Baseline Aerobic Fitness in High School and College Football Players: Critical for Prescribing Safe Exercise Regimens.

BACKGROUND: Nontraumatic fatalities occur on a regular basis in high school (HS) and college football athletes, primarily in obese linemen performing high-intensity exercise. One contributing factor to these deaths may be a mismatch between baseline aerobic (cardiorespiratory) fitness and exercise regimens. HYPOTHESIS: There is a wide range of aerobic fitness in HS and college football players. Body mass index (BMI) is a safe and simple method for estimating baseline aerobic fitness. STUDY DESIGN: Retrospective cohort study. LEVEL OF EVIDENCE: Level 3. METHODS: A retrospective review was performed on 79 HS football athletes who had VO2Peak (mL·kg-1·min-1) measured during the offseason. Multivariate regression analysis was used to determine if BMI (obese, overweight, and normal; kg/m2), position played (linemen vs other), year in school (freshmen vs other), and/or race (African American vs White) were risk factors for poor aerobic fitness. A separate cohort of 135 (48 HS; 87 college) football athletes performed a 6-minute run test to determine speed (miles/min), extrapolate VO2Max, and calculate reference values for suggested upper threshold safe starting speeds (85% of maximum) for aerobic training based on BMI. The relationship between BMI and VO2Peak was assessed. The exercise regimens (speeds) of 2 collegiate football fatalities from the public domain were used to predict their VO2Max values. RESULTS: Mean VO2Peak (mL·kg-1·min-1) was 38.5 ± 8.6 (range 19.1-60.6); when grouped by BMI, low scores (<40) were found in 87.5% of obese (32.4 ± 7.7), 47.8% of overweight (40.8 ± 7.6), and 45.2% of normal (41.4 ± 7.8) athletes. VO2Peak was significantly lower in linemen (32.8 ± 6.4; P = 0.007) compared with nonlineman (41.8 ± 7.9), and in obese players (by BMI; 32.4; P = 0.019) compared with nonobese players (41.4 ± 7.6), but did not differ by age, year in school, or race. Means for speed (min/mile) and extrapolated VO2Max (mL·kg-1·min-1) for the 6-minute run test by BMI groups were both significantly different (P = 0.001) for normal (7.0 ± 0.6; 51.1 ± 2.6), overweight (7.6 ± 0.8; 46.5 ± 3.2), and obese (8.9 ± 1.5; 36.8 ± 5.9) athletes. There was a significant negative correlation (r = -0.551; P = 0.001; R2 = 0.304) between VO2Peak and BMI. Safe starting speed recommendations for running 1 mile range from 7.3 to 12.1 min/mile for BMIs 20 to 40 kg/m2 for HS and college athletes. For the 2 fatalities (mean, BMI of 36.5 kg/m2) repetitive sprint speeds were 49 and 89% higher than our safe starting speeds for their BMI. CONCLUSION: A large spectrum of baseline aerobic fitness was noted in HS and college football players. Obese players and linemen had statistically lower baseline aerobic fitness, a major risk factor for possible heat illness. BMI is an acceptable surrogate for VO2Peak and can be employed to develop safe training regimens without the need for a maximum fitness test, which can place the athlete at risk for a medical event. CLINICAL RELEVANCE: Knowledge of BMI provides an estimate of baseline aerobic fitness and a foundation for prescribing safe, individualized exercise regimens.

Following up fighting fit: the long-term impact of health practitioner input on obesity and BMI amongst adults with intellectual disabilities.

This article presents findings on the long-term impact of health practitioner input to reduce obesity amongst adults with intellectual disabilities. Body mass index (BMI) was measured for an input group (N = 33) and a comparison group (N = 40) 6 years after the input group first received input. Data on BMI were collected at baseline, 6 months, 1 year and 6 years. Mean BMI for the input group reduced steadily over 6 years. Mean BMI in the non-input group rose initially, stabilized and then decreased (although remaining higher than at baseline). The input group demonstrated improvements in obesity levels and lost more weight than the non-input group. However, the differences between groups did not reach statistical significance. This and the improvements in BMI within the non-input group may be due to the relatively small sample size, effect size and the impact of other local initiatives.

Fighting fit? An evaluation of health practitioner input to improve healthy living and reduce obesity for adults with learning disabilities.

People with learning disabilities are at high risk of obesity and consequent health risks. This study aimed to (1) describe levels of obesity for adults supported by learning disability services, and to (2) evaluate the effectiveness of health practitioner input with individuals with learning disabilities. Body mass index (BMI) was measured at 6 month intervals and change in BMI over time was compared between a non-input group and a group receiving practitioner input to improve healthy living. Initially 35 percent of the non-input sample was classified as clinically obese. Mean BMI increased over time for the non-input group at first, but decreased for the group that received practitioner input. The differences in weight change between the two groups reached statistical significance with a greater weight reduction in the input group. Implications for service provision are discussed.