ArticleBMJ open2022
Identifying non-communicable disease multimorbidity patterns and associated factors: a latent class analysis approach.
Article in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 21 citations in OpenAlex.
- Asthma and Multimorbidity Amongst Ethnic Minority Groups in High Income Countries.Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology · 2026Review
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- Financial impact of non-communicable diseases on households with older adults in india: a mixed methods study.BMC geriatrics · 2026Article
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- The trajectories of cardiometabolic multimorbidity associate with mortality risk: a study based on Guangdong adult chronic diseases and risk factors cohort.Frontiers in public health · 2026Article
- Association of socioeconomic and lifestyle factors with the prevalence of chronic noncommunicable disease multimorbidity in rural Southwest China: a structural equation modeling approach.Archives of public health = Archives belges de sante publique · 2025Article
- Prevalence, incidence, risk factors and economic burden in multimorbidity among adult Indians: the MILAN cohort study protocol.BMJ open · 2025Article
- Rising to the challenges of research in multiple long-term conditions: health and social care research ecosystem approaches.BMJ open · 2025Review
- Multimorbidity patterns in older adults from Northern Netherlands: comparing factor analysis and latent class analysis solutions.BMC geriatrics · 2025Article
- Dietary risk factors for non-communicable diseases among Omani adults by latent class analysis and structural equation modelling.BMC nutrition · 2025Article
- Investigating multimorbidity patterns and associated risk factors in the fasa adults cohort study (FACS): A latent class analysis.PloS one · 2025Article
- Multimorbidity, health Literacy, and quality of life among older adults in an urban slum in India: a community-based cross-sectional study.BMC public health · 2024Article
- Latent class analysis of chronic disease co-occurrence, clustering and their determinants in India using Study on global AGEing and adult health (SAGE) India Wave-2.Journal of global health · 2024Article
- Risk factors of multimorbidity among older adults in India: A systematic review and meta-analysis.Health science reports · 2024Article
- Article
- Concurrent Undernutrition and Overnutrition within Indian Families between 2006 and 2021.Current developments in nutrition · 2023Article
- Multimorbidity Patterns and Associations with Gait, Balance and Lower Extremity Muscle Function in the Elderly: A Cross-Sectional Study in Northwest China.International journal of general medicine · 2023Article
- Exploring multimorbidity clusters in relation to healthcare use and its impact on self-rated health among older people in India.PLOS global public health · 2023Article
- Overview of multimorbidity research in India: A scoping review.Journal of multimorbidity and comorbidityReview
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveIn the absence of adequate nationally-representative empirical evidence on multimorbidity, the existing healthcare delivery system is not adequately oriented to cater to the growing needs of the older adult population. Therefore, the present study identifies frequently occurring multimorbidity patterns among older adults in India. Further, the study examines the linkages between the identified patterns and socioeconomic, demographic, lifestyle and anthropometric correlates.
designThe present findings rest on a large nationally-representative sample from a cross-sectional study. SETTING AND
participantsThe study used data on 58 975 older adults (45 years and older) from the Longitudinal Ageing Study in India, 2017-2018. PRIMARY AND SECONDARY OUTCOME MEASURES: The study incorporated a list of 16 non-communicable diseases to identify commonly occurring patterns using latent class analysis. The study employed multinomial logistic regression models to assess the association between identified disease patterns with unit-level socioeconomic, demographic, lifestyle and anthropometric characteristics.
resultsThe present study demonstrates that older adults in the country can be segmented into six patterns: 'relatively healthy', 'hypertension', 'gastrointestinal disorders-hypertension-musculoskeletal disorders', 'musculoskeletal disorders-hypertension-asthma', 'metabolic disorders' and 'complex cardiometabolic disorders'. Additionally, socioeconomic, demographic, lifestyle and anthropometric factors are significantly associated with one or more identified disease patterns.
conclusionsThe identified classes 'hypertension', 'metabolic disorders' and 'complex cardiometabolic disorders' reflect three stages of cardiometabolic morbidity with hypertension as the first and 'complex cardiometabolic disorders' as the last stage of disease progression. This underscores the need for effective prevention strategies for high-risk hypertension group. Also, targeted interventions are essential to reduce the burden on the high-risk population and provide equitable health services at the community level.
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