Background: Teenage obesity is a national epidemic that requires school- and community-based initiatives to support healthy behaviors of students regarding exercise and nutrition to decrease the prevalence. Objectives: The aim of this study was to demonstrate a methodology for an estimation of causal effects of the adoption of healthy behaviors with a potential outcomes approach within a multilevel treatment setting of school program adoption of a socially supportive environment. Methods: Propensity score estimates within a multilevel model provided causal estimates of the impact of the adoption of health habits by students within supportive school environments (SSEs) and non-SSEs. A potential outcomes approach to causal modeling was shown with a secondary analysis of the National Longitudinal Study of Adolescent Health study. The student participants consisted of 13,854 adolescent students, with an accompanying sample of 164 school administrators. Results: The effect of healthy eating habits in an SSE was a statistically nonsignificant decrease in body mass index (BMI). The effect of healthy eating habits in a non-SSE was a statistically nonsignificant increase in BMI. The difference between the healthy habit practices for students in supportive and nonsupportive schools was a resultant difference in BMI of 0.3484. Discussion: The results demonstrate a difference in causal effects of eating habits in different school settings. Further research regarding causal effects of student habits and school programs is indicated.
机构:
Beijing Univ Technol, Coll Appl Sci, Beijing 100124, Peoples R China
Shangqiu Normal Univ, Sch Math & Informat Sci, Shangqiu 476000, Peoples R ChinaBeijing Univ Technol, Coll Appl Sci, Beijing 100124, Peoples R China
Guo, Donglin
Xue, Liugen
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Beijing Univ Technol, Coll Appl Sci, Beijing 100124, Peoples R ChinaBeijing Univ Technol, Coll Appl Sci, Beijing 100124, Peoples R China
Xue, Liugen
Hu, Yuqin
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Beijing Univ Technol, Coll Appl Sci, Beijing 100124, Peoples R China
Zhejiang Univ Finance & Econ, Sch Data Sci, Hangzhou 310018, Peoples R ChinaBeijing Univ Technol, Coll Appl Sci, Beijing 100124, Peoples R China