title: Factors predicting overweight in US kindergartners.
abstract: BACKGROUND
  Childhood overweight is a substantial public-health problem, but little is known about predictors of early childhood overweight.
  
  
  OBJECTIVE
  We aimed to identify factors--alone and in combination--that predict kindergarten overweight.
  
  
  METHODS
  We analyzed nationally representative data from the Early Childhood Longitudinal Study-Birth Cohort, a longitudinal cohort study of 6800 children followed from birth through kindergarten. Multivariable logistic regression and recursive partitioning analysis (RPA) were performed to identify individual and clusters of parental, prenatal/pregnancy, infant, and toddler factors predicting kindergarten overweight. The main outcome was kindergarten overweight [body mass index (BMI) ≥85th percentile, which includes obesity].
  
  
  RESULTS
  The prevalence of kindergarten overweight was 32%. By using combinations (derived from 131 factors) of a weight-for-length or BMI ≥85th percentile at earlier ages, race/ethnicity, a maternal gestational diabetes history, birth weight, and ages at solid-food introduction and the child pulling to a stand, the RPA identified 6 groups with a particularly high prevalence of kindergarten overweight (56-100%) and 2 groups with a particularly low prevalence (11-15%). An especially high prevalence was noted for children with a ≥85th BMI percentile at preschool age (77%) and in children with a ≥85th BMI percentile at 2 y old, for white children whose mother had gestational diabetes (100%), and for minority children with a birth weight <2695.5 g and who pulled themselves to a stand at <7.5 mo old (89%).
  
  
  CONCLUSIONS
  Clusters of parental, prenatal/pregnancy, infant, and toddler factors can be used to predict which children are at particularly high and low risk of becoming overweight kindergartners.
authors.affiliation: Division of General Pediatrics, Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA. glenn.flores@utsouthwestern.edu
authors.forename: Glenn
authors.initials: G
authors.lastname: Flores
authors.forename: Hua
authors.initials: H
authors.lastname: Lin
mesh_terms: D001724:Birth Weight; D015992:Body Mass Index; D002648:Child; D002675:Child, Preschool; D016208:Databases, Factual; D016640:Diabetes, Gestational; D005260:Female; D006801:Humans; D007223:Infant; D016015:Logistic Models; D008137:Longitudinal Studies; D009035:Mothers; D015999:Multivariate Analysis; D050177:Overweight / Q000453:epidemiology* / Q000209:etiology*; D011247:Pregnancy; D015995:Prevalence; D012307:Risk Factors; D012959:Socioeconomic Factors; D012984:Software