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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.AE

Abstract

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.

Authors+Show Affiliations

Channing Laboratory, Department of Medicine, Brigham & Women's Hospital and Harvard Medical School, Boston, MA 02115, USA. catherine.berkey@channing.harvard.eduNo affiliation info available

Pub Type(s)

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

Language

eng

PubMed ID

17140812

Citation

Berkey, Catherine S., and Graham A. Colditz. "Adiposity in Adolescents: Change in Actual BMI Works Better Than Change in BMI Z Score for Longitudinal Studies." Annals of Epidemiology, vol. 17, no. 1, 2007, pp. 44-50.
Berkey CS, Colditz GA. Adiposity in adolescents: change in actual BMI works better than change in BMI z score for longitudinal studies. Ann Epidemiol. 2007;17(1):44-50.
Berkey, C. S., & Colditz, G. A. (2007). Adiposity in adolescents: change in actual BMI works better than change in BMI z score for longitudinal studies. Annals of Epidemiology, 17(1), 44-50.
Berkey CS, Colditz GA. Adiposity in Adolescents: Change in Actual BMI Works Better Than Change in BMI Z Score for Longitudinal Studies. Ann Epidemiol. 2007;17(1):44-50. PubMed PMID: 17140812.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Adiposity in adolescents: change in actual BMI works better than change in BMI z score for longitudinal studies. AU - Berkey,Catherine S, AU - Colditz,Graham A, Y1 - 2006/11/29/ PY - 2005/11/30/received PY - 2006/07/22/revised PY - 2006/07/31/accepted PY - 2006/12/5/pubmed PY - 2007/2/21/medline PY - 2006/12/5/entrez SP - 44 EP - 50 JF - Annals of epidemiology JO - Ann Epidemiol VL - 17 IS - 1 N2 - 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. SN - 1047-2797 UR - https://www.unboundmedicine.com/medline/citation/17140812/Adiposity_in_adolescents:_change_in_actual_BMI_works_better_than_change_in_BMI_z_score_for_longitudinal_studies_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S1047-2797(06)00231-6 DB - PRIME DP - Unbound Medicine ER -