Frontiers in Psychiatry (Mar 2022)

What Is the Optimal Cut-Off Point of the 10-Item Center for Epidemiologic Studies Depression Scale for Screening Depression Among Chinese Individuals Aged 45 and Over? An Exploration Using Latent Profile Analysis

  • Hanlin Fu,
  • Lulu Si,
  • Ruixia Guo

DOI
https://doi.org/10.3389/fpsyt.2022.820777
Journal volume & issue
Vol. 13

Abstract

Read online

BackgroundThe main objective of the current study was to gain insight into the heterogeneity and profiles of depressive symptoms in Chinese individuals aged 45 and over and to determine the optimal cut-off point for the 10-item Center for Epidemiologic Studies Depression Scale (CES-D-10) to provide a reference for future practical application.MethodsThe participants were 16,997 Chinese community-dwelling adults aged 45 years or older who completed survey interviews for the 2018 China Health and Retirement Longitudinal Study. The current study utilised latent profile analysis (LPA) to identify distinct profiles based on participants’ responses to CES-D-10 items, and receiver operating characteristic (ROC) curve analyses were applied to determine the optimal cut-off point for the CES-D-10 scale.ResultsA three-profile solution was suggested as the optimum and included a “minimal depression” group (63.1%), “mild depression” group (23.4%) and “moderate-severe depression” group (13.5%); 36.9% (95% CI: 36.2 ∼ 37.6%) were considered at risk for probable depression. The “minimal depression” group was viewed as “non-cases,” and the remaining were viewed as “cases” that served as the reference standard for the ROC analysis, which obtained an AUC value of 97.8% (95% CI: 97.7–98.0%) and identified an optimal cut-off point of 10 (sensitivity:91.93%, specificity: 92.76%, and accuracy: 92.45).ConclusionThe identification of these distinct profiles underscores the heterogeneity in depressive symptoms among Chinese middle-aged and older adults. The CES-D-10 scale was demonstrated to have acceptable psychometric properties, with a cut-off point of 10 recommended for future research and practical application.

Keywords