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Discipline-specific insulin sensitivity in athletes
Nutrition 25 (2009) 1137–1142
Applied nutritional investigation
www.nutritionjrnl.com
Discipline-specific insulin sensitivity in athletes Yi-Liang Chen, Ph.D.a, Chih-Yang Huang, Ph.D.b, Shin-Da Lee, Ph.D.c, Shih-Wei Chou, M.D., Ph.D.d, Po-Shiuan Hsieh, M.D., Ph.D.e, City C. Hsieh, Ph.D.f, Yueh-Guey Huang, Ph.D.a, and Chia-Hua Kuo, Ph.D.a,* a Laboratory of Exercise Biochemistry, Taipei Physical Education College, Taipei, Taiwan Institute of Medical Science, China Medical University and Department of Healthcare Administration, Asia University, Taichung, Taiwan c Graduate Institute of Chinese Medicine and Physical Therapy, China Medical University and Department of Health and Nutrition Biotechnology, Asia University, Taichung, Taiwan d Department of Physical Medicine and Rehabilitation, Chung Gung Memorial Hospital, Graduate Institute of Rehabilitation Science, Chung Gung University, Taoyuan, Taiwan e Department of Physiology and Biophysics, National Defense Medical Center, Taipei, Taiwan f Department of Physical Education, National Hsinchu University of Education, Hsinchu, Taiwan b
Manuscript received September 24, 2008; accepted March 15, 2009
Abstract
Objective: Weight status and abnormal liver function are the two factors that influence whole-body insulin sensitivity. The main goal of the study was to compare insulin sensitivity in athletes (n ¼ 757) and physically active controls (n ¼ 670) in relation to the two factors. Methods: Homeostatic metabolic assessment for insulin resistance (HOMA-IR), weight status, and abnormal liver function (alanine aminotransferase and aspartate aminotransferase) were determined from 33 sports disciplines under morning fasted condition. This study was initiated in autumn 2006 and repeated in autumn 2007 (n ¼ 1508) to ensure consistency of all observations. Results: In general, HOMA-IR and blood pressure levels in athletes were significantly greater than those in physically active controls but varied widely with sport disciplines. Rowing and short-distance track athletes had significantly lower HOMA-IR values and archery and field-throwing athletes had significantly higher values than the control group. Intriguingly, athletes from 22 sports disciplines displayed significantly greater body mass index values above control values. Multiple regression analysis showed that, for non-athlete controls, body mass index was the only factor that contributed to the variations in HOMA-IR. For athletes, body mass index and alanine aminotransferase independently contributed to the variation of HOMA-IR. Conclusion: This is the first report documenting HOMA-IR values in athletes from a broad range of sport disciplines. Weight status and abnormal liver function levels appear to be the major contributors predicting insulin sensitivity for the physically active population. Ó 2009 Elsevier Inc. All rights reserved.
Keywords:
Aspartate aminotransaminase; Alanine aminotransferase; Glutamic oxaloacetic transaminase; Glutamic pyruvic transaminase; Obesity; Overweight; Insulin sensitivity; Blood pressure
Introduction Carbohydrate is the major fuel for most types of athletic competition. High insulin sensitivity may help to optimize carbohydrate storage for athletic competition. Exercise This study is partly sponsored by grant NSC 96-2413-H-154-003-MY3 from the National Science Council, Taipei, Taiwan. *Corresponding author. Tel.: þ886-2-287-18288, ext. 5101; fax: þ8862-287-53383. E-mail address: [email protected] (C.-H. Kuo). 0899-9007/09/$ – see front matter Ó 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.nut.2009.03.003
training is generally known to enhance whole-body insulin sensitivity for glucose uptake [1], mainly due to repeatedly depleting fuel storage, which enhances insulin-stimulated glucose transport (by increasing GLUT4 and capillary density expression) in skeletal muscle [2,3]. The lifestyle of an elite athlete is characterized by substantially greater magnitudes of energy depletion and tissue damage than in recreational athletes. Little is known about whether this physical condition reflects on their insulin sensitivity, divergent from normal physically active people. A recent study by Lippi et al. [4] examined 47 male professional road cyclists, 72 male elite road
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cyclists, and 58 male sedentary controls and found a consistent trend toward higher glycated hemoglobin values for cyclists, suggesting higher glycemia during the previous 3 mo. This result points to a possibility that insulin sensitivity for athletes and regularly trained non-athletes can be different. Two key components that can affect insulin sensitivity and glycemic control are weight status and liver function [5–9]. Both factors could vary with sport disciplines. Banfi et al. [10] evaluated athletes from five sport disciplines and reported high body mass index (BMI) values in rugby players (28.8 kg/m2), skiers (25.8 kg/m2), and sailors (26.9 kg/m2). Whether greater weight status in athletes reflected on insulin sensitivity and associated metabolic measurements, such as blood pressure, was not reported. Liver health can potentially affect insulin sensitivity because the rate of hepatic glucose output into the circulation is regulated by insulin [8]. Increased circulating liver enzyme levels usually occur after high-intensity exercise but not moderate-intensity exercise [11]. In general, elevated liverspecific enzyme levels (alanine aminotransferase [ALT] and aspartate aminotransferase [AST]) in the circulation mirror the magnitude of abnormal liver function [12]. Little is known about whether liver-specific enzyme levels in athletes are linked to insulin sensitivity. The purpose of the study was to investigate insulin sensitivity using homeostatic metabolic assessment for insulin resistance (HOMA-IR) and the weight status and levels of abnormal liver function for a large number of elite athletes at the national level. Athletes from 33 sport disciplines were evaluated in parallel with normal physically active people. Materials and methods This institution-based study was performed to compare the metabolic characteristics between elite athletes and physically active controls. Data collection started from September 2006. A total of 1427 subjects, aged 19–25 y, were divided into two groups: athletes (n ¼ 757, regularly participating in athletic competition, from 33 sports disciplines) and phys-
ically active controls (n ¼ 670). To ensure consistency of the result, the same measurements were repeated in September 2007 for 1507 subjects (75% of subjects were identical to those in 2006). The control group did not consist of athletes but of subjects who participated in sport or physical conditioning courses more often than 150 min/wk. These courses primarily consist of demonstration and instructional techniques on various types of sports, but not of training activity toward athletic competition. Local institutional approvals were obtained. Plasma samples for measurements of liver enzymes (ALT and AST), glucose, and insulin were obtained after an overnight fast. Insulin resistance was estimated according to the HOMA-IR as the product of fasting plasma glucose (millimoles per liter) and insulin (microunits per milliliter) divided by the constant 22.5 [13,14]. Using the HOMA-IR to assess the degree of insulin resistance is based on a glucose–insulin feedback system in the homeostatic state (overnight fasting) [14,15]. Glucose and insulin were freshly measured with the method previously described no later than 4 h after blood sample collection [16]. Statistical analysis For numerical variables, the assumption of normality was tested by the Kolmogorov-Smirnov nonparametric test. After application of the Levene test to evaluate homogeneity of variances between the measurements, an independent twosample t test was used for mean comparison between athletes and controls. Stepwise regression analysis was used to assess the relations between HOMA-IR and the rest of the variables (BMI and liver function test). P < 0.05 was considered statistically significant for all tests, and all values are expressed as means 6 standard errors. Results The metabolic characteristics for athletes and physically active controls in 2006 and 2007 are listed in Table 1. The
Table 1 Metabolic characteristics* Measurements
Age BMI (kg/m2) Glucose (mg/dL) Insulin (mU/mL) HOMA-IR ALT (IU/L) AST (IU/L) SBP (mmHg) DBP (mmHg)
2006
2007
Control (n ¼ 670)
Athletes (n ¼ 757)
Control (n ¼ 748)
Athletes (n ¼ 760)
21.4 6 0.1 21.1 6 0.1 82.7 6 0.21 6.8 6 0.2 1.4 6 0.03 18.3 6 0.23 14.4 6 0.42 119 6 0.47 71 6 0.31
21.2 6 0.1 23.0 6 0.1x 83.19 6 0.22 7.8 6 0.2x 1.6 6 0.05x 19.8 6 0.28x 16.9 6 0.50x 124 6 0.52x 73 6 0.30x
21.0 6 0.06 21.2 6 0.11 87.9 6 0.44 7.8 6 0.30 1.7 6 0.08 17.1 6 0.53 21.9 6 0.67 122.8 6 0.56 73.3 6 0.31
21.1 6 0.05 23.0 6 0.12x 89.3 6 0.31y 9.5 6 0.34x 2.2 6 0.09x 20.2 6 0.75x 23.4 6 0.43x 127.5 6 0.55x 74.1 6 0.29x
ALT, alanine aminotransferase; AST, aspartate aminotransferase; BMI, body mass index; DBP, diastolic blood pressure; HOMA-IR, homeostatic metabolic assessment for insulin resistance; SBP, systolice blood pressure * To ensure consistency of the result, measurements were initiated in 2006 and repeated in 2007. Probabilities of type I error <5%y, <1%z, and < 0.1%x (for the mean difference against the control group).
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Table 2 Regression analysis (stepwise) predicting HOMA-IR by weight status and marker for abnormal liver function* Variable
BMI ALT
Athletes (n ¼ 757)
Controls (n ¼ 670)
b coefficient
SE
P
b coefficient
SE
P
0.356 0.125
0.014 0.004
<0.001 <0.001
0.306 0.071
0.012 0.003
<0.001 NS
ALT, alanine aminotransferase; BMI, body mass index; HOMA-IR, homeostatic metabolic assessment for insulin resistance * For athletes, BMI and ALT were selected as variables significantly contributing to HOMA-IR; for controls, only BMI remained as the only variable contributing to HOMA-IR.
significant between-group differences in BMI, HOMA-IR, ALT, systolic blood pressure (SBP), and diastolic blood pressure (DBP) were consistent for both years. Fasting plasma glucose level was not different between two groups in 2006 but slightly different in 2007. Insulin, HOMA-IR, BMI, ALT, AST, SBP, and DBP values of the athlete group were significantly greater than those of the control group (P < 0.05). Table 2 summarizes the results of stepwise regression analysis for variables predicting HOMA-IR value. For the athlete group, BMI and ALT were included as contributors for the variation of HOMA-IR values. For non-athlete controls, BMI was the only contributor for the variation of HOMA-IR values. Table 3 lists the mean values of insulin resistance-associated variables, including HOMA-IR, SBP, and DBP, across 33 sport disciplines. It is generally known that BP is strongly correlated with insulin sensitivity [17]; thus BPs were also determined in the study. Mean HOMA-IR values from four disciplines were significantly different from the control group. HOMA-IR values from rowing and short-distance track athletes were significantly lower than those from the control group (P < 0.05). HOMA-IR values from archery and field-throwing athletes were significantly greater than those from the control group (P < 0.05). Athletes from both disciplines also had significantly greater SBP above control values. There were 15 sport disciplines that showed significantly greater SBP than the control group. Eight sport disciplines displayed significantly greater DBP than the control group. Table 4 lists the mean values for the factors (BMI and liver function test) that predict HOMA-IR from athletes across 33 sport disciplines. There were 22 among 33 sports disciplines that showed significantly greater BMI values compared with the physically active controls. Athletes from kayaking, hockey, rugby, track, and swimming had significantly greater ALT values than the control group (P < 0.05). Athletes from baseball, hockey, karate, rowing, rugby, soccer, and track had significantly greater AST values than the control group (P < 0.05). Discussion Athletes are a special group of highly physically active people selected by outstanding fitness against physical chal-
lenge. However, abnormal liver function levels could occur during strenuous exercise training and competition [11,12]. This suboptimal condition might influence whole-body insulin sensitivity and glucose metabolism [5,8]. The present study found that markers for abnormal liver function independently contributed to the variation of HOMA-IR value in athletes. Athletes from archery and field-throwing disciplines showed significantly greater HOMA-IR values than Table 3 Insulin resistance variables from 33 sports disciplines Sports disciplines (N)
HOMA-IR
SBP
DBP
Control (670) Archery (18) Badminton (22) Baseball (27) Basketball (39) Bowling (9) Boxing (25) Cycling, road (22) Fencing (15) Field, jumping (19) Field, throwing (17) Golf (20) Gymnastics (10) Handball (41) Hockey (23) Ice skating (4) Judo (26) Karate (20) Kayaking (25) Kendo (22) Martial art (16) Ping pong (30) Rowing (20) Rugby (37) Soccer (23) Softball (24) Swimming (31) Taekwondo (36) Tennis (30) Track, distance (15) Track, short distance (22) Volleyball (27) Water polo (26) Weight lifting (16)
1.40 6 0.03 2.59 6 0.51* 1.33 6 0.12 1.19 6 0.1 1.55 6 0.15 1.73 6 0.28 1.65 6 0.18 1.40 6 0.17 1.92 6 0.46 1.19 6 0.15 2.91 6 0.73* 1.82 6 0.27* 1.76 6 0.34 1.52 6 0.11 1.43 6 0.19 0.97 6 0.35 1.63 6 0.27 1.28 6 0.14 2.17 6 0.56 1.63 6 0.16 1.32 6 0.19 1.52 6 0.14 0.90 6 0.10** 2.10 6 0.40 1.26 6 0.10 2.03 6 0.34 1.48 6 0.13 1.58 6 0.14 1.39 6 0.11 1.42 6 0.18 1.10 6 0.08** 1.64 6 0.25 1.49 6 0.23 1.61 6 0.19
119.8 6 0.52 127.4 6 4.07* 126.2 6 2.89* 130.2 6 1.96*** 127.2 6 2.4*** 127.7 6 2.09** 130.4 6 2.31*** 124.0 6 2.69 125.4 6 3.15 124.2 6 1.74* 131.7 6 2.28*** 123.7 6 2.47 126.8 6 4.51 122.2 6 2.16 125.3 6 1.81** 105.5 6 5.20* 124.3 6 2.83 125.8 6 2.83 129.4 6 2.87*** 127.5 6 3.05** 117.1 6 2.68 120.0 6 2.12 124.1 6 3.23 129.9 6 1.66*** 127.6 6 2.18** 115.2 6 0.20 131.6 6 1.61*** 120.5 6 2.41 124.6 6 2.40 123.7 6 3.57 120.3 6 3.05 118.4 6 3.16 128.0 6 2.38** 125.0 6 3.67
71.4 6 0.31 76.1 6 3.09* 72.5 6 1.51 71.8 6 1.48 73.0 6 1.3 76.8 6 2.65* 75.8 6 1.56** 73.5 6 1.77 70.0 6 1.83 73.0 6 1.24 74.6 6 2.05 72.4 6 1.39 75.7 6 1.68 72.2 6 1.32 72.9 6 1.77 63.0 6 1.48* 73.5 6 2.04 73.0 6 1.89 75.3 6 1.78* 74.1 6 1.64 67.6 6 1.89 70.8 6 1.75 71.3 6 1.90 75.0 6 1.44** 75.0 6 1.45* 67.8 6 1.40* 75.0 6 1.36* 69.7 6 1.14 70.4 6 1.12 76.5 6 2.13* 72.7 6 1.85 72.7 6 1.97 72.8 6 1.82 74.5 6 1.91
DBP, diastolic blood pressure; HOMA-IR, homeostatic metabolic assessment for insulin resistance; SBP, systolice blood pressure Probabilities of type I error <5%*, <1%y, and <0.1%z (for the mean difference against the control group).
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1140 Table 4 Predictors for HOMA-IR from 33 sports disciplines Sports disciplines (N) BMI Control (670) Archery (18) Badminton (22) Baseball (27) Basketball (39) Bowling (9) Boxing (25) Cycling, road (22) Fencing (15) Field, jumping (19) Field, throwing (17) Golf (20) Gymnastics (10) Handball (41) Hockey (23) Ice skating (4) Judo (26) Karate (20) Kayaking (25) Kendo (22) Martial art (16) Ping pong (30) Rowing (20) Rugby (37) Soccer (23) Softball (24) Swimming (31) Taekwondo (36) Tennis (30) Track, distance (15) Track, short distance (22) Volleyball (27) Water polo (26) Weight lifting (16)
21.1 6 0.10 25.2 6 1.52* 22.4 6 0.52* 24.3 6 0.51*** 22.6 6 0.29*** 24.7 6 0.71*** 22.9 6 0.82* 22.9 6 0.44 23.0 6 0.42*** 20.7 6 0.42 29.2 6 1.44*** 21.8 6 0.64 22.0 6 0.78 22.9 6 0.49*** 23.6 6 0.54*** 21.5 6 1.19 25.5 6 0.93*** 21.3 6 0.43 23.6 6 0.51*** 22.5 6 0.67** 22.2 6 0.45 21.4 6 0.45 21.9 6 0.43 26.4 6 0.61*** 22.3 6 0.36* 22.4 6 0.53* 22.7 6 0.45*** 22.4 6 0.57* 22.3 6 0.51* 20.6 6 0.50 21.3 6 0.44
ALT
AST
14.4 6 0.42 26.2 6 7.15 16.0 6 1.51 18.1 6 2.74 13.2 6 0.91 14.6 6 2.32 15.6 6 2.36 19.7 6 5.17 22.7 6 6.57 14.8 6 2.38 25.0 6 5.32 16.2 6 2.60 15.3 6 4.79 13.2 6 1.06 25.7 6 4.40* 8.7 6 0.75 17.5 6 3.64 18.6 6 2.13 19.6 6 2.55* 15.7 6 2.11 16.1 6 4.03 13.7 6 1.42 13.9 6 1.65 17.8 6 1.73* 16.0 6 1.66 10.5 6 0.66*** 19.5 6 2.53* 13.6 6 1.80 16.9 6 2.19 20.3 6 3.92* 13.8 6 1.90
18.3 6 0.23 21.1 6 2.64 19.0 6 0.79 21.6 6 1.31** 19.3 6 1.05 20.4 6 0.96 18.4 6 1.02 20.1 6 1.44 23.7 6 4.57 19.3 6 1.75 20.5 6 1.88 17.6 6 1.37 15.7 6 1.68 17.2 6 1.74 26.0 6 1.92*** 14.7 6 1.03 19.9 6 1.40 22.2 6 1.74* 20.3 6 0.95 17.8 6 1.32 18.7 6 1.64 16.8 6 0.83 22.9 6 1.20*** 20.1 6 0.77* 21.4 6 1.47* 17.9 6 0.85 21.8 6 2.11 17.5 6 0.80 18.7 6 0.82 20.9 6 2.54** 18.9 6 1.35
22.2 6 0.55* 12.9 6 0.83 23.9 6 0.73*** 18.7 6 3.71 26.4 6 0.70*** 19.0 6 4.18
16.8 6 0.80 20.1 6 1.59 21.1 6 2.37
ALT, alanine aminotransferase; AST, aspartate aminotransferase; BMI, body mass index; HOMA-IR, homeostatic metabolic assessment for insulin resistance Probabilities of type I error <5%*, <1%y, and <0.1%z (for the mean difference against the control group).
controls, but the markers for abnormal liver function were not significantly different from controls. For both disciplines, overweight (BMI > 25 kg/m2) appears to be the main contributor to low insulin sensitivity. To the best of our knowledge, this is the first population report to document HOMA-IR values for athletes across multiple sports disciplines. The HOMA-IR value in athletes was predicted by abnormal liver function and BMI. The information of this study could be important because carbohydrate is the major fuel for a great variety of sport competitions [18]. High insulin sensitivity could ensure efficient carbohydrate storage for athletes [1,19]. The most striking finding of the study is that BMI values from 22 of 33 sports disciplines were significantly greater than in physically active control subjects, which explains, to some extent, the greater overall HOMA-IR in athletes above controls. The finding of the present study presents a novel
message to young athletes that insulin sensitivity remains associated with BMI for this physically active group. Although BMI may not be the best obesity indicator for athletes because the variation in BMI could be due to differences in muscle mass [20,21], greater BP and HOMA-IR values above control suggested a trend toward greater adiposity, even though the athletes in this study were considered healthy [22]. Most clinical studies have repeatedly shown that BP is highly correlated with insulin sensitivity, secondary to weight status [22–24]. Consistent with previous data, athletes with a BMI greater than 25 kg/m2 in this study, such as those involved in archery, field throwing, judo, rugby, and weightlifting, displayed a relatively higher SBP than the control group. In fact, the relation between BP and weight in elite athletes was reported in 1949 [25]. Data have shown that SBP is proportional to body weight, ranging from 90 to 160 mmHg for athletes participating in the London Olympic Games. This is consistent with the present data that SBP and DBP were increased with weight status. However, it should be noted that there were quite a few extreme values in the athlete group. Whether the extreme BP value in some athletes has pathophysiologic implications requires further investigation. In contrast to the normal physically active non-athletes, athletes are subjected to greater magnitudes of daily energy depletion–repletion cycle and variations in yearly training load in compliance with a competition schedule. It has been reported that reducing training volume during off-season or completely stop a training routine after retirement can result in increased fatness and decreased insulin sensitivity [20]. Because the rate of insulin-stimulated glucose utilization [26] and body weight [27] are regulated by training intensity and duration, modulation in training volume according to competition season would undoubtedly have ramifications on the metabolic homeostasis in athletes. It is thus possible that body fat is easy to accumulate during detraining periods or off-season [28], but their weight status did not completely returns to the previous level by competition season. Genetic differences between elite athletes and physically active controls were not evaluated in this study, but there is little doubt that elite athletes are a genetically selected group for outstanding muscular fitness [29,30]. In this study, some athletes with higher HOMA-IR values were in power-related disciplines, such as field throwing. The fact that elite power athletes tend to be more insulin resistant than elite endurance athletes has been previously documented [31]. A Finnish study has found a greater relative risk in diabetes and several associated metabolic complications for former elite power athletes versus endurance athletes [32,33]. Power athletes are normally selected by greater number of type IIb muscle fibers. This type of muscle fiber is substantially more insulin resistant compared with type IIa and I fibers [34]. Because skeletal muscle is the largest insulin-sensitive tissue for postprandial glucose disposal, muscle insulin sensitivity could influence whole-body insulin sensitivity [35]. It has been shown that muscle fiber composition can be modulated by different types of exercise training programs [36]. This could
Y.-L. Chen et al. / Nutrition 25 (2009) 1137–1142
be another possibility contributing the lower HOMA-IR value in field-throwing athletes. However, our data show that HOMA-IR for elite short-distance sprinters was significantly lower than that for the control group. Differences in insulin sensitivity between non-athletes and athletes from different sports disciplines are within a physiologic range. In general, a small difference in insulin sensitivity is not a clinical concern for young adults. However, sensitivity to insulin deteriorates with advancing aging. A longitudinal study has reported that middle-aged individuals with less insulin sensitivity, evaluated by steady-state plasma glucose and insulin levels, had a greater incidence of stroke, coronary heart disease, diabetes, hypertension, and cancer than their counterparts with high insulin sensitivity in future decades [23]. It is currently unknown whether the small difference in insulin sensitivity could be amplified with age. Long-term follow-up for the specific active population is required to confirm this possibility. The main limitation of the study was that the amounts and types of food and beverage ingested by athletes were not evaluated, which might contribute to the greater HOMA-IR and BPs for select disciplines of athletes. One possibility that needs to be clarified is the consumption amount of fructose-containing sports drinks. Sports drinks are widely used by athletes during regular training and competition, and most sports drinks contain fructose. Recently, fructose intake has been increasingly recognized as causative in the development of prediabetes and metabolic syndrome [37,38]. Fructose has an approximately eight-fold higher reactivity than glucose in the contribution of protein glycation [39], which is known to causally link with insulin resistance and hypertension [40]. Another nutritional factor that remains to be investigated is whether red meat is overconsumed by athletes due to a high demand for muscle protein resynthesis during training. Higher consumption of total red meat, especially processed meats, could increase the risk of insulin resistance and diabetes [41]. Furthermore, data related to total cholesterol, low-density lipoprotein and high-density lipoprotein cholesterol, triacylglycerols, and free fatty acids should be studied in the future because some of them are involved with states of insulin resistance and hypertension. Conclusions This is the first population study determining HOMA-IR values across multiple sport disciplines. The present study demonstrated that insulin sensitivity in athletes is independently predicted by BMI and abnormal liver function level. According to our repeated observations in 2006 and 2007, the elite athletes were slightly heavier with greater HOMAIR compared with the physically active controls. Interestingly, 22 of 33 sports disciplines showed significantly greater BMI values than those in physically active controls. BPs, a metabolic measurement closely associated with insulin resistance, were also greater in athletes from several disciplines compared with controls. Long-term investigation is required
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Applied nutritional investigation
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Discipline-specific insulin sensitivity in athletes Yi-Liang Chen, Ph.D.a, Chih-Yang Huang, Ph.D.b, Shin-Da Lee, Ph.D.c, Shih-Wei Chou, M.D., Ph.D.d, Po-Shiuan Hsieh, M.D., Ph.D.e, City C. Hsieh, Ph.D.f, Yueh-Guey Huang, Ph.D.a, and Chia-Hua Kuo, Ph.D.a,* a Laboratory of Exercise Biochemistry, Taipei Physical Education College, Taipei, Taiwan Institute of Medical Science, China Medical University and Department of Healthcare Administration, Asia University, Taichung, Taiwan c Graduate Institute of Chinese Medicine and Physical Therapy, China Medical University and Department of Health and Nutrition Biotechnology, Asia University, Taichung, Taiwan d Department of Physical Medicine and Rehabilitation, Chung Gung Memorial Hospital, Graduate Institute of Rehabilitation Science, Chung Gung University, Taoyuan, Taiwan e Department of Physiology and Biophysics, National Defense Medical Center, Taipei, Taiwan f Department of Physical Education, National Hsinchu University of Education, Hsinchu, Taiwan b
Manuscript received September 24, 2008; accepted March 15, 2009
Abstract
Objective: Weight status and abnormal liver function are the two factors that influence whole-body insulin sensitivity. The main goal of the study was to compare insulin sensitivity in athletes (n ¼ 757) and physically active controls (n ¼ 670) in relation to the two factors. Methods: Homeostatic metabolic assessment for insulin resistance (HOMA-IR), weight status, and abnormal liver function (alanine aminotransferase and aspartate aminotransferase) were determined from 33 sports disciplines under morning fasted condition. This study was initiated in autumn 2006 and repeated in autumn 2007 (n ¼ 1508) to ensure consistency of all observations. Results: In general, HOMA-IR and blood pressure levels in athletes were significantly greater than those in physically active controls but varied widely with sport disciplines. Rowing and short-distance track athletes had significantly lower HOMA-IR values and archery and field-throwing athletes had significantly higher values than the control group. Intriguingly, athletes from 22 sports disciplines displayed significantly greater body mass index values above control values. Multiple regression analysis showed that, for non-athlete controls, body mass index was the only factor that contributed to the variations in HOMA-IR. For athletes, body mass index and alanine aminotransferase independently contributed to the variation of HOMA-IR. Conclusion: This is the first report documenting HOMA-IR values in athletes from a broad range of sport disciplines. Weight status and abnormal liver function levels appear to be the major contributors predicting insulin sensitivity for the physically active population. Ó 2009 Elsevier Inc. All rights reserved.
Keywords:
Aspartate aminotransaminase; Alanine aminotransferase; Glutamic oxaloacetic transaminase; Glutamic pyruvic transaminase; Obesity; Overweight; Insulin sensitivity; Blood pressure
Introduction Carbohydrate is the major fuel for most types of athletic competition. High insulin sensitivity may help to optimize carbohydrate storage for athletic competition. Exercise This study is partly sponsored by grant NSC 96-2413-H-154-003-MY3 from the National Science Council, Taipei, Taiwan. *Corresponding author. Tel.: þ886-2-287-18288, ext. 5101; fax: þ8862-287-53383. E-mail address: [email protected] (C.-H. Kuo). 0899-9007/09/$ – see front matter Ó 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.nut.2009.03.003
training is generally known to enhance whole-body insulin sensitivity for glucose uptake [1], mainly due to repeatedly depleting fuel storage, which enhances insulin-stimulated glucose transport (by increasing GLUT4 and capillary density expression) in skeletal muscle [2,3]. The lifestyle of an elite athlete is characterized by substantially greater magnitudes of energy depletion and tissue damage than in recreational athletes. Little is known about whether this physical condition reflects on their insulin sensitivity, divergent from normal physically active people. A recent study by Lippi et al. [4] examined 47 male professional road cyclists, 72 male elite road
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cyclists, and 58 male sedentary controls and found a consistent trend toward higher glycated hemoglobin values for cyclists, suggesting higher glycemia during the previous 3 mo. This result points to a possibility that insulin sensitivity for athletes and regularly trained non-athletes can be different. Two key components that can affect insulin sensitivity and glycemic control are weight status and liver function [5–9]. Both factors could vary with sport disciplines. Banfi et al. [10] evaluated athletes from five sport disciplines and reported high body mass index (BMI) values in rugby players (28.8 kg/m2), skiers (25.8 kg/m2), and sailors (26.9 kg/m2). Whether greater weight status in athletes reflected on insulin sensitivity and associated metabolic measurements, such as blood pressure, was not reported. Liver health can potentially affect insulin sensitivity because the rate of hepatic glucose output into the circulation is regulated by insulin [8]. Increased circulating liver enzyme levels usually occur after high-intensity exercise but not moderate-intensity exercise [11]. In general, elevated liverspecific enzyme levels (alanine aminotransferase [ALT] and aspartate aminotransferase [AST]) in the circulation mirror the magnitude of abnormal liver function [12]. Little is known about whether liver-specific enzyme levels in athletes are linked to insulin sensitivity. The purpose of the study was to investigate insulin sensitivity using homeostatic metabolic assessment for insulin resistance (HOMA-IR) and the weight status and levels of abnormal liver function for a large number of elite athletes at the national level. Athletes from 33 sport disciplines were evaluated in parallel with normal physically active people. Materials and methods This institution-based study was performed to compare the metabolic characteristics between elite athletes and physically active controls. Data collection started from September 2006. A total of 1427 subjects, aged 19–25 y, were divided into two groups: athletes (n ¼ 757, regularly participating in athletic competition, from 33 sports disciplines) and phys-
ically active controls (n ¼ 670). To ensure consistency of the result, the same measurements were repeated in September 2007 for 1507 subjects (75% of subjects were identical to those in 2006). The control group did not consist of athletes but of subjects who participated in sport or physical conditioning courses more often than 150 min/wk. These courses primarily consist of demonstration and instructional techniques on various types of sports, but not of training activity toward athletic competition. Local institutional approvals were obtained. Plasma samples for measurements of liver enzymes (ALT and AST), glucose, and insulin were obtained after an overnight fast. Insulin resistance was estimated according to the HOMA-IR as the product of fasting plasma glucose (millimoles per liter) and insulin (microunits per milliliter) divided by the constant 22.5 [13,14]. Using the HOMA-IR to assess the degree of insulin resistance is based on a glucose–insulin feedback system in the homeostatic state (overnight fasting) [14,15]. Glucose and insulin were freshly measured with the method previously described no later than 4 h after blood sample collection [16]. Statistical analysis For numerical variables, the assumption of normality was tested by the Kolmogorov-Smirnov nonparametric test. After application of the Levene test to evaluate homogeneity of variances between the measurements, an independent twosample t test was used for mean comparison between athletes and controls. Stepwise regression analysis was used to assess the relations between HOMA-IR and the rest of the variables (BMI and liver function test). P < 0.05 was considered statistically significant for all tests, and all values are expressed as means 6 standard errors. Results The metabolic characteristics for athletes and physically active controls in 2006 and 2007 are listed in Table 1. The
Table 1 Metabolic characteristics* Measurements
Age BMI (kg/m2) Glucose (mg/dL) Insulin (mU/mL) HOMA-IR ALT (IU/L) AST (IU/L) SBP (mmHg) DBP (mmHg)
2006
2007
Control (n ¼ 670)
Athletes (n ¼ 757)
Control (n ¼ 748)
Athletes (n ¼ 760)
21.4 6 0.1 21.1 6 0.1 82.7 6 0.21 6.8 6 0.2 1.4 6 0.03 18.3 6 0.23 14.4 6 0.42 119 6 0.47 71 6 0.31
21.2 6 0.1 23.0 6 0.1x 83.19 6 0.22 7.8 6 0.2x 1.6 6 0.05x 19.8 6 0.28x 16.9 6 0.50x 124 6 0.52x 73 6 0.30x
21.0 6 0.06 21.2 6 0.11 87.9 6 0.44 7.8 6 0.30 1.7 6 0.08 17.1 6 0.53 21.9 6 0.67 122.8 6 0.56 73.3 6 0.31
21.1 6 0.05 23.0 6 0.12x 89.3 6 0.31y 9.5 6 0.34x 2.2 6 0.09x 20.2 6 0.75x 23.4 6 0.43x 127.5 6 0.55x 74.1 6 0.29x
ALT, alanine aminotransferase; AST, aspartate aminotransferase; BMI, body mass index; DBP, diastolic blood pressure; HOMA-IR, homeostatic metabolic assessment for insulin resistance; SBP, systolice blood pressure * To ensure consistency of the result, measurements were initiated in 2006 and repeated in 2007. Probabilities of type I error <5%y, <1%z, and < 0.1%x (for the mean difference against the control group).
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Table 2 Regression analysis (stepwise) predicting HOMA-IR by weight status and marker for abnormal liver function* Variable
BMI ALT
Athletes (n ¼ 757)
Controls (n ¼ 670)
b coefficient
SE
P
b coefficient
SE
P
0.356 0.125
0.014 0.004
<0.001 <0.001
0.306 0.071
0.012 0.003
<0.001 NS
ALT, alanine aminotransferase; BMI, body mass index; HOMA-IR, homeostatic metabolic assessment for insulin resistance * For athletes, BMI and ALT were selected as variables significantly contributing to HOMA-IR; for controls, only BMI remained as the only variable contributing to HOMA-IR.
significant between-group differences in BMI, HOMA-IR, ALT, systolic blood pressure (SBP), and diastolic blood pressure (DBP) were consistent for both years. Fasting plasma glucose level was not different between two groups in 2006 but slightly different in 2007. Insulin, HOMA-IR, BMI, ALT, AST, SBP, and DBP values of the athlete group were significantly greater than those of the control group (P < 0.05). Table 2 summarizes the results of stepwise regression analysis for variables predicting HOMA-IR value. For the athlete group, BMI and ALT were included as contributors for the variation of HOMA-IR values. For non-athlete controls, BMI was the only contributor for the variation of HOMA-IR values. Table 3 lists the mean values of insulin resistance-associated variables, including HOMA-IR, SBP, and DBP, across 33 sport disciplines. It is generally known that BP is strongly correlated with insulin sensitivity [17]; thus BPs were also determined in the study. Mean HOMA-IR values from four disciplines were significantly different from the control group. HOMA-IR values from rowing and short-distance track athletes were significantly lower than those from the control group (P < 0.05). HOMA-IR values from archery and field-throwing athletes were significantly greater than those from the control group (P < 0.05). Athletes from both disciplines also had significantly greater SBP above control values. There were 15 sport disciplines that showed significantly greater SBP than the control group. Eight sport disciplines displayed significantly greater DBP than the control group. Table 4 lists the mean values for the factors (BMI and liver function test) that predict HOMA-IR from athletes across 33 sport disciplines. There were 22 among 33 sports disciplines that showed significantly greater BMI values compared with the physically active controls. Athletes from kayaking, hockey, rugby, track, and swimming had significantly greater ALT values than the control group (P < 0.05). Athletes from baseball, hockey, karate, rowing, rugby, soccer, and track had significantly greater AST values than the control group (P < 0.05). Discussion Athletes are a special group of highly physically active people selected by outstanding fitness against physical chal-
lenge. However, abnormal liver function levels could occur during strenuous exercise training and competition [11,12]. This suboptimal condition might influence whole-body insulin sensitivity and glucose metabolism [5,8]. The present study found that markers for abnormal liver function independently contributed to the variation of HOMA-IR value in athletes. Athletes from archery and field-throwing disciplines showed significantly greater HOMA-IR values than Table 3 Insulin resistance variables from 33 sports disciplines Sports disciplines (N)
HOMA-IR
SBP
DBP
Control (670) Archery (18) Badminton (22) Baseball (27) Basketball (39) Bowling (9) Boxing (25) Cycling, road (22) Fencing (15) Field, jumping (19) Field, throwing (17) Golf (20) Gymnastics (10) Handball (41) Hockey (23) Ice skating (4) Judo (26) Karate (20) Kayaking (25) Kendo (22) Martial art (16) Ping pong (30) Rowing (20) Rugby (37) Soccer (23) Softball (24) Swimming (31) Taekwondo (36) Tennis (30) Track, distance (15) Track, short distance (22) Volleyball (27) Water polo (26) Weight lifting (16)
1.40 6 0.03 2.59 6 0.51* 1.33 6 0.12 1.19 6 0.1 1.55 6 0.15 1.73 6 0.28 1.65 6 0.18 1.40 6 0.17 1.92 6 0.46 1.19 6 0.15 2.91 6 0.73* 1.82 6 0.27* 1.76 6 0.34 1.52 6 0.11 1.43 6 0.19 0.97 6 0.35 1.63 6 0.27 1.28 6 0.14 2.17 6 0.56 1.63 6 0.16 1.32 6 0.19 1.52 6 0.14 0.90 6 0.10** 2.10 6 0.40 1.26 6 0.10 2.03 6 0.34 1.48 6 0.13 1.58 6 0.14 1.39 6 0.11 1.42 6 0.18 1.10 6 0.08** 1.64 6 0.25 1.49 6 0.23 1.61 6 0.19
119.8 6 0.52 127.4 6 4.07* 126.2 6 2.89* 130.2 6 1.96*** 127.2 6 2.4*** 127.7 6 2.09** 130.4 6 2.31*** 124.0 6 2.69 125.4 6 3.15 124.2 6 1.74* 131.7 6 2.28*** 123.7 6 2.47 126.8 6 4.51 122.2 6 2.16 125.3 6 1.81** 105.5 6 5.20* 124.3 6 2.83 125.8 6 2.83 129.4 6 2.87*** 127.5 6 3.05** 117.1 6 2.68 120.0 6 2.12 124.1 6 3.23 129.9 6 1.66*** 127.6 6 2.18** 115.2 6 0.20 131.6 6 1.61*** 120.5 6 2.41 124.6 6 2.40 123.7 6 3.57 120.3 6 3.05 118.4 6 3.16 128.0 6 2.38** 125.0 6 3.67
71.4 6 0.31 76.1 6 3.09* 72.5 6 1.51 71.8 6 1.48 73.0 6 1.3 76.8 6 2.65* 75.8 6 1.56** 73.5 6 1.77 70.0 6 1.83 73.0 6 1.24 74.6 6 2.05 72.4 6 1.39 75.7 6 1.68 72.2 6 1.32 72.9 6 1.77 63.0 6 1.48* 73.5 6 2.04 73.0 6 1.89 75.3 6 1.78* 74.1 6 1.64 67.6 6 1.89 70.8 6 1.75 71.3 6 1.90 75.0 6 1.44** 75.0 6 1.45* 67.8 6 1.40* 75.0 6 1.36* 69.7 6 1.14 70.4 6 1.12 76.5 6 2.13* 72.7 6 1.85 72.7 6 1.97 72.8 6 1.82 74.5 6 1.91
DBP, diastolic blood pressure; HOMA-IR, homeostatic metabolic assessment for insulin resistance; SBP, systolice blood pressure Probabilities of type I error <5%*, <1%y, and <0.1%z (for the mean difference against the control group).
Y.-L. Chen et al. / Nutrition 25 (2009) 1137–1142
1140 Table 4 Predictors for HOMA-IR from 33 sports disciplines Sports disciplines (N) BMI Control (670) Archery (18) Badminton (22) Baseball (27) Basketball (39) Bowling (9) Boxing (25) Cycling, road (22) Fencing (15) Field, jumping (19) Field, throwing (17) Golf (20) Gymnastics (10) Handball (41) Hockey (23) Ice skating (4) Judo (26) Karate (20) Kayaking (25) Kendo (22) Martial art (16) Ping pong (30) Rowing (20) Rugby (37) Soccer (23) Softball (24) Swimming (31) Taekwondo (36) Tennis (30) Track, distance (15) Track, short distance (22) Volleyball (27) Water polo (26) Weight lifting (16)
21.1 6 0.10 25.2 6 1.52* 22.4 6 0.52* 24.3 6 0.51*** 22.6 6 0.29*** 24.7 6 0.71*** 22.9 6 0.82* 22.9 6 0.44 23.0 6 0.42*** 20.7 6 0.42 29.2 6 1.44*** 21.8 6 0.64 22.0 6 0.78 22.9 6 0.49*** 23.6 6 0.54*** 21.5 6 1.19 25.5 6 0.93*** 21.3 6 0.43 23.6 6 0.51*** 22.5 6 0.67** 22.2 6 0.45 21.4 6 0.45 21.9 6 0.43 26.4 6 0.61*** 22.3 6 0.36* 22.4 6 0.53* 22.7 6 0.45*** 22.4 6 0.57* 22.3 6 0.51* 20.6 6 0.50 21.3 6 0.44
ALT
AST
14.4 6 0.42 26.2 6 7.15 16.0 6 1.51 18.1 6 2.74 13.2 6 0.91 14.6 6 2.32 15.6 6 2.36 19.7 6 5.17 22.7 6 6.57 14.8 6 2.38 25.0 6 5.32 16.2 6 2.60 15.3 6 4.79 13.2 6 1.06 25.7 6 4.40* 8.7 6 0.75 17.5 6 3.64 18.6 6 2.13 19.6 6 2.55* 15.7 6 2.11 16.1 6 4.03 13.7 6 1.42 13.9 6 1.65 17.8 6 1.73* 16.0 6 1.66 10.5 6 0.66*** 19.5 6 2.53* 13.6 6 1.80 16.9 6 2.19 20.3 6 3.92* 13.8 6 1.90
18.3 6 0.23 21.1 6 2.64 19.0 6 0.79 21.6 6 1.31** 19.3 6 1.05 20.4 6 0.96 18.4 6 1.02 20.1 6 1.44 23.7 6 4.57 19.3 6 1.75 20.5 6 1.88 17.6 6 1.37 15.7 6 1.68 17.2 6 1.74 26.0 6 1.92*** 14.7 6 1.03 19.9 6 1.40 22.2 6 1.74* 20.3 6 0.95 17.8 6 1.32 18.7 6 1.64 16.8 6 0.83 22.9 6 1.20*** 20.1 6 0.77* 21.4 6 1.47* 17.9 6 0.85 21.8 6 2.11 17.5 6 0.80 18.7 6 0.82 20.9 6 2.54** 18.9 6 1.35
22.2 6 0.55* 12.9 6 0.83 23.9 6 0.73*** 18.7 6 3.71 26.4 6 0.70*** 19.0 6 4.18
16.8 6 0.80 20.1 6 1.59 21.1 6 2.37
ALT, alanine aminotransferase; AST, aspartate aminotransferase; BMI, body mass index; HOMA-IR, homeostatic metabolic assessment for insulin resistance Probabilities of type I error <5%*, <1%y, and <0.1%z (for the mean difference against the control group).
controls, but the markers for abnormal liver function were not significantly different from controls. For both disciplines, overweight (BMI > 25 kg/m2) appears to be the main contributor to low insulin sensitivity. To the best of our knowledge, this is the first population report to document HOMA-IR values for athletes across multiple sports disciplines. The HOMA-IR value in athletes was predicted by abnormal liver function and BMI. The information of this study could be important because carbohydrate is the major fuel for a great variety of sport competitions [18]. High insulin sensitivity could ensure efficient carbohydrate storage for athletes [1,19]. The most striking finding of the study is that BMI values from 22 of 33 sports disciplines were significantly greater than in physically active control subjects, which explains, to some extent, the greater overall HOMA-IR in athletes above controls. The finding of the present study presents a novel
message to young athletes that insulin sensitivity remains associated with BMI for this physically active group. Although BMI may not be the best obesity indicator for athletes because the variation in BMI could be due to differences in muscle mass [20,21], greater BP and HOMA-IR values above control suggested a trend toward greater adiposity, even though the athletes in this study were considered healthy [22]. Most clinical studies have repeatedly shown that BP is highly correlated with insulin sensitivity, secondary to weight status [22–24]. Consistent with previous data, athletes with a BMI greater than 25 kg/m2 in this study, such as those involved in archery, field throwing, judo, rugby, and weightlifting, displayed a relatively higher SBP than the control group. In fact, the relation between BP and weight in elite athletes was reported in 1949 [25]. Data have shown that SBP is proportional to body weight, ranging from 90 to 160 mmHg for athletes participating in the London Olympic Games. This is consistent with the present data that SBP and DBP were increased with weight status. However, it should be noted that there were quite a few extreme values in the athlete group. Whether the extreme BP value in some athletes has pathophysiologic implications requires further investigation. In contrast to the normal physically active non-athletes, athletes are subjected to greater magnitudes of daily energy depletion–repletion cycle and variations in yearly training load in compliance with a competition schedule. It has been reported that reducing training volume during off-season or completely stop a training routine after retirement can result in increased fatness and decreased insulin sensitivity [20]. Because the rate of insulin-stimulated glucose utilization [26] and body weight [27] are regulated by training intensity and duration, modulation in training volume according to competition season would undoubtedly have ramifications on the metabolic homeostasis in athletes. It is thus possible that body fat is easy to accumulate during detraining periods or off-season [28], but their weight status did not completely returns to the previous level by competition season. Genetic differences between elite athletes and physically active controls were not evaluated in this study, but there is little doubt that elite athletes are a genetically selected group for outstanding muscular fitness [29,30]. In this study, some athletes with higher HOMA-IR values were in power-related disciplines, such as field throwing. The fact that elite power athletes tend to be more insulin resistant than elite endurance athletes has been previously documented [31]. A Finnish study has found a greater relative risk in diabetes and several associated metabolic complications for former elite power athletes versus endurance athletes [32,33]. Power athletes are normally selected by greater number of type IIb muscle fibers. This type of muscle fiber is substantially more insulin resistant compared with type IIa and I fibers [34]. Because skeletal muscle is the largest insulin-sensitive tissue for postprandial glucose disposal, muscle insulin sensitivity could influence whole-body insulin sensitivity [35]. It has been shown that muscle fiber composition can be modulated by different types of exercise training programs [36]. This could
Y.-L. Chen et al. / Nutrition 25 (2009) 1137–1142
be another possibility contributing the lower HOMA-IR value in field-throwing athletes. However, our data show that HOMA-IR for elite short-distance sprinters was significantly lower than that for the control group. Differences in insulin sensitivity between non-athletes and athletes from different sports disciplines are within a physiologic range. In general, a small difference in insulin sensitivity is not a clinical concern for young adults. However, sensitivity to insulin deteriorates with advancing aging. A longitudinal study has reported that middle-aged individuals with less insulin sensitivity, evaluated by steady-state plasma glucose and insulin levels, had a greater incidence of stroke, coronary heart disease, diabetes, hypertension, and cancer than their counterparts with high insulin sensitivity in future decades [23]. It is currently unknown whether the small difference in insulin sensitivity could be amplified with age. Long-term follow-up for the specific active population is required to confirm this possibility. The main limitation of the study was that the amounts and types of food and beverage ingested by athletes were not evaluated, which might contribute to the greater HOMA-IR and BPs for select disciplines of athletes. One possibility that needs to be clarified is the consumption amount of fructose-containing sports drinks. Sports drinks are widely used by athletes during regular training and competition, and most sports drinks contain fructose. Recently, fructose intake has been increasingly recognized as causative in the development of prediabetes and metabolic syndrome [37,38]. Fructose has an approximately eight-fold higher reactivity than glucose in the contribution of protein glycation [39], which is known to causally link with insulin resistance and hypertension [40]. Another nutritional factor that remains to be investigated is whether red meat is overconsumed by athletes due to a high demand for muscle protein resynthesis during training. Higher consumption of total red meat, especially processed meats, could increase the risk of insulin resistance and diabetes [41]. Furthermore, data related to total cholesterol, low-density lipoprotein and high-density lipoprotein cholesterol, triacylglycerols, and free fatty acids should be studied in the future because some of them are involved with states of insulin resistance and hypertension. Conclusions This is the first population study determining HOMA-IR values across multiple sport disciplines. The present study demonstrated that insulin sensitivity in athletes is independently predicted by BMI and abnormal liver function level. According to our repeated observations in 2006 and 2007, the elite athletes were slightly heavier with greater HOMAIR compared with the physically active controls. Interestingly, 22 of 33 sports disciplines showed significantly greater BMI values than those in physically active controls. BPs, a metabolic measurement closely associated with insulin resistance, were also greater in athletes from several disciplines compared with controls. Long-term investigation is required
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