title: Using routinely collected growth data to assess a school-based obesity prevention strategy.
abstract: BACKGROUND
  Studies of school-based anti-obesity interventions have yielded inconsistent results. Using growth screening data from a school administrative database, we re-evaluated an obesity prevention strategy that was previously reported to have a beneficial effect on weight status of a sample of students in grades 5-7.
  
  
  METHODS
  Ten K-8 schools (five control and five intervention) participated in a 2-year cluster-randomized trial of a multi-component nutrition education intervention. We obtained student height and weight data for 6 consecutive school years and imputed missing baseline and follow-up measurements (53% and 55%, respectively) and defined the target population based on the intent-to-treat principle. We analyzed changes in body mass index (BMI) Z-scores via mixed-effects linear regression and in the prevalence of overweight/obesity via conditional logistic regression. We also assessed incidence and remission of overweight/obesity and long-term effects.
  
  
  RESULTS
  We analyzed data for 8186 (96%) K-8 students in the 10 schools (4511 in intervention; 3675 in control). From baseline to the end of the intervention period, mean increases in BMI Z-score were 0.10 and 0.09 in the control and intervention groups, respectively (P=0.671). The prevalence of overweight/obesity increased by 3% in both groups (P=0.926). There was no significant intervention effect on the incidence or remission of overweight/obesity. Among 5469 students who attended study schools during both years of the intervention, there was no significant intervention effect. Furthermore, there was no long-term effect among students with up to 2 years of data beyond the end of the intervention.
  
  
  CONCLUSIONS
  Using routinely collected data for the entire target population, we failed to confirm earlier findings of an intervention effect observed in a subset of students in grades 5-7. Volunteer bias in the prior evaluation and/or measurement error in the routinely collected data are potential reasons for the discrepant findings.
authors.affiliation: Department of Family and Community Medicine, Thomas Jefferson University, Philadelphia, PA 19107, USA. elizabeth.rappaport@jefferson.edu
authors.forename: E B
authors.initials: EB
authors.lastname: Rappaport
authors.forename: C
authors.initials: C
authors.lastname: Daskalakis
authors.forename: J A
authors.initials: JA
authors.lastname: Sendecki
mesh_terms: D000704:Analysis of Variance; D002648:Child; D002662:Child Health Services / Q000458:organization & administration*; D002664:Child Nutritional Physiological Phenomena; D002675:Child, Preschool; D016000:Cluster Analysis; D004032:Diet; D015444:Exercise; D005260:Female; D005500:Follow-Up Studies; D006293:Health Promotion / Q000458:organization & administration*; D006801:Humans; D015994:Incidence; D008297:Male; D009765:Obesity / Q000453:epidemiology / Q000517:prevention & control*; D015143:Philadelphia / Q000453:epidemiology; D015397:Program Evaluation; D015203:Reproducibility of Results; D018570:Risk Assessment; D012572:School Health Services / Q000458:organization & administration*; D017678:Sex Distribution