Associations between neighbourhood characteristics, body mass index and health-related behaviours of adolescents in the Kiel Obesity Prevention Study: a multilevel analysis
Associations between neighbourhood characteristics, body mass index and health-related behaviours of adolescents in the Kiel Obesity Prevention Study: a multilevel analysis
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DOI：
10.1038/ejcn.2011.21
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发表时间：
2011-06-01
影响因子：
4.7
通讯作者：
Mueller, M. J.
中科院分区：
文献类型：
--
作者：
Lange, D.;Wahrendorf, M.;Mueller, M. J.
背景/目的：为了了解超重的决定因素，一些研究探讨了邻里特征与成人肥胖之间的关联。然而，这些特征与青少年超重之间的关系却知之甚少。本研究的目的是在青少年的身体质量指数（BMI）和生活方式的影响，在何种程度上的BMI和生活方式的变化之间的邻里可以解释邻里characteristics.Subjects/Methods：我们使用的横断面数据从基尔肥胖预防研究收集2004年至2008年在28个不同的住宅区的城市基尔（北德国）。1675名男孩和1765名女孩（n = 3440）年龄在13-15岁，人体测量数据，个人生活方式因素和社会人口学数据被纳入分析。在宏观一级，使用了六种不同的邻里特征：失业率、人口密度、交通密度、高能量食品供应的普及率、运动场和公园的数量以及犯罪率。为了检验我们的主要假设，线性和Logistic多层次回归分析进行预测BMI和生活方式因素的个人嵌套在neighborhoods.Results：结果的多层次分析显示，BMI和健康相关行为的邻里之间的变化很小。在所有的，2%的BMI变化，4%的媒体时间变化和3%的变化，在吃零食的行为可以归因于差异在neighborhoods.Conclusions：环境因素与青少年的BMI和健康相关的行为显着相关，但是，他们的总效果是小的。鉴于这些结果，必须谨慎地提出作为预防青少年超重的一部分的结构性政策措施的建议。欧洲临床营养学杂志（2011）65，711-719; doi：10.1038/ejcn.2011.21; 2011年3月30日在线发表
Background/Objectives: To understand determinants of overweight, several studies addressed the association between neighbourhood characteristics and adult obesity. However, little is known about the association of such characteristics with adolescents' overweight. This study aims at the influence of neighbourhood characteristics on adolescent body mass index (BMI) and lifestyle and to what extent BMI and lifestyle variation between neighbourhoods can be explained by neighbourhood characteristics.Subjects/Methods: We used cross-sectional data from the Kiel Obesity Prevention Study collected between 2004 and 2008 in 28 different residential districts of the city of Kiel (North Germany). Anthropometric data were available for 1675 boys and 1765 girls (n = 3440) aged 13-15 years, and individual lifestyle factors and sociodemographic data were included in the analysis. At the macro level, six different neighbourhood characteristics were used: unemployment rate, population density, traffic density, prevalence of energy-dense food supply, number of sports fields and parks, and crime rate. To test our main hypothesis, linear and logistic multilevel regression analyses were performed to predict BMI and lifestyle factors in individuals nested in neighbourhoods.Results: Findings of multilevel analysis show little between-neighbourhood variations in BMI and health-related behaviours. In all, 2% of BMI variation, 4% of media time variation and 3% of variation in snacking behaviour could be attributed to differences in neighbourhoods.Conclusions: Environmental factors are significantly associated with adolescent BMI and health-related behaviour; however, their total effect is small. Owing to these results, recommendations for structural policy measures as part of prevention of overweight in adolescents must be made cautiously. European Journal of Clinical Nutrition (2011) 65, 711-719; doi:10.1038/ejcn.2011.21; published online 30 March 2011