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Prevalence of Metabolic Syndrome Risk Factors in High School and NCAA Division I Football Players

Steffes, Gary D.1; Megura, Alex E.1; Adams, James1; Claytor, Randal P.1; Ward, Rose M.1; Horn, Thelma S.1; Potteiger, Jeffrey A.2

Journal of Strength and Conditioning Research: July 2013 - Volume 27 - Issue 7 - p 1749–1757
doi: 10.1519/JSC.0b013e31827367cd
Original Research
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Steffes, GD, Megura, AE, Adams, J, Claytor, RP, Ward, RM, Horn, TS, and Potteiger, JA. Prevalence of metabolic syndrome risk factors in high school and NCAA Division I football players. J Strength Cond Res 27(7): 1749–1757, 2013—Metabolic syndrome (MetSyn) is a clustering of metabolic and cardiovascular disease risk factors. The purpose of this study was to determine the prevalence of MetSyn risk factors in high school (HS) and college (College) football players and to examine if the prevalence varied according to body fat percent (%Fat). One hundred twenty-three males (height 179.0 ± 6.7 cm; weight 89.4 ± 19.6 kg) from 7 different high schools and 82 males (height 186.2 ± 6.8 cm; weight 99.6 ± 16.8 kg) from one university participated. All testing occurred in the early morning after an overnight fast. %Fat, waist circumference, resting systolic and diastolic blood pressure, fasting triglyceride, high-density lipoprotein (HDL) cholesterol, and blood glucose were determined using standard testing procedures. The MetSyn risk factor levels were determined using American Heart Association criteria. Subjects were grouped by position and playing level (HS, College). Independent t-tests, chi-square analysis, 2-way analysis of variance, and path analytic models were used in the statistical analysis. Significance was set at p < 0.05. 6.8% (n = 14) of the sample met the American Heart Association criteria for MetSyn. Offensive and defensive linemen accounted for 92.3% of the players meeting MetSyn criteria with each playing level (HS, College) having 7 subjects. The MetSyn criteria differed significantly across %Fat. Obese players were more likely to meet the criteria for MetSyn. %Fat was a statistically significant predictor of mean arterial blood pressure, HDL cholesterol, and waist circumference. The MetSyn exists in both HS- and College-level football players, with almost all cases occurring in the athletes with the highest levels of %Fat (offensive/defensive lineman). Strength and conditioning coaches should be aware of the prevalence of MetSyn risk factors in offensive and defensive linemen and take appropriate actions to ensure athlete safety.

1Department of Kinesiology and Health, Miami University, Oxford, Ohio

2Department of Movement Science, Grand Valley State University, Grand Rapids, Michigan

Address correspondence to Dr. Jeffrey A. Potteiger, jeffrey_potteiger@gvsu.edu.

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Introduction

Metabolic syndrome (MetSyn) is a clustering of risk factors identifying individuals at an increased risk for metabolic and cardiovascular disease (14). The most common criteria for MetSyn are elevated fasting plasma glucose and triglyceride levels, abdominal obesity, hypertension, and depressed high-density lipoprotein (HDL) cholesterol levels (4,14). Insulin resistance and markers of inflammation are often considered secondary indicators of MetSyn (2). There is an increasing prevalence of the MetSyn among U.S. adults with a recent report showing an estimated 34% of individuals 20 years of age and older having at least 3 risk factors for MetSyn (11).

Although some may believe that athletes are exempt from acquiring MetSyn and subsequently having an increased risk of metabolic and cardiovascular disease, several recent studies have revealed high incidence rates of MetSyn and cardiovascular disease risk factors in National Football League (NFL) lineman (3,4,19,22,23,28). For example, in one recent finding, former NFL linemen had a 52% greater risk of death from cardiovascular disease compared with the general population, 3 times the risk of dying from heart disease compared with nonlinemen, and almost 60% of retired linemen had MetSyn compared with less than one-third of age-matched subjects from the National Health and Nutrition Examination Survey data base (19). Several other reports have also indicated that college football linemen have a significantly increased risk for developing MetSyn and insulin resistance (3,4,28). Strong associations among body fat levels, waist circumference, and MetSyn risk factors have been demonstrated in National Collegiate Athletic Association (NCAA) football players across all division levels (3,4,28).

The risk factors for MetSyn can be detected during childhood and commonly persist throughout adolescence and adulthood (5,9). As with adults, the levels of body fat and waist circumference are strong predictors of the prevalence of MetSyn (5,7,24). For example, Vissers et al. (24) demonstrated that the prevalence of MetSyn in 16- to 19-year old students was highest in the obese students (39.1%) compared with overweight (2.8%) and normal weight (0.3%) students. There is an increased prevalence of excess body weight in adolescents (26), and this excess body weight also extends to football athletes (6,17,18). Elevated levels of body weight in adolescent football players are likely to result in an increased prevalence of MetSyn in this population as well. However, currently few data exist defining this prevalence rate.

It is important to expand the research on the prevalence of MetSyn in high school age and college age football players. It is imperative that the identification and management of risk factors for MetSyn occur early in life so that preventive measures and treatment interventions can reduce the likelihood of developing metabolic and cardiovascular disease later in life. The purpose of this investigation was to make an assessment of body composition levels and MetSyn prevalence in both high school and Division I college football players aged 15–22 years. We hypothesized that the players with the highest level of body fat (e.g., offensive and defensive linemen) would have the greatest prevalence of MetSyn risk factors and that this premise would hold true for both high school and college players. We also hypothesized that body mass index (BMI) and %Fat would be strong predictors of the MetSyn risk factors. This study was designed to improve our understanding of both the prevalence and the factors that contribute to development of MetSyn, thereby improving the accuracy of metabolic and cardiovascular disease risk assessment and management in these individuals.

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Methods

Experimental Approach to the Problem

We used a cross-sectional design to examine the prevalence of MetSyn in high school and college football players. All subjects participated in one data collection session between 0600 and 1000 hours during which the measurements were made for all dependent variables. The prevalence of MetSyn was determined using the risk factor criteria for MetSyn as defined by American Heart Association/National Heart, Lung, and Blood Institute Criteria for defining MetSyn (14). We used the revised NCEP ATP III clinical criteria for MetSyn: (a) increased waist circumference (≥102 cm in men); (b) increased triglycerides (≥150 mg·dl−1); (c) decreased HDL cholesterol (<40 mg·dl−1 in men); (d) increased blood pressure (≥130 mm Hg systolic or ≥85 mm Hg diastolic); and (e) increased fasting glucose (≥100 mg·dl−1) (14). Subjects refrained from any exercise and from consuming any food or fluids, except water for 8 hours before testing. Subjects completed a questionnaire about training status and playing experience, as well as a health history questionnaire.

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Subjects

High school (HS, n = 123; age 16.3 ± 0.9 years) and college (College, n = 82; age 19.8 ± 1.4 years) football players between the ages of 15 and 22 years voluntarily participated in this study. The HS subjects were recruited from 7 different high schools in the greater suburban and urban Cincinnati Ohio area. The College subjects were all from an NCAA Division I University. All subjects younger than 18 years provided written parental informed consent and verbal informed assent, and subjects older than 18 years read and voluntarily signed a written informed consent form. All methods and procedures were approved by the Human Subjects Institutional Review Board at Miami University. Inclusionary criteria were male, aged 15–22 years, and a member of their high school or college football team. All subjects were participating in an off-season training session during the time they were tested.

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Anthropometric Measures

Height was measured using a Seca 213 platform stadiometer (Seca Corp, Hanover, MD, USA). Body weight was measured using the calibrated electronic platform scale (BIA, Tanita TBF 300A; Tanita, Arlington Heights, IL, USA) while the subject was wearing only compression shorts. Body mass index was calculated from the height and weight measures (1). Waist circumference was measured to the nearest 0.1 cm at the highest point of the iliac crest, at minimal respiration (1). Circumference measures were made using a spring loaded Gulick II tape measure that applies 4 ounces of tension to the measuring tape to insure accuracy. Three measurements were made, with the average used in the statistical analysis.

Body composition was assessed using bioelectrical impedance analysis (BIA, Tanita TBF 300A; Tanita) and air displacement plythesmography (Bod Pod; Life Measurement, Inc., Concord, CA, USA) according to the manufacturer's instructions. All subjects were tested after voiding and while wearing only compression shorts. Percent body fat (%FAT) and body mass were used to calculate the amount of fat mass and fat-free mass for each subject (1). All HS subjects were tested using the BIA, with a subsample assessed using the Bod Pod. All College subjects were tested using the BIA and the Bod Pod. A paired t-test indicated no significant difference in %FAT between the 2 body composition assessment methods for both the HS and College subjects (p > 0.05).

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Resting Blood Pressure

Before testing, all subjects were required to rest sitting in a chair for 10 minutes. In the HS subjects, resting blood pressure was measured using an automated blood pressure measurement cuff (Omron HEM907XL; Omron, Bannockburn, IL, USA). In the College subjects, blood pressure was measured by the same research technician using a mercury-gravity manometer and stethoscope. The right arm was placed on a table so it was resting at the same height as the heart. The average of the 2 blood pressures was then determined. If the 2 blood pressures varied by more than 5 mm Hg, then blood pressure was retaken until it was within a 5 mm Hg range of variation. Systolic blood pressure was measured as the appearance of the first Korotkoff sound, whereas diastolic blood pressure was measured as the fifth phase Korotkoff sound. The 2 closest measurements were averaged and used in the statistical analysis. Mean arterial pressure (MAP) was calculated as ([systolic blood pressure − diastolic blood pressure] × 0.33) + diastolic blood pressure (1).

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Blood Chemistry

A small sample of blood (150 ml) was collected from a fingerstick puncture into a microcapillary tube using standard phlebotomy techniques. The blood was analyzed for blood glucose, total cholesterol, low-density lipoprotein cholesterol, HDL cholesterol, and triglycerides using an automated blood chemistry analyzer (Cholestec LDX; Hayward, CA, USA). The Cholestec was calibrated before each testing session according to the manufacturer's instructions.

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Statistical Analyses

All subjects were categorized by playing level (HS and College) and by playing position: Big (offensive and defensive linemen), Athletic (quarterbacks, tight ends, running backs, and linebackers), and Skilled (wide receivers and defensive backs). To test for the effects of playing level or playing position on MetSyn, we used a continuous z score that was calculated from the 5 MetSyn risk factors. The MetSyn z score was calculated from individual subject data, NCEP ATP III criteria, and SDs using data from the entire subject cohort. The equation used was: z score = ([40 − HDL cholesterol]/SD) + ([triglycerides − 150]/SD) + ([fasting plasma glucose − 100]/SD) + ([waist circumference – 102]/SD) + ([mean arterial pressure − 100]/SD) (13,16,27).

A series of analyses were used to examine the data separately (HS only and College only) and in combination. Initial analyses using independent t-tests examined differences across the samples (HS vs. College) with respect to demographic variables. A chi-square analysis examined the prevalence of MetSyn by football position across playing level. Two-way analysis of variance (ANOVA) tests were used to assess differences across the playing level (HS, College) and the playing position (Big, Athletic, Skilled). The prevalence of the symptoms of MetSyn was also assessed with a 1-way ANOVA. Finally, path analytic models were used to provide a simultaneous examination of the risk factors BMI and body fat percentage across the samples. All analyses were conducted using SPSS version 18.0, with statistical significance set at p < 0.05. Values are reported as mean ± SD.

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Results

Participants

The majority of the HS subjects were white (79.7%) and in 12th grade (54.9%). The majority of the College participants were white (61%), and first-year students (54.9%). There were no significant differences across playing position by playing level (χ2(n = 204, 2) = 4.03, p = 0.13). The HS subjects were distributed as follows: Big 41.8%, Athletic 32.0%, and Skilled 26.2%. The College subjects were distributed as follows: Big 28.0%, Athletic 40.2%, and Skilled 31.7%. The demographic data and independent t-tests comparing the HS and College subjects are presented in Table 1. There was a significant difference between the HS and College subjects for each dependent variable (p < 0.05), with the exception of BMI and mean arterial blood pressure.

Table 1

Table 1

Table 2 presents the means and SDs for the dependent variables across the playing levels and the playing position. Table 3 presents the results of the 2-way ANOVAs comparing playing levels and playing positions. There were significant differences between the HS and College subjects for all dependent variables. There were also significant differences across playing position for most of the dependent variables. There was a significant difference between HS and College football players for %FAT, χ2(n = 165, 2) = 7.78, p = 0.02. The HS players were more likely to be overweight or obese. A chi-square test of independence examining the %FAT categories by the football positions was significant, χ2(n = 164, 4) = 54.99, p < 0.001. Very few of the Skilled or Athletic players were obese based on the %FAT categories. Primarily, the offensive and defensive linemen were in the obese category.

Table 2

Table 2

Table 3

Table 3

The percent of players who had abnormal levels of the dependent variables are presented in Tables 4 and 5 (playing level and playing position, respectively). Significant differences were noted by playing level for diastolic blood pressure, glucose, and HDL cholesterol. Significant differences were observed by playing position for systolic blood pressure, HDL cholesterol, and waist circumference.

Table 4

Table 4

Table 5

Table 5

Using the standard clinical criteria for MetSyn, 6.8% (n = 14) of the total sample (n = 205) would be classified as having MetSyn. Players in the Big category (offensive and defensive linemen) accounted for 92.3% of the players meeting these criteria. A total of 7 and 7 of the subjects were HS and College players, respectively. There were not significantly more College players with MetSyn compared with the HS players, χ2(n = 193, 1) = 0.40, p = 0.53. The MetSyn criteria did differ across %FAT, χ2(n = 155, 2) = 22.69, p < 0.001. Players who were obese were more likely to also meet the clinical criteria for MetSyn.

Three path analytic models were tested to determine the relationship among BMI, %FAT, and risk factors that comprise MetSyn. The primary model assessed the impact of both BMI and %FAT on the MetSyn risk factors. The second and third models assessed the ability of %FAT and BMI to independently predict the MetSyn risk factors. Due to the saturated nature of the models examined, there are no fit statistics available for the models. Parameter estimates are presented in Figures 1–3. In the primary model (Figure 1), BMI and %FAT are strongly correlated (r = 0.60). In this model, both BMI and %FAT significantly predict mean arterial blood pressure while BMI significantly predicted triglycerides, HDL cholesterol, and waist circumference. In the second model (Figure 2), BMI significantly predicted the MetSyn risk factors of triglycerides, waist circumference, HDL cholesterol, and mean arterial blood pressure. In the third model (Figure 3), %Fat significantly predicted mean arterial blood pressure, HDL cholesterol, and waist circumference.

Figure 1

Figure 1

Figure 2

Figure 2

Figure 3

Figure 3

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Discussion

The primary findings of this investigation are as follows: (a) MetSyn is similarly prevalent in this sample of HS and College football athletes, (b) differences in the prevalence of MetSyn exist by playing position, and (c) BMI and %FAT are strong predictors of MetSyn risk factors. These finding suggest that despite high levels of physical activity, certain subsets of HS and College football players have multiple risk factors for metabolic and cardiovascular disease, thereby classifying them as having MetSyn. Because BMI and %FAT were strong predictors of MetSyn risk factors, these 2 assessments may serve as inexpensive screening tools for identifying individuals who may require additional evaluation and possible intervention for protecting the health of certain subsets of HS and College football players.

The findings of this investigation both support and expand the conclusions of previous research. Elevated levels of risk factors have been identified in both active professional (23,25), retired professional (19), and college (3,4,15,28) level football players. To our knowledge, this is the first article to demonstrate that HS football players also have multiple risk factors for MetSyn, placing them at increased risk of developing metabolic and cardiovascular disease. As a group, active professional football players seem to have similar overall prevalence rates for cardiovascular disease risk factors when compared with an age-matched sample of the general U.S. population (23). As might be expected, however, large body size, as measured by BMI, is associated with increased levels of cardiovascular disease risk factors (19,22,23). This trend is also observed at the College level, where several reports have demonstrated that offensive and defensive linemen (typically the largest individuals on a team) have elevated rates of MetSyn (3,4), as well as higher levels of metabolic and cardiovascular disease risk factors (15,28). In our sample, the HS subjects had a similar prevalence rate of MetSyn (5.7%) compared with the College subjects (8.5%). When compared with the general population, the prevalence of MetSyn in this group of adolescent athletes is similar to that reported in other findings (8) but is slightly lower than that reported by Flouris et al. (12) who found that 16% of a population of 17-year-old boys diagnosed with MetSyn. Given the increase in the obesity rate among adolescents (21), it is certainly possible that the MetSyn rate in the general adolescent population is higher than that observed among the HS football players in the current study. It is difficult to interpret these findings and speculate whether the group of HS and College subjects with MetSyn would in fact have the same risk factors if they had not participated in football. One does not know if the subjects participated in football because they were of a large body size or if participation in football required them to gain excess amounts of body mass in an effort to be successful as a football athlete.

The findings of the current, and previous research (3,4,28), are not surprising given the importance of increased body mass in promoting success in all playing levels of football. In particular, offensive and defensive linemen may be required and encouraged to gain body mass as they age. Given the strong relationship between increased body mass and disease risk factors (20), it is not surprising that professional and college football players with the largest body size display high levels of cardiovascular disease risk factors. The current data support that of previous research that demonstrates the high rate of both obesity and high number of risk factors in College lineman (19,22). We should not be surprised that high school football players are also gaining large amounts of body mass in an effort to improve performance and increase the potential for continued play at the college and professional level. Several recent studies have demonstrated an increase in body size (6,10,18) among adolescent football players compared with other sports and peer groups. This increase in body size may place these players at risk for overweight or obesity and potentially increase their risk for metabolic and cardiovascular disease as an adult.

The results from the path analytic models indicate that using both BMI and %FAT can be effective for predicting the MetSyn risk factors in adolescent and young adult football players (Figures 1–3). Haskins et al. (15) have also demonstrated that BMI and %FAT are strongly correlated with risk factors for MetSyn in College football lineman. Both these assessment tools (BMI and %FAT) are inexpensive and commonly available to sports medicine personal at the HS and College level.

Although athletes are often viewed as being healthy and free from disease, the data from the current study support previous research that certain subsets of athletic populations are at increased risk of disease and often have multiple risk factors (3,4,28). As with the general population, those individuals at increased risk are often those with increased body weight and/or body fat. The type of training and expectations for successful performance in football necessitate potentially unhealthy practices and behaviors of the athletes. Despite high levels of physical activity and certain aspects of physical fitness, we should not view all football players as models of health. The increased number of disease risk factors in offensive and defensive linemen necessitates that close attention be paid to the overall health of individuals at a young age for both current and prospective conditions. These findings point to the importance of preparing the athlete for the postcompetitive period of their career. Equally important will be the commitment and cooperation of medical and allied health professionals to promote effective ways to achieve healthier lifestyles and ensure that the at-risk athlete will engage in healthy behaviors.

There are several potential limitations in our study. The HS and College subjects were convenience samples. It is important to note, however, that the HS subjects were from 7 different high schools that represent all classifications of schools in the Ohio High School Athletic Association, and the recruited subjects from the university team represent participants from the entire Midwest region. An additional limitation could be the use of 2 different methods for measuring blood pressure in the current study. Minimization of some of the variance occurred by having all College subjects measured by the same research technician and having all subjects engage in identical pretesting protocols.

In conclusion, the prevalence rate of MetSyn in HS and College is similar to that reported for the general population of adolescents and young adults. Differences in the prevalence of MetSyn exist by playing position with nearly all cases of MetSyn being limited to offensive and defensive linemen. In this subject sample, both BMI and %FAT were strong predictors of MetSyn risk factors, and these assessments may serve as a screening tool for identifying those individuals who may require closer health monitoring.

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Practical Applications

Metabolic syndrome and the respective risk factors are strong predictors of cardiovascular disease. Strength and conditioning coaches, as well as other allied health care professionals associated with high school and college football teams, have an obligation to ensure the health and well-being of the athletes under their responsibility. In this sample of high school and college football players, the MetSyn risk factors were most prevalent in those individuals with the largest BMI and %FAT. We believe that it is the responsibility of strength and conditioning coaches to be aware of the individual MetSyn risk factors in those large body size individuals (i.e., offensive and defensive linemen) on a football team. Individuals with a high BMI or elevated levels of body fat should be screened for other MetSyn risk factors and appropriate interventions should be taken, under the guidance of allied health care professionals, if the health of the athlete is at risk.

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Acknowledgments

This research was supported by Miami University Undergraduate Summer Scholar Awards to Gary Steffes and Alex Megura. The authors report no conflicts of interest.

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References

1. American College of Sports Medicine. ACSM's Guidelines for Exercise Testing and Prescription. Philadelphia, PA: Lippincott, Williams & Wilkins, 2009.
2. Andersen PJ, Critchley JAJH, Chan JCN, Cockram CS, Lee ZSK, Thomas GN, Tomlinson B. Factor analysis of the metabolic syndrome: Obesity vs insulin resistance as the central abnormality. Int J Obes Relat Metab Disord 25: 1782–1788, 2001.
3. Borchers JR, Clem KL, Habash DL, Nagaraja HN, Stokley LM, Best TM. Metabolic syndrome and insulin resistance in Division 1 collegiate football players. Med Sci Sports Exerc 41: 2105–2110, 2009.
4. Buell JL, Calland D, Hanks F, Johnston B, Pester B, Sweeney R, Thorne R. Presence of metabolic syndrome in football lineman. J Athl Train 43: 608–616, 2008.
5. Camhi SM, Kuo J, Young DR. Identifying adolescent metabolic syndrome using body mass index and waist circumference. Prev Chronic Dis 5: 1–9, 2008.
6. Chaote N, Forster C, Almquist J, Olsen C, Poth M. The prevalence of overweight participants in high school extramural sports. J Adolesc Health 40: 283–285, 2007.
7. DuBose KD, Eisenmann JC, Donnelly JE. Aerobic fitness attenuates the metabolic syndrome score in normal-weight, at-risk-for-overweight, and overweight children. Pediatrics 120: e1262–e1268, 2007.
8. Duncan GE, Li SM, Zhou XH. Prevalence and trends of a metabolic syndrome phenotype among U.S. adolescents, 1999-2000. Diabetes Care 27: 2438–2443, 2004.
9. Eisenmann JC, Welk GJ, Wickel EE, Blair SN. Stability of variables associated with the metabolic syndrome from adolescence to adulthood: The aerobics center longitudinal study. Am J Hum Biol 16: 690–696, 2004.
10. Elkins WL, Cohen DA, Koralewicz LM, Taylor SN. After school activities, overweight, and obesity among inner city youth. J Adolesc 27: 181–189, 2004.
11. Ervin RB. Prevalence of metabolic syndrome among adults 20 years of age and over, by sex, age, race and ethnicity, and body mass index: United States, 2003–2006. Natl Health Stat Report 13: 1–8, 2009. Hyattsville, MD, National Center for Health Statistics.
12. Flouris AD, Bouziotas C, Christodoulos AD, Koutedakis Y. Longitudinal preventive-screening cutoffs for metabolic syndrome in adolescents. Int J Obes (Lond) 32: 1506–1512, 2008.
13. Franks PW, Ekelund U, Brage S, Wong M, Wareham N. Does the association of habitual physical activity with the metabolic syndrome differ by level of cardiorespiratory fitness? Diabetes Care 27: 1187–1193, 2004.
14. Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, Gordon DJ, Krauss RM, Savage PJ, Smith SC, Spertus JA, Costa F. Diagnosis and management of the metabolic syndrome: An American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement: Executive summary. Circulation 112: e285–e290, 2005.
15. Haskins S, Bernhardt DT, Koscik RL. Screening for insulin resistance and cardiovascular risk in collegiate football linemen. Clin J Sport Med 21: 233–236, 2011.
16. Johnson JL, Slentz CA, Houmard JA, Samsa GP, Duscha BD, Aiken LB, McCartney JS, Tanner CJ, Kraus WE. Exercise training amount and intensity effects on metabolic syndrome (from Studies of a Targeted Risk Reduction Intervention through Defined Exercise). Am J Cardiol 100: 1759–1766, 2007.
17. Laurson KR, Eisenmann JC. Prevalence of overweight among high school football linemen. JAMA 297: 363–364, 2007.
18. Malina RM, Morano PJ, Barron M, Miller SJ, Cumming SP, Kontos AP, Little BB. Overweight and obesity among youth participants in American football. J Pediatr 151: 378–382, 2007.
19. Miller MA, Croft LB, Belanger AR, Romero-Corral A, Somers VK, Roberts AJ, Goldman ME. Prevalence of metabolic syndrome in retired National Football League players. Am J Cardiol 101: 1281–1284, 2008.
20. Navas-Nacher EL, Colangelo L, Beam C, Greenland P. Risk factors for coronary heart disease in men 18 to 39 years of age. Ann Intern Med 134: 433–439, 2001.
21. Ogden CL, Carroll MD, Curtin LR, Lamb MM, Flegal KM. Prevalence of high body mass index in US children and adolescents, 2007-2008. JAMA 303: 242–249, 2010.
22. Selden MA, Helzberg JH, Waeckerle JF, Browne JE, Brewer JH, Monaco ME, Tang F, O'Keefe JH. Cardiometabolic abnormalities in current National Football League players. Am J Cardiol 103: 969–971, 2009.
23. Tucker AM, Vogel RA, Lincoln AE, Dunn RE, Ahrensfield DC, Allen TW, Castle LW, Heyer RA, Pellman EJ, Strollo PJ, Wilson PWF, Yates AP. Prevalence of cardiovascular disease risk factors among National Football League players. JAMA 301: 2111–2119, 2009.
24. Vissers D, Vanroy C, DeMeulenaere A, Van de Sompel A, Truijen S, Van Gaal L. Metabolic syndrome in youth: A cross-sectional school-based survey. Acta Paediatr 96: 1809–1813, 2007.
25. Wallis GA, Yeo SE, Blannin AK, Jeukendrup AE. Dose-response effects of ingested carbohydrate on exercise metabolism in women. Med Sci Sports Exerc 39: 131–138, 2007.
26. Wang Y, Beydoun MA. The obesity epidemic in the United States—Gender, age, socioeconomic, racial/ethnic, and geographic characteristics: A systematic review and meta-regression analysis. Epidermiol Rev 29: 6–28, 2007.
27. Wijndaele K, Beunen G, Duvigneaud N, Matton L, Duquet W, Thomis M, Lefevre J, Philippaerts R. A continuous metabolic syndrome risk score: Utility for epidemiological analyses. Diabetes Care 29: 2329, 2006.
28. Wilkerson GB, Bullard JT, Bartal DW. Identification of cardiometabolic risk among collegiate football players. J Athl Train 45: 67–74, 2010.
Keywords:

cardiovascular disease; health; risk factors; athletes

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