Obesity and diabetes in vulnerable populations: reflection on proximal and distal causes

Abstract

Around the world obesity and diabetes are climbing to epidemic proportion, even in countries previously characterized by scarcity. Likewise, people from low-income and minority communities, as well as immigrants from the developing world, increasingly visit physicians in North America with obesity, metabolic syndrome, or diabetes. Explanations limited to lifestyle factors such as diet and exercise are inadequate to explain the universality of what can be called a syndemic, a complex and widespread phenomenon in population health produced by multiple reinforcing conditions. Underlying the problem are complex factors-genetic, physiological, psychological, familial, social, economic, and political-coalescing to overdetermine these conditions. These interacting factors include events occurring during fetal life, maternal physiology and life context, the thrifty genotype, the nutritional transition, health impact of urbanization and immigration, social attributions and cultural perceptions of increased weight, and changes in food costs and availability resulting from globalization. Better appreciation of the complexity of causation underlying the worldwide epidemic of obesity and diabetes can refocus the work of clinicians and researchers to work at multiple levels to address prevention and treatment for these conditions among vulnerable populations.

Figure 1.

Pathways to obesity and diabetes.

Figure 2.

Model output for 3 intervention scenarios compared with the baseline scenario for diabetes prevalence (a) and complication-related deaths (b). From: Jones AP, Homer JB, Murphy DL, Essien JD, Milstein B, Seville DA. Understanding diabetes population dynamics through simulation modeling and experimentation. Am J Public Health. 2006;96(3):488–494 . Reprinted with permission from the American Public Health Association.

Figure 2.

Model output for 3 intervention scenarios compared with the baseline scenario for diabetes prevalence (a) and complication-related deaths (b). From: Jones AP, Homer JB, Murphy DL, Essien JD, Milstein B, Seville DA. Understanding diabetes population dynamics through simulation modeling and experimentation. Am J Public Health. 2006;96(3):488–494 . Reprinted with permission from the American Public Health Association.