Determinants of Depression: Implications for African Americans and other populations during the COVID-19 pandemic

Abstract

Objective: To explore the impact of Social Determinants of Health (SDH) on the prevalence of selfreported
depression among adults aged ≥18 years in the United States to understand baseline data in
advance of an anticipated increase in depression due to the COVID-19 pandemic.
Methods: Data were analyzed from the 2017 Behavioral Risk Factor Surveillance System (BRFSS)
for adults aged ≥ 18 years. A multivariable logistic regression model was used to estimate the adjusted
odds ratios (AORs) and 95% confidence intervals (95% CIs) for factors associated with self-reported
depression. All analyses were conducted using SAS version 9.4.
Results: The results of the multivariable logistic regression analysis show that females (AOR: 1.80;
95% CI: 1.71-1.87); those with an annual household income of less than $50,000; those who were
divorced (AOR= 1.42; 95% CI=1.34-1.51); those who were separated (AOR= 1.41; 95% CI=1.23-1.60);
those who were never married (AOR= 1.24; 95% CI=1.16-1.32) and those who perceived their health as
poor (AOR= 2.18; 95% CI=2.07-2.30) were significantly more likely to report a history of depression
diagnosis. The findings also indicate that feeling unsafe or extremely unsafe in one's neighborhood, not
being able to pay bills, and having higher levels of stress were associated with higher odds of reporting
a history of depression diagnosis.
Conclusion: Three variables of SDH were associated with depression. Since these variables are also
impacted due to the COVID-19 pandemic, we can anticipate an increase in depression diagnoses. The
results of this study can be used to inform the allocation of resources for depression prevention and
treatment.