Abstract

Background: Few studies have investigated the sociodemographic impact on depression prevalence. This study aimed to describe the prevalence of depression according to sociodemographic characteristics.

Methods: A cross-sectional study was performed and involved 17,708 middle-aged and elderly participants (≥ 45years old) from the China Health and Retirement Longitudinal Study (CHARLS). Depression was diagnosed by Center for Epidemiological Studies Depression Scale-10 (CES-D) score. Multivariable logistic regression model was used to analyze the association between sociodemographic factors and depression by providing odd ratios (ORs) and 95% confidence intervals (CIs).

Results: The prevalence of depression in the middle-aged and elderly was 37.1% (30.2% for men and 43.2% for women, respectively). Multivariable logistic regression model showed that odds of depression in women was 1.82 (95% CI: 1.68-1.97) times than in men, while the odds of depression in rural area was 1.42 (95% CI: 1.31-1.55) times than in urban area. Moreover, the depression prevalence was positively associated with age, and negatively associated with body mass index (BMI), education and household income level (p for trend < 0.001). Compared with participants living in North region, the ORs and 95% CIs of depression among participants who lived in East, South-Central, North-West, SouthWest, and North-East regions were 0.81 (0.71-0.93), 0.95 (0.83-1.08), 1.36 (1.15-1.62), 1.26 (1.09-1.45), and 0.84 (0.70-1.00), respectively.

Conclusions: There was about one third of Chinese middle-aged and elderly having depression. Prior measures should be taken among high-risk middle-aged and elderly with lower education and income levels, older women, living in rural area or west China.