2016
DOI: 10.4085/1062-6050-51.5.14
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Body Size Changes Among National Collegiate Athletic Association New England Division III Football Players, 1956−2014: Comparison With Age-Matched Population Controls

Abstract: Main Outcome Measure(s): Body weight, height, and calculated body mass index were evaluated using analysis of variance, linear regression, and nonlinear regression to determine the distribution features of size variables and changes associated with time (year), school, and position. Conclusions: High body weight and body mass indices were evident in offensive linemen, even among those in Division III football programs with no athletic scholarships. These characteristics may be associated with adverse cardiovas… Show more

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Cited by 8 publications
(7 citation statements)
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“…The method in principle is generalizable, but prediction accuracy might be compromised among subject groups having body construction that is not "typical" of the representative population sample used to develop the algorithm. [55][56][57][58][59][60][61][62][63][64][65][66][67] Another potential source of variance includes differences among study sites in manufacturer and calibration procedures of the DXA scanning instrumentation itself. [44][45][46] In the present study, instrumentation differences were accounted for, insofar as possible, through cross-calibration studies evaluating DXA scanning instruments from different manufacturers.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…The method in principle is generalizable, but prediction accuracy might be compromised among subject groups having body construction that is not "typical" of the representative population sample used to develop the algorithm. [55][56][57][58][59][60][61][62][63][64][65][66][67] Another potential source of variance includes differences among study sites in manufacturer and calibration procedures of the DXA scanning instrumentation itself. [44][45][46] In the present study, instrumentation differences were accounted for, insofar as possible, through cross-calibration studies evaluating DXA scanning instruments from different manufacturers.…”
Section: Discussionmentioning
confidence: 99%
“…Deviations between predicted body fat based on quantitative surrogates (such as BMI) and actual body fat as measured by DXA are reported in studies of "atypical" groups such as muscular athletes, endurance athletes, jockeys, and individuals with eating disorders. [55][56][57][58][59][60][61][62][63][64][65][66][67]…”
Section: S45mentioning
confidence: 99%
“…We previously estimated the global prevalence of the overfat population using several subpopulations that included those who are overweight, obese, MONW individuals, those with sarcopenic obesity and others ( 1 ). Additionally, the overfat pandemic has not spared physically active people, including professional athletes in various sports ( 82 , 83 ) and active US military personnel ( 84 , 85 ).…”
Section: Who Is Overfatmentioning
confidence: 99%
“…However, physical activity and exercise is expected to increase energy expenditure and whole body fat oxidation, with a sedentary lifestyle decreasing insulin sensitivity and fat oxidation, potentially increasing stored body fat ( 78 82 ). This includes elite athletes and those in active military, who can also have excess body fat ( 83 86 ). In healthy adults, high glycemic foods can also reduce overall energy expenditure by nearly 50% compared with isoenergetic meals containing whole foods ( 87 ).…”
Section: Lifestyle Influence On Body Fatmentioning
confidence: 99%