Adjusting athletes' body mass index to better reflect adiposity in epidemiological research

NEVILL, A. M., WINTER, E., INGHAM, S., WATTS, A., METSIOS, G. S. and STEWART, A. D. (2010). Adjusting athletes' body mass index to better reflect adiposity in epidemiological research. Journal of sport sciences, 28 (9), 1009-1016.

Full text not available from this repository.
Link to published version:: https://doi.org/10.1080/02640414.2010.487071

Abstract

The aim of the present study was to identify when body mass index (BMI) is unlikely to be a valid measure of adiposity in athletic populations and to propose a simple adjustment that will allow the BMI of athletes to reflect the adiposity normally associated with non-athletic populations. Using data from three previously published studies containing 236 athletes from seven sports and 293 age-matched controls, the association between adiposity (sum of 4 skinfold thicknesses, in millimetres) and BMI was explored using correlation, linear regression, and analysis of covariance (ANCOVA). As anticipated, there were strong positive correlations (r=0.83 for both men and women) and slope parameters between adiposity and BMI in age-matched controls from Study 1 (all P0.001). The standard of sport participation reduced these associations. Of the correlations and linear-regression slope parameters between adiposity and BMI in the sports from Studies 2 and 3, although still positive in most groups, less than half of the correlations and slope parameters were statistically significant. When data from the three studies were combined, the ANCOVA identified that the BMI slope parameter of controls (5.81mm center dot(kg center dot m-2)-1) was greater than the BMI slope parameter for sports (2.62mm center dot(kg center dot m-2)-1) and middle-distance runners (0.94mm center dot(kg center dot m-2)-1) (P0.001). Based on these contrasting associations, we calculated how the BMI of athletes can be adjusted to reflect the same adiposity associated with age-matched controls. This simple adjustment allows the BMI of athletes and non-athletes to be used with greater confidence when investigating the effect of BMI as a risk factor in epidemiological research.

Item Type: Article
Research Institute, Centre or Group - Does NOT include content added after October 2018: Centre for Sport and Exercise Science
Identification Number: https://doi.org/10.1080/02640414.2010.487071
Page Range: 1009-1016
Depositing User: Rachel Davison
Date Deposited: 19 Oct 2010 13:38
Last Modified: 19 Mar 2021 00:46
URI: https://shura.shu.ac.uk/id/eprint/2570

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics