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Socio-Economic Differences in Health, Nutrition, and Population Within Developing Countries: An Overview
By D. R. Gwatkin, S. Rutstein, K. Johnson, E. Suliman, A. Wagstaff, and A. Amozou.
Washington, DC, World Bank, 2007.
http://go.worldbank.org/XJK7WKSE40.
JAMA. 2007;298:1943-1944.
Around 1990, a child born in sub-Saharan Africa was 20 times more likely to die by age 5 years than one born in a developed country. Ten years later, the gap had increased 29-fold.1 Similar gaps are also present within low- and middle-income countries, but these are still greatly overlooked. For instance, research in an impoverished area of rural Tanzania examining this relationship between household assets (eg, ownership of bicycles, radios, tin roofs) and health status demonstrated that among those in the poorest quintile of wealth, not a single child with recent symptoms of pneumonia was given an antibiotic, compared with a third of those in the upper quintile receiving antibiotics. Even the least poor were grossly undertreated, but there were consistently marked disparities, even in the midst of appalling poverty.2
The use of household assets to rank families according to wealth gained popularity in the 1990s.3 Asset indices are more reliable and much easier to collect than data on income, consumption, or expenditure. Assets are also more constant over time than other similar measures. Their incorporation in nationally representative maternal and child health surveys—eg, demographic and health surveys (DHS)4 and multiple indicator cluster surveys5—that are carried out in approximately 100 low- and middle-income countries provides a unique opportunity for equity analyses.
The World Bank has launched an ambitious project—the PovertyNet.6-7 A high point of this project has been the recent publication of this report, entitled Socio-Economic Differences in Health, Nutrition, and Population Within Developing Countries: An Overview, a reanalysis of 56 recent national DHS providing a breakdown of 120 indicators by wealth quintiles. The indicators cover traditional maternal and child health variables such as child mortality and morbidity, nutritional status of children and women, childhood immunizations, treatment of childhood illnesses, antenatal and delivery care, hygiene practices, use of mosquito nets for malaria prevention, breastfeeding, and micronutrient consumption. They also include information on sexual and reproductive health, fertility and contraception, human immunodeficiency virus/AIDS, female circumcision, sexually transmitted diseases, treatment of select adult illnesses, and sexual practices. In addition, a broader set of indicators is presented, including alcohol and tobacco use, domestic violence, education, exposure to mass media, and status of women.
This World Bank report has become the main source of information on within-country health inequities. Its short introduction discusses the advantages and limitations of asset indices and summarizes the key messages arising from the analyses. The messages are that (1) the poor fare worse in terms of health outcomes and are less likely to benefit from effective, life-saving public health interventions; (2) strategies designed to benefit the poorest, such as primary health care, have proven more likely to reach those who are better off; and (3) the poor will likely be left behind in future improvements, because new effective interventions tend to be first adopted by the rich.
To counteract this bleak scenario, the authors propose feasible strategies for monitoring whether country-level programs and interventions are effectively reaching the poorest individuals. One simple option is to administer a short questionnaire on household assets to program recipients, for example, pregnant women leaving antenatal clinics in a given geographical area. Alternatively, program users can be identified through simple household surveys. The distribution of users in terms of asset quintiles can then be compared with that in the national DHS, as the authors propose, or with local quintile distributions—disaggregated from national census data. These simple analyses can classify a program as pro-poor (if more than 20% of its recipients belong to the lowest asset quintile) or as pro-rich if otherwise. Sadly, a majority of the programs most likely will fall into the latter category.
To avoid being simplistic, not all differences favor the rich. For example, wealthy mothers are more likely to bottle-feed their babies and to breastfeed them for short periods. Information on cesarean births is not presented, but unnecessary operations are more prevalent among the rich, as a separate DHS analysis showed.7 The same is true for childhood obesity, at least in middle-income countries.8 It appears that whatever is perceived as being good—truly effective interventions such as vaccines or necessary antibiotics but also baby bottles, cesarean births, or treatment for childhood obesity—tends to be more frequent among those who are better off.
Socioeconomic inequalities in health care are persistent yet dynamic. As some conditions are eradicated—for example, polio, measles, or neonatal tetanus—new inequities arise to take their place—for example, unequal access to new technologies such as obstetric ultrasound or admission to neonatal intensive care. Indeed, health inequities are found wherever and whenever one looks for them.
Gwatkin and colleagues provide a snapshot of global inequities in maternal and child health. Because the countries in their analyses range from the poorest nations on earth to relatively developed middle-income societies, many further analyses of their data are possible. For example, how does the shape of the quintile curves change according to the level of economic development? Which countries are outliers in terms of achieving greater equity, and what can be learned from them? How can their results be used to mainstream equity considerations when planning and implementing maternal and child health programs?
The bottom line from this remarkable report is that unless there is a proactive effort at reaching the poor through the design and monitoring of maternal and child health interventions, inequities in health will remain unchanged or even worsen as new technologies are introduced. Leaders from almost 200 countries met in 2000 to propose an ambitious set of Millennium Development Goals, including the reduction by two-thirds of mortality among children younger than 5 years and by four-fifths of maternal mortality by 2015. The work by Gwatkin and colleagues provides compelling evidence that progress toward these goals will fail unless equity is taken seriously.
Financial Disclosures: None reported.
Editor's Note: Socio-Economic Differences in Health, Nutrition, and Population Within Developing Countries was produced by the World Bank in collaboration with the government of the Netherlands and the Swedish International Development Cooperation Agency.
Cesar G. Victora, MD, PhD, Reviewer
Federal University of Pelotas, Brazil
Pelotas, RS, Brazil
cvictora{at}terra.com.br
REFERENCES
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1. Victora CG, Wagstaff A, Schellenberg JA, Gwatkin D, Claeson M, Habicht JP. Applying an equity lens to child health and mortality: more of the same is not enough. Lancet. 2003;362(9379):233-241.
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2. Schellenberg JA, Victora CG, Mushi A, et al. Inequities among the very poor: health care for children in rural southern Tanzania. Lancet. 2003;361(9357):561-566.
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3. Filmer D, Pritchett LH. Estimating wealth effects without expenditure data—or tears: an application to educational enrollments in states of India. Demography. 2001;38(1):115-132.
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4. DHS surveys: overview. Demographic and Health Surveys (DHS) Web site. http://www.measuredhs.com/aboutsurveys/dhs/start.cfm. Accessed September 9, 2007.5. Multiple Indicator Cluster Surveys (MICS). United Nations Children's Fund Web site. http://www.childinfo.org/. Accessed September 9, 2007.6. PovertyNet. World Bank Web site. http://www.worldbank.org/poverty/. Accessed September 9, 2007.7. Ronsmans C, Holtz S, Stanton C. Socioeconomic differentials in caesarean rates in developing countries: a retrospective analysis. Lancet. 2006;368(9546):1516-1523.
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8. Wang Y, Monteiro C, Popkin BM. Trends of obesity and underweight in older children and adolescents in the United States, Brazil, China, and Russia. Am J Clin Nutr. 2002;75(6):971-977.
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Book and Media Reviews Section Editor: John L. Zeller, MD, PhD, Contributing Editor.
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