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Multilevel built environment features and individual odds of overweight and obesity in Utah

机译:犹他州的多层建筑环境特征以及超重和肥胖的几率

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Based on the data from the Behavioral Risk Factor Surveillance System (BRFSS) in 2007, 2009 and 2011 in Utah, this research uses multilevel modeling (MLM) to examine the associations between neighborhood built environments and individual odds of overweight and obesity after controlling for individual risk factors. The BRFSS data include information on 21,961 individuals geocoded to zip code areas. Individual variables include BMI (body mass index) and socio-demographic attributes such as age, gender, race, marital status, education attainment, employment status, and whether an individual smokes. Neighborhood built environment factors measured at both zip code and county levels include street connectivity, walk score, distance to parks, and food environment. Two additional neighborhood variables, namely the poverty rate and urbanicity, are also included as control variables. MLM results show that at the zip code level, poverty rate and distance to parks are significant and negative covariates of the odds of overweight and obesity; and at the county level, food environment is the sole significant factor with stronger fast food presence linked to higher odds of overweight and obesity. These findings suggest that obesity risk factors lie in multiple neighborhood levels and built environment features need to be defined at a neighborhood size relevant to residents' activity space. (C) 2014 Elsevier Ltd. All rights reserved.
机译:根据犹他州2007年,2009年和2011年的行为危险因素监测系统(BRFSS)的数据,本研究使用多级建模(MLM)来研究邻里建成环境与个体控制后个体超重和肥胖几率之间的关联。风险因素。 BRFSS数据包含有关21,961个人的信息,这些个人已地理编码到邮政编码区域。个体变量包括BMI(体重指数)和社会人口统计学属性,例如年龄,性别,种族,婚姻状况,受教育程度,就业状况以及个人是否吸烟。在邮政编码和县一级测量的邻里建筑环境因素包括街道连通性,步行分数,到公园的距离以及饮食环境。作为控制变量,还包括另外两个邻域变量,即贫困率和城市化程度。传销结果显示,在邮政编码级别,贫困率和公园距离是超重和肥胖几率的显着负相关变量。在县一级,食品环境是唯一的重要因素,快餐店的存在与超重和肥胖的几率更高有关。这些发现表明,肥胖风险因素存在于多个邻里级别中,并且需要根据与居民活动空间相关的邻里规模来定义建筑环境特征。 (C)2014 Elsevier Ltd.保留所有权利。

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