title: The transition to post-industrial BMI values among US children.
abstract: The trend in the BMI values of US children has not been estimated very convincingly because of the absence of longitudinal data. Our objective is to estimate time series of BMI values by birth cohorts instead of measurement years. We use five regression models to estimate the BMI trends of non-Hispanic US-born black and white children and adolescents ages 2-19 between 1941 and 2004. The increase in BMIZ values during the period considered was 1.3 sigma (95% CI: 1.16 sigma; 1.44 sigma) among black girls, 0.8 sigma for black boys, 0.7 sigma for white boys, and 0.6 sigma for white girls. This translates into an increase in BMI values of some 5.6, 3.3, 2.4, and 1.5 units, respectively. While the increase in BMI values started among the birth cohorts of the 1940s among black girls, the rate of increase tended to accelerate among all four ethnic/gender groups born in the mid-1950s to early-1960s. Some regional evidence leads to the conjecture that the spread of automobiles and radios affected the BMI values of boys already in the interwar period. We suppose that the changes in lifestyle associated with the labor saving technological developments of the 20th century are associated with the weight gains observed. The increased popularity of television viewing was most prominently associated with the contemporaneous acceleration in BMI gain.
authors.affiliation: Department of Economics, University of Munich, Munich, Germany. John.Komlos@gmx.de
authors.forename: John
authors.initials: J
authors.lastname: Komlos
authors.forename: Ariane
authors.initials: A
authors.lastname: Breitfelder
authors.forename: Marco
authors.initials: M
authors.lastname: Sunder
mesh_terms: D000293:Adolescent; D044383:Black People / Q000706:statistics & numerical data*; D015992:Body Mass Index; D002648:Child; D002675:Child, Preschool; D005260:Female; D006801:Humans; D007223:Infant; D008019:Life Style; D008297:Male; D050177:Overweight / Q000453:epidemiology / Q000208:ethnology* / Q000209:etiology; D012044:Regression Analysis; D012307:Risk Factors; D013690:Television; D014481:United States / Q000453:epidemiology; D044465:White People / Q000706:statistics & numerical data*; D055815:Young Adult; D001741:Black or African American