Suppr超能文献

识别非传染性疾病多重疾病模式和相关因素:一种潜在类别分析方法。

Identifying non-communicable disease multimorbidity patterns and associated factors: a latent class analysis approach.

机构信息

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.

出版信息

BMJ Open. 2022 Jul 12;12(7):e053981. doi: 10.1136/bmjopen-2021-053981.

Abstract

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.

摘要

目的

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。

设计

本研究基于一项来自横断面研究的大型全国代表性样本。

地点和参与者

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。

主要和次要结果

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。

结果

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。

结论

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。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验