Influencing factors associated with depression among middle-aged and older adults with disabilities: a latent profile analysis.

Abstract

This study aimed to explore heterogeneous profiles of depression among middle-aged and older adults with disabilities, and the influencing factors associated with the profiles were identified to provide a reference for improving mental health in this population. Data were obtained from the 2020 China Health and Retirement Longitudinal Study (CHARLS). A total of 3019 participants aged ≥45 years with disabilities were included. Latent profile analysis (LPA) was employed to identify profiles of depression. Chi-square tests, one-way ANOVA, and multivariate logistic regression were used to examine the influencing factors associated with different depression profiles among middle-aged and older adults with disabilities. The prevalence of depression among middle-aged and older adults with disabilities was 63.53%. Three depression profiles were identified: 'mild depression' (44.98%), 'severe depression-mild fear' (28.32%), and 'severe depression' (26.70%). Compared to 'mild depression', both severe depression profiles were associated with lower life satisfaction and poorer cognitive function. Other significant factors included gender, age, retirement, sleep hours per night, moderate physical activity, number of chronic diseases, bodily pain, and ADL disability. Depression among middle-aged and older adults with disabilities manifests in distinct latent profiles with varying severity and characteristics. Tailored interventions addressing lifestyle factors, chronic disease management, and functional support are needed to mitigate depression in this vulnerable population.