Development of a machine learning-based risk assessment model for loneliness among elderly Chinese: a cross-sectional study based on Chinese longitudinal healthy longevity survey

The study found a 23.4% prevalence of loneliness among elderly individuals in China. SHAP values indicated that marital status has the strongest evaluative value across all forecasting periods. Specifically, elderly individuals who are never married, widowed, divorced, or separated are more likely to experience loneliness compared to their married counterparts.

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Publication Details

Journal
BMC Geriatrics
Published
2024-11-13
DOI
https://doi.org/10.1186/s12877-024-05443-x
Citations
5
Primary Topic
Health disparities and outcomes
Type
article
Field-Weighted Citation Impact
2.64

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article

Development of a machine learning-based risk assessment model for loneliness among elderly Chinese: a cross-sectional study based on Chinese longitudinal healthy longevity survey

Yen‐Chun Lin, Chuang Li, Hongyu Li, Xiuli Wang
5 citations
BMC Geriatrics
Health disparities and outcomes
2.64
article

Development of a machine learning-based risk assessment model for loneliness among elderly Chinese: a cross-sectional study based on Chinese longitudinal healthy longevity survey

Yen‐Chun Lin, Chuang Li, Hongyu Li, Xiuli Wang
article en
5 citations

Abstract

The study found a 23.4% prevalence of loneliness among elderly individuals in China. SHAP values indicated that marital status has the strongest evaluative value across all forecasting periods. Specifically, elderly individuals who are never married, widowed, divorced, or separated are more likely to experience loneliness compared to their married counterparts.

BMC GeriatricsVol. 24(1)
Jinzhou Medical University (CN)
Peking University
Openalex Percentile: Top 9%
Health disparities and outcomes
2.64
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