Journal Logo

CLINICAL SCIENCES: Clinically Relevant

Effect of High Cardiorespiratory Fitness and High Body Fat on Insulin Resistance


Author Information
Medicine & Science in Sports & Exercise: October 2006 - Volume 38 - Issue 10 - p 1709-1715
doi: 10.1249/01.mss.0000228365.31821.22
  • Free


Insulin resistance, a metabolic disturbance that underlies the development of both type 2 diabetes and cardiovascular disease (20), is more prevalent in individuals with excess body fat than normal-weight individuals (8). However, overweight and obese people often have low cardiorespiratory fitness (CRF) (6), which can independently contribute to insulin resistance (13,22). Studies that have linked obesity and insulin resistance have not always accounted for differences in CRF between the normal-weight and overweight subjects (8).

Results from numerous observational trials suggest that fitness mitigates the impact of fatness on the risk for metabolic syndrome (15) and type 2 diabetes (29) even in high-risk groups, such as those with general obesity (29) or high levels of visceral fat (15). As a result, elevated risk for cardiometabolic disease in overweight and obese people may be partially explained by low CRF. Because physical activity increases sensitivity to insulin (by opposing insulin resistance), a likely explanation for the protective effect of fitness, independent of fatness, is enhanced insulin sensitivity in the fitter populations. Furthermore, because fit individuals have lower rates of cardiometabolic disturbances than their unfit counterparts, regardless of body fat (15,29), insulin sensitivity may be more strongly associated with fitness than fatness, implying that overweight individuals with high CRF will be relatively insulin sensitive.

However, to date, the authors are unaware of any studies that have carefully measured the insulin response to a glucose challenge, a commonly used method to estimate insulin sensitivity (16), in a group of women with both high body fat and high CRF. Therefore, the primary goal of the current investigation was to compare the blood glucose and insulin response to an oral glucose tolerance test (OGTT) in three groups of women: 1) overweight, endurance-trained women with high CRF (OF); 2) lean, endurance-trained women with high CRF (LF); and 3) a reference group of overweight, untrained women (OU). By design, the trained groups were matched for high CRF but were discordant for body fat, whereas the overweight groups were matched for body fat but discordant for CRF. We hypothesized that, despite considerable excess body fat, plasma glucose and insulin response to an OGTT in overweight women with high CRF would be similar to fitness-matched lean women.


Study Design

To test the hypothesis we measured the glucose and insulin responses to a 75-g glucose challenge in three groups of women matched for either high CRF (LF and OF) or high body fat (OF and OU).


There were 21 healthy, endurance-trained women who participated in this study. All of the subjects were in excellent overall health, had no history of cardiovascular, metabolic, or hormonal disorders, and used no medications other than birth control or occasional over-the-counter aspirin or ibuprofen. After study procedures were explained verbally, subjects signed a written informed consent document approved by institutional review board at the University of Massachusetts. All participants were runners, triathletes, or rowers and trained 5-6 d·wk−1 for an average of 1.5 h·d−1. All had been training for at least 12 months. Subjects were eligible if they met three criteria: 1) their body fat was < 22% or > 28%; 2) their V˙O2peak (scaled to lean mass) was greater than 60 mL·kg−1 LM·min−1; and 3) they had been weight stable (±2 kg) for the last 6 months (self-reported) as well as in the weeks before testing (as measured by investigators). Data from women in the OU group were collected during screening in a prior study in the laboratory focused on substrate kinetics (3). Data from two women were excluded from the analysis. One woman presented with numerous symptoms of polycystic ovarian syndrome. After hormonal analyses were completed, her plasma insulin concentrations during the OGTT were > 3 SD above the mean. Because of the combination of her symptoms and the deviation of her insulin concentrations from the mean, her data were excluded from the analysis. Another woman was suffering from an eating disorder during data collection and did not notify investigators until after data collection; her data were also excluded. Therefore, all results are reported with N = 9 for LF, N = 10 for OF, and N = 10 for OU. Subject characteristics are shown in Table 1.

Subject characteristics.

In the final cohort, LF and OF subjects were well matched on all anthropometric variables, including training and fitness, except for (by design) percent body fat (Table 1). The LF group had 50% less body fat than the OF group. OU women had similar amounts of body fat as the OF women, but they were considerably less fit. Thus, these groups allow us to make comparisons between women who have equally high levels of CRF but drastically different levels of body fat (LF vs OF) as well as between women who have comparable levels of body fat but very different levels of fitness (OU vs OF).

Screening Procedures

Exercise patterns were assessed via a training history that queried long-term (> 2 yr) and recent (during the last 2 yr) training patterns. A 7-d training log was also completed to ensure participants were training > 6 h·wk−1. Body composition was determined by a dual-energy x-ray absorptiometry total body scan (GE/Lunar Corp., Madison, WI). Peak oxygen consumption (V˙O2peak) was measured on either an electronically braked cycle ergometer (SensorMedics 800S, Yorba Linda, CA) or a treadmill (LifeFitness 9100HR, Schiller Park, IL). Briefly, after an initial 5-min warm-up, the workload of the cycle ergometer or the grade of the treadmill was increased every 2 min until volitional exhaustion. Oxygen consumption and carbon dioxide production were measured by indirect calorimetry with a TrueMax 2400 metabolic measurement system (Parvo Medics, Sandy, UT). V˙O2peak was defined as the highest value obtained (15-s average).


Subjects reported to the laboratory in an overnight fasted condition. A catheter was inserted into a forearm vein, and a resting blood sample was taken. Subjects ingested a 75-g glucose solution (Sun Dex, Fisherbrand) within the next 5 min, and blood samples were collected every 30 min for the next 2 h while subjects rested in a seated position.

Dietary Control, Energy Balance, and Pre-OGTT Exercise

To ensure that subjects were tested in their "habitual" state during the OGTT, women in the OF and LF groups were tested 16-24 h after a bout of exercise that took place during a "normal" training week. To standardize the pre-OGTT exercise, all subjects were instructed to participate in activities (run approximately 16 km, cycle approximately 48 km, or row 20 km) that would require approximately 4000 kJ of energy expenditure. To simulate their habitual state, women in the OU group refrained from any exercise before testing.

The Harris-Benedict equation specific to women, 655 + 9.6 · (weight in kilograms) + 1.8 · (height in centimeters) - 4.7 · (age in years), was used to calculate resting metabolic rate, and this value was multiplied by an activity factor of 1.55-1.9 (depending on the subject's individual habitual physical activity) to estimate daily energy requirements. Although diet was not rigidly controlled throughout the entire study, the night before testing, all subjects consumed a meal consisting of 35% of estimated daily energy requirements (approximately 1000 kcal for most subjects) and composed of 55% carbohydrate, 15% protein, and 30% fat. The meal contained more than 120 g of carbohydrate and was designed to minimize individual differences in muscle glycogen stores. To maintain energy balance, subjects were also instructed to replace the 1000 kcal expended during exercise in their food choices the day before testing. Based on body weight and activity level, energy intake on the day before testing was approximately 2500-3500 kcal. All subjects reported pre-OGTT exercise and food consumption to investigators before testing. If exercise duration or food choices were not in approximate caloric balance, investigators instructed subjects on appropriate adjustments before testing.

Estimation of Abdominal Fat

Abdominal fat was determined from anatomical landmarks and default calculations of the Lunar computer software. The recommendations of the manufacturer were followed for manual designation of a region of interest (ROI) around the abdomen for an approximation of abdominal fat. The ROI was bound inferiorly by the top of the iliac crest and superiorly by the T12-L1 intervertebral space. All ROI were drawn manually by a single investigator for all scans. Because the back-up files were lost, ROI were only available for 6 of the 10 OU subjects.

Previously Tested Comparison Group

Data from 10 of the 12 women in a cohort of overweight sedentary women who had previously completed a study in our laboratory (3) were included as a third reference group. Two women were not included for the present analysis because their body fat levels (49 and 51% body fat) were much greater than any of the women in the OF group, who ranged from 28.8 to 39.4%. All OU women completed the same V˙O2peak and OGTT procedures as the current cohort of LF and OF.

Biochemical Assays

Samples of venous blood for analysis of glucose and triacylglycerols were collected in heparinized syringes and then transferred to vacutainers containing sodium fluoride. Samples for analysis of insulin were collected in heparinized syringes and then transferred to vacutainers containing EDTA. All samples were immediately centrifuged, and the plasma/serum was transferred to cryogenic vials and frozen at −80°C until analysis. Glucose concentrations were determined using a glucose/lactate analyzer (GL5 Analyzer, Analox Instruments, Lunenberg, MA). Insulin was measured using radioimmunoassay (Linco Research, St. Charles, MO). Triacylglycerols were determined using an enzymatic colorimetric assay kit (Sigma Chemical, St. Louis, MO).

Indices of Insulin Sensitivity and Calculations

Areas under the glucose and insulin curves (glucose and insulin AUC) were calculated for the 2-h OGTT using the trapezoidal method. Insulin sensitivity was estimated from the insulin AUC and from the composite insulin-sensitivity index (C-ISI) (16):

where FPG and FPI are fasting plasma glucose (mmol·L−1) and fasting plasma insulin (μU·mL−1), respectively, and G(mmol·L−1) and I (μU·mL−1) are the mean glucose and mean insulin concentrations during the 2-h OGTT. The C-ISI incorporates both fasting values and the glucose and insulin responses to OGTT into a whole-body insulin-sensitivity index. The C-ISI encompasses a range from 0 (extremely resistant) to 12 (very sensitive) and is very well correlated with total body glucose disposal rate per unit of insulin measured during euglycemic clamps in subjects with normal glucose tolerance, impaired glucose tolerance, and type 2 diabetes (16). The insulin AUC in response to an OGTT is also often used as an estimate of insulin sensitivity (23,28).

Fasting insulin resistance was also estimated using the homeostasis model assessment (HOMA-IR) equation: HOMA-IR = (FPG × FPI)/22.5 (17). HOMA-IR allows for quantitative assessment of insulin resistance using only fasting glucose and insulin concentrations and is useful to detect differences between glucose-tolerant and glucose-intolerant individuals (9).

Statistical Analysis

Data were analyzed using SAS Inc. software (Cary, NC). A mixed-model two-way analysis of variance (ANOVA) with unstructured covariance structure was used to test for a group × time interaction for glucose and insulin concentrations during the OGTT. A one-way ANOVA was used to detect differences between groups for all anthropometric variables, fasting insulin, fasting glucose, fasting triacylglycerols, insulin AUC, glucose AUC, CISI, and HOMA-IR. In general, data are presented as group means, 95% confidence interval for the difference between group means, and the exact P value.


Fasting Glucose, Insulin, and Triacylglycerol Concentrations

There was no difference in fasting blood glucose between LF and OF subjects (P = 0.77), but fasting glucose was 13% higher in OU than in OF subjects (P = 0.03). Fasting insulin concentrations were not different between any of the groups. There was no difference in HOMA-IR, calculated from fasting glucose and insulin concentrations, between LF and OF subjects. However, HOMA-IR was 50% higher in OU than in OF subjects (P = 0.05). Fasting triacylglycerol concentrations were markedly similar between LF and OF subjects (P = 0.99) but were 69% higher in OU than in OF subjects (P = 0.004) (Table 2).

Comparison of measured parameters in lean fit, overweight fit, and overweight unfit women during a 2-h OGTT.

Glucose Response to OGTT

There was no difference between LF and OF in either peak glucose (average of each individual's highest blood concentration) or glucose AUC. However both peak glucose and glucose AUC were significantly higher in OU than in OF subjects (26 and 24%, respectively, both P < 0.03) (Table 2).

Insulin Response to OGTT

Using insulin AUC to estimate insulin sensitivity, there was no statistical difference between LF and OF subjects (P = 0.08), but the mean insulin AUC was 44% lower in LF than in OF subjects, suggesting that the differences would have been significant with slightly more statistical power (given the group mean differences and variability, the power to detect a difference at the 0.05 level was 0.768). Insulin AUC was 50% higher in OU than in OF subjects (P = 0.04) (Fig. 1). Using the C-ISI score to estimate insulin sensitivity, C-ISI was significantly higher for LF (indicating more insulin sensitivity) than for OF subjects (P = 0.01). However, the OF group mean (6.9 ± 0.9) is indicative of an insulin-sensitive state (16). OU subjects tended to have a lower C-ISI score than OF subjects (P = 0.09), although the difference was not significant (Table 2).

Plasma glucose (A) and insulin (B) concentrations during a 2-h OGTT in lean fit, overweight fit, and overweight unfit women. Data are means ± SEM. The bar charts on the right show the mean AUC of the plasma glucose (C) and insulin (D) concentrations during the OGTT for all groups. Statistical differences in AUC are denoted with † (overweight fit vs overweight unfit P < 0.05).

Estimated Abdominal Fat

OF subjects had nearly three times the abdominal fat as LF subjects (1.7 ± 0.1 vs 0.6 ± 0.1 kg, P < 0.001); however, abdominal fat as a percentage of total fat was not different between the groups (6.5 ± 0.4 vs 5.2 ± 0.5%, P = 0.13). Corresponding data for the OS group were only available for 6 of the 10 subjects. Although the OU and OF groups had a similar amount of total body fat (Table 1), OU subjects had significantly more total abdominal fat (2.4 ± 0.2 vs 1.7 ± 0.1 kg, P < 0.004). Similarly, when expressed as a percent of total body fat, percent abdominal fat in the OU group was significantly greater than in the OF group (8.5 ± 0.8 vs 6.5 ± 0.4%, P = 0.04).


The primary goal of the current investigation was to compare the blood glucose and insulin responses to an OGTT in overweight, fit women (OF) with those of lean, fit women (LF) matched for high CRF but with much lower body fat. To put the differences between the OF and LF groups into perspective, we used data from a cohort of overweight, unfit (OU) women from a previous study in our laboratory. Compared with the OF group, the OU group was matched for high body fat but had considerably lower CRF. The main findings were that 1) insulin sensitivity estimated from the insulin AUC was not significantly different between OF and LF, although the group mean difference was large; 2) insulin sensitivity estimated from the C-ISI was significantly lower in OF compared with LF, but the mean value was higher than in OU; and 3) the LF and OF glucose responses to an OGTT and fasting triacylglycerols were indistinguishable. Taken together, these data suggest that excess body fat has only a minimal impact on estimated insulin sensitivity and triacylglycerols in women with high CRF.

Fasting concentrations of glucose, insulin, and triacylglycerols for the LF group were similar to those reported in the literature for lean, trained cohorts. The LF peak glucose and insulin concentrations during the OGTT were also similar to previously reported values, as were the 2-h concentrations, which had returned to, or were very close to, fasting values (10,13).

Our reference OU group was likely more insulin sensitive than a group of randomly selected overweight, sedentary women would have been. These women had been enrolled as subjects in a previous study because they were either insulin resistant (C-ISI < 4) or insulin sensitive (C-ISI > 6). Therefore, half of the OU group was specifically chosen because they were insulin sensitive. As we expected, literature values for insulin AUC in overweight or obese subjects tend to be even greater than what we observed in the OU group (18,27). Recent NHANES III data also suggest that our OU group was relatively insulin sensitive for individuals with BMI in the overweight range (25.0-29.9 kg·m−2). In a sample of over 6000 individuals, HOMA-IR was 2.8 for individuals with BMI in the range of 25.0-29.9 kg·m−2 (4). The average HOMA-IR in our OU group (average BMI, 28.1 ± 0.4 kg·m−2) was 2.3, an indication that our OU group was more insulin sensitive than would be expected. Fasting triacylglycerol levels also tended to be slightly lower than those usually reported for similar cohorts (2). Therefore, any comparisons between our OF and OU groups most likely underestimate the true differences between overweight, fit and overweight, sedentary individuals.

The peak insulin concentrations and insulin AUC are higher in the OF group than values reported for lean, fit individuals (10,13). Plasma glucose concentrations during the OGTT were similar between OF and other lean, trained cohorts (10,13). Overall, as evidenced by similar glucose concentrations during the OGTT, despite higher insulin concentrations, the OF group was less insulin sensitive than leaner, trained individuals. Our assessment of insulin sensitivity is approximated from the glucose and insulin responses to the OGTT, rather than being directly assessed. However, 30-50% of the variability in experimentally determined insulin action (e.g., euglycemic clamp) is explained by plasma insulin response to an OGTT (11,31), and the OGTT is often used as a surrogate for directly measured insulin sensitivity (10,23,28).

Despite being less insulin sensitive than leaner, trained individuals, the OF group is clearly more insulin sensitive, as indicated by substantially lower insulin concentrations during an OGTT, than sedentary individuals with comparable levels of body fat. Peak insulin concentrations in overweight/obese populations during an OGTT are often >600 pM, and insulin AUC is often close to 60,000 pM·120 min (18,27). Therefore, OF peak insulin concentration and insulin AUC values during the OGTT were markedly lower than those reported in the literature for overweight/obese, sedentary individuals. The large difference in insulin AUC between OF and other overweight/obese, sedentary cohorts was driven largely by the 2-h insulin concentrations. Reported 2-h insulin concentrations in the literature are often > 360 pM and are five to six times greater than the fasting insulin concentrations (18,27). This is in contrast to the observed 2-h insulin concentration in OF (164 ± 47 pM), which was only about 2.5 times greater than fasting insulin concentrations (45 ± 4 pM). Insulin concentrations returning to fasting levels within 2 h is characteristic of lean, trained cohorts (10,13). Therefore, the overall pattern of insulin response in the OF group is more similar to that of their "fitness" counterparts than their "fatness" counterparts.

Use of two independent indices of insulin sensitivity (HOMA-IR and C-ISI) also suggests that the OF group, although less sensitive than their fitness-matched counterparts, are considerably more sensitive than their body fat-matched counterparts. HOMA-IR, measured under fasting conditions, was not different between LF and OF, though OU was 66% higher than OF (Table 2). To place the observed HOMA-IR scores observed in our study into context, in a Caucasian population with normal glucose tolerance from the San Antonio Heart study, the mean HOMA-IR was 2.1 ± 0.2 (9). A HOMA-IR score of 1 is a very insulin-sensitive score; therefore, the HOMA-IR score of our OF group (1.5 ± 0.1) is indicative of substantial insulin sensitivity, even compared with individuals with normal glucose tolerance. Additionally, in recently published NHANES III data, mean HOMA-IR was 2.8 for individuals with a BMI in the range of 25.0-29.9 kg·m−2 (4), nearly twice the HOMA-IR of the OF group, in which the mean BMI was 26.3 kg·m−2.

The C-ISI score of the OF group also indicates that this group was more insulin sensitive than would be expected based on their excess body fat. As reported by Matsuda and DeFronzo, the C-ISI correlates very well not only with insulin sensitivity measured with a hyperinsulinemic clamp (r = 0.836) but also with glucose clamp-derived total body glucose disposal (r = 0.73, P < 0.0001) (16). This allows us to place the C-ISI score of the OF group into more physiologically relevant terms. The OF C-ISI of 6.9 corresponds to a glucose disposal rate of approximately 4 mg·m−2·min−1·μU−1·mL−1, which is within the upper 30% of the normal range. For comparison, the C-ISI of the OU group (which, again, is most likely an overestimation of insulin sensitivity for a group of overweight, sedentary women) was 4.5, which corresponds to a glucose disposal rate of approximately 2.5 mg·m−2·min−1·μU−1·mL−1, which is in the lower 30% of the normal range, slightly greater than the values from individuals with impaired glucose tolerance.

Observational and intervention trials suggest that type 2 diabetes can be delayed or prevented by lifestyle modifications including weight loss and exercise (14), both of which are known to independently increase insulin sensitivity (5). If this is the case, it is likely that the observed decrease in incidence of metabolic syndrome (7,15) and type 2 diabetes (29) in fit populations, independent of fatness, is attributable to increased insulin sensitivity in the fitter populations. Recently, it has been speculated by some of the authors of these observational trials that a mechanism by which CRF improves overall metabolic health is by lowering insulin resistance (15). Our data, which suggest that fit women with moderately high levels of body fat are more insulin sensitive (as indicated by lower insulin AUC, HOMA-IR, and C-ISI) than unfit women with equivalent amounts of body fat, support this theory.

There are a number of mechanisms that may be responsible for improved glucose tolerance in OF compared with OU. At the whole-body level, exercise training may prevent the deposition of metabolically harmful visceral fat. Individuals with high CRF have lower levels of visceral fat, independent of BMI (30). In addition, exercise without weight loss significantly reduces visceral fat in women (21). Although visceral fat was not measured in the current investigation, total abdominal fat was approximated using DEXA computer software. OF had significantly less abdominal fat than OU when expressed as either total abdominal fat or as a percentage of total body fat. Because high levels of abdominal fat are associated with insulin resistance (15), the lower levels of abdominal fat in the OF group may partially explain their enhanced insulin sensitivity compared with OU.

Insulin AUC was lower in OF than OU, potentially because the OF women had "trained" muscle, despite their excess body fat. In cross-sectional studies, athletes have more muscle GLUT4 protein and increased insulin sensitivity compared with sedentary controls (1). Training also increases mitochondrial number and oxidative capacity, characteristics that are associated with increased insulin sensitivity (12). Because muscle represents the major site of glucose uptake in the presence of insulin, it appears that "fit" muscle partially compensates for excess body fat in the OF group.

Lastly, high CRF and high body fat are not mutually exclusive, especially in women (19,26). Although exercise may induce or maintain leanness by increasing daily caloric expenditure, weight loss often eludes those who begin exercise programs (19,26), most likely because of an increase in caloric intake (25). Women are more likely than men to experience significant increases in fitness in response to training without concomitant fat loss (19,26). The current cohort of OF demonstrate that excess body fat does not preclude the development or maintenance of high CRF. CRF, when expressed in absolute terms (L·min−1) or relative to lean mass (mL·kg−1 LM·min−1), were not different between LF and OF. The prevalence of "fit-fat" women has also been documented by Stevens et al., who report that in a cohort of 2500 women, 25% of the most fit women were overweight or obese (24).

In summary, the aim of the current investigation was to compare plasma glucose and insulin responses to an OGTT in women matched for high CRF but discordant for body fatness with women discordant for CRF but matched for excess body fat. We have shown that women with excess body fat and high CRF are more insulin sensitive than overweight, sedentary women with equal amounts of body fat. Furthermore, we have shown that the glucose and insulin responses to an OGTT, as well as fasting triacylglycerols, are more similar between women with high CRF but vastly different body fatness than between women with equal amounts of body fat but different levels of CRF. Our findings support the theory that overweight/obese individuals with high CRF have lower rates of cardiometabolic disease than sedentary overweight/obese individuals with low CRF because the fitter individuals are more insulin sensitive.

The authors thank the dedicated subjects for their enthusiastic participation in this study. We acknowledge excellent assistance from Elizabeth Mitchell B.S., Allison Gruber B.S., and Stuart Chipkin, M.D. This study was supported by the Glass Family Trust and by a Junior Faculty Award from the American Diabetes Association (BB).


1. Andersen, P. H., S. Lund, O. Schmitz, S. Junker, B. B. Kahn, and O. Pedersen. Increased insulin-stimulated glucose uptake in athletes: the importance of GLUT4 mRNA, GLUT4 protein and fibre type composition of skeletal muscle. Acta Physiol. Scand. 149:393-404, 1993.
2. Ardern, C. I., P. T. Katzmarzyk, I. Janssen, and R. Ross. Discrimination of health risk by combined body mass index and waist circumference. Obes. Res. 11:135-142, 2003.
3. Braun, B., C. Sharoff, S. R. Chipkin, and F. Beaudoin. Effects of insulin resistance on substrate utilization during exercise in overweight women. J. Appl. Physiol. 97:991-997, 2004.
4. Bravata, D. M., C. K. Wells, J. Concato, W. N. Kernan, L. M. Brass, and B. I. Gulanski. Two measures of insulin sensitivity provided similar information in a U.S. population. J. Clin. Epidemiol. 57:1214-1217, 2004.
5. Cox, K. L., V. Burke, A. R. Morton, L. J. Beilin, and I. B. Puddey. Independent and additive effects of energy restriction and exercise on glucose and insulin concentrations in sedentary overweight men. Am. J. Clin. Nutr. 80:308-316, 2004.
6. Farrell, S. W., L. Braun, C. E. Barlow, Y. J. Cheng, and S. N. Blair. The relation of body mass index, cardiorespiratory fitness, and all-cause mortality in women. Obes. Res. 10:417-423, 2002.
7. Farrell, S. W., Y. J. Cheng, and S. N. Blair. Prevalence of the metabolic syndrome across cardiorespiratory fitness levels in women. Obes. Res. 12:824-830, 2004.
8. Ferrannini, E., A. Natali, P. Bell, P. Cavallo-Perin, N. Lalic, and G. Mingrone. Insulin resistance and hypersecretion in obesity. European Group for the Study of Insulin Resistance (EGIR). J. Clin. Invest. 100:1166-1173, 1997.
9. Haffner, S. M., H. Miettinen, and M. P. Stern. The homeostasis model in the San Antonio Heart Study. Diabetes Care 20:1087-1092, 1997.
10. Heath, G. W., J. R. Gavin III, J. M. Hinderliter, J. M. Hagberg, S. A. Bloomfield, and J. O. Holloszy. Effects of exercise and lack of exercise on glucose tolerance and insulin sensitivity. J. Appl. Physiol. 55:512-517, 1983.
11. Hollenbeck, C. B., N. Chen, Y. D. Chen, and G. M. Reaven. Relationship between the plasma insulin response to oral glucose and insulin-stimulated glucose utilization in normal subjects. Diabetes 33:460-463, 1984.
12. Holloszy, J. O., and E. F. Coyle. Adaptations of skeletal muscle to endurance exercise and their metabolic consequences. J. Appl. Physiol. 56:831-838, 1984.
13. King, D. S., G. P. Dalsky, M. A. Staten, W. E. Clutter, D. R. Van Houten, and J. O. Holloszy. Insulin action and secretion in endurance-trained and untrained humans. J. Appl. Physiol. 63:2247-2252, 1987.
14. Knowler, W. C., E. Barrett-Connor, S. E. Fowler, et al. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N. Engl. J. Med. 346:393-403, 2002.
15. Lee, S., J. L. Kuk, P. T. Katzmarzyk, S. N. Blair, T. S. Church, and R. Ross. Cardiorespiratory fitness attenuates metabolic risk independent of abdominal subcutaneous and visceral fat in men. Diabetes Care 28:895-901, 2005.
16. Matsuda, M., and R. A. DeFronzo. Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp. Diabetes Care 22:1462-1470, 1999.
17. Matthews, D. R., J. P. Hosker, A. S. Rudenski, B. A. Naylor, D. F. Treacher, and R. C. Turner. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28:412-419, 1985.
18. Petrie, H. J., S. E. Chown, L. M. Belfie, et al. Caffeine ingestion increases the insulin response to an oral-glucose-tolerance test in obese men before and after weight loss. Am. J. Clin. Nutr. 80:22-28, 2004.
19. Potteiger, J. A., D. J. Jacobsen, J. E. Donnelly, and J. O. Hill. Glucose and insulin responses following 16 months of exercise training in overweight adults: the Midwest Exercise Trial. Metabolism 52:1175-1181, 2003.
20. Quinn, L. Type 2 diabetes: epidemiology, pathophysiology, and diagnosis. Nurs. Clin. North Am. 36:175-192, 2001.
21. Ross, R., I. Janssen, J. Dawson, et al. Exercise-induced reduction in obesity and insulin resistance in women: a randomized controlled trial. Obes. Res. 12:789-798, 2004.
22. Sato, Y., A. Iguchi, and N. Sakamoto. Biochemical determination of training effects using insulin clamp technique. Horm. Metab. Res. 16:483-486, 1984.
23. Seals, D. R., J. M. Hagberg, W. K. Allen, et al. Glucose tolerance in young and older athletes and sedentary men. J. Appl. Physiol. 56:1521-1525, 1984.
24. Stevens, J., J. Cai, K. R. Evenson, and R. Thomas. Fitness and fatness as predictors of mortality from all causes and from cardiovascular disease in men and women in the lipid research clinics study. Am. J. Epidemiol. 156:832-841, 2002.
25. Stubbs, R. J., A. Sepp, D. A. Hughes, et al. The effect of graded levels of exercise on energy intake and balance in free-living women. Int. J. Obes. Relat. Metab. Disord. 26:866-869, 2002.
26. Tremblay, A., J. P. Despres, J. LeBlanc, and C. Bouchard. Sex dimorphism in fat loss in response to exercise-training. J. Obes. Weight Reg. 3:193-203, 1984.
27. Tremblay, A., J. P. Despres, J. Maheux, et al. Normalization of the metabolic profile in obese women by exercise and a low fat diet. Med. Sci. Sports Exerc. 23:1326-1331, 1991.
28. Villareal, D. T., and J. O. Holloszy. Effect of DHEA on abdominal fat and insulin action in elderly women and men: a randomized controlled trial. JAMA 292:2243-2248, 2004.
29. Wei, M., L. W. Gibbons, T. L. Mitchell, J. B. Kampert, C.D.Lee, and S. N. Blair. The association between cardiorespiratory fitness and impaired fasting glucose and type 2 diabetes mellitus in men. Ann. Intern. Med. 130:89-96, 1999.
30. Wong, S. L., P. Katzmarzyk, M. Z. Nichaman, T. S. Church, S.N. Blair, and R. Ross. Cardiorespiratory fitness is associated with lower abdominal fat independent of body mass index. Med. Sci. Sports Exerc. 36:286-291, 2004.
31. Yeni-Komshian, H., M. Carantoni, F. Abbasi, and G. M. Reaven. Relationship between several surrogate estimates of insulin resistance and quantification of insulin-mediated glucose disposal in 490 healthy nondiabetic volunteers. Diabetes Care 23:171-175, 2000.


©2006The American College of Sports Medicine