The Impact of Social and Economic Indicators on Maternal and Child Health

As early as 1985, Rosenfield and Maine began to look at what is called the maternal child field (MCH). More than two decades later, maternal and infant mortality is still among the worst performing health indicator in resource-poor countries and regions, and it has barely changed since 1990. Although three of the eight United Nations Millennium Development Goals aim at reducing child mortality, maternal mortality, and promoting gender equality, most literature in the field is either clinical or exclusively deals with women’s health problems. In this study, I proposed an empirical model that tests the impact of gender equality, women’s human rights, and maternity care on MCH with economic and political development as background factors. The proposed model was tested by using structural equation analysis. Data were obtained from 137 developing countries. The proposed model is partially supported by the data. Empirical findings demonstrate that gender equality has a pivotal role to play in the promotion of MCH. The relationship between MCH and maternity care is found to be strong and statistically significant. This finding may permit a probable verification given the current social conditions in some developing countries, particularly the neglect of many of women’s health needs and the assignment of their primary responsibilities in childrearing. The women’s human rights hypothesis is not supported by the data. It is perhaps that human rights instruments provide a legal discourse for political functions and social welfare issues, but that the legal approach alone does not necessarily provide a moral and social foundation to ensure the implementation of social welfare and human well-being, particularly maternal and child health in developing countries. The findings also indicate the importance of economic development in predicting maternity care. Finally, a positive and statistically significant relationship is found between economic development and gender equality. Implications and limitations of the study are discussed.     

A method for deriving mortality estimates from incomplete vital Statistics

Summary Although they are available in many developing countries vital registration records are very little used for mortality estimation which is still mainly based on census returns. However, defective death records may yield accurate estimations of mortality. This procedure requires few data only; a sex-age distribution of the population (preferably at the middle of a period) and a sexage distribution of deaths, either derived from vital records or from census returns to questions relating to deaths during the preceding twelve months. This method is based on the observation that for a fixed age structure of the population, there is a one-one relation between the age structure of deaths (measured by the proportion of deaths at older ages) and the level of mortality (measured by the death rate above a certain minimum age). It is assumed that at ages above this minimum the rate of underregistration of deaths does not vary significantly with age. Therefore, the age distribution of registered deaths makes it possible to estimate the true proportion of deaths at older ages. This in its turn will permit the estimation of the true level of mortality, because of the relation which exists between age structure of deaths and level of mortality. The true level is then compared with the observed, to estimate the rate of underregistration, and observed age-specific death rates can be adjusted in the light of this knowledge.     

Maternal mortality in South Africa: lessons from a case study in the use of deaths reported by households in censuses and surveys

South Africa is unique in being a developing country which has asked questions on pregnancy-related deaths in both its 2001 census and 2007 household survey, and monitors maternal and pregnancy-related mortality through vital registration and a confidential enquiry into maternal deaths. These sources of data provide a wide range of estimates of maternal mortality for the country. This paper examines these estimates to assess to what extent the differences between them are due to data deficiencies, methodological deficiencies or definitional differences. The results show that since maternal deaths are relatively rare it is fairly difficult to establish the maternal mortality rate with a great degree of accuracy in a setting where data are less than perfect. They also show that to some extent the differences are due to differences and errors in processing of data but that pregnancy-related mortality should not be treated as synonymous with maternal mortality. However, after adjustment, pregnancy-related mortality from vital registration was comparable with the level that may be expected using several alternative approaches, while the rate reported by households in census and surveys was about double that from vital registration. Nonetheless, all the data indicate an upward trend in maternal mortality that is in keeping with the impact of the HIV/AIDS epidemic, which is likely to have contributed to the discrepancies.     

Estimating Mortality Differences in Developed Countries From Survey Information on Maternal and Paternal Orphanhood

In general, the use of indirect methods is limited to developing countries. Developed countries are usually assumed to have no need to apply such methods because detailed demographic data exist. However, the potentialities of demographic analysis with direct methods are limited to the characteristics of available macro data on births, deaths, and migration. For instance, in many Western countries, official population statistics do not permit the estimation of mortality by socioeconomic status (SES) or migration background, or for estimating the relationship between parity and mortality. In order to overcome these shortcomings, I modify and extend the so-called orphanhood method for indirect estimation of adult mortality from survey information on maternal and paternal survival to allow its application to populations of developed countries. The method is demonstrated and tested with data from two independent Italian cross-sectional surveys by estimating overall and SES-specific life expectancy. The empirical applications reveal that the proposed method can be used successfully for estimating levels and trends of mortality differences in developed countries and thus offers new prospects for the analysis of mortality.     

Maternal education and child health: Is there a strong causal relationship?

Using data from the first round of Demographic and Health Surveys for 22 developing countries, we examine the effect of maternal education on three markers of child health: infant mortality, children s height-for-age, and immunization status. In contrast to other studies, we argue that although there is a strong correlation between maternal education and markers of child health, a causal relationship is far from established. Education acts as a proxy for the socioeconomic status of the family and geographic area of residence. Introducing controls for husband’s education and access to piped water and toilet attenuate the impact of maternal education on infant mortality and children’s height-for-age. This effect is further reduced by controlling for area of residence through the use of fixed-effects models. In the final model. maternal education has a statistically significant impact on infant mortality and height-forage in only a handful of countries. In contrast. maternal education remains statistically significant for chidren’s immunization status in about one-half of the countries even after individual-level and community-level controls are introduced.     

Maternal mortality: What can we learn from stories of postpartum haemorrhage?

Death from pregnancy is rare in developed countries such as Australia but is still common in third world and developing countries. The investigation of each maternal death yields valuable information and lessons that all health care providers involved with the care of women can learn from. The aim of these investigations is to prevent future maternal morbidity and mortality.Obstetric haemorrhage remains a leading cause of maternal death internationally. It is the most common cause of death in developing countries. In Australia and the United Kingdom, obstetric haemorrhage is ranked as the 4th and 3rd most common cause of direct maternal death respectively. In a number of cases there are readily identifiable factors associated with the care that the women received that may have contributed to their death. It is from these identifiable factors that both midwives and doctors can learn to help prevent similar episodes from occurring.This article will identify some of the lessons that can be learnt from the recent Australian and UK maternal death reports. This paper presents an overview of the process and systems for the reporting of maternal death in Australia. It will then specifically focus on obstetric haemorrhage, with a focus on postpartum haemorrhage, for the 12-year period, 1994–2005. Vignettes from the maternal mortality reports in Australia and the United Kingdom are used to highlight the important lessons for providers of maternity care.     

Differences in mortality by marital status in Finland from 1976 to 2000: analyses of changes in marital-status distributions, socio-demographic and household composition, and cause of death

Being currently not married is more common today than 25 years ago. Over this period relative differences in mortality by marital status have increased in several countries, mainly as a result of a sharp decline in mortality among the married. Using Finnish census data linked with death certificates, we show that these increases are not explained by the non-married population becoming more marginalized in socio-economic status or household composition. However, the increases in marital-status differences in mortality from accidental, violent, and alcohol-related causes of death in the 30-64 age group indicate that changes in the health-related behaviour of the non-married population may play a role. The public-health burden associated with not being married has also grown. At the end of the 1990s about 15 per cent of all deaths above the age of 30 would not have occurred if the non-married population had had the same age-specific mortality rates as the married population.     

Estimation of demographic measures for India, 1881-1961, based on census age distributions

Abstract India is one of the very few developing countries which have a relatively long history of population censuses. The first census was taken in 1872, the second in 1881 and since then there has been a census every ten years, the latest in 1971. Yet the registration of births and deaths in India, even at the present time, is too inadequate to be of much help in estimating fertility and mortality conditions in the country. From time to time Indian census actuaries have indirectly constructed life tables by comparing one census age distribution with the preceding one. Official life tables are available for all the decades from 1872-1881 to 1951-1961, except for 1911-1921 and 1931-1941. Kingsley Davis(1) filled in the gap by constructing life tables for the latter two decades. He also estimated the birth and death rates ofIndia for the decades from 1881-1891 to 1931-1941. Estimates of these rates for the following two decades, 1941-1951 and 1951-1961, were made by Indian census actuaries. The birth rates of Davis and the Indian actuaries were obtained basically by the reverse survival method from the age distribution and the computed life table of the population. Coale and Hoover(2), however, estimated the birth and death rates and the life table of the Indian population in 1951 by applying stable population theory. The most recent estimates of the birth rate and death rate for 1963-1964 are based on the results of the National Sample Survey. All these estimates are presented in summary form in Table 1.     

Slum Residence and Child Health in Developing Countries

Continued population growth and increasing urbanization have led to the formation of large informal urban settlements in many developing countries in recent decades. The high prevalence of poverty, overcrowding, and poor sanitation observed in these settlements—commonly referred to as “slums”—suggests that slum residence constitutes a major health risk for children. In this article, we use data from 191 Demographic and Health Surveys (DHS) across 73 developing countries to investigate this concern empirically. Our results indicate that children in slums have better health outcomes than children living in rural areas yet fare worse than children in better-off neighborhoods of the same urban settlements. A large fraction of the observed health differences appears to be explained by pronounced differences in maternal education, household wealth, and access to health services across residential areas. After we control for these characteristics, children growing up in the slums and better-off neighborhoods of towns show levels of morbidity and mortality that are not statistically different from those of children living in rural areas. Compared with rural children, children living in cities (irrespective of slum or formal residence) fare better with respect to mortality and stunting but not with respect to recent illness episodes.     

2000-2010年福建省人口死亡统计分析

人口死亡水平的变动与趋势包含了与社会发展互为因果的潜在信息,对其进行挖掘可以为人口数量与素质、城市化与劳动就业、人口分布与资源环境承载力以及人口老龄化等问题的解决提供重要参考。基于“五普”、“六普”的人口普查数据,文章利用模型生命表方法对福建省的人口死亡率进行了校正;宏观角度对比分析了2000年-2010年福建省人口死亡水平与模式变化,微观多角度剖析了设区市之间预期寿命、婴儿死亡的差异及其原因。研究结论为：一是福建省人口死亡率显著降低,人口健康水平大幅提升,婴儿死亡漏报、错报问题明显减少;二是九个设区市之间的死亡模式存在地区差异,城市化水平、生育水平及社会卫生条件是差异产生的显著性影响因素,但经济发展、教育水平和公共医疗卫生的作用不明显。     

Bayesian population reconstruction of female populations for less developed and more developed countries

We show that Bayesian population reconstruction, a recent method for estimating past populations by age, works for data of widely varying quality. Bayesian reconstruction simultaneously estimates age-specific population counts, fertility rates, mortality rates, and net international migration flows from fragmentary data, while formally accounting for measurement error. As inputs, Bayesian reconstruction uses initial bias-reduced estimates of standard demographic variables. We reconstruct the female populations of three countries: Laos, a country with little vital registration data where population estimation depends largely on surveys; Sri Lanka, a country with some vital registration data; and New Zealand, a country with a highly developed statistical system and good quality vital registration data. In addition, we extend the method to countries without censuses at regular intervals. We also use it to assess the consistency of results between model life tables and available census data, and hence to compare different model life table systems.     

Mortality among elderly hispanics in the United States: Past evidence and new results

We used vital records and census data and Medicare and NUMIDENT records to estimate age- and sex-specific death rates for elderly non-Hispanic whites and Hispanics, including five Hispanic subgroups: persons born in Cuba, Mexico, Puerto Rico, other foreign countries, and the United States. We found that corrections for data errors in vital and census records lead to substantial changes in death rates for Hispanics and that conventionally constructed Hispanic death rates are lower than rates based on Medicare-NUMIDENT records. Both sources revealed a Hispanic mortality advantage relative to non-Hispanic whites that holds for most Hispanic subgroups. We also present a new methodology for inferring Hispanic origin from a combination of surname, given name, and county of residence.     

A census-based method for estimating adult mortality

Abstract A simple method is presented for converting an age distribution in any closed population into the stationary population corresponding to its current mortality conditions. The conversion only requires a set of age-specific growth rates, which will normally be available from successive censuses. From the stationary population, any life table mortality measure of interest can be computed. The index most robust to normal data errors in developing countries is life expectancy, and the paper focuses on its calculation. The sensitivity of results to various forms of data error is considered, and procedures are proposed for removing errors resulting from differential census coverage completeness and from age misstatement at older ages. Applications of the procedures are made to data from Sweden, India and South Korea. Because of the absence of a radix, estimation of life expectancy usually will begin at the fifth birthday.     

Long-term effect of in utero conditions on maternal survival later in life: evidence from Sub-Saharan Africa

Sub-Saharan African countries have some of the world’s highest rates of maternal mortality. Most research on maternal mortality focuses on factors during pregnancy and delivery. However, consistent with the fetal programming hypothesis, a woman’s maternal survival may also be related to conditions she experienced while in utero. I examine this hypothesis in 14 African countries by relating rainfall when a woman was in utero with her maternal survival later in her life. High levels of rainfall, representing better in utero conditions, decrease the probability of maternal death by 1.1 percentage points, a 58 % decrease from a mean of 1.9 %. Higher rainfall while in utero reduces the probability of anemia during pregnancy, a risk factor for postpartum hemorrhage. Another plausible pathway is through a reduction in body mass index, a predictor of pregnancy-induced hypertension. Improving conditions for pregnant women will have inter-generational effects, benefiting pregnant women today and improving their daughters’ maternal survival.     

Lifetime risk of pregnancy-related death among Zambian women: district-level estimates from the 2010 census

The aim of this study was to examine district differentials in the lifetime risk of pregnancy-related death among females aged 15–49 in Zambia. We used data on household deaths collected in the 2010 census to estimate the lifetime risk of pregnancy-related death among females in Zambia. Using all-cause age-specific death rates, we generated female life tables for 74 districts and estimated person-years of exposure to all-cause mortality at each age. We then applied age-specific pregnancy-related mortality rates to the person-years of exposure to obtain estimates of adult lifetime risk that took account of competing causes of death. We used the ArcGIS software to analyse clustering and the spatial distribution of risk. A female aged 15 in Zambia had a 3.7 % chance of dying a pregnancy-related death before the age of 50. At district level, the lifetime risk ranged from 1.7 to 7.7 %. The Global Moran’s I was 0.452 (z-score 5.8, p value <0.01), indicating clustering of districts with similar risk levels of pregnancy-related mortality. Clustering of high-risk districts was found in Western province while clustering of low risk districts was found in Lusaka and Muchinga provinces. The level of adult lifetime risk was more positively associated with pregnancy-related mortality than with fertility. Females in Zambia have a high lifetime risk of pregnancy-related death overall but this risk varies greatly across the different districts of the country. The observed diversity is larger than when merely studying differences between provinces and is only weakly linked to differences in fertility levels. The identification of districts with varying levels of risk should enable evidence-based and focused delivery of maternal health services in districts where risk of death from maternal causes is greatest.     

死亡人口受教育水平的预测模型和效果研究——对中国1990～2010年省级面板数据的估计

由于缺乏健全的死亡民事登记和医疗登记制度,中国死亡人口的受教育水平只能获得人口普查年份的数据,非普查年份数据只能用普查年份数据代替,这种替代法在使用中存在诸多不足,构建模型对非普查年数据进行估计是另一种可行的方法。本研究利用经过识别和有效性检验的模型,以社会经济发展水平、人口结构水平、医疗卫生水平和存活人口受教育水平作为解释变量,利用可得资料对1990²010年期间非普查年份数据进行估计,得到更为有效的省级死亡人口受教育水平逐年数据。     

Model life tables: An empirical test of their applicability to less developed countries

Model life tables are commonly used for estimating various parameters of mortality of populations in developing countries with limited data. The application of the models is based on the assumption that the agemortality pattern of the population under consideration resembles one of the life tables in the models. The analysis in this paper tests the validity of this assumption for developing countries with data usable for the purpose. The major conclusion is that infant mortality in the populations analyzed is higher than predicted by the models corresponding to the levels of adult mortality of these populations. The observed discrepancy is ascribed to the selectivity involved in the construction of model life tables, which are primarily derived from the historical experience of Western countries. Populations in the currently developing countries apparently differ in the process of mortality change from those used in the models. Though the analysis is limited to a few countries and may not necessarily be true for all the less developed countries, it suggests the need for caution in the use of conventional model life tables.     

Causes of death to women of reproductive age in two developing countries

Data on cause of death are deficient for most developing countries. Nevertheless, it is important for policy makers to have access to such information to plan the use of resources and to evaluate health programs. In this study, deaths among women of reproductive age (15 to 49) in two areas in developing countries were located, and family members were interviewed. Local physicians reviewed the completed interviews and determined the cause of death.Complications of pregnancy and childbirth were the cause of 23% of the deaths in Menoufia, Egypt and Bali, Indonesia. In Egypt, the first cause of death was circulatory system disease (28%), followed by complications of pregnancy and childbirth (23%), and trauma (14%, primarily burns). In Indonesia, complications of pregnancy and childbirth was the first cause of death, followed by infectious disease (22%, primarily tuberculosis), and circulatory system disease (13%).Although the method of data collection was unorthodox, findings for Menoufia are comparable to data from other sources for the country as a whole. There are few data with which to compare our findings for Bali, but their similarity to the data from the Egyptian study lends credence to their quality.     

Separating the Signal From the Noise: Evidence for Deceleration in Old-Age Death Rates

Widespread population aging has made it critical to understand death rates at old ages. However, studying mortality at old ages is challenging because the data are sparse: numbers of survivors and deaths get smaller and smaller with age. I show how to address this challenge by using principled model selection techniques to empirically evaluate theoretical mortality models. I test nine models of old-age death rates by fitting them to 360 high-quality data sets on cohort mortality after age 80. Models that allow for the possibility of decelerating death rates tend to fit better than models that assume exponentially increasing death rates. No single model is capable of universally explaining observed old-age mortality patterns, but the log-quadratic model most consistently predicts well. Patterns of model fit differ by country and sex. I discuss possible mechanisms, including sample size, period effects, and regional or cultural factors that may be important keys to understanding patterns of old-age mortality. I introduce mortfit, a freely available R package that enables researchers to extend the analysis to other models, age ranges, and data sources.     

Child mortality in India: the community-level effect of education

When assessing the health benefits of increased education in less developed countries, many researchers have been concerned about the omission of important determinants of an individual's education from the models. The study presented here shows that one should also be concerned about the limitations of the individual-level perspective. According to a multilevel discrete-time hazard model estimated with data from the National Family Health Survey II, the average education of women in a census enumeration area has a strong impact on child mortality, in addition to the effect of the mother's own education. The lower child mortality associated with women's autonomy is taken into account in this estimation. Results from similar models for various health and health-care variables suggest that the effect of community education, like that of individual education, operates through the use of maternity services and other preventive health services, the child's nutrition, and the mother's care for a sick child.