The Border Epidemiologic Study of Aging (BESA) offers the unique opportunity to investigate intra-group health disparities in a longitudinal study of 1133 middle aged and older Mexicans Americans. The proposed study builds and extends on three earlier waves of data and expands previous research to include two new emphases: the investigation of diabetes and health disparities. In exploring health disparities two additional dimensions of social stratification have been added, social trust and work productivity and conditions.
Five Specific Aims are proposed: 1)To examine and compare the dynamic association between socioeconomic status (SES) and disease, mainly diabetes and coronary heart disease which disproportionately affect the Mexican American population along the border; 2)To identify predictors of risk factors for diabetes and to explore the economic, social and psychological consequences of diabetes for this population over time; 3)To identify predictors and patterns of change, particularly, incidence rates for major diseases, changes in risk factors for major diseases; changes in productivity and earnings, family dynamics, acculturative status, and changes in social support and other ways of coping over time; 4)To identify predictors of mortality for each wave; 5)To identify predictors of survival for the 80+ in Waves 3 & 4. The proposed research strategies include: (1) Conducting extensive longitudinal analyses on the three waves of available data; (2) Building on the current three waves by collecting a fourth wave; (3) Increasing the current sub-sample of the 39-44 years old to 250 participants; and, (4) Gathering qualitative data through a series of focus groups and in-depth interviews with selected participants in the established BESA sample and in the younger sub-sample. A Social stratification theoretical model of Health is proposed. This model is used in drawing a set of hypotheses for each of the listed aims above. Various statistical methods are proposed in discussing hypotheses testing and evaluation.
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