2.50
Hdl Handle:
http://hdl.handle.net/2436/107236
Title:
Adjusting athletes' body mass index to better reflect adiposity in epidemiological research.
Authors:
Nevill, Alan M.; Winter, Edward M.; Ingham, Steve; Watts, Adam; Metsios, Giorgos S.; Stewart, Arthur D.
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 P < 0.001). 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 (5.81 mm . (kg . m(-2))(-1)) was greater than the BMI slope parameter for sports (2.62 mm . (kg . m(-2))(-1)) and middle-distance runners (0.94 mm . (kg . m(-2))(-1)) (P < 0.001). 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.
Affiliation:
Research Institute of Healthcare Sciences, University of Wolverhampton, Walsall.
Citation:
Journal of Sports Sciences, First published on: 07 June 2010 (iFirst)
Publisher:
Routledge
Journal:
Journal of sports sciences
Issue Date:
2010
URI:
http://hdl.handle.net/2436/107236
DOI:
10.1080/02640414.2010.487071
PubMed ID:
20544485
Type:
Article
Language:
en
Description:
iFirst article (Epub ahead of print)
ISSN:
0264-0414
EISSN:
1466-447X
Appears in Collections:
Learning and Teaching in Sport, Exercise and Performance

Full metadata record

DC FieldValue Language
dc.contributor.authorNevill, Alan M.en
dc.contributor.authorWinter, Edward M.en
dc.contributor.authorIngham, Steveen
dc.contributor.authorWatts, Adamen
dc.contributor.authorMetsios, Giorgos S.en
dc.contributor.authorStewart, Arthur D.en
dc.date.accessioned2010-07-06T09:27:24Z-
dc.date.available2010-07-06T09:27:24Z-
dc.date.issued2010-
dc.identifier.citationJournal of Sports Sciences, First published on: 07 June 2010 (iFirst)en
dc.identifier.issn0264-0414-
dc.identifier.pmid20544485-
dc.identifier.doi10.1080/02640414.2010.487071-
dc.identifier.urihttp://hdl.handle.net/2436/107236-
dc.descriptioniFirst article (Epub ahead of print)en
dc.description.abstractThe 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 P < 0.001). 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 (5.81 mm . (kg . m(-2))(-1)) was greater than the BMI slope parameter for sports (2.62 mm . (kg . m(-2))(-1)) and middle-distance runners (0.94 mm . (kg . m(-2))(-1)) (P < 0.001). 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.en
dc.languageENG-
dc.language.isoenen
dc.publisherRoutledgeen
dc.subjectAdiposityen
dc.subjectObesityen
dc.subjectBody mass indexen
dc.subjectBody compositionen
dc.subjectSporten
dc.subjectAthletesen
dc.subjectSlope parametersen
dc.subjectSkinfold thicknessen
dc.titleAdjusting athletes' body mass index to better reflect adiposity in epidemiological research.en
dc.typeArticleen
dc.identifier.eissn1466-447X-
dc.contributor.departmentResearch Institute of Healthcare Sciences, University of Wolverhampton, Walsall.en
dc.identifier.journalJournal of sports sciencesen

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