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全球多重疾病模式:一项基于人群的多国横断面研究

Global Multimorbidity Patterns: A Cross-Sectional, Population-Based, Multi-Country Study.

作者信息

Garin Noe, Koyanagi Ai, Chatterji Somnath, Tyrovolas Stefanos, Olaya Beatriz, Leonardi Matilde, Lara Elvira, Koskinen Seppo, Tobiasz-Adamczyk Beata, Ayuso-Mateos Jose Luis, Haro Josep Maria

机构信息

Pharmacy Department, Hospital de la Santa Creu i Sant Pau, Institut d'Investigacions Biomèdiques Sant Pau (IIB Sant Pau), Barcelona, Spain. Universitat Autònoma de Barcelona, Bellaterra (Cerdanyola del Vallès), Spain. Research and Development Unit, Parc Sanitari Sant Joan de Déu, Universitat de Barcelona, Spain. Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, Madrid, Spain.

Research and Development Unit, Parc Sanitari Sant Joan de Déu, Universitat de Barcelona, Spain. Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, Madrid, Spain.

出版信息

J Gerontol A Biol Sci Med Sci. 2016 Feb;71(2):205-14. doi: 10.1093/gerona/glv128. Epub 2015 Sep 29.

Abstract

BACKGROUND

Population ageing challenges health care systems due to the high prevalence and impact of multimorbidity in older adults. However, little is known about how chronic conditions present in certain multimorbidity patterns, which could have great impact on public health at several levels. The aim of our study was to identify and describe multimorbidity patterns in low-, middle-, and high-income countries.

METHODS

We analyzed data from the Collaborative Research on Ageing in Europe project (Finland, Poland, and Spain) and the World Health Organization's Study on Global Ageing and Adult Health (China, Ghana, India, Mexico, Russia, and South Africa). These cross-sectional studies obtained data from 41,909 noninstitutionalized adults older than 50 years. Exploratory factor analysis was performed to detect multimorbidity patterns. Additional adjusted binary logistic regressions were performed to identify associations between sociodemographic factors and multimorbidity.

RESULTS

Overall multimorbidity prevalence was high across countries. Hypertension, cataract, and arthritis were the most prevalent comorbid conditions. Two or three multimorbidity patterns were found per country. Several patterns were identified across several countries: "cardio-respiratory" (angina, asthma, and chronic obstructive pulmonary disease), "metabolic" (diabetes, obesity, and hypertension), and "mental-articular" (arthritis and depression).

CONCLUSIONS

A high prevalence of multimorbidity occurs in older adults across countries, with low- and middle-income countries gradually approaching the figures of richer countries. Certain multimorbidity patterns are present in several countries, which suggest that common underlying etiopathogenic factors may play a role. Deeper understanding of these patterns may lead to the development of preventive actions to diminish their prevalence and also give rise to new, comprehensive approaches for the management of these co-occurring conditions.

摘要

背景

由于老年人中多重疾病的高患病率及其影响,人口老龄化给医疗保健系统带来了挑战。然而,对于某些多重疾病模式中慢性病的呈现方式知之甚少,而这可能在多个层面上对公共卫生产生重大影响。我们研究的目的是识别和描述低收入、中等收入和高收入国家的多重疾病模式。

方法

我们分析了欧洲老龄化合作研究项目(芬兰、波兰和西班牙)以及世界卫生组织全球老龄化与成人健康研究(中国、加纳、印度、墨西哥、俄罗斯和南非)的数据。这些横断面研究收集了41909名50岁以上非机构化成年人的数据。进行探索性因素分析以检测多重疾病模式。还进行了额外的调整二元逻辑回归分析,以确定社会人口学因素与多重疾病之间的关联。

结果

各国总体多重疾病患病率都很高。高血压、白内障和关节炎是最常见的合并症。每个国家发现了两到三种多重疾病模式。在多个国家识别出了几种模式:“心肺型”(心绞痛、哮喘和慢性阻塞性肺疾病)、“代谢型”(糖尿病、肥胖症和高血压)以及“精神关节型”(关节炎和抑郁症)。

结论

各国老年人中多重疾病的患病率都很高,低收入和中等收入国家的患病率正逐渐接近富裕国家。某些多重疾病模式在多个国家都存在,这表明共同的潜在病因可能起了作用。对这些模式的更深入理解可能会促成预防措施的制定,以降低其患病率,还可能催生针对这些并存疾病的新的综合管理方法。

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