ArticleBMJ open2018
Comparative analysis of methods for identifying multimorbidity patterns: a study of 'real-world' data.
Article in BMJ open, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 2 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
45 citing papers in PubMed, 2 syntheses or guidelines pooled it, 80 citations in OpenAlex.
- A systematic review and meta-analysis of disease clusters in multimorbidity.Nature communications · 2025Pooled it
- Social determinants of multimorbidity patterns: A systematic review.Frontiers in public health · 2023Pooled it
- Co-recorded conditions in ischemic and hemorrhagic stroke: a 20-year national analysis of 598,186 natural deaths with machine learning.Frontiers in neurology · 2026Article
- Exploring the genetic architecture of multiple long-term conditions using a genome-wide association study in the UK Biobank population.Scientific reports · 2025Article
- Multimorbidity Patterns and Functioning Associations Among Adults in a Local South African Setting: A Cross-Sectional Study.International journal of environmental research and public health · 2025Article
- Multimorbidity patterns of mental disorders and physical diseases of adults in northeast China: a cross-sectional network analysis.Epidemiology and psychiatric sciences · 2025Article
- Multimorbidity Patterns, Hospital Uses and Mortality by Race and Ethnicity Among Oldest-Old Patients.Journal of racial and ethnic health disparities · 2025Article
- Spatial Analysis of patterns of Multimorbidity in the Thai Cohort Study Using Latent Class Analysis.Journal of epidemiology and global health · 2025Article
- Multimorbidity patterns and function among adults in low- and middle-income countries: a scoping review.BMJ open · 2025Article
- Multimorbidity clusters and their associations with health-related quality of life in two UK cohorts.BMC medicine · 2025Article
- Patterns of multimorbidity in older adults with multiple myeloma: An analysis of SEER-Medicare.PloS one · 2025Article
- Article
- Multimorbidity measures associated with cognitive function among community-dwelling older Chinese adults.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Learning prevalent patterns of co-morbidities in multichronic patients using population-based healthcare data.Scientific reports · 2024Article
- Multimorbidity clusters in adults 50 years or older with and without a history of cancer: National Health Interview Survey, 2018.BMC geriatrics · 2024Article
- Article
- Cardiometabolic and renal phenotypes and transitions in the United States population.Nature cardiovascular research · 2023Article
- Epidemiology, mortality, and health service use of local-level multimorbidity patterns in South Spain.Nature communications · 2023Article
- Topic modeling identifies novel genetic loci associated with multimorbidities in UK Biobank.Cell genomics · 2023Article
- Analysis of Multiple Causes of Death: A Review of Methods and Practices.Epidemiology (Cambridge, Mass.) · 2023Review
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe aim was to compare multimorbidity patterns identified with the two most commonly used methods: hierarchical cluster analysis (HCA) and exploratory factor analysis (EFA) in a large primary care database. Specific objectives were: (1) to determine whether choice of method affects the composition of these patterns and (2) to consider the potential application of each method in the clinical setting.
designCross-sectional study. Diagnoses were based on the 263 corresponding blocks of the International Classification of Diseases version 10. Multimorbidity patterns were identified using HCA and EFA. Analysis was stratified by sex, and results compared for each method. SETTING AND
participantsElectronic health records for 408 994 patients with multimorbidity aged 45-64 years in 274 primary health care teams from 2010 in Catalonia, Spain.
resultsHCA identified 53 clusters for women, with just 12 clusters including at least 2 diagnoses, and 15 clusters for men, all of them including at least two diagnoses. EFA showed 9 factors for women and 10 factors for men. We observed differences by sex and method of analysis, although some patterns were consistent. Three combinations of diseases were observed consistently across sex groups and across both methods: hypertension and obesity, spondylopathies and deforming dorsopathies, and dermatitis eczema and mycosis.
conclusionsThis study showed that multimorbidity patterns vary depending on the method of analysis used (HCA vs EFA) and provided new evidence about the known limitations of attempts to compare multimorbidity patterns in real-world data studies. We found that EFA was useful in describing comorbidity relationships and HCA could be useful for in-depth study of multimorbidity. Our results suggest possible applications for each of these methods in clinical and research settings, and add information about some aspects that must be considered in standardisation of future studies: spectrum of diseases, data usage and methods of analysis.
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