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

Multilevel built environment features and individual odds of overweight and obesity in Utah.
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DOI:
10.1016/j.apgeog.2014.10.006
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发表时间:
2015-06
期刊:
Applied geography (Sevenoaks, England)
影响因子:
--
通讯作者:
Wang F
Wang F
中科院分区:
其他
文献类型:
--
作者:
Xu Y;Wen M;Wang F

文献摘要

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基于行为风险因素监测系统(BRFSS)在2007年,2009年和2011年在犹他州的数据,本研究使用多层次模型(MLM)来检查邻里建筑环境和个体超重和肥胖的几率之间的关联控制后的个体风险因素。BRFSS的数据包括21,961名地理编码为邮政编码地区的个人的信息。个体变量包括BMI(身体质量指数)和社会人口属性,如年龄,性别,种族,婚姻状况,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社区建筑环境因素包括街道连通性,步行得分,到公园的距离和食物环境。两个额外的邻里变量,即贫困率和城市化,也包括作为控制变量。MLM结果表明,在邮政编码水平,贫困率和公园距离是超重和肥胖几率的显着和负协变量;在县一级,食品环境是唯一的显着因素,更强的快餐存在与超重和肥胖的几率更高。这些发现表明,肥胖风险因素存在于多个社区层面,并且需要根据与居民活动空间相关的社区规模来定义建筑环境特征。
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.