Body Mass Index and the Built and Social Environments in Children and Adolescents Using Electronic Health Records
Body Mass Index and the Built and Social Environments in Children and Adolescents Using Electronic Health Records
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DOI：
10.1016/j.amepre.2011.06.038
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发表时间：
2011-10-01
影响因子：
5.5
通讯作者：
Glass, Thomas A.
中科院分区：
文献类型：
--
作者：
Schwartz, Brian S.;Stewart, Walter F.;Glass, Thomas A.
背景资料：以前没有儿童研究评估年龄如何改变建筑和社会环境与BMI的关系，也没有评估地方可能影响健康的尺度和背景范围。目的：系统地评估三个领域的33个环境指标的关联（土地利用、体力活动和社会环境）与五个地区儿童和青少年BMI的关系。2009-2010年，对居住在宾夕法尼亚州31个县的47,769名5-18岁儿童的电子健康记录数据（2001-2008年）进行了横断面、多层次分析。使用0.5英里的网络缓冲区、人口普查区、小的民事分区（即，城镇、自治市、城市）;地点的混合定义（城镇、自治市和城市人口普查区）;以及县，总体和按年龄层。结果：在所有儿童中，较低的社区社会经济贫困水平和更多样化的体育活动机构与较低的BMI相关。环境措施的关联因年代而异，取决于规模和背景。例如，较高的人口密度与年龄较大的儿童的较低BMI相关;这种影响在较大的地区最强。同样，一个较低的水平县蔓延与较低的BMI在大龄child.Conclusions：协会不同的年龄和定义的地方，这表明环境干预的好处可能是不统一的整个儿童年龄范围。该研究证明了使用电子患者信息进行大规模、基于人群的流行病学研究的实用性，这是美国越来越感兴趣和投资的研究领域（Am J Prev Med 2011;41（4）：e17-e28）（C）2011年美国预防医学杂志
Background: No prior studies in children have evaluated how age may modify relationships of the built and social environments with BMI, nor evaluated the range of scales and contexts over which places may influence health.Purpose: To systematically evaluate associations of 33 environmental measures in three domains (land use, physical activity, and social environments) with BMI in children and adolescents in five geographies.Methods: Across-sectional, multilevel analysis was completed in 2009-2010 of electronic health record data (2001-2008) from 47,769 children aged 5-18 years residing in a 31-county region of Pennsylvania. Associations of environmental measures with BMI were evaluated using 0.5-mile network buffers; census tracts; minor civil divisions (i.e., townships, boroughs, cities); a mixed definition of place (townships, boroughs, and census tracts in cities); and counties, overall and by age strata.Results: Among all children, lower levels of community socioeconomic deprivation and greater diversity of physical activity establishments were associated with lower BMI. Associations of environmental measures differed by age, depending on scale and context. For example, higher population density was associated with lower BMI in older children; this effect was strongest in the larger geographies. Similarly, a lower level of county sprawl was associated with lower BMI in older children.Conclusions: Associations differed by age and definition of place, suggesting that the benefits of environmental intervention may not be uniform across the childhood age range. The study demonstrated the utility of using electronic patient information for large-scale, population-based epidemiologic research, a research area of growing interest and investment in the U.S. (Am J Prev Med 2011;41(4):e17-e28) (C) 2011 American Journal of Preventive Medicine