Presenter(s): Aida Goma Petit − Anthropology (Double Concentration In Biological Anthropology And Archaeology)
Faculty Mentor(s): Josh Snodgrass , Alicia DeLouize
Poster 95
Research Area: Anthropology, Global Health, Depression, Global Mental Health
Depression is a leading contributor to disease burden worldwide. Although there are known and effective treatments for depression, far fewer than half of those affected by the disease will receive treatment, in part due to barriers in health care access contributing to underdiagnosis. Using the World Health Organization’s Study on global AGEing and adult health (SAGE) Wave 1 dataset, this study examines older adults (50+ years old) in Mexico (n = 1,725) to determine factors that may lead to depression as determined by a symptom-based algorithm, but not self-reported clinical depression diagnosis. We hypothesized that men were more likely to have depression without a self-reported clinical diagnosis. Hierarchical logistic regression analysis was utilized to examine the effects of sex, age, education, wealth, marital status, social relationships, and residence location (urban vs. rural) on depression diagnosis. Model 1 showed that females were, in fact, more likely than males to have depression without a self-reported diagnosis (β= 0.60, p = 0.006), but age (β = 0.00, p = 0.71) was not significant.
In model 2, being female was still a significant predictor of depression without a diagnosis (β= 0.62, p = 0.007) despite controlling for lower education (β = -0.03, p = 0.005) and more difficulty with interpersonal relationships (β = 0.45, p < 0.001). Age, wealth, marital status, and residence location (urban/rural) were not associated with undiagnosed depression. These findings highlight the importance of evaluating gender differences, improving education, and ameliorating social barriers to provide proper diagnosis and care for depression.