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邻里环境中的致肥胖因素与女性体重指数有关吗?致肥胖指数在社会经济条件不利社区的应用。

Is neighbourhood obesogenicity associated with body mass index in women? Application of an obesogenicity index in socioeconomically disadvantaged neighbourhoods.

作者信息

Tseng Marilyn, Thornton Lukar E, Lamb Karen E, Ball Kylie, Crawford David

机构信息

Centre for Physical Activity and Nutrition Research, School of Exercise and Nutrition Sciences, Deakin University, Melbourne Burwood Campus, 221 Burwood Highway, Burwood, VIC 3125, Australia.

出版信息

Health Place. 2014 Nov;30:20-7. doi: 10.1016/j.healthplace.2014.07.012. Epub 2014 Aug 23.

DOI:10.1016/j.healthplace.2014.07.012
PMID:25155451
Abstract

An aggregate index is potentially useful to represent neighbourhood obesogenicity. We created a conceptually-based obesogenicity index and examined its association with body mass index (BMI) among 3786 women (age 18-45y) in socio-economically disadvantaged neighbourhoods in Victoria, Australia. The index included 3 items from each of 3 domains: food resources (supermarkets, green grocers, fast food restaurants), recreational activity resources (gyms, pools, park space), and walkability (4+ leg intersections, neighbourhood walking environment, neighbourhood safety), with a possible range from 0 to 18 reflecting 0-2 for each of the 9 items. Using generalised estimating equations, neighbourhood obesogenicity was not associated with BMI in the overall sample. However, stratified analyses revealed generally positive associations with BMI in urban areas and inverse associations in rural areas (interaction p=0.02). These analyses are a first step towards combining neighbourhood characteristics into an aggregate obesogenicity index that is transparent enough to be adopted elsewhere and to allow examination of the relevance of its specific components in different settings.

摘要

综合指数可能有助于表示邻里环境中的致肥胖因素。我们创建了一个基于概念的致肥胖指数,并在澳大利亚维多利亚州社会经济条件不利社区的3786名18至45岁女性中,研究了该指数与体重指数(BMI)之间的关联。该指数包括三个领域中每个领域的3项指标:食物资源(超市、蔬菜水果店、快餐店)、休闲活动资源(健身房、游泳池、公园空间)和步行便利性(四个及以上的路口、邻里步行环境、邻里安全性),取值范围为0至18,反映9项指标中每项指标的得分从0至2。使用广义估计方程,在总体样本中,邻里致肥胖因素与BMI无关。然而,分层分析显示,在城市地区,邻里致肥胖因素与BMI总体呈正相关,而在农村地区呈负相关(交互作用p = 0.02)。这些分析是将邻里特征纳入综合致肥胖指数的第一步,该指数足够透明,可在其他地方采用,并能在不同环境中考察其特定组成部分的相关性。

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