Latent Profile Analysis of Depression and Its Influencing Factors Among Frail Older Adults in China.

Abstract

The present investigation set out to examine potential categories regarding depressive symptoms in frail senior individuals in China and to identify the contributing variables associated with each category, with the goal of informing more targeted mental health interventions. Data were drawn from the 2018 China Health and Retirement Longitudinal Survey, commonly called CHARLS, which comprised an overall cohort of 1083 qualifying respondents. A latent profile analysis (LPA) revealed the following four distinct depression profiles: a Low Depression-High Loneliness Group (38.4%), a Moderately Low Depression-High Suicidal Ideation Group (7.5%), a Moderately High Depression-High Negative Emotion Group (33.4%), and a High Depression-High Suicidal Ideation Group (20.7%). Ordered multi-categorical logistic regression and restricted cubic spline analyses revealed that age, gender, body pain, pension insurance, sleep duration, and frailty index were significant predictors of depression classification. These findings suggest that depressive symptoms among frail older individuals in China are markedly heterogeneous, highlighting the need to develop differentiated intervention strategies for distinct depression risk groups to promote their mental health.