Prevalence and associated factors of post-stroke depression among patients on follow-up at medical referral clinics of Bahir Dar city public specialized hospitals

• Published in: BMC neurology 2024-12, Vol.24 (1), p.470-9, Article 470
• Main Authors: Debebe, Ermiyas Yemane, Biyadgie, Mulugeta, Chekol, Hanamariam Abebe, Asmare, Lakew, Yigzaw, Zeamanuel Anteneh
• Format: Article
• Language: English
• Subjects: Adult; Aged; Analysis; Aphasia; Bahir Dar; Care and treatment; Clinics; Complications and side effects; Cross-Sectional Studies; Depression - epidemiology; Depression - etiology; Depression, Mental; Diabetes; Emotional disorders; Female; Follow-Up Studies; Health surveys; Heart diseases; Hospitals; Hospitals, Public; Hospitals, Special - statistics & numerical data; Humans; Interviews; Ischemia; Male; Medical referral; Medical referral clinic; Medical referrals; Mental depression; Mental disorders; Middle Aged; Mood disorders; Mortality; Neurology; Patients; Post-stroke depression; Prevalence; Prevalence studies (Epidemiology); Prevention; Prospective Studies; Public health; Quality of life; Questionnaires; Referral and Consultation - statistics & numerical data; Risk Factors; Sample size; Sociodemographics; Statistical analysis; Stroke; Stroke (Disease); Stroke - complications; Stroke - epidemiology; Stroke - psychology
• ISSN: 1471-2377; 1471-2377
• DOI: 10.1186/s12883-024-03974-9

Post-stroke depression is among the most common neuropsychiatric complications in stroke survivors. Post-stroke depression is commonly under-recognized and under-treated. This study aimed to assess the prevalence and associated factors of post-stroke depression among patients on follow-up at medical referral clinics of Bahir Dar City public specialized hospitals. An institutional-based prospective cross-sectional study was conducted from September to December 2023 on 394 patients. Public Health Questionnaire-9 was used to diagnose depression. Data was checked for cleanness manually and then exported to SPSS version 25 software for analysis. A systematic randomized sampling method was used to identify study participants. Bivariate and multivariate logistic regression analysis was performed to identify independent predictors of post-stroke depression. A p-value less than 0.05 is considered as significant with a 95% confidence interval. The overall prevalence of post-stroke depression was found to be 42.9%. Employment status (AOR = 0.282, 95% CI: 0.112-0.709 C, P-value = 0.007), depression before stroke (AOR = 3.237, 95% CI: 1.098-9.544, P-value = 0.033), ischemic heart disease (AOR = 4.090, 95% CI: 1.745-9.583, P-value = 0.001) and physical disability (AOR = 4.051 95% CI: 2.239-7.332, P-value = 0.000) were found to be statistically significant independent predictors of post-stroke depression (PSD). The prevalence of post-stroke depression was found to be high relative to other similar studies. Patients with known depression before stroke, ischemic heart disease, and significant physical disability were at a higher risk of developing PSD. Employed patients had less risk of developing PSD. Sufficient and comprehensive evaluation of stroke patients for depression is recommended.