Title page for ETD etd-03272008-085840


Type of Document Master's Thesis
Author Zanovec, Michael
Author's Email Address mzanov1@lsu.edu, mzanovec@agcenter.lsu.edu
URN etd-03272008-085840
Title The Impact of Self-Reported Physical Activity Levels on the Prediction of Body Fatness from BMI in White and Black College Students
Degree Master of Science (M.S.)
Department Human Ecology
Advisory Committee
Advisor Name Title
Georgianna Tuuri Committee Chair
Brian Marx Committee Member
Lisa Johnson Committee Member
Michael Keenan Committee Member
Keywords
  • Prediction equation
  • IPAQ
  • self-reported physical activity
  • college students
  • BMI
  • DXA
  • Body composition
  • body fat
Date of Defense 2008-03-11
Availability unrestricted
Abstract
The purpose of this study was to test the hypothesis that self-reported physical activity (PA) levels quantified from the International Physical Activity Questionnaire (IPAQ) could be used to improve the prediction of percent body fat (%BF) measured by dual-energy X-ray absorptiometry (DXA) from body mass index (BMI), gender, and race in White and Black college students.

A total of 278 students, aged 18 24 yr, volunteered to participate. There were 133 males (85 White and 48 Black) and 145 females (77 White and 68 Black). Total activity levels were quantified in MET-hours per week (MET-hrswk-1) using the IPAQ short form. Height and weight were measured and BMI values calculated (kgm-2). Percent fat was assessed using DXA. Regression analysis was used to determine the impact of MET-hrswk-1 on the relationship between %BF and BMI, taking gender and race into account. The prediction sum of squares (PRESS) statistic was used to cross-validate the models.

Mean ( SD) values were as follows: MET-hrswk-1 37.4 21.9, %BF 24.5 9.3%, and BMI 24.4 4.1 kgm-2. Percent body fat was significantly correlated with MET-hrswk-1 (r = -0.44, p < 0.0001) and BMI (r = 0.38, p < 0.0001). Stepwise regression analysis of a reduced model with BMI, gender and race produced an R2 value of 0.81 (root mean square error [RMSE] = 4.07). The full model with MET-hrswk-1 marginally improved the prediction of %BF (R2 = 0.83, RMSE = 3.87). When cross-validated, the corresponding PRESS statistic for the reduced and full model was 4.10 and 3.90, respectively.

These results suggest that %BF can be predicted with greater precision and accuracy in a college-aged population when MET-hrswk-1 are included in addition to BMI, gender, and race.

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