Observational studyInternational journal of environmental research and public health2022
Multimorbidity Patterns and Their Association with Social Determinants, Mental and Physical Health during the COVID-19 Pandemic.
Observational study in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 9 citations in OpenAlex.
- Unveiling the hidden effect of multi-morbidities on the severity of Covid-19: a latent class analysis approach.BMC public health · 2025Article
- Exploring patterns of multimorbidity in South Korea using exploratory factor analysis and non negative matrix factorization.Scientific reports · 2025Article
- Uncovering bridging diseases in complex multimorbidity pathways: A network science approach.PloS one · 2025Article
- Creating a Modified Version of the Cambridge Multimorbidity Score to Predict Mortality in People Older Than 16 Years: Model Development and Validation.Journal of medical Internet research · 2024Article
- Epidemiology, mortality, and health service use of local-level multimorbidity patterns in South Spain.Nature communications · 2023Article
Corrections and comments
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Authors and funding
14 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe challenge posed by multimorbidity makes it necessary to look at new forms of prevention, a fact that has become heightened in the context of the pandemic. We designed a questionnaire to detect multimorbidity patterns in people over 50 and to associate these patterns with mental and physical health, COVID-19, and possible social inequalities.
methodsThis was an observational study conducted through a telephone interview. The sample size was 1592 individuals with multimorbidity. We use Latent Class Analysis to detect patterns and SF-12 scale to measure mental and physical quality-of-life health. We introduced the two dimensions of health and other social determinants in a multinomial regression model.
resultsWe obtained a model with five patterns (entropy = 0.727): 'Relative Healthy', 'Cardiometabolic', 'Musculoskeletal', 'Musculoskeletal and Mental', and 'Complex Multimorbidity'. We found some differences in mental and physical health among patterns and COVID-19 diagnoses, and some social determinants were significant in the multinomial regression.
conclusionsWe identified that prevention requires the location of certain inequalities associated with the multimorbidity patterns and how physical and mental health have been affected not only by the patterns but also by COVID-19. These findings may be critical in future interventions by health services and governments.
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