Trans-generational Impact of Maternal Obesity and Diabetes on Health Disparities

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DESCRIPTION (provided by the applicant): As obesity and diabetes increasingly affect women of childbearing age, understanding their public health impact on offspring health is paramount. If the obese and diabetic intrauterine environments are substantially contributing to these epidemics, not only will their prevalence continue to increase across all populations, but populations with a high prevalence of obesity and diabetes will continue to be disproportionately affected, resulting in a perpetual widening of health disparities between racial and ethnic groups. Black and Hispanic women, members of the two largest minority groups in the U.S., are not only more likely to be obese and have diabetes during pregnancy than non-Hispanic white women, but their body fat is distributed differently, their diabetes is more severe, and they have higher cardiovascular risk than non-Hispanic white women. Despite this, relatively few studies have examined potential racial/ethnic differences in the obese and diabetic intrauterine environments. South Carolina (SC) is largely rural and centrally located in the Southeastern United States, an area of the country historically plagued by obesity, diabetes and racial health disparities. We propose to investigate and characterize the epidemiology of diabetes and obesity during pregnancy and related birth outcomes in SC, a population-based setting, and to use a simulation model to predict the potential impact of maternal obesity and diabetes during pregnancy at the population level across multiple generations. Responding to RFA-MD-09-004 entitled, "NCMHD Health Disparities Research on Minority and Underserved Populations (R01)" will enable us to (1) examine the impact of maternal diabetes and obesity on racial disparities in maternal and infant outcomes in SC, (2) examine the intrauterine environment as a mechanism through which diabetes and obesity differentially impact infant outcomes across racial/ethnic groups in SC and (3) use a discrete event simulation model to predict the impact of maternal obesity and diabetes during pregnancy on their prevalence in subsequent generations in blacks, non-Hispanic whites and Hispanics in the United States. The research is innovative in that the team leaders consist of a systems engineer and an epidemiologist who proposes to use a systems engineering approach (simulation) to conduct research that goes beyond what is feasible in epidemiologic studies. The conceptual framework for our hypotheses is that a mother's health impacts her infant's health which in turn defines the population's health and subsequently impacts the next generation. Critical areas currently understudied are targeted by the study: the effects of maternal obesity and diabetes on infant health at the population level and a potential widening of racial/ethnic health disparities with respect to obesity and diabetes.