, like direct estimates, can be biased by reporting errors. Such data are the primary basis for the remaining 11 sets of national estimates presented here (Benin, The Gambia, Ghana, Mauritania, Sierra Leone, Burundi, Kenya, Malawi, northern Sudan, Zimbabwe, and Swaziland) and provide important support for estimates based on recent deaths in five other countries, namely, Mali, Cameroon, Congo, Tanzania, and Lesotho. The basic orphanhood estimates were calculated by using the variant of the method proposed by Timæus (1992). Brass and Bamgboye’s (1981) method was used to determine the time reference of the results.

2  

Some of these data exhibit signs of having been adjusted already, without it being documented in the sources from which they were obtained for this study.

3  

Only summary measures of e15—the number of years that a person who survives to age 15 can expect to live—have been published for Senegal, so reevaluation of the data was impossible and 45p15—the probability of surviving from exact age 15 to exact age 60—had to be inferred from a model life table. It has been suggested that, if anything, the level of adult mortality is overstated (Cantrelle et al., 1986). In Côte d’Ivoire, the original survey study (Ahonzo et al., 1984) concluded that the reports of adult deaths were incomplete. My reevaluation of the results leads to a different conclusion.

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

TABLE 6–1 Survivorship from Age 15 to Age 60 by Sex, 1970s and 1980s

 

45P15

 

Region and Country

Date

Males

Females

Both Sexes

Reliability

Source

Western

 

Benin

1978

.749

.779

.764

Very low

Orphanhood

Côte d’Ivoire

1978–1979

.646

.741

.694

Fair

Multiround survey

The Gambia

1978

.773

.812

.793

Fair

Intercensal orphanhood

Ghana

1982

.778

.880

.830

Low

Orphanhood since marriage

Liberia

1970–1971

.550

.584

.567

Fair

Multiround survey

Mali

1986

.579

.541

.560

Low

Recent deaths and orphanhood

Mauritania

1980

.782

.823

.803

Fair

Orphanhood and recent deaths

Senegal

1978

.652

.710

.682

Fair

Multiround surveys

Sierra Leone

1974

.466

.510

.488

Very low

Orphanhood

Togo

1981

.704

.760

.733

Very low

Recent deaths

Middle

 

Cameroon

1976

.644

.666

.654

Low

Recent deaths and orphanhood

Congo

1984

.656

.703

.680

Very low

Recent deaths and orphanhood

Eastern

 

Burundi

1981

.622

.699

.661

Low

Orphanhood since marriage

Kenya

1974

.714

.769

.742

Fair

Intercensal orphanhood

Madagascar

1974–1975

.487

.551

.518

Very low

Recent deaths

Malawi

1977

.741

.706

.723

Low

Intersurvey orphanhood

Rwanda

1978

.584

.629

.607

Low

Recent deaths

Tanzania

1988

.656

.675

.666

Very low

Recent deaths and orphanhood

Zimbabwe

1978

.801

.863

.833

Very low

Orphanhood

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

Southern

 

Botswana

1980

.555

.732

.646

Low

Recent deaths

Lesotho

1976

.503

.749

.627

Fair

Recent deaths and orphanhood

South Africa

1985

.638

.766

.702

Fair

Vital registration

Swaziland

1981

.561

.761

.663

Fair

Intercensal orphanhood

Northern

 

Sudan (northern)

1975

.695

.768

.732

Fair

Orphanhood and widowhood

 

SOURCES: Data from Benin (Benin, n.d.); Côte d’Ivoire (Ahonzo et al., 1984); The Gambia (Blacker and Mukiza-Gapere, 1988); Ghana and Senegal (Timæus, 1991d); Liberia, Madagascar and Rwanda (Waltisperger and Rabetsitonta, 1988b); Mali (Mali, 1980 and provisional 1987 census tables); Mauritania (Timæus, 1987); Sierra Leone (Okoye, 1980); Togo (Togo, 1985); Cameroon (Cameroon, 1978, 1983); Congo (Congo, 1978, 1987); Burundi (Timæus, 1991c); Kenya (Mukiza-Gapere, 1989); Malawi (Timæus, 1991b); northern Sudan (Sudan, 1982); Tanzania (Tanzania, 1982 and provisional 1988 census tables); Zimbabwe (Zimbabwe, 1985); Botswana (Botswana, 1972, 1983); Lesotho (Timæus, 1984); South Africa (South Africa, 1988); Swaziland (Swaziland, 1980 and unpublished 1986 census tables).

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

In countries where more than one set of orphanhood data exists, it is possible to calculate more recent and reliable estimates by basing them on changes in orphanhood in adulthood between two inquiries (Timæus, 1991b). This approach was adopted in four countries: The Gambia, Kenya, Malawi, and Swaziland. In addition, several recent DHS surveys have asked whether deceased parents died before or after the respondent married. This information can also be used to produce more recent and reliable results than are obtained from the basic orphanhood method (Timæus, 1991c). The technique was used to produce the estimates for Ghana and Burundi, and to confirm the results of the multiround surveys in Senegal.

One set of techniques for estimating adult mortality that could not be used to produce any estimates represents those based on intercensal survival and growth. In an attempt to increase the scope of the results, the integrated intercensal growth method (Preston, 1983) was applied to data from several countries. It yielded very erratic and implausible results. As one might expect, poor age reporting, high levels of international migration, and changes in census coverage combine to render such techniques useless in most African countries.

Estimating adult mortality from African data involves a large element of judgment. Most of the results presented are based on data that have been subjected to some form of smoothing and adjustment. Decisions not to adjust certain data are to some extent arbitrary.4 Moreover, on the principle that estimates that are largely guesses are to be preferred to those that are complete guesses, results have been presented even for countries where the data are very difficult to interpret. Thus, none of the results is definitely accurate. The estimates obtained from the registration data for South Africa, multiround surveys, and several different sources of data that yield reasonably consistent results are assumed to be fairly reliable. The estimates are judged of low reliability in countries where different sources of data yield less consistent results; where only a single set of recent data on deaths exists, but it appears reasonably complete; or where the partitioning of the data on orphanhood into deaths before and after the respondent’s marriage provides a partial check on the results. Finally, the reliability of the estimates for countries in which only a single set of incomplete recent death data or orphanhood data is available must be considered very low. This category of estimates also includes those for Congo and Tanzania. Several sources of data exist for these two countries, but they yield inconsistent results and are difficult to interpret.

4  

The mortality rates obtained from direct data on adult deaths were smoothed by fitting a two-parameter logit model life table based on the general standard (Brass, 1971) to observed survivorship from age 15. Time series of indirect estimates were smoothed by fitting regression lines, excluding any obviously discrepant points for extreme age groups.

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

ADULT MORTALITY LEVELS

Estimates of adult mortality in the 24 countries for which information is available are shown in Table 6–1. Only data for 1970 or later are presented and the figures are the most recent available. Four of the estimates refer to the first half of the 1970s, ten to the late 1970s, and ten to the 1980s. The index presented is life table survivorship from exact age 15 years to exact age 60 years (45p15). It can be interpreted as the probability of surviving to old age, subject to surviving childhood, at the prevailing level of mortality. Unlike measures of life expectancy, survivorship from 15 to 60 years can be calculated without making assumptions about old-age mortality. It is the complement of the probability of dying between ages 15 and 60 (45q15), which has been adopted in a recent World Bank volume as the preferred index of adult mortality (Feachem et al., 1992).

Perhaps the most striking feature of the results shown in Table 6–1 is that large differences exist in the level of adult mortality between different African countries. These estimates suggest that in Benin and The Gambia, more than 75 percent of those aged 15 would survive to their 60th birthday at the levels of mortality prevailing around 1980. In Ghana, Mauritania, and Zimbabwe, the equivalent figure is more than 80 percent. These figures represent moderate adult mortality by world standards. For example, survivorship from 15 to 60 years in Sri Lanka or in Trinidad and Tobago is similar to that in these lower-mortality countries of sub-Saharan Africa. Moreover, adult male survivorship is much lower in several East European countries. The apparently low level of adult mortality in these countries is somewhat surprising. Although it is possible that the orphanhood method has produced underestimates of adult mortality in all of these countries, the results for The Gambia, at least (see appendix), and Ghana (Timaeus, 1991d) exhibit a high degree of internal consistency. In Zimbabwe, adjusted registration data for Harare yield an estimate of adult survivorship for 1982–1986 that is almost identical to that in Table 6–1 (Moyo, 1991). Thus, the national estimate of survivorship may be somewhat too high but is unlikely to be grossly inaccurate.

In contrast, in many African countries for which we have data, adult mortality is high. The estimated probability of surviving from age 15 to age 60 falls to less than 70 percent in half of these countries, and to less than 60 percent in Liberia, Sierra Leone, Mali, and Madagascar. Except in Mali, the highest estimates refer to the 1970s. They seem plausible: Some intensive, longitudinal studies of rural populations in Africa have documented even more severe levels of adult mortality. For example, in Bandafassi, Senegal, the probability of dying between 15 and 60 years of age still exceeded 50 percent during the 1970s (Pison and Langaney, 1985). Such elevated levels of adult mortality have been eliminated in most other parts

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

of the world since the Second World War. World Bank estimates suggest that outside sub-Saharan Africa, 45q15 exceeds 30 percent in only nine countries (Feachem et al., 1992). In few, if any, countries outside sub-Saharan Africa is 45q15 as high as 40 percent.

These estimates of adult mortality do not follow an obvious regional pattern. Hill (1991) and Blacker (1991) suggest that child mortality is higher in western than eastern Africa. An earlier study, based on fewer countries, suggested that this differential was also true of adult mortality (Timæus, 1991e). However, the estimates in Table 6–1, apart from those for the four southern African countries, which form a fairly homogeneous group, suggest that high adult mortality and low adult mortality are to be found on both the western and the eastern sides of the continent. This change in interpretation reflects, in part, differing definitions of the regions used and, in part, incorporation into the analysis of additional data that support a gloomier view of eastern African mortality. In addition, evidence presented later in this chapter suggests that the disappearance of this broad geographical contrast to some extent reflects differential mortality trends: The estimates presented here are centered on the late 1970s, about six years later than those in the earlier study.

Gender Differentials

There are extensive data indicating that gender differentials in child mortality in sub-Saharan Africa are small but usually favor girls slightly (e.g., Rutstein, 1984). Less is known about gender differentials in adult mortality. The subject is of particular interest because of the high maternal mortality that has been documented recently in many parts of the continent (Graham, 1991). Figure 6–1 compares the male and female estimates from Table 6–1.

Given the range of different data sources and methods used to make these estimates, the results are remarkably consistent.5 They suggest that female survivorship in adulthood is slightly higher than male survivorship in most of sub-Saharan Africa. In the majority of this sample of countries, the gender differential in adult mortality is similar to that found in most other parts of the developing world and in the United Nations’ (1982a) Latin American and general families of model life tables and the four families of Princeton model life tables (Coale and Demeny, 1983).

Only in two countries is there any evidence of excess female adult

5  

When making the estimates, I attempted to consider each set of data for men and women on its own merits and not to look for patterns in the results until they were all available. Despite this precaution, my preconceptions have probably influenced somewhat the results shown in Figure 6–1.

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

FIGURE 6–1 Gender differentials in survivorship from age 15 to age 60. SOURCE: Table 1.

mortality. The country with higher mortality is Mali. The estimates used here are based on census reports of recent deaths, and it is possible that the adjustments made for underreporting have led to the overestimation of female mortality. Orphanhood data collected at the same time suggest a more usual gender differential in adult mortality in Mali. The other country that apparently has excess female mortality in adulthood is Malawi. There is stronger evidence that this country is genuinely anomalous because both the results of the 1970–1971 multiround survey and the more recent orphanhood estimates shown in Table 6–1 support this conclusion.

The four southern African countries included in Figure 6–1 stand out as having high mortality among adult men. The differential is somewhat attenuated in South Africa due to the more usual mortality patterns among the “White” population. Among the “Black” majority, however, the differential between male and female mortality is as large as in Swaziland or Botswana. These southern African countries are exceptional, not just within sub-Saharan Africa, but compared with the rest of the world. The absolute difference between adult male and female death rates in Lesotho is probably larger than in any other national population. The high mortality of adult men in southern Africa is almost certainly related to the importance of labor migration, particularly to the mines, in the economy of this part of the continent. Mining is in itself a hazardous occupation; the lifestyle associated with prolonged absences from home encourages heavy smoking and drinking; and the region suffers from an “epidemic” of tuberculosis that originated in the mining industry (Packard, 1990).

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

FIGURE 6–2 Survivorship in childhood and adulthood. SOURCES: Sources cited in footnote 6.

Age Patterns of Mortality

Figure 6–2 compares the estimates of adult survivorship from Table 6–1 with corresponding estimates of the probability of surviving to age 5, l(5).6 In many sub-Saharan African countries the relationship between the overall levels of child and adult mortality falls within the range of experience of the developed world during its mortality transition as encapsulated in the Coale and Demeny (1983) regional model life tables. In particular, in all the countries with high adult mortality, the relationship between survivorship to age 5 and survivorship from 15 to 60 years lies between those in the Coale and Demeny South and West families of models.

In contrast, the five countries in which adult survivorship had risen to more than 75 percent by the end of the 1970s still had much higher child mortality than one would expect based on the Coale-Demeny models. The pattern is most extreme in The Gambia, where the estimate of adult survivorship is probably somewhat too high. However, as the section on mortality levels argues, it seems unlikely that adult survivorship has been overestimated in all five countries by as much as the 5 to 10 percentage points required to

6  

For most countries the estimates of child survivorship made by the United Nations (1988) have been used, supplemented by those of Hill (1991). In a few countries, estimates based on information that has become available recently are used but no systematic search for such data was attempted.

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

bring them into line with the South models. It is also unlikely that child survival has been underestimated by a large amount. Yet, it is not the failure of these countries to improve child survival that differentiates them. They have all experienced a substantial fall in child mortality since the 1950s. The decline in adult mortality, however, appears to have outpaced the decline in child mortality.

One high-mortality country in eastern Africa also stands out as extreme on the left-hand side of the plot: Malawi. Quite a lot of data are available for this country, and although they exhibit some inconsistencies for both adults and children, the general pattern of the results is clear. It is Malawi’s unusually high child mortality, compared to other eastern African countries, that is distinctive (Blacker, 1991), rather than its adult mortality.

The countries of southern Africa again stand out as exceptional, having high adult mortality, relative to that of children, compared with the Princeton models. This is accounted for largely by the excess mortality of adult males. Even for women, however, adult mortality in these populations is relatively high compared with the pattern in most of sub-Saharan Africa. The only other population that lies on the right-hand side of the plot is the Congo. The incomplete information on recent deaths that provides the basis for the adult mortality estimates is particularly difficult to interpret, and it is possible that adult mortality is considerably lower in the Congo than is suggested here.

Figure 6–2 suggests that the age pattern of mortality is related to the overall level of mortality. An attempt was made to model this relationship to establish whether it obscures significant regional variation in the age pattern of mortality. By using the Coale and Demeny (1983) South family level 14 life tables for men and women as standards, a two-parameter relational logit model life table was fitted to sex-specific estimates of l(5) and 45p15 in each population.7 The β parameter of the fitted life tables measures the relationship between adult and early child mortality, and the β parameter measures the overall level of mortality.8 In an initial model β was regressed on α, by weighting each life table by an estimate of annual births in the population concerned. The residuals are generally negative (observed β less than predicted) in western Africa and positive (observed β greater than predicted) in eastern and middle Africa. They are strongly negative in Malawi and strongly positive in southern Africa. Therefore, dummy vari-

7  

Subnational data from Ondo State, Nigeria, are included in this analysis to provide some indication of the age pattern of mortality in this important country.

8  

In the standard life table, α=0 and β=1. Values of α less than zero imply that mortality is lighter than in the standard, whereas values of β less than 1 imply relatively high child mortality, compared with adult mortality (Brass, 1971)

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

TABLE 6–2 Relationship Between Adult and Early Child Mortality (β), Predicted from Overall Mortality (α) and Region

Variable

Males (standard error)

Females (standard error)

Constant

1.156 (0.023)

1.143 (0.028)

α

0.459 (0.085)

0.697 (0.086)

Western Africa

–0.129 (0.037)

–0.152 (0.047)

Southern Africa

0.436 (0.049)

0.282 (0.064)

Malawi

–0.520 (0.079)

–0.408 (0.100)

R2

.897

.821

 

SOURCES: Based on data in Table 6–1 and footnote 6.

ables representing these areas were introduced into the regression equations.

The final models are shown in Table 6–2. The reference region is eastern and middle Africa. All the coefficients are highly significant. The positive coefficients for α confirm that African populations with low overall mortality have particularly low adult mortality, compared to the pattern in higher-mortality African populations. The effect is stronger for women than for men. Further modeling suggests that it does not vary significantly between the regions of sub-Saharan Africa. When controlling for the overall level of mortality, the estimated values of β for southern Africa are very high, which implies relatively heavy adult mortality. The effect is largest for men, but is also substantial for women. In contrast, Malawi has relatively low adult mortality. These effects have been discussed with reference to Figure 6–2. In addition, the regression model suggests that, when controlling for the overall level of mortality, western Africa is characterized by lower adult and higher child mortality than eastern and middle Africa. On average, South models represent the relationship between child and adult mortality well in western African populations with a life expectancy at birth of about 50 years. A typical eastern or middle African population with this life expectancy at birth, however, has higher adult, and lower child, mortality than the corresponding South model.

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

Trends in Female Mortality

Figure 6–3 portrays the improvement in adult female survivorship over time in a subset of 15 mainland sub-Saharan African countries. Some of the trends are estimated from two inquiries conducted at different dates, others from series of orphanhood estimates that have been located in time and smoothed by fitting a regression line. Unfortunately, the countries for which we can estimate the trend in mortality include only one of those in Table 6– 1 with very high adult mortality: Sierra Leone.

The uniformity of the rate of improvement in adult female survivorship between different countries and in different decades is striking. Although some of the trends may be distorted by errors in the data, there is certainly no evidence of general stagnation in adult mortality during the 1970s. In

FIGURE 6–3 Trends in female survivorship from age 15 to age 60. SOURCES: Data from Benin (Benin, n.d.); Côte d’Ivoire (Ahonzo et al., 1984); The Gambia (Blacker and Mukiza-Gapere, 1988); Ghana and Senegal (Timæus, 1991d); Liberia, Madagascar and Rwanda (Waltisperger and Rabetsitonta, 1988b); Mali (Mali, 1980 and provisional 1987 census tables); Mauritania (Timæus, 1987); Sierra Leone (Okoye, 1980); Togo (Togo, 1985); Cameroon (Cameroon, 1978, 1983); Congo (Congo, 1978, 1987); Burundi (Timæus, 1991c); Kenya (Mukiza-Gapere, 1989); Malawi (Timæus, 1991b); northern Sudan (Sudan, 1982); Tanzania (Tanzania, 1982 and provisional 1988 census tables); Zimbabwe (Zimbabwe, 1985); Botswana (Botswana, 1972, 1983); Lesotho (Timæus, 1984); South Africa (South Africa, 1988); Swaziland (Swaziland, 1980 and unpublished 1986 census tables).

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

the few countries for which data are available, moreover, improvements in adult survivorship seem to have continued until at least the early 1980s.

All the western and middle African countries included in Figure 6–3 have experienced a rapid decline in adult female mortality. Thus, except for Ghana, the western African countries in which the time series of estimates extends back to 1965 had very high adult mortality at that time. This finding accords with the results of a series of surveys conducted in francophone Africa between the mid-1950s and mid-1960s. The quality of these data varies, but modern techniques of evaluation suggest that many of them are plausible (Condé et al., 1980; Waltisperger and Rabetsitonta, 1988a,b). The surveys conducted in Guinea (1955) and Chad (1962) indicate that survivorship from 15 to 60 years was as low as 27 percent, corresponding to a life expectancy at age 15 of about 30 years. It is unclear whether the persistence of such elevated levels of adult mortality into the second half of this century was widespread. The surveys in Burkina Faso (1960), Central African Republic (1960), Côte d’Ivoire (1963), and Togo (1961) all yield somewhat higher probabilities of surviving from 15 to 60 years of about 40 percent. We lack recent data for Burkina Faso, the Central African Republic, and Chad, but the estimates for Côte d’Ivoire and Togo in Table 6–1, together with those for countries such as Mali and Sierra Leone, suggest that sufficient progress had been made everywhere by 1980 to increase the probability of surviving from age 15 to 60 to more than 50 percent.

The experience of other regions of Africa seems to have been more diverse. The four populations in Figure 6–3 that experienced little improvement in adult female survivorship during the 1960s and 1970s comprise the two southern African states for which data are available (Lesotho and Swaziland), northern Sudan, and Kenya in eastern Africa. Of the countries for which estimates extend back to the early 1960s, they are the four that then had the lowest mortality.9 In other eastern African countries, adult mortality has declined more rapidly. Many of these countries had rather high mortality in the 1960s. In Zimbabwe, however, adult survivorship seems to have risen rapidly during the 1970s, although, at the start of the decade, it already had lower mortality than any other African country for which data are available.

Figure 6–4 compares the absolute annual improvement in female adult survivorship with that in child survivorship in each of these 15 countries over the period for which data are available. Whether or not one ignores the outliers, there is, as one would expect, some association between the

9  

The data available for Kenya and northern Sudan exhibit inconsistencies, and it is possible that their adult mortality decline has been underestimated. The evidence that adult mortality has stagnated in Lesotho (Timæus, 1984) and Swaziland, on the other hand, is compelling.

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

FIGURE 6–4 Annual increases in child and adult female survivorship. SOURCES: Based on data in Table 6–1 and footnote 5.

rates of improvement in child and adult survivorship. The relationship is much clearer in western and middle Africa than in other regions of Africa, particularly Kenya and northern Sudan, where the slow declines in adult mortality again stand out as anomalous. In addition, the increase in adult survivorship in The Gambia of nearly 2 percent per year seems implausibly rapid. Even if one allows for errors in the estimates of both child and adult mortality, however, the relationship between mortality trends in these two age ranges is clearly rather loose. This suggests that the effect on mortality of health care programs, economic advances, social development, and other factors may differ between these age ranges.

Socioeconomic and Areal Differentials

Although inequalities in adult mortality in developed countries have been a major focus of research, very little is known about the size of such differentials in developing country populations. The topic is particularly difficult to investigate. Very large sample sizes are required to measure such differentials by using direct data. Indirect data, on the other hand, can usually be analyzed only according to the characteristics of the respondents, not those of their dead relatives. Indirect methods are valuable for the study of areal differentials in adult mortality and can provide detailed estimates when the necessary data have been collected in national censuses.

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

One of the main difficulties in interpreting the results is allowing for the migration of respondents or parents away from the areas where their parents lived.

Figure 6–5 presents estimates of adult mortality by district for Kenya. They were provided by John Blacker and are based on the orphanhood data collected in the 1969 and 1979 censuses. Each bar represents the range of values of 45p15 for districts within a province, with outliers represented by crosses. The figure emphasizes that in at least some countries, the national estimates presented in Table 6–1 may well conceal massive differences in the level of adult mortality between areas of a country. In much of Central Province, adult mortality in the 1970s was even lower than in Ghana or Zimbabwe. On the other hand, in parts of the sparsely populated north and east of the country, adult mortality was nearly as high as in the least healthy African countries for which we have data. Figure 6–5 also reveals that variation in the level of adult mortality is not restricted to the provincial level. There are also large differences between districts within many provinces.

A second axis of variation in adult mortality that can be examined in several countries is type of place of residence. Some of the direct estimates

FIGURE 6–5 District-level variation in adult survivorship by province, Kenya, 1970s. NOTE: Each bar represents the range of values of 45p15 for districts within a province, with outliers represented by crosses. SOURCE: Unpublished analysis by John Blacker.

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

TABLE 6–3 Life Expectancy at Age 15 According to Residence, Both Sexes

 

Life Expectancy at 15 Years

Country

Date

Capital City

Urban

Rural

National

Côte d’Ivoire

Late 1970s

 

52.1

49.0

50.0

Liberia

Early 1970s

47.5

43.7

45.0

Mali

Late 1970s

47.6

 

44.6

 

Early 1980s

50.8

44.2

Senegal

Late 1970s

51.8

50.0

Sierra Leone

Early 1970s

47.5

41.0

Zimbabwe

Late 1970s

 

56.9

 

Early 1980s

57.0

 

Botswana

Early 1980s

 

53.4

46.9

48.3

 

SOURCES: For capital cities: Bamako (Fargues and Nassour, 1988); Dakar (Cantrelle et al., 1986); Freetown (Wurrie, 1979); Harare (Moyo, 1991). Otherwise as in Table 6–1.

of adult mortality in Table 6–1 can be broken down into estimates for urban and rural areas. In addition, in certain countries, registration data for the capital city can be compared with national estimates from other sources.10 Both types of comparison are shown in Table 6–3. The results are presented in terms of life expectancy at age 15, rather than 45p15, to maximize the number of countries that can be considered. These data suggest that adult mortality is lower in urban Africa than in the countryside. If they can be relied upon, the differential is larger in the high-mortality countries, indicating that the advantage of urban areas is eroded as overall mortality declines. Thus, the national and rural adult mortality estimates vary far more between countries than those of urban mortality.

Little is known about differentials in adult mortality in Africa according to factors such as occupation and income that have received attention in the literature on mortality in developed countries and child mortality in the developing world. Table 6–4 presents indirect estimates of adult mortality in Lesotho according to the level of education of the respondent answering the questions about the survival of relatives. In this analysis, level of education probably should be interpreted as a proxy for socioeconomic status. One would not normally expect the education of young adults to have a large direct effect on the mortality of their parents. Moreover, since the

10  

Differential errors in the two sources of data are potentially a major problem with such comparisons.

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

TABLE 6–4 Survivorship from Age 15 to Age 60 by Sex, According to Education of One’s Close Relatives, Lesotho, Late 1960s

 

Relative

Level of Education

Sons

Daughters

Spouses

Men’s survivorship

 

None

.54

.50

.53

Lower primary

.58

.53

.57

Upper primary

.60

.67

.62

Secondary+

.62

.57

.68

Women’s survivorship

 

None

.76

.65

.77

Lower primary

.80

.74

.77

Upper primary

.82

.77

.79

Secondary+

.87

.85

.88

 

SOURCE: Timæus (1984).

cells in each row of the table are based on different respondents, one should not expect them to agree exactly. Nevertheless, the data on orphanhood supplied by men and women, as well as those on widowhood, all suggest that adult survivorship rises monotonically with increases in the education of the individual making the reports. The differentials are large, being broadly equivalent to those between Kenya and Zimbabwe for women and those between Liberia and Côte d’Ivoire for men. They suggest that the tenth of adults whose relatives went to secondary school have considerably lower mortality than the rest of the population.

Given the shortage of individual-level data that can be used to study the influence of socioeconomic factors on adult mortality, another approach is to examine the association between mortality and indicators of development at the national level. In sub-Saharan Africa, Feachem et al. (1991) find the probability of dying by age 5 to be significantly related to both gross national product (GNP) per capita and secondary-school enrollment. Timæus (1991e) suggests that adult survivorship in sub-Saharan Africa is also related to GNP per capita. Figures 6–6 and 6–7 compare estimates of adult female survivorship in the mid-1970s for 21 mainland countries with GNP per capita and secondary-school enrollments at the same date (World Bank, 1988). The fitted regression lines indicate that a relationship exists in both cases, but neither index of development is closely associated with adult survivorship in the sample of countries considered in this analysis. Similar plots of survivorship against other indices of social and economic development and multiple regression modeling yield no other significant associa-

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

FIGURE 6–6 Income levels and female survivorship in adulthood, mid-1970s. NOTE: R=.4376. SOURCE: World Bank (1988).

FIGURE 6–7 Secondary schooling and female survivorship in adulthood, mid-1970s. NOTE: R=.3115. SOURCE: World Bank (1988).

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

tions. Thus, broad indicators of development are not very helpful in understanding variation in adult mortality across the continent.

CAUSES OF DEATH

One reason it may be difficult to interpret the differences in adult mortality levels between countries is because fragmentary evidence suggests that the cause-of-death patterns underlying them vary widely. Unfortunately, representative data on the causes of adult deaths are very rare in sub-Saharan Africa. The few studies that exist tend to be based on differing measures and classifications of cause-specific mortality. Moreover, the samples of deaths involved are often small (Omondi-Odhiambo et al., 1990).

In Table 6–5, cause-specific probabilities of dying (per 1,000) in four sub-Saharan African populations are presented for two broad age groups. Unfortunately, eastern Africa is not represented, and none of these populations is drawn from rural, tropical mainland sub-Saharan Africa.11 The classification of causes of death adopted is that used by Feachem et al. (1992). To minimize the effect of errors in the coding of causes of death, only broad categories are used. For example, the classification fails to distinguish coronary heart disease, which is believed to be rather unimportant in sub-Saharan Africa (Hutt, 1991), from other forms of cardiac disease and cerebrovascular disease.

Even these statistics should be interpreted with caution. Only about 80 percent of adult deaths were registered in Bamako and western Sierra Leone, and unregistered deaths have been distributed by cause in proportion to registered ones, rather than assigned wholly to the ill-defined category. In addition, not all the registered deaths were medically certified at the time of death, and even clinicians’ diagnoses of causes of death are subject to considerable error unless confirmed by autopsy. The basic data were also compiled by using several different versions of the International Classification of Diseases and are not detailed enough in either Bamako or western Sierra Leone to be grouped exactly into Feachem et al.’s (1992) classification. Thus, only consistent features of the results should be accorded much significance.

The first aspect of Table 6–5 that deserves emphasis is that although communicable disease and reproductive mortality are more important than in lower-mortality populations elsewhere in the world, they still account for only a minority of adult deaths in these four populations. The proportion of such deaths ranges from about one-fifth in Cape Verde to slightly more than

11  

Western Sierra Leone is the area around Freetown, which represented about two-thirds of the area’s population in the early 1970s.

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

one-third in western Sierra Leone. If the category “senile or ill-defined” is excluded, cardiovascular disease is universally the leading cause of death in middle age (ages 45–64), followed in most instances by neoplasms and respiratory infections.

Cardiovascular disease is also one of the three most important causes of death among young men and women. In this age group, injuries are the leading cause of death for men in Cape Verde and for the “Colored” (including “Asian”) population of South Africa. Maternal mortality is the leading cause of death for young women in Sierra Leone and the second most important in Bamako, excluding those deaths coded as senile or ill defined. It is worth noting, however, that maternal mortality accounts only for between 6 and 13 percent of deaths of women of childbearing age, though it might be proportionally more important in isolated rural areas. Diseases of the digestive system are an important cause of death in Bamako, especially among men. This is accounted for primarily by liver disease, which is the leading cause of loss of life among adults aged less than 60 in this population (Fargues and Nassour, 1988).12

Gender differentials in cause-specific mortality are generally small, particularly in the age group 15–44 years and for noncommunicable disease. Such small differentials suggest that certain lifestyle factors that are important determinants of adult mortality differentials in other parts of the world may not yet play a major role in their explanation in this region. The two consistent exceptions are mortality from diseases of the digestive system, which is typically about twice as common among men as women, and mortality from injuries, which is about three times as high among men as women. Among young adults, deaths from external causes account for most of the gender differential in overall mortality, offset to a considerable degree by maternal deaths. In the age group 45 to 64 years, deaths from injuries decline in both absolute and relative importance, and two further diseases make a significant contribution to the gender differential in overall mortality: tuberculosis and respiratory infections. Both are responsible for about twice as many deaths in middle-aged men as middle-aged women.

With the exception of injuries, the population of Cape Verde has low mortality rates in adulthood from all cause categories. The island’s advantage is least marked with respect to cardiovascular disease. Not only the overall level of mortality, but the level of noncommunicable disease mortality, is broadly similar in the other three populations. In other respects, the cause of death structure experienced by “Colored” adults in South Africa is

12  

The prevalence of liver disease appears to vary greatly across Africa. It is thought to be linked to infection with hepatitis B virus and to the contamination of foodstuffs with aflatoxin (Hutt, 1991).

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

TABLE 6–5 Cause-Specific Probabilities of Dying by Broad Age Group and Sex

 

Cape Verde 1980

Bamako, Mali 1974–1985

Western Sierra Leone 1972–1975

South Africa “Colored” and “Asian,” 1971

Cause of Death

15–44

45–64

15–44

45–64

15–44

45–64

15–44

45–64

Males

 

Communicable/reproductive

10.3

35.1

46.5

118.1

64.1

137.3

33.1

86.5

Diarrheal

0.6

1.3

7.2

19.3

6.7

24.5

1.9

3.1

Tuberculosis

4.8

12.9

10.9

30.0

13.6

19.5

15.3

31.7

Malaria

0.0

6.5

9.5

0.1

Respiratory

4.2

19.3

8.3a

39.0a

22.3a

53.5a

13.5

47.6

Noncommunicable

20.5

123.0

89.3

263.4

76.5

248.5

65.5

303.3

Neoplasms

3.5

27.5

9.5

38.7

1.6

18.5

11.3

67.8

Cardiovascular

7.9

63.7

11.8

55.1

13.8

69.0

25.1

157.1

Digestive

1.7

8.1

19.1

45.1

11.5b

29.0b

5.6

19.9

Senile/ill-defined

2.1

7.3

27.7

75.8

6.7

17.9

Injuries

29.2

17.9

21.1

19.5

16.4

12.3

93.5

44.2

Unintentional

18.7

13.1

60.0

32.4

Suicide

1.6

1.1

5.1

2.8

Homicide and war

8.9

3.7

28.4

9.1

Total

60.0

176.0

157.0

401.0

157.0

398.0

192.0

434.0

Females

 

Communicable/reproductive

13.2

14.4

45.2

75.6

72.4

108.5

36.8

36.9

Diarrheal

0.4

0.8

5.8

17.7

7.3

23.4

1.2

2.1

Tuberculosis

4.2

3.4

4.8

11.7

8.5

9.3

11.7

8.7

Malaria

4.2

9.1

Respiratory

4.8

8.8

6.1a

21.0a

15.0a

30.0a

13.5

22.5

Maternal

2.8

0.2

11.4

0.7

19.8

0.6

7.7

0.6

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

Noncommunicable

24.4

80.5

72.9

220.5

68.7

272.6

67.9

206.1

Neoplasms

4.6

14.6

7.1

36.0

2.4

26.2

12.9

37.4

Cardiovascular

9.4

48.5

15.9

61.5

10.4

85.1

26.2

124.1

Digestive

0.8

2.5

10.2

21.7

5.6b

20.7b

2.2

6.4

Senile/ill-defined

2.6

3.7

21.3

62.4

7.4

9.4

Injuries

9.4

5.1

6.8

11.0

5.9

4.9

26.2

13.0

Unintentional

5.9

3.8

16.5

9.8

Suicide

0.8

0.3

2.2

0.7

Homicide and war

2.8

1.0

7.7

2.6

Total

47.0

100.0

125.0

307.0

147.0

386.0

131.0

256.0

Number of deaths

432

15,801

4,542

11,384

Deaths registered (%)

90+

77c

80

90+

Medically certified (%)

60c

56

42+d

aIncludes chronic respiratory disease.

bCategory comprises diabetes mellitus, peptic ulcer, cirrhosis, nephritis, and nephrosis.

cAll ages 5 years and over.

dNot known, but 42 percent of deaths at all ages occurred in hospitals.

SOURCES: Cape Verde (United Nations, 1987); Bamako (Fargues and Nassour, 1988); Western Sierra Leone (Wurrie, 1979); South Africa (United Nations, 1982b).

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

distinctive. They have higher death rates from cardiovascular disease and neoplasms than populations further north, but lower death rates from most other noncommunicable diseases. Except for tuberculosis, the South African population also experiences fairly low communicable disease mortality. Its overall mortality is maintained at a high level by deaths from both accidents and violence.

One way of relating these data on the causes of adult mortality in sub-Saharan Africa to those from other regions is to compare them with the predicted cause-of-death structures presented by Murray et al. (1992) for different levels of 45q15. These predictions are based on data from 56 non-African populations, including 23 from the developing world. Although the results are presented for levels of adult mortality comparable with those in Africa, all the data used to generate the predictions are from populations with lower mortality than that in Bamako, Western Sierra Leone, or South Africa.

The comparison suggests that adults in the three tropical populations included in Table 6–5 experience unusually high communicable disease mortality. However, although it remains an important cause of death, tuberculosis mortality is only about half as common in these four populations as one would expect based on the experience of other parts of the world. Mortality from diarrheal disease and the infectious and parasitic diseases is particularly high. Second, “Colored” men and women in South Africa are about two-thirds more likely to die of cardiovascular disease than one would expect from the predicted figures. Cape Verde also has slightly higher cardiovascular disease mortality than one would expect, given its fairly low overall mortality, but reported mortality from this group of diseases is moderate in the other two populations. Third, diseases of the digestive system appear to be relatively unimportant causes of adult death in sub-Saharan Africa. Except in Bamako, where such deaths are about three-quarters as common as predicted, the reported death rate from this group of diseases lies between 20 and 50 percent of the expected level. Finally, male, but not female, death rates from injuries in Bamako and western Sierra Leone are low for such high-mortality populations. In South Africa, however, mortality from injuries is relatively high, reaching more than three times the predicted level for women.

It is important to note that most of the data in Table 6–5 are rather out-of-date. Information on particular diseases indicates that patterns of causes of death among adults in Africa may be undergoing a rapid evolution. For example, hypertension appears to be a health problem of growing importance in populations where it was previously rare (Hutt, 1991). It is associated with urbanization and the adoption of more “Western” diets and lifestyles. The growing AIDS epidemic is also, of course, of particular importance.

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

CONCLUSIONS

The statistics presented in the previous sections are based on very imperfect data. Nevertheless, with some exceptions, they suggest a coherent and plausible, though sometimes surprising, picture of adult mortality patterns across sub-Saharan Africa. Future work undoubtedly will prove that some of the estimates are wrong. Nevertheless, in concentrating on the overall pattern of the findings, rather than on results for particular countries, several general conclusions seem justified.

First, the average level of adult mortality in sub-Saharan Africa is high, compared to the rest of the world, but the experience of different countries is very heterogeneous. By the late 1970s, adult mortality was fairly low in some countries but remained high in others. Second, offsetting this rather depressing picture were the considerable reductions in adult mortality achieved in Africa during the 1960s and 1970s, particularly in western Africa. Many sub-Saharan African countries entered the second half of this century with extremely high adult mortality. There is no evidence that this persists anywhere. Moreover, in those countries that succeeded in reducing overall mortality to a moderate level by about 1980, adults tended to benefit more, and children less, than one would expect based on the historical experience of the developed world. Third, and of significance for health planning at the national level, the limited information available suggests that large areal, residential, and socioeconomic differentials in adult mortality exist in at least some African countries. Fourth, only in southern Africa do neighboring countries appear to have closely linked levels, trends, and patterns of mortality. In this region, adult mortality appears to have stagnated at a high level, while that of children has declined further than in most of Africa. Adult men suffer particularly high mortality. If cause-of-death data for South Africa’s “Colored” population are of relevance to the rest of the region, this pattern may be accounted for by high mortality from cardiovascular disease and injuries. Fifth, women’s mortality is also lower than men’s mortality in most other parts of Africa, but the differential is usually small. It may be accounted for largely by higher male death rates from injuries, tuberculosis, and respiratory disease, offset to some extent among younger adults by maternal mortality. Sixth, when controlling for the overall level of mortality, adult mortality is on average lower in western Africa than in middle or eastern Africa, compared with the mortality of children. Finally, although infectious disease mortality appears of greater absolute and relative importance for adults in sub-Saharan Africa than in other regions of the world, it still accounts for only a minority of adult deaths. Tuberculosis and diseases of the digestive system remain important causes of death in adulthood, but may be relatively less important in sub-Saharan Africa than in other parts of the developing world.

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

Several intriguing exceptions to the general pattern of the results have been mentioned in the previous sections. The apparently high level of adult mortality in the Congo, despite the favorable indicators of social and economic development and the relatively low childhood mortality, deserves mention. To take a contrasting example, adult mortality in The Gambia may have fallen to a low level despite the country’s rather high child mortality. Other notable findings include the relatively slow decline in adult mortality in Kenya and northern Sudan, and the distinctive pattern of mortality in Malawi. Although plausible explanations for some of these findings could readily be suggested, they may reflect no more than errors in the data.

It has been emphasized throughout this chapter that even the basic descriptive knowledge of levels and trends in adult mortality across sub-Saharan Africa is incomplete. Nevertheless, to return to the questions posed in the introduction, adult mortality patterns in sub-Saharan Africa are distinctive. They also seem to vary across the continent. Neither knowledge of adult mortality in other regions of the world, nor knowledge of child mortality in Africa, is a particularly good guide to the health problems of adults in this region. Valuable advances in methods for estimating adult mortality in countries with limited and defective data have been made since the 1970s. In sub-Saharan Africa, however, relatively few countries have collected the data needed to apply them. Very little is known about differentials in adult mortality or causes of death in adulthood, and even less about the underlying determinants of adult mortality patterns. Ignorance about the mortality baseline against which the AIDS epidemic in sub-Saharan Africa is unfolding, and about the distribution within the population of other diseases, such as tuberculosis and venereal disease, with which human immunodeficiency virus (HIV) infection is known to interact, is particularly disturbing.

Despite progress made during the 1960s and 1970s, many adults were still dying before age 60 in Africa even prior to the spread of HIV. For adults, as for children, sub-Saharan Africa is undoubtedly the region of the world with the poorest health. Until 1980, adults usually benefited more than children in those African countries that managed to reduce overall mortality to a moderate level. During the 1980s, vigorous promotion of universal immunization and other measures to improve child survival, together with the AIDS epidemic, may have begun to reverse this pattern. In considering the efforts being made to improve the survival of Africa’s children, it is notable how little is known about what would constitute a corresponding strategy to maintain their health when they grow up.

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

APPENDIX

As the body of this chapter emphasizes, only limited and defective data on adult mortality exist for sub-Saharan Africa. Analysis of this information is far from straightforward. To illustrate the procedures involved and the difficulties that arise in interpretation of the results, this appendix presents applications of various methods of estimation for some of the data analyzed in this chapter and explains how the summary indices presented in Table 6–1 were derived.

The first important form of data is on deaths by age during a specified period. Such data are collected by registration systems or by asking direct questions in censuses and single- or multiround household surveys. Reporting may be incomplete or, with retrospectively collected data, may refer to the wrong reference period. In addition, inaccurate reporting of either ages at death or ages of the living population used as a denominator to calculate rates may bias the estimates.

Several methods exist for evaluating such data. Most of them are based on the relationship between the number of people of any age and the number of deaths above that age. If one adjusts for population growth, these numbers should be the same because nobody can live forever. To exploit this identity, one has to assume that reporting is equally incomplete at all adult ages. On this basis, various approaches can be used to compare the two quantities and assess the shortfall in reported deaths (Brass, 1975; Preston et al., 1980; Bennett and Horiuchi, 1981). Sampling errors, deviations from the assumption of constant underreporting of deaths by age, the distorting effect of past mortality change and migration on the population’s age structure, and age misreporting can all make such comparisons difficult to interpret.

Such methods of evaluation have been applied to all the direct data used in this chapter for which sufficiently detailed tabulations are available. Figure 6–A.1 illustrates the application of Preston et al.’s (1980) method to registration data on male deaths among “Blacks” in South Africa in 1985. It compares the estimated population between each age and age 75, calculated from deaths adjusted for growth at 2.6 percent per annum, with the enumerated population in the same age range according to the 1985 population census. If all the assumptions held and reporting was perfectly accurate, apart from being incomplete, the plot would be a horizontal straight line. Although it is not, the assumptions involved appear to have held up reasonably well until about age 55. Thus, the analysis provides rather convincing evidence that relative to the census, only about 72 percent of adult male deaths were reported. In fact, in absolute terms, the registration of deaths of “Black” men is certainly worse than this because the 1985 census enumeration was also incomplete. It is, however, only relative in-

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

FIGURE 6–A.1 Ratio of estimated to reported population, “Black” men, South Africa. SOURCE: South Africa (1988).

consistencies between the two sources that bias the estimated death rates. A similar analysis for “Black” South African women suggests that relative to the census, about 59 percent of adult female deaths were registered in 1985. Once the degree to which reports of adult deaths are incomplete is known, it is a straightforward matter to adjust them upward before calculating age-specific death rates and life table measures of mortality and survivorship.

Besides the problem of incomplete death reporting, life tables calculated from developing country data tend to be distorted by age reporting, sampling, and other errors. To reduce the effect of such problems, the life tables were smoothed prior to extracting the final estimates of 45p15. The approach adopted is to fit a two-parameter logit relational model life table based on the general standard (Brass, 1971). These models exploit the fact that after the logistic transformation is applied, the differences between any two life table survivorship functions, l(x), are approximately linear. Thus, plotting the logits, Y(x), of the observed survivorship function against those of the standard, Ys(x), one can fit a line to the points for ages at which the data seem reliable and extrapolate from them to age ranges in which the observed data are clearly biased. Figure 6–A.2 illustrates the procedure

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

with data on “Black” female deaths in South Africa in 1985. The radix of the life table is at age 15 years, and reported deaths were multiplied by a factor of 1.695 before calculating death rates and measures of survivorship.

Inspection of Figure 6–A.2 reveals that the line representing the observed data bends downward for the oldest ages on the right-hand side of the plot. This deviation indicates that the reported mortality of elderly women is lower than one would expect based on the data for younger age groups and the age pattern of mortality in the general standard. It is likely that reporting of deaths of elderly women is particularly incomplete or that their ages at death tend to be exaggerated. Therefore, the last three points were discarded and a model life table was fit to the points for ages 20 to 60 years. This procedure yields a line with an intercept of –0.34, implying an overall level of adult mortality among “Black” women in South Africa that is a little lower than in the standard, and a slope of 1.26, implying relatively heavy mortality in middle age compared with early adulthood. The prob-

FIGURE 6–A.2 Logit survivorship, compared with standard, “Black” women, South Africa. SOURCE: Figure 6–A.1.

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

ability of surviving from 15 to 60 years (45p15) is 70.4 percent in the fitted life table, as opposed to 70.8 percent according to the unsmoothed data.

The final estimates for South Africa presented in Table 6–1 are based on similar analyses for the “Colored” and “Asian” populations. These were combined with the unadjusted life table for the “White” population, weighting by each group’s share in the total population. Because the official statistics do not cover the four so-called independent homelands, the mortality of the adult population of these areas was assumed to be the same as that of the “Black” population in the rest of South Africa. This assumption may be unjustified but is unlikely to bias the national estimates appreciably.

The second important form of information used to estimate adult mortality is that on the survival of respondents’ mothers and fathers. The questions required are simply, Is your mother alive? and Is your father alive? They can be administered in censuses and single-round household surveys. No attempt is made to collect the ages at death of parents. Instead, these ages are implicitly assumed from respondents’ ages by using demographic models. The information used is the proportion of respondents in each 5-year age group with a living mother (or father). This proportion is closely related to the life table probability of surviving from about the average age at which women (or men) have children to that age plus the current age of the respondents. By using this fact, regression-based procedures have been developed for estimating life table survivorship from data on orphanhood (e.g., Timæus, 1992). Each 5-year age group yields a separate estimate of adult mortality. Although the estimates refer to different age ranges, they can all be converted to 45p15 by using any one-parameter system of model life tables, without reducing their precision greatly.

The younger the age group of respondents, the more recently did their parents die, on average. If it is assumed that the level of mortality has changed steadily, it becomes possible to estimate the date at which the mortality of the cohort of parents reported on by an age group of respondents equaled the level of mortality prevailing in the population (e.g., Brass and Bamgboye, 1981). In this way, the series of estimates obtained from respondents aged 5 to 55 years in a single inquiry can be used to infer the past trend in the level of adult mortality over a decade or more.

The kind of results obtained from the orphanhood method of estimating adult mortality are illustrated in Figure 6–A.3 by using data from Swaziland. Questions about the survival of mothers and of fathers were asked in both the 1976 and the 1986 censuses, yielding the four lines shown in the figure. Swaziland illustrates a common problem with estimates of adult mortality obtained from orphanhood data. Each of the four sets of results suggests that adult mortality is declining. Because the questions have been asked twice, however, it is possible to compare estimates from the two sources for the early 1970s. They are clearly inconsistent. The reports of younger

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

FIGURE 6–A.3 Adult survivorship estimated from orphanhood, Swaziland. SOURCE: Data from Swaziland (1980) and unpublished 1986 census tables.

respondents in the earlier census indicate lower mortality than the reports of older respondents in the later census. Similar inconsistencies characterize the data on several other eastern African countries that have asked about orphanhood more than once. They include Kenya, Malawi, northern Sudan, and Tanzania. Elsewhere in Africa, however, successive surveys have yielded much more consistent results, permitting one to have reasonable confidence in the accuracy of the data. Results for one such country, The Gambia, are shown in Figure 6–A.4 (only maternal orphanhood data are available from both censuses). Others include Cameroon, Lesotho, and Mauritania.

Accumulated experience makes it clear that when such inconsistencies between two sets of data arise, they stem from underreporting of orphanhood at early ages (e.g., Timæus, 1991a,b). Data supplied about young orphans often refer to a foster parent or stepparent, rather than to a dead natural parent. Each set of estimates exaggerates the decline in mortality, and the most recent estimates of adult mortality from both inquiries are probably too low.

In Swaziland at least, it remains likely that adult mortality has declined somewhat. Every age group of respondents reported more living parents in

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

FIGURE 6–A.4 Adult female survivorship estimated from orphanhood, The Gambia. SOURCE: Blacker and Mukiza-Gapere (1988).

1986 than in 1976. If questions about orphanhood have been asked more than once, the effect of underreporting of orphanhood in childhood can be reduced by analyzing data on the incidence of orphanhood between the two inquiries among young adults. This analysis is done by using the two sets of proportions to construct a synthetic cohort based at age 20. Life table survivorship is estimated from the proportion of each age group in this synthetic cohort with a living mother (or father) by using regression coefficients developed for the purpose (Timæus, 1991b). All the estimates refer to the same intersurvey period, but they tend to differ somewhat because of sampling and age reporting errors. Averaging the results for different age groups, produces point estimates such as those shown in Figures 6–A.3 and 6–A.4.

In The Gambia, the synthetic cohort estimate for the 1973–1983 intercensal period emphasizes the consistency of the two sets of orphanhood results. In contrast, in Swaziland the intercensal estimates for both men and women indicate much higher mortality than estimates for 1981 made from 1986 data on children. They do, however, fall in line with the earlier estimates from each census, which are obtained from respondents aged 25 to 45 years. These results suggest that a fairly slow decline in adult mortality has oc-

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

curred in Swaziland. Moreover, the trends for men and women are fairly consistent. Thus the intercensal results seem plausible. The results from applying this approach to Kenya and Malawi are similar to those for Swaziland (Timæus, 1991b). Therefore, intercensal and intersurvey orphanhood estimates of 45p15 were also adopted for these countries. Unfortunately, in northern Sudan and Tanzania the method worked less well, probably because the accuracy of the reports changed markedly between inquiries.

In several countries the only information available on adult mortality is a single set of orphanhood data. In Burundi, Ghana, and Senegal, such data were obtained in a DHS survey that also asked women whether they were orphaned before or after they were first married. Data from a single survey on orphanhood since first marriage share the advantages of synthetic cohort data computed for countries that have asked about orphanhood repeatedly. They reflect the recent incidence of orphanhood among young adults and are unaffected by underreporting of orphanhood in childhood. The information analyzed for each five-year age group is the proportion of women with a living mother (or father) among those women whose mother (or father) was alive when the woman first married. Regression methods exist for estimating life table survivorship from these data (Timæus, 1991c). The results for different age groups refer to similar dates. Therefore, like synthetic cohort data, they are usually averaged to produce a single recent estimate. In the three countries with this form of data, underreporting of orphanhood in childhood does not seem to be a problem. Estimates from orphanhood since marriage are consistent with the trend estimated from lifetime orphanhood but are more up-to-date (see Timæus, 1991c,d). They are judged moderately reliable and presented in Table 6–1.

Finally, in several countries, only one set of orphanhood data was available for this study and the supplementary question on whether respondents were orphaned before or after marriage was not asked. In some of them, useful data on recent deaths were available, but in Benin, Sierra Leone, and Zimbabwe they were not. This circumstance makes it impossible to determine whether orphanhood among young children is underreported or not. Thus, the most recent estimates cannot be trusted. In such countries, most significance was accorded to the results obtained from respondents aged 15 to 40 years. Data about children were discarded if they suggested an accelerating decline in the level of adult mortality. Similarly, discrepant data obtained from respondents aged 40 to 55 years were ignored. The estimation methods are less reliable for these age groups, and the respondents are likely to exaggerate their own ages, thereby biasing the results. To smooth out the effects of imprecision in the data and estimation methods, the remaining estimates were regressed on the dates to which they apply. The predicted values of 45p15 for the most recent date at which the data seem reliable are presented in Table 6–1.

Suggested Citation:"6 Adult Mortality." National Research Council. 1993. Demographic Change in Sub-Saharan Africa. Washington, DC: The National Academies Press. doi: 10.17226/2207.
×

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