October 1, 2019 at 10:26 am

Miller Presents on Depression Across Racial Groups at American Sociological Association

Dr. Paula Miller

Dr. Paula Miller, Assistant Professor of Sociology in the College of Arts & Sciences at Ohio University, presented “Uncovering Profiles of Economic, Social, and Cultural Capital to Explore Depression Across Racial Groups” at the annual meeting of the American Sociological Association in August in New York. The meeting was a chance for those involved in the social sciences to share current research and steer the field in new directions.

Abstract: Research exploring the association between socio-economic status (SES) and depression is limited by conceptualizations of SES and conflicting findings across racial groups. We broaden previous research by (1) reconceptualizing SES through the lens of Bourdieusian theory to identify profiles of economic, social, and cultural capital; (2) investigating whether these profiles differ for Black and white adults; and (3) exploring whether specific profiles of capital are associated with increased depression scores. This study analyzed secondary data from the National Longitudinal Study of Adolescent to Adult Health, a nationally representative sample of US individuals. A sub-population of the sample was used, which was comprised of 4339 Black and white participants from wave IV. To address the study aims, we used the new three-step approach to conducting latent class analysis. We identified five profiles of capital, the composition of which varied by race. Compared to Blacks, whites were more likely to be in the “cultural-economic capital” (14% vs. 10%), “elevated overall capital” (35% vs. 14%), and “social-economic capital” (13% vs. 10%) profiles, whereas Blacks were more likely to be in the “limited overall capital” (35% vs. 16%) and “moderate economic capital” (32% vs 22%) profiles. Profiles differed in risk for depression; the “limited overall capital” profile had the highest depression scores, whereas the “elevated overall capital” profile had the lowest depression scores. This research has the potential to reduce health disparities, by providing policy makers and researchers with information that will allow them to target populations that are most at risk for depression.