The purpose of our proposed study is to test the hypothesis that racial discrimination is associated with the occurrence of well-known behavioral, anthropometric, and physiological risk factors for chronic disease and contributes to US black/white disparities in health. Salient to key objectives of the National Institutes of Health and Healthy People 2010 to eliminate racial/ethnic health disparities, our proposed study addresses the paucity of rigorous empirical research explicitly investigating links between racial discrimination and somatic health. Two new national reports: Measuring Racial Discrimination (National Research Council, 2004) and Unequal Treatment: Confronting Racial and Ethnic Disparities in Healthcare (Institute of Medicine, 2003) have recently emphasized the urgent need for sound scientific research on racial discrimination and health, with both additionally recommending use of multiple methods to measure experiences of racial discrimination, since any one method has its strengths and limitations. BUILDING ON A NEWLY CONDUCTED PILOT STUDY, We accordingly propose a multi-method study to investigate associations between (a) explicit and implicit measures of racial discrimination, AND (B) factors included in the metabolic syndrome AND THE FRAMINGHAM CORONARY HEART DISEASE PREDICTION SCORES: body mass index (BMI);waist circumference (WC);blood pressure;fasting glucose;TOTAL, HDL, and LDL cholesterol;triglycerides;DIABETES;AND SMOKING. These diverse well-established risk factors are relevant to 1 or more of the 3 major chronic diseases ~ cardiovascular disease, CANCER, AND DIABETES, each with black/white disparities - that contribute notably to black excess premature mortality. The study population will consist of a random sample of 1000 US-born non-Hispanic black and white adults (ages 35-64, 500 in each group) recruited from the membership base of a consortium of community-based health centers in Boston, MA. The explicit and implicit data on racial discrimination will be obtained, respectively, by: (1) self-report, using the newly psychometrically-validated """"""""Experiences of Discrimination"""""""" instrument developed by Krieger, and (2) an implicit association test (IAT), a cognitive reaction-time measure, building on use of the IAT to measure racial prejudice. Analyses to investigate whether the measured experiences of racial discrimination contribute to observed racial/ethnic disparities in the selected health outcomes will use structural equation modeling and other relevant statistical methods, taking into account relevant covariates. The public health significance of the proposed project is that it will provide novel evidence adding to the scant literature on links between racial discrimination and risk of chronic disease, AND ALSO YIELD preliminary data relevant to estimating the health care costs imposed by racial inequality, thereby generating new and needed data and insights regarding racial/ethnic health disparities.

National Institute of Health (NIH)
National Institute on Aging (NIA)
Research Project (R01)
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Kidney, Nutrition, Obesity and Diabetes (KNOD)
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Patmios, Georgeanne E
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Harvard University
Social Sciences
Schools of Public Health
United States
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Krieger, Nancy (2014) Discrimination and health inequities. Int J Health Serv 44:643-710
Krieger, Nancy; Waterman, Pamela D; Kosheleva, Anna et al. (2013) Racial discrimination & cardiovascular disease risk: my body my story study of 1005 US-born black and white community health center participants (US). PLoS One 8:e77174
Krieger, Nancy; Waterman, Pamela D; Kosheleva, Anna et al. (2011) Exposing racial discrimination: implicit & explicit measures--the My Body, My Story study of 1005 US-born black & white community health center members. PLoS One 6:e27636
Patton, Kristen K; Benjamin, Emelia J; Kosheleva, Anna et al. (2011) Early-life antecedents of atrial fibrillation: place of birth and atrial fibrillation-related mortality. Ann Epidemiol 21:732-8
Glymour, M Maria; Kosheleva, Anna; Boden-Albala, Bernadette (2009) Birth and adult residence in the Stroke Belt independently predict stroke mortality. Neurology 73:1858-65