ArticleFrontiers in aging neuroscience2022
Development and Validation of a Multimorbidity Index Predicting Mortality Among Older Chinese Adults.
Article in Frontiers in aging neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- How to assess multimorbidity: a systematic review.Frontiers in public health · 2025Pooled it
- Association of multimorbidity with mortality risk in Chinese senior adults: a population-based cohort study.BMC geriatrics · 2026Article
- Associations of dietary diversity trajectories with depressive symptoms among Chinese older adults: a 10-year longitudinal study.Frontiers in nutrition · 2026Article
- Higher-Order Disease Interactions in Multimorbidity Measurement: Marginal Benefit Over Additive Disease Summation.The journals of gerontology. Series A, Biological sciences and medical sciences · 2024Article
- Multimorbidity patterns and the relation to self-rated health among older Japanese people: a nationwide cross-sectional study.BMJ open · 2022Article
- The economic impact of multimorbidity in Italy: evaluation of direct costs and scenario analysis of patients with type 2 diabetes, heart failure, and chronic kidney disease using real-world data.Global & regional health technology assessmentArticle
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This study aimed to develop and validate a multimorbidity index using self-reported chronic conditions for predicting 5-year mortality risk. Methods: We analyzed data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) and included 11,853 community-dwelling older adults aged 65-84 years. Restrictive association rule mining (ARM) was used to identify disease combinations associated with mortality based on 13 chronic conditions. Data were randomly split into the training ( Results: A total of 13 disease combinations were identified. Compared with condition count (C-statistic: 0.710), MIDC (C-statistic: 0.713) showed significantly better discriminative ability (C-statistic: Conclusion: Although current multimorbidity status is commonly defined by individual chronic conditions, this study found that the multimorbidity index incorporating disease combinations showed supreme performance in predicting mortality among community-dwelling older adults. These findings suggest a need to consider significant disease combinations when measuring multimorbidity in medical research and clinical practice.
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