Multidimensional profiles of health status: an application of the grade of membership model to the world health survey.
Multidimensional profiles of health status: an application of the grade of membership model to the world health survey.
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DOI：
10.1371/journal.pone.0004426
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发表时间：
2009
期刊：
影响因子：
3.7
通讯作者：
Chatterji S
中科院分区：
文献类型：
--
作者：
Andreotti A;Minicuci N;Kowal P;Chatterji S
世界卫生组织（世卫组织）在2002年至2004年期间在70个国家进行了世界卫生调查，以提供关于健康、与健康有关的结果和风险因素的跨人口可比数据。本研究的目的是应用会员等级（GoM）建模作为一种手段，将WHS中广泛的健康信息浓缩成一组易于理解的健康档案，并分配个人属于每个档案的程度。本文介绍了GoM模型在世界卫生调查数据中的应用。隶属度分析是一种灵活的、非参数的、多变量的方法，用于从WHS自我报告的健康状态和健康状况计算健康概况。WHS数据集根据世界银行的经济分组（高收入、中上收入、中低收入和低收入经济体）分为四个国家经济类别，用于单独的墨西哥政府分析。为这四个地区中的每一个地区编制了三份主要的健康概况：鲁棒性; II.中间体; III.脆弱;此外，还为每个经济领域的国家界定了人口健康、财富和不平等，作为正确看待健康结果的一种手段。这些分析提供了一个强大的方法，以更好地了解健康概况和组成部分，可以帮助确定健康和不健康的个人。所获得的概况描述了具体的健康水平，并明确界定了健康和不健康的受访者的特点。墨西哥政府的结果提供了一种总结复杂的个人健康信息的可用方法，并选择了可用于改善健康的干预措施的中间决定因素。随着人口的老龄化，以及用于医疗保健和社会服务的额外费用的预算有限，应用黑山政府的方法可能有助于确定决策和资源分配的较高风险状况。
The World Health Organization (WHO) conducted the World Health Survey (WHS) between 2002 and 2004 in 70 countries to provide cross-population comparable data on health, health-related outcomes and risk factors. The aim of this study was to apply Grade of Membership (GoM) modelling as a means to condense extensive health information from the WHS into a set of easily understandable health profiles and to assign the degree to which an individual belongs to each profile. This paper described the application of the GoM models to summarize population health status using World Health Survey data. Grade of Membership analysis is a flexible, non-parametric, multivariate method, used to calculate health profiles from WHS self-reported health state and health conditions. The WHS dataset was divided into four country economic categories based on the World Bank economic groupings (high, upper-middle, lower-middle and low income economies) for separate GoM analysis. Three main health profiles were produced for each of the four areas: I. Robust; II. Intermediate; III. Frail; moreover population health, wealth and inequalities are defined for countries in each economic area as a means to put the health results into perspective. These analyses have provided a robust method to better understand health profiles and the components which can help to identify healthy and non-healthy individuals. The obtained profiles have described concrete levels of health and have clearly delineated characteristics of healthy and non-healthy respondents. The GoM results provided both a useable way of summarising complex individual health information and a selection of intermediate determinants which can be targeted for interventions to improve health. As populations' age, and with limited budgets for additional costs for health care and social services, applying the GoM methods may assist with identifying higher risk profiles for decision-making and resource allocations.
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