BMJ Open · 2022 · 24 citations · 31 references
Public HealthHealth SciencesPopulation Health SciencesEpidemiologic MethodsEpidemiologySocial Determinants Of HealthAnalytic EpidemiologyChronic DiseaseChronic Disease EpidemiologyComorbidityEpidemiology Of Noncommunicable DiseasesSocioeconomic Determinants Of HealthAge-specific Morbidity PatternsCross-sectional EpidemiologyDisease Prevalence PatternsMultimorbidity EpidemiologyMultimorbidity PatternsMultimorbidity SegmentationMultinomial RegressionOlder Adult Population
OBJECTIVE: In 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. DESIGN: The present findings rest on a large nationally-representative sample from a cross-sectional study. SETTING AND PARTICIPANTS: The 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. RESULTS: The 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. CONCLUSIONS: The 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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<b>MatchIt</b>: Nonparametric Preprocessing for Parametric Causal Inference
Daniel E. Ho, Kosuke Imai, Gary King et al. · Journal of Statistical Software · 2011 · 4.4K citations · Full text
Modern Biological Theories of Aging
Roger B. McDonald · Journal of Nutrition · 1989 · 474 citations · Full text
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