ArticlePloS one2023
Latent class analyses of multimorbidity and all-cause mortality: A prospective study in Chilean adults.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 11 citations in OpenAlex.
- Multimorbidity Patterns and Mortality Risk in a National Sample of US Adults Identified Using Latent Class Analysis.Diseases (Basel, Switzerland) · 2026Article
- Multimorbidity patterns, sociodemographic characteristics, and mortality: Data science insights from low-resource settings.American journal of epidemiology · 2026Article
- Multimorbidity profile among cancer-related hospitalization events in younger and older patients: a large-scale nationwide cross-sectional study.Lancet regional health. Americas · 2026Article
- Article
- Extrahepatic disease clusters and mortality in people with steatotic liver diseases: a prospective analysis of 64,749 females and 113,587 males in the UK Biobank.BMC medicine · 2025Article
- Multimorbidity patterns and premature mortality in a prospective cohort: effect modifications by socioeconomic status and healthy lifestyles.BMC public health · 2025Article
- Multimorbidity clusters and their associations with health-related quality of life in two UK cohorts.BMC medicine · 2025Article
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Authors and funding
7 authors at 7 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Multimorbidity patterns can lead to differential risks for all-cause mortality. Within the Chilean context, research on morbidity and mortality predominantly emphasizes individual diseases or combinations thereof, rather than specific disease clusters. This study aimed to identify multimorbidity patterns, along with their associations with mortality, within a representative sample of the Chilean population. 3,701 participants aged ≥18 from the Chilean National Health Survey 2009-2010 were included in this prospective study. Multimorbidity patterns were identified from 16 chronic conditions and then classified using latent class analyses. All-cause mortality data were extracted from the Chilean Civil Registry. The association of classes with all-cause mortality was carried out using Cox proportional regression models, adjusting by sociodemographic and lifestyle variables. Three classes were identified: a) Class 1, the healthiest (72.1%); b) Class 2, the depression/cardiovascular disease/cancer class (17.5%); and c) Class 3, hypertension/chronic kidney disease class (10.4%). Classes 2 and 3 showed higher mortality risk than the healthiest class. After adjusting, Class 2 showed 45% higher mortality risk, and Class 3 98% higher mortality risk, compared with the healthiest class. Hypertension appeared to be a critical underlying factor of all-cause morbidity. Particular combinations of chronic diseases have a higher excess risk of mortality than others.
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