The Epidemiological Transition in Africa: Are There Lessons from Asia?
Sub-Saharan Africa remains the only major area in the world where the burden of infectious disease still outweighs the burden of noncommunicable disease and injuries. While the rates of decline in fertility and mortality vary considerably across the region, at least one clear pattern is emerging that holds across all of sub-Saharan Africa: a steady rise in noncommunicable disease (including cardio-metabolic and respiratory conditions as well as cancers) in the presence of significant, long-standing infectious disease prevalence.
In the session devoted to asking whether the experience in Asia offers any lessons for understanding the epidemiological transition in Africa, Stephen Tollman began his presentation by noting that while the coexistence of infectious and noncommunicable disease is well documented in the low-and middle-income countries of South America and Asia, the scale and intensity at which infectious and noncommunicable diseases are proceeding concurrently in sub-Saharan Africa is unprecedented. Given the prevalence and trends in HIV/AIDS, the interaction between infectious and noncommunicable diseases is likely to be prolonged in sub-Saharan Africa for decades. This will transpire at the same time that sub-Saharan Africa will see significant population aging, and these trends pose major challenges to economic and social development which the region’s health and social systems are—at least for now—unable to address.
In Asia, noncommunicable diseases (NCDs) are now the leading cause of death among adults in nearly every nation. However, the levels of NCDs do vary widely across countries. For example, while acute coronary events (heart attack) dominate death counts in India, stroke accounts for a greater proportion of NCD deaths in China. There are also clear differences in the rates of specific cancers: Indians experience more oral and lip cancers than lung cancers, for example, whereas lung cancer is a leading cause of death among Chinese adults. The growing preponderance of NCDs is a consequence of various factors, not the least of which is the rapid decline in fertility over the past several decades in many Asian nations. This decline, along with a decline in childhood-disease mortality, causes the shift in the age and cause-of-death structure that we call the epidemiologic transition. Much of Asia also has seen the emergence of tobacco use as a major cause of premature mortality among adults. Still, tuberculosis and malaria continue to pose significant burdens in India and also among adults in selected parts of Southeast Asia.
Tollman reported that in spite of the magnitude of the differences in mortality and morbidity between sub-Saharan Africa and much of Asia, the patterns of mortality and morbidity are not so different, with the clear exception of HIV/AIDS and its effects. To better understand the age—cause differences among countries and regions, Tollman described recent work aimed at identifying families of mortality trends, each of which reflects a different underlying mortality pattern. These families were identified by
analyzing standardized, pooled data from 24 INDEPTH data centers representing close to 20 million person-years of data and 207,000 deaths. As more data centers are added, the further goals will be to (1) further develop typical age patterns of mortality using longitudinal data from the INDEPTH network of demographic surveillance sites throughout Africa and South Asia; (2) build an easy-to-use system of model life tables based on the identified age patterns; and (3) use such data to support evaluations of progress towards the United Nations Millennium Development Goals.
This session also highlighted the potential for using INDEPTH data on individual and social exposures to explain differences in health outcomes. INDEPTH centers increasingly have the data to support such analyses, which will permit researchers to investigate the reasons for differences and inequalities across settings. Explanations for the observed patterns could include the effects of education, employment, and migration experience as well as the composition and economic status of households.
