Religion
There is evidence that religious affiliation has some relationship to child survival: Caldwell (1986:175-177), in a comparative study of mortality in developing countries, used aggregate data and noted that Islam tended to be associated with relatively high child mortality levels. He surmised that this might be because of the Moslem attitude to women's education. This view was supported by data from the 1981-1982 Nigeria Fertility Survey (Ogunlade and Mezue, 1987:213). In the Nigerian data, the higher infant mortality rates among Moslems disappeared after controlling for education. Using survey data from three sub-Saharan African countries (Cameroon, Ghana and Kenya), Akoto (1990) found lower infant mortality rates among children of Christians, but the difference was weakened after controlling for the effects of place of delivery, literacy, and socio-occupation group. In Ilorin, Nigeria, Oni (1988: 611) observed that Moslems had slightly higher infant mortality rates than Christians but did not explain the mechanisms involved.
Many of the earlier studies in Africa and also in Nigeria have examined the differences between the major religious groups: Christians and Muslims, and in some cases, distinction is made between Protestants and Catholics. Relatively little has been done to explore the differences in infant and child mortality among various African independent churches. However, recent literature tends to suggest that there is a growing influence of the Aladura (or 'praying') churches, a brand of independent African churches that usually believes, inter alia, in spiritual healing by faith only (Crumbley, 1992:506). Many of the beliefs and practices of these Aladura churches may have health consequences, especially for women and children (Uche, 1990; Crumbley, 1992; Dennis, 1992).
A stages theory of socio-economic effects on infant and child mortality
Before the conclusion of this review of the relationship between infant and child mortality and socio-economic variables, a recent theoretical effort to summarize the relationship between infant and child mortality and socio-economic variables is presented. Using data from the Korea Fertility Survey of 1974, Kim (1988, 1990) applied a stages theory to explain the shifting relationships between infant and child mortality, and socio-economic and demographic variables. According to him, as a society moves from the traditional to the early stages of socio-economic development, the importance of demographic variables in explaining infant mortality declines and socio-economic variables gain ascendancy. However, as class differentials in living standards narrow at the intermediate stage of development, the explanatory importance of socio-economic variables is replaced by demographic factors. Demographic variables in turn weaken in significance relative to socio-economic variables in the later stage of socio-economic development. The validity of this theory is yet to be proved, although Gubhaju et al. (1991:434) tended to agree with it in their explanation of the importance of demographic variables in their study of Nepal.
In summary, one thing is clear from the literature: the mechanisms through which socio economic variables affect child survival are yet to be clearly understood. One of the reasons for this is heavy reliance on large-scale aggregate data from surveys. The United Nations (1985:289) team concluded that the socio-cultural factors of education and ethnicity seemed more important than the socio-economic variables, income, occupation and household possessions. The team pointed out that more attention should be given to cultural patterns of childcare, hygienic behaviours and practices relating to pregnancy care and childbirth. To study these issues, there is a need to go beyond conventional survey methods and include information derived from in-depth interviews and observational methods with the aim of investigating the structural and contextual factors that are relevant to child health.
The next section therefore focuses on the demographic variables, most of which are classified as proximate determinants through which the background variables pass to affect the risk of child mortality (Mosley and Chen, 1984).
Demographic and proximate variables
Demographic variables include age and parity, sex and birth order of the child, birth interval and duration of breastfeeding. Among these demographic variables, maternal age at childbirth, birth order or parity, and birth interval have been classified as proximate variables in the Mosley and Chen (1984) framework. Research findings on the effects of some of these demographic variables on mortality are equivocal (Rutstein, 1983; Geronimus, 1987; Bongaarts, 1987; Aly, 1990). The following sections summarize the literature on maternal age at childbirth, birth interval and breastfeeding.
Maternal age
The relationship between mother's age at childbirth and infant mortality has been a subject of active debate in the literature. The debate is principally about the cause of the excessively high infant mortality among children of teenage mothers relative to the children of mothers who give birth in their twenties. Scholars are divided on whether poorer teenage pregnancy outcomes are due to intrinsic biological and physiological factors or whether the poorer outcomes reflect social and economic disadvantages (Sweeney, 1989:1366)5. At the beginning of the debate, some scholars believed that teenagers were biologically less capable of effective mothering and that their babies were biologically at increased risk of death from medical and obstetric complications (Grant and Heald, 1972; Nortman, 1974; National Centers for Health Statistics, 1980). Another group of researchers more recently have argued that the higher mortality rates observed among infants of teenage mothers compared to mothers aged 20-29 reflect the
5 The latest trend in the debate on teenage childbearing, especially in the US, is about whether it is, in itself, a cause of economic disadvantage (Hofferth and Moore, 1979; Geronimus and Korenman, 1992; Hoffman, Foster and Furstenberg, 1993). However, this argument is not presented here because it relates to the future economic status of women who became mothers in their teenage years, which has little to do with factors affecting the health status of such children in infancy.
poorer socio-economic background of teenage mothers (Hollingsworth and Kreutner, 1980; Zuckerman et al., 1983; Geronimus, 1986, 1987; Cramer, 1987). This group argues that teenage childbearing is not inherently risky, but that the social selection process that causes teenagers from poorer socio-economic backgrounds to become mothers is a major explanatory factor. A study in the US, using 1983-84 data from Los Angeles County, California, found that teenagers had better pregnancy outcomes than women aged 35 and older and concluded that age per se was not responsible for the poor pregnancy outcomes, but socio-economic status and use of prenatal care (Davidson and Fukushima, 1985:469-470).
Regardless of the reasons, medical and demographic studies have shown that the survival of pregnancy outcomes is curvilinearly related to maternal age at birth. Using the World Fertility Survey data for 29 countries, Rutstein (1983:17-27) observed that infant mortality was low for mothers aged 20-29 and high for mothers aged below 20 and above 30 years. DaVanzo et al. (1983:386-388) observed a similar effect of maternal age on infant mortality in their Malaysian study. Infants of mothers aged less than 18 years were at a significantly higher risk of death than those of mothers aged between 18 and 40. However, using US data, Geronimus (1987:265-266) argued that the mortality consequences of adolescent fertility were largely a result of social factors and not merely the effect of age. He questioned the validity of the 'true age effect' paradigm currently existing in the demographic literature and argued that teenage mothers in the United States were more likely to come from economically disadvantaged groups and that a teenage birth was likely to occur under extreme social pressures (Geronimus, 1987:248-259). Babson and Clarke (1983) studied the relationship between maternal age and infant mortality, comparing the incidence of sudden infant death syndrome with other causes. Their study showed that the higher rates of neonatal mortality among the children of teenagers were explained by low birthweights, while post-neonatal mortality was mainly related to socio-environmental factors (Babson and Clarke, 1983:392-393). The association of low birthweight with
young maternal age at childbirth has also been observed in Cameroon (Defo and Partin, 1993:93-94).
The study by Santow and Bracher (1988:17-19) based on Australian data showed that, given the same previous sequences of reproductive outcomes, teenage mothers did not have a significantly greater risk of foetal loss than women in the age group 20-24. They described the elevated foetal loss ratios that had been observed among teenage mothers in earlier studies as a result of faulty arithmetic and hence spurious. They called for further evidence to show real excess risk in the teens.
Reasoning along a similar line, Trussed (1988:173-174) argued that the observed higher infant mortality among children of young mothers was predicated upon their non-use of prenatal care. This was borne out by the study of Davidson and Fukushima (1985:469) who found that children of adolescent mothers were low-risk children given adequate prenatal care; children of teenagers even experienced a lower perinatal mortality rate6 (7 per thousand) than those of mothers aged above 34 years (23 per thousand). Trussed (1988) pointed out that young mothers were also more likely to have poor socio economic backgrounds, and concluded that there was no biological cause for teenage mothers to experience higher infant mortality after age 15. Thus, he is in agreement with Bobadilla, Schlaepfer and Alagon's (1990:1) conclusion that there is no causal relationship between perinatal mortality and childbearing between ages 16 and 20. In fact, medical evidence tends to suggest that the prime age for childbearing would be between these ages (Merritt, Lawrence and Naeye, 1980, cited in Geronimus, 1987:249).
Behavioural factors therefore tend to be the major mechanism through which maternal age affects child survival. Apart from use of modern health services, breastfeeding practice is another behavioural factor which has appeared to differ by maternal age in some studies (Feinstein et al., 1986; Ryan et al., 1991; Peterson and DaVanzo, 1992).
6 Perinatal mortality rate is calculated as death per 1000 births, including stillbirths and deaths in the first