Department of Survey Research and Data Analytics, International Institute for Population Sciences, Mumbai, Maharashtra, India
Department of Survey Research and Data Analytics, International Institute for Population Sciences, Mumbai, Maharashtra, India.
BMJ Open. 2022 Jul 12;12(7):e053981. doi: 10.1136/bmjopen-2021-053981.
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.
The present findings rest on a large nationally-representative sample from a cross-sectional study.
The study used data on 58 975 older adults (45 years and older) from the Longitudinal Ageing Study in India, 2017-2018.
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.
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.
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.
由于缺乏关于多种疾病的充分的全国代表性实证证据,现有的医疗保健提供系统无法充分满足老年人口不断增长的需求。因此,本研究旨在确定印度老年人中常见的多种疾病模式。此外,本研究还探讨了所确定的模式与社会经济、人口统计学、生活方式和人体测量学相关因素之间的联系。
本研究基于一项来自横断面研究的大型全国代表性样本。
本研究使用了来自印度纵向老龄化研究 2017-2018 年的 58975 名 45 岁及以上老年人的数据。
本研究纳入了 16 种非传染性疾病,使用潜在类别分析来确定常见的模式。本研究采用多项逻辑回归模型来评估所确定的疾病模式与单位水平的社会经济、人口统计学、生活方式和人体测量学特征之间的关联。
本研究表明,该国的老年人可以分为六种模式:“相对健康”、“高血压”、“胃肠道疾病-高血压-肌肉骨骼疾病”、“肌肉骨骼疾病-高血压-哮喘”、“代谢疾病”和“复杂心血管代谢疾病”。此外,社会经济、人口统计学、生活方式和人体测量学因素与一种或多种确定的疾病模式显著相关。
所确定的“高血压”、“代谢疾病”和“复杂心血管代谢疾病”类反映了心血管代谢疾病的三个阶段,其中高血压是第一阶段,“复杂心血管代谢疾病”是疾病进展的最后阶段。这凸显了针对高危高血压人群制定有效预防策略的必要性。此外,还需要有针对性的干预措施,以减轻高危人群的负担,并在社区层面提供公平的医疗服务。