Purpose: Longitudinal epidemiologic studies often relate adiposity changes to suspected causal factors. In growing adolescents, this becomes complicated. Many investigators use within-child change in body mass index (BMI) z scores (Δz) from sex- and age-specific BMI charts developed by the Centers for Disease Control and Prevention (CDC). These charts, derived from cross-sectional data, may not represent BMI growth patterns of real children. Furthermore, because cross-sectional BMIs are not Gaussian, these z scores are from month-specific transformed distributions, with possible unintended consequences when used longitudinally. Alternatively, we can directly analyze BMI change (ΔBMI). We compare these two widely used measures of change in adiposity. Methods and Results: With real adolescent data, we show that annual ΔBMIs have nonlinear peaks that are inconsistent with the CDC curves. We also show that a specified Δz represents a broad range of adiposity changes for children measured at the same two ages. To see how this affects power, we performed simulation studies confirming that analyzing ΔBMIs in models with hypothesized factors is more powerful than analyzing Δzs. Conclusions: In longitudinal studies of adolescent adiposity, investigators should be encouraged to analyze ΔBMI rather than Δz because analyses using BMI are more powerful and findings presented in BMI units are more interpretable.

Original languageEnglish
Pages (from-to)44-50
Number of pages7
JournalAnnals of Epidemiology
Issue number1
StatePublished - Jan 2007


  • Body Mass Index (BMI)
  • Children
  • Longitudinal
  • Overweight
  • Simulation
  • Weight Gain
  • z Scores


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