title: Propensity score estimates in multilevel models for causal inference.
abstract: 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.
  
  
  OBJECTIVE
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: School of Nursing, Stony Brook University, New York 11794-8240, USA. patricia.eckardt@stonybrook.edu
authors.forename: Patricia
authors.initials: P
authors.lastname: Eckardt
mesh_terms: D000293:Adolescent; D015992:Body Mass Index; D015984:Causality; D005247:Feeding Behavior; D006801:Humans; D016015:Logistic Models; D008137:Longitudinal Studies / Q000706:statistics & numerical data; D015999:Multivariate Analysis; D009765:Obesity / Q000209:etiology / Q000517:prevention & control*; D057216:Propensity Score; D012944:Social Support; D013334:Students / Q000523:psychology*; D014481:United States