Contribution of Chronic Disease in Predicting Depression and Suicidal Ideation Among the Older Adult Population.

ABSTRACT:

Objective

This study aimed to clarify how chronic diseases (CDs) contribute to depression and suicidal ideation (SI) prediction using machine learning (ML) techniques among the older adult population.

Methods

National representative data of 5,419 older adults from the Korea National Health and Nutrition Examination Survey conducted in 2013, 2015, 2017, and 2019 were used in this study. The number and type of CDs were incorporated into Models 1 and 2, respectively, using five ML methods.

Results

The average age of the participants was 72.7 years, with 43.2% males, 15.2% reporting depression, and 7.3% reporting SI. The number of CDs was correlated with increased depression and SI. The ML models showed moderate-to-good performance in the prediction of depression and SI.

SUBMITTER: Seo Y 

PROVIDER: S-EPMC12444204 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature