Poulsen Melissa N, Glass Thomas A, Pollak Jonathan, Bandeen-Roche Karen, Hirsch Annemarie G, Bailey-Davis Lisa, Schwartz Brian S
Department of Epidemiology and Health Services Research, Geisinger, 100 North Academy Avenue, Danville, PA 17822, USA.
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe Street, Baltimore, MD 21205, USA.
Prev Med Rep. 2019 Jun 29;15:100939. doi: 10.1016/j.pmedr.2019.100939. eCollection 2019 Sep.
Understanding contextual influences on obesity requires comparison of heterogeneous communities and concurrent assessment of multiple contextual domains. We used a theoretically-based measurement model to assess multidimensional socioeconomic and built environment factors theorized to influence childhood obesity across a diverse geography ranging from rural to urban. Confirmatory factor analysis specified four factors-community socioeconomic deprivation (CSED), food outlet abundance (FOOD), fitness and recreational assets (FIT), and utilitarian physical activity favorability (UTIL)-which were assigned to communities (townships, boroughs, city census tracts) in 37 Pennsylvania counties. Using electronic health records from 2001 to 2012 from 163,820 youth aged 3-18 years from 1288 communities, we conducted multilevel linear regression analyses with factor quartiles and their cross products with age, age, and age to test whether community factors impacted body mass index (BMI) growth trajectories. Models controlled for sex, age, race/ethnicity, and Medical Assistance. Factor scores were lowest in townships, indicating less deprivation, fewer food and physical activity outlets, and lower utilitarian physical activity favorability. BMI at average age was lower in townships versus boroughs (beta [SE]) (0.217 [0.027], < 0.001) and cities (0.378 [0.036], < 0.001), as was BMI growth over time. Factor distributions across community types lacked overlap, requiring stratified analyses to avoid extrapolation. In townships, FOOD, UTIL, and FIT were inversely associated with BMI trajectories. Across community types, youth in the lowest (versus higher) CSED quartiles had lower BMI at average age and slower BMI growth, signifying the importance of community deprivation to the obesogenicity of environments.
了解环境因素对肥胖的影响需要对不同社区进行比较,并同时评估多个环境领域。我们使用了一个基于理论的测量模型,来评估从农村到城市的不同地理区域中,那些理论上会影响儿童肥胖的多维社会经济和建成环境因素。验证性因素分析确定了四个因素——社区社会经济剥夺(CSED)、食品销售点丰富程度(FOOD)、健身和娱乐资源(FIT)以及功利性体力活动适宜性(UTIL)——这些因素被分配到宾夕法尼亚州37个县的社区(乡镇、行政区、城市普查区)。利用来自1288个社区的163820名3至18岁青少年在2001年至2012年期间的电子健康记录,我们进行了多水平线性回归分析,将因素四分位数及其与年龄、年龄²和年龄³的交叉乘积纳入分析,以检验社区因素是否会影响体重指数(BMI)的增长轨迹。模型对性别、年龄、种族/族裔和医疗救助进行了控制。乡镇的因素得分最低,表明贫困程度较低、食品和体育活动场所较少,以及功利性体力活动适宜性较低。乡镇的平均年龄BMI低于行政区(β[标准误])(0.217[0.027],<0.001)和城市(0.378[0.036],<0.001),BMI随时间的增长情况也是如此。不同社区类型的因素分布缺乏重叠,需要进行分层分析以避免外推。在乡镇,FOOD、UTIL和FIT与BMI轨迹呈负相关。在所有社区类型中,处于最低(相对于较高)CSED四分位数的青少年在平均年龄时BMI较低,BMI增长较慢,这表明社区贫困对环境致肥胖性的重要性。