Stratified Multilevel Logistic Regression Modeling for Risk Factors of Adolescent Obesity in Tennessee

<p> Background: US adolescent obesity rates have quadrupled over the past 3 decades. Research examining complex factors associatedwith obesity is limited.Objectives: The purpose of this study was to utilize a representative sample of students (grades 6 - 8) in Tennessee to determine theco-occurrence of risk behaviors with adolescent obesity prevalence and to analyze variations by strata. Methods: The 2010 youth risk behavior survey dataset was used to examine associations of obesity with variables related to sampledemographics, risk and protective behaviors, and region. Hierarchical logistic regression analyses strati&filig;ed by demographics andregion were conducted to evaluate variation in obesity risk occurring on three hierarchical levels: class, school and district. Results: The sample consisted of 60715 subjects. The overall obesity rate was 22%. High prevalence of obesity existed in males, non-white race, those ever smoked and was positively correlated with age. Across three state regions, race, gender, and speci&filig;c behaviors (smoking, weight misperception, disordered eating, +3 hours TV viewing, and no sports team participation) persisted as signi&filig;cantpredictors of adolescent obesity, although variations by region and demographics were observed. Multilevel analyses indicate that&lt; 1%, 0 - 1.97% and4.03 - 13.06% of the variation in obesity was associated with district, school and class di&fflig;erences, respectively, whenstratifying the sample by demographic characteristics or region. Conclusions: Uniform school-based prevention e&fflig;orts targeting adolescent obesity risk may have limited impact if they fail torespond to geographical and demographic nuances that hierarchal modeling can detect. Study results reveal that strati&filig;ed hi-erarchical analytic approaches to examine adolescent obesity risk have tremendous potential to elucidate signi&filig;cant prevention insights.</p>