Objective

To conduct a state-wide examination of public schools and the school neighborhood as potential targets for environmental public health tracking to address childhood obesity.

Methods

We examined the relationship of social and physical environmental attributes of the school environment (within school and neighborhood) and childhood obesity in California with machine learning (Random Forest) and multilevel methods. We used data compiled from the California Department of Education, the U.S. Geological Survey, ESRI's Business Analyst, the U.S. Census, and other public sources for ecologic level variables for various years and assessed their relative importance to obesity as determined from the statewide Physical Fitness Test 2003 through 2007 for grades 5, 7, and 9 (n = 5,265,265).

Results

In addition to individual-level race and gender, the following within and school neighborhood variables ranked as the most important model contributors based on the Random Forest analysis and were included in multilevel regressions clustered on the county. Violent crime, English learners, socioeconomic disadvantage, fewer physical education (PE) and fully credentialed teachers, and diversity index were positively associated with obesity while academic performance index, PE participation, mean educational attainment and per capita income were negatively associated with obesity. The most highly ranked built or physical environment variables were distance to the nearest highway and greenness, which were 10th and 11th most important, respectively.

Conclusions

Many states in the U.S. do not have school-based surveillance programs that collect body mass index data. System-level determinants of obesity can be important for tracking and intervention. The results of these analyses suggest that the school social environment factors may be especially important. Disadvantaged and low academic performing schools have a higher risk for obesity. Supporting such schools in a targeted way may be an efficient way to intervene and could impact both health and academic outcomes. Some of the more important variables, such as having credentialed teachers and participating in PE, are modifiable risk factors.

中文翻译：

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学校环境对加州儿童肥胖的影响

客观的

在全州范围内对公立学校和学校社区进行检查，将其作为环境公共卫生追踪以解决儿童肥胖的潜在目标。

方法

我们使用机器学习（随机森林）和多级方法研究了学校环境（在学校和社区内）的社会和自然环境属性与加利福尼亚州儿童肥胖的关系。我们使用了加利福尼亚教育部，美国地质调查局，ESRI的业务分析师，美国人口普查以及其他公共来源收集的数据，对多年来的生态水平变量进行了评估，并根据全州身体素质测验评估了它们对肥胖症的相对重要性。 2003年至2007年，分别为5、7和9年级（n = 5,265,265）。

结果

除了个人级别的种族和性别以外，以下这些变量和学校邻里变量在随机森林分析的基础上被列为最重要的模型贡献者，并被包括在该县的多级回归中。暴力，犯罪，英语学习者，社会经济劣势，较少的体育教育和完全合格的教师以及多样性指数与肥胖呈正相关，而学业成绩指数，体育参与度，平均教育程度和人均收入与肥胖呈负相关。排名最高的建筑或物理环境变量是距最近的高速公路的距离和绿色程度，这分别是最重要的第十和第十一位。

结论

美国的许多州没有基于学校的监视程序来收集体重指数数据。肥胖的系统级决定因素对于跟踪和干预可能很重要。这些分析的结果表明，学校的社会环境因素可能尤其重要。处于劣势和学术表现不佳的学校患肥胖症的风险更高。有针对性地为此类学校提供支持可能是一种有效的干预方式，并且可能影响健康和学业成果。一些更重要的变量，例如具有资格证书的老师和参加体育活动，是可更改的风险因素。