To estimate the prevalence of metabolic syndrome and insulin resistance in a cohort of Division 1 collegiate football players.
Ninety football players were evaluated in a cross-sectional study to estimate the prevalence of metabolic syndrome, insulin resistance, and associated risk factors. Obesity was defined as a body fat ≥25% determined by BOD POD measurements. The National Cholesterol Education Program Adult Treatment Panel III criteria were used to estimate prevalence of metabolic syndrome. Quantitative insulin sensitivity check index calculations were performed to estimate prevalence of insulin resistance. Linear regression techniques were used to determine association between body fat percentage and other measured continuous parameters. Fisher exact test was used to determine association between nominal variables, and one-way ANOVA compared the three groups defined by position.
Summary measures showed a small prevalence of abnormal individual measurements. There was an association between body fat percentage and most evaluated parameters (P < 0.05). The prevalence of obesity, insulin resistance, and metabolic syndrome was 21%, 21%, and 9%, respectively. Obesity is closely associated with metabolic syndrome (P < 0.0001) and insulin resistance (P < 0.0001) in this population. All subjects with metabolic syndrome were obese, and the odds for insulin resistance in the obese group are 10.6 times the odds for the nonobese group. Linemen (n = 29) had 19 of the 19 obese subjects, 13 of the 19 subjects with insulin resistance, and all subjects with metabolic syndrome.
There is a strong association between obesity and both metabolic syndrome and insulin resistance in Division 1 collegiate football players. Linemen are at significant risk for metabolic syndrome and insulin resistance compared with other positions. This may be predictive of future health problems in Division 1 collegiate football players, especially linemen.
Ohio State University, Columbus, OH
Address for correspondence: James R. Borchers, M.D., M.P.H., 2050 Kenny Rd, Columbus, OH 43210; E-mail: email@example.com.
Submitted for publication January 2009.
Accepted for publication April 2009.