Key Factors Associated with Major Depression in a National Sample of Stroke Survivors

Abstract

Background: Depression, one of the most common complications encountered after stroke, is associated with poorer outcomes. The aim of this study was to determine the factors independently associated with and predictive of poststroke depression (PSD).

Methods: We assessed the prevalence of depression (Patient Health Questionnaire [PHQ-8] score >10) among a national sample of adults (≥20 years) with stroke who participated in the National Health and Nutrition Examination Surveys from 2005 to 2010. Logistic regression and random forest models were used to determine the factors associated with and predictive of PSD, after adjusting for sociodemographic and clinical factors.

Results: Of the 17,132 individuals surveyed, 546 stroke survivors were screened for depression, and 17% had depression, corresponding to 872,237 stroke survivors with depression in the United States. In the logistic regression model, after adjustment for sociodemographic variables, poverty (poverty index <200% versus ≥200%, odds ratio [OR] 2.61, 95% confidence interval [CI] 1.23-5.53) and 3 or more medical comorbidities (OR 1.59, 95% CI 1.01-2.49) were associated with higher odds of PSD; increasing age was associated with lower odds of PSD (per year OR .95, 95% CI .94-.97). In the random forest model, the 10 most important factors predictive of PSD were younger age, lower education level, higher body mass index, black race, poverty, smoking, female sex, single marital status, lack of cancer history, and previous myocardial infarction (specificity = 70%, sensitivity = 64%).

Conclusion: Although numerous factors were predictive of developing PSD, younger age, poverty, and multiple comorbidities were strong and independent factors. More aggressive screening for depression in these individuals may be warranted.

Keywords: Depression; NHANES; factors; poststroke depression; stroke.