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预测小区域内与健康相关的行为:吸烟与饮酒指标的比较

Predicting small-area health-related behaviour: a comparison of smoking and drinking indicators.

作者信息

Twigg L, Moon G, Jones K

机构信息

School of Social and Historical Studies, Institute for the Geography of Health, University of Portsmouth, UK.

出版信息

Soc Sci Med. 2000 Apr;50(7-8):1109-20. doi: 10.1016/s0277-9536(99)00359-7.

Abstract

Health-related behaviours are of central importance to health promotion and to the promotion of enhanced population health. In the UK, localised knowledge of the quantitative dimensions of health-related behaviours is traditionally attained by conducting a costly sample survey. Such surveys seldom generate reliable data at scales more local than that of the health authority, they also need to be repeated regularly. This paper outlines an alternative framework for generating statistics on small-area health related behaviours using routinely available data from the annual Health Survey for England (N = 17,000) and the decennial Population Census. Using a multilevel modelling approach nesting individuals within postcode sectors within health authorities, and focusing on the prevalence of smoking and 'problem' drinking, the paper comprises four sections: a consideration of the modelling strategy, a comparison of the smoking and drinking models, an outline of the estimation strategy, and the presentation and discussion of ward-level estimates of smoking and drinking behaviour for England. The paper concludes that the method is better at estimating smoking than drinking but that it offers a feasible, cheap and more informative alternative to the survey approach to the generation of information on smoking and drinking behaviour.

摘要

与健康相关的行为对于健康促进以及提升人群健康水平至关重要。在英国,传统上通过开展成本高昂的抽样调查来获取与健康相关行为定量维度的局部知识。此类调查很少能在比卫生当局更局部的层面上生成可靠数据,而且还需要定期重复进行。本文概述了一个替代框架,该框架利用来自英格兰年度健康调查(样本量N = 17,000)和十年一次的人口普查的常规可用数据,来生成关于小区域与健康相关行为的统计数据。本文采用多层次建模方法,将个体嵌套在卫生当局内的邮政编码区域中,并聚焦于吸烟和“问题”饮酒的患病率,共包含四个部分:对建模策略的考量、吸烟和饮酒模型的比较、估计策略的概述,以及英格兰病房层面吸烟和饮酒行为估计值的呈现与讨论。本文得出结论,该方法在估计吸烟情况方面比估计饮酒情况表现更佳,但它为生成关于吸烟和饮酒行为信息的调查方法提供了一种可行、廉价且信息更丰富的替代方案。

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