Race/Ethnicity, Socioeconomic Status, and Polypharmacy among Older Americans

Abstract

Background: Very few studies with nationally representative samples have investigated the combined effects of race/ethnicity and socioeconomic position (SEP) on polypharmacy (PP) among older Americans. For instance, we do not know if prevalence of PP differs between African Americans (AA) and white older adults, whether this difference is due to a racial gap in SEP, or whether racial and ethnic differences exist in the effects of SEP indicators on PP. Aims: We investigated joint effects of race/ethnicity and SEP on PP in a national household sample of American older adults. Methods: The first wave of the University of Michigan National Poll on Healthy Aging included a total of 906 older adults who were 65 years or older (80 AA and 826 white). Race/ethnicity, SEP (income, education attainment, marital status, and employment), age, gender, and PP (using 5+ medications) were measured. Logistic regression was applied for data analysis. Results: Race/ethnicity, age, marital status, and employment did not correlate with PP; however, female gender, low education attainment, and low income were associated with higher odds of PP among participants. Race/ethnicity interacted with low income on odds of PP, suggesting that low income might be more strongly associated with PP in AA than white older adults. Conclusions: While SEP indicators influence the risk of PP, such effects may not be identical across diverse racial and ethnic groups. That is, race/ethnicity and SEP have combined/interdependent rather than separate/independent effects on PP. Low-income AA older adults particularly need to be evaluated for PP. Given that race and SEP have intertwined effects on PP, racially and ethnically tailored interventions that address PP among low-income AA older adults may be superior to universal interventions and programs that ignore the specific needs of diverse populations. The results are preliminary and require replication in larger sample sizes, with PP measured directly without relying on individuals’ self-reports, and with joint data collected on chronic disease.