医学
生物统计学
萧条(经济学)
社会经济地位
冲程(发动机)
优势比
公共卫生
流行病学
人口
纵向研究
老年学
置信区间
逻辑回归
人口学
环境卫生
内科学
机械工程
护理部
病理
社会学
工程类
经济
宏观经济学
作者
Qianru Cai,Mengyi Qian,Mei-Ling Chen
标识
DOI:10.1186/s12889-024-18503-z
摘要
Abstract Introduction Post-stroke depression (PSD) is a common neuropsychiatric complication that affects approximately one-third of stroke patients. The treatment and prognosis of this disease are poor. Socioeconomic status (SES) is closely related to health outcomes; however, only a few previous studies have focused on the association between SES and PSD. Given the substantial population of stroke patients in China, it is crucial to examine the potential risk factors associated with PSD. Conducting studies on this population and investigating the influence of economic conditions can provide valuable guiding theoretical insights into PSD prevention and management. Methods We used data from the 2018 China Health and Retirement Longitudinal Study and selected appropriate samples for analysis. Depression was estimated using the Center of Epidemiologic Studies Depression Scale-10, a validated tool for assessing depression in the general population. Multiple logistic regression analysis was employed to assess the association between SES and PSD and to evaluate any urban–rural differences. Results Of the 749 respondents, 370 (49.4%) had depression. Stroke patients with a middle school education demonstrated a greater risk of developing depression than those with a primary school education or below after adjusting for all control variables (odds ratio (OR) = 1.60, 95% confidence interval (CI): 1.03–2.51, P = 0.036). However, stroke patients with a high school education or above had a lower risk of developing depression than those with a primary school education or below (OR = 0.50, 95% CI: 0.28–0.88, P = 0.016). In rural areas, stroke patients with a high school or above education level had lower rates of depression than those with a primary school education or below (OR = 0.44, 95% CI: 0.21–0.91, P = 0.027). This difference was not significant in urban areas. Conclusions SES significantly influences the occurrence of PSD, which is reflected by education attainment and annual household expenditures. Education attainment was an independent influence on PSD, with a more pronounced effect in rural versus urban areas. We hope to reduce the prevalence of PSD and enhance the comprehensive management of this disease by modifying the influencing factors. Sex, self-reported health status, activities of daily living, night-time sleep duration, and life satisfaction also influenced the occurrence of PSD.
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