Recent advances in geographic information systems software and multilevel methodology provide opportunities for more extensive characterization of "at-risk" populations in epidemiologic studies. The authors used age-restricted, geocoded data from the all-African-American Jackson Heart Study (JHS), 2000-2004, to demonstrate a novel use of the Lorenz curve and Gini coefficient to determine the representativeness of the JHS cohort to the African-American population in a geographic setting. The authors also used a spatial binomial model to assess the geographic variability in participant recruitment across the Jackson, Mississippi, Metropolitan Statistical Area. The overall Gini coefficient, an equality measure that ranges from 0 (perfect equality) to 1 (perfect inequality), was 0.37 (95% confidence interval (CI): 0.30, 0.45), indicating moderate representation. The population of sampled women (Gini coefficient = 0.34, 95% CI: 0.30, 0.39) tended to be more representative of the underlying population than did the population of sampled men (Gini coefficient = 0.49, 95% CI: 0.35, 0.61). Representative recruitment of JHS participants was observed in predominantly African-American and mixed-race census tracts and in the center of the study area, the area nearest the examination clinic. This is of critical importance as the authors continue to explore novel approaches to investigate the geographic variation in disease etiology.