FIELD CENTER FOR CCSP

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ARIC is a large-scale, long-term program that will measure associations of established and suspected coronary heart disease risk factors (CHD) with both atherosclerosis and new CHD events such as myocardial infarction in men and women from four diverse communities. The project has two components: community surveillance of morbidity and mortality, and repeated examinations of a representative cohort of men and women in each community. The community surveillance involves abstracting hospital records and death certificates and investigating out-of- hospital deaths. The representative cohorts include 4,000 persons from each community. Three of these reflect the ethnic composition of the communities in which they live; one cohort is black. All cohort participants are examined four times (1987-90), and 1990-93, 1993-96, and 1996-99), and contacted annually to update their medical histories. Atherosclerosis is measured by carotid and ultrasonography. Arteriosclerosis is measured using retinal photography. Cerebrovascular disease is assessed using MRI in a sample of black and white participants. Rick factors studied include: blood lipids, lipoprotein cholesterols, and apolipoproteins; plasma hemostatic factors; diabetes and glucose intolerance; blood chemistries and hematology and indicators and infectious and inflammatory disease; DNA markers of these risk factors; sitting, supine and standing blood pressures to track the development of hypertension; anthropometry; fasting blood glucose and insulin level as predictors of diabetes; ECG findings; heart rate variability; cigarette and alcohol use; physical activity level; dietary aspects; and family history. The diverse communities can be compared with respect to CHD incidence and medical care and, through the cohort component, with respect to risk factors and peripheral atherosclerosis. The results will provide a measure of the variation in the distribution and determinants of CHD in the U.S. and, within the limits of ecologic analysis, suggest possible reasons for observed differences.