Prevalence and Associated Factors of Poststroke Depression among Outpatient Stroke Patients Who Have a Follow-Up at the Outpatient Neurology Clinic of Zewditu Memorial Hospital in Addis Ababa, Ethiopia

• Published in: Depression research and treatment Vol. 2022; pp. 9750035 - 7
• Main Authors: Wubshet, Tsion Yehualashet, Geberemichael, Sisay Gizaw, Adilo, Takle Menna, Arusi, Temesgen Tantu, Gutulo, Muluken Gunta, Assefa, Dereje Zewdu, Asfaw, Mekete Wondesen
• Format: Journal Article
• Language: English
• Published: United States Hindawi 22-03-2022; John Wiley & Sons, Inc; Hindawi Limited
• Subjects: Analysis; Angina pectoris; Confidence intervals; COVID-19; Data collection; Depression, Mental; Emotional disorders; Epidemiology; Hospitals; Medical research; Medicine, Experimental; Mental depression; Mental disorders; Mood disorders; Neurology; Population; Questionnaires; Regression analysis; Sample size; Social aspects; Social support; Sociodemographics; Stroke; Stroke patients; Supervisors; Variables; Sub-Saharan Africa; Ethiopia; Africa; Addis Ababa Ethiopia
• ISSN: 2090-1321; 2090-133X
• DOI: 10.1155/2022/9750035

Background. Poststroke depression is the most common and burdensome poststroke psychiatric complication. Studies showed discrepancies in reporting frequencies and risk factors for poststroke depression. Updated local data are relevant for efficient strategies of poststroke depression screening and prevention. Objectives. To determine the prevalence and associated factors of poststroke depression among outpatient stroke patients from the outpatient neurology clinic of Zewditu Memorial Hospital in Addis Ababa, Ethiopia. Methods. An institution-based cross-sectional study was conducted on 249 stroke patients. Data was collected through structured questionnaire using interviews and a review of medical charts. PHQ-9 depression questionnaire was used to diagnose poststroke depression. Descriptive analysis was used to see the nature of the characteristics of interests. Bivariate analysis was used to sort out variables at p values less than 0.05 for multivariate logistic regression. Significance level was obtained using an odds ratio with 95% CI and p value < 0.05. Results. Point prevalence for poststroke depression was 27.5 percent. Female gender, unemployment, low social support level, diabetes mellitus, and poststroke period under 2 years were statistically significant and independent predictors for poststroke depression. Conclusions. The point prevalence estimate of poststroke depression was comparable with other studies. Low social support levels increased the odds for poststroke depression by more than eight folds. It appeared that external factors are more important in the pathogenesis of poststroke depression in the African population. Detection and prevention programs should consider disparities of poststroke depression incidence and risk factors.