Adiposity in adolescents: change in actual BMI works better than change in BMI z score for longitudinal studies

Ann Epidemiol. 2007 Jan;17(1):44-50. doi: 10.1016/j.annepidem.2006.07.014. Epub 2006 Nov 29.


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 (Delta z) 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 (Delta BMI). We compare these two widely used measures of change in adiposity.

Methods and results: With real adolescent data, we show that annual Delta BMIs have nonlinear peaks that are inconsistent with the CDC curves. We also show that a specified Delta z 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 Delta BMIs in models with hypothesized factors is more powerful than analyzing Delta zs.

Conclusions: In longitudinal studies of adolescent adiposity, investigators should be encouraged to analyze Delta BMI rather than Delta z because analyses using BMI are more powerful and findings presented in BMI units are more interpretable.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adipose Tissue / growth & development*
  • Adiposity / physiology*
  • Adolescent
  • Adolescent Behavior
  • Adolescent Development / physiology*
  • Body Mass Index*
  • Centers for Disease Control and Prevention, U.S.
  • Child
  • Child Development / physiology
  • Computer Simulation
  • Exercise / physiology
  • Female
  • Humans
  • Longitudinal Studies*
  • Male
  • Overweight / physiology
  • Reference Values
  • United States
  • Weight Gain / physiology