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Ann Nutr Metab. Dec 2009; 55(4): 326–333.
Published online Oct 16, 2009. doi:  10.1159/000248991
PMCID: PMC2853590
Exercise Training and Dietary Glycemic Load May Have Synergistic Effects on Insulin Resistance in Older Obese Adults
John P. Kirwan,abcd* Hope Barkoukis,d Latina M. Brooks,ab Christine M. Marchetti,e Bradley P. Stetzer,e and Frank Gonzalezf
aDepartment of Gastroenterology and Hepatology, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA
bDepartment of Pathobiology, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA
cDepartment of Physiology, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
dDepartment of Nutrition, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
eDepartment of Reproductive Biology, Case Western Reserve University School of Medicine and MetroHealth Medical Center, Cleveland, Ohio, USA
fDepartment of Obstetrics and Gynecology, Mayo Clinic, Rochester, Minn., USA
*John P. Kirwan, PhD, Department of Gastroenterology and Hepatology, Cleveland Clinic, Lerner Research Institute, 9500 Euclid Ave/NE4-209, Cleveland, OH 44195 (USA), Tel. +1 216 444 3412, Fax +1 216 636 0104, E-Mail kirwanj/at/ccf.org
Received January 4, 2009; Accepted August 28, 2009.
Background/Aims
The aim of this study was to assess the combined effects of exercise and dietary glycemic load on insulin resistance in older obese adults.
Methods
Eleven men and women (62 ± 2 years; 97.6 ± 4.8 kg; body mass index 33.2 ± 2.0) participated in a 12-week supervised exercise program, 5 days/week, for about 1 h/day, at 80–85% of maximum heart rate. Dietary glycemic load was calculated from dietary intake records. Insulin resistance was determined using the euglycemic (5.0 mM) hyperinsulinemic (40 mU/m2/min) clamp.
Results
The intervention improved insulin sensitivity (2.37 ± 0.37 to 3.28 ± 0.52 mg/kg/min, p < 0.004), increased VO2max (p < 0.009), and decreased body weight (p < 0.009). Despite similar caloric intakes (1,816 ± 128 vs. 1,610 ± 100 kcal/day), dietary glycemic load trended towards a decrease during the study (140 ± 10 g before, vs. 115 ± 8 g during, p < 0.04). The change in insulin sensitivity correlated with the change in glycemic load (r = 0.84, p < 0.009). Four subjects reduced their glycemic load by 61 ± 8%, and had significantly greater increases in insulin sensitivity (78 ± 11 vs. 23 ± 8%, p < 0.003), and decreases in body weight (p < 0.004) and plasma triglycerides (p < 0.04) compared to the rest of the group.
Conclusion
The data suggest that combining a low-glycemic diet with exercise may provide an alternative and more effective treatment for insulin resistance in older obese adults.
Key Words: Diabetes, Obesity, Aging, Insulin sensitivity, Physical activity, Glycemic index
Diabetes is a source of considerable health burden for our elderly population. Statistics from the United States indicate that individuals over the age of 65 currently account for approximately 40% of those with diagnosed diabetes, and the prevalence of diabetes is known to increase with advancing age [1]. Identifying effective treatment and prevention strategies is essential to address this public health burden. Exercise and dietary modifications have been broadly recommended as first-line interventions in the treatment of diabetes and insulin resistance, and the success of randomized controlled trials such as the Diabetes Prevention Program underscores the effectiveness of lifestyle changes compared to pharmacotherapy in reducing the risk of diabetes, particularly among those over the age of 60 years [2].
Diet alone has been shown to improve insulin sensitivity and the risk of type 2 diabetes; however, the composition of the diet and the precise role of carbohydrate quantity and quality remain unresolved. The glycemic index provides a means to quantify carbohydrate quality. It classifies carbohydrate foods according to the incremental plasma glucose response observed following consumption of a specific carbohydrate food relative to the glucose response observed following ingestion of an equivalent amount of a standard, either glucose or white bread [3]. The glycemic load incorporates both carbohydrate quantity and quality since it reflects the product of the glycemic index and total dietary carbohydrates. The concept that the glycemic load influences the risk of glucose intolerance, type 2 diabetes, and insulin resistance is increasingly recognized [4]. However, studies examining the effects of low- and high-glycemic diets on insulin sensitivity in humans have yielded equivocal results [5,6,7]. Kiens and Richter [7] conducted a 30-day randomized crossover high- and low-glycemic diet study on young healthy men and reported that insulin sensitivity was similar for both diets. Jarvi et al. [6] found an increase in insulin sensitivity in lean type 2 diabetics after 3 weeks on high- and low-glycemic diets. Frost et al. [5] performed a 3-week randomized trial using high- and low-glycemic diets in young women with a family history of coronary heart disease; insulin sensitivity was increased on the low-glycemic diet and decreased on the high-glycemic diet. A recent study by Philippou et al. [8] provided energy-restricted high- and low-glycemic diets to overweight/obese volunteers for 12 weeks and found that weight loss and glucose metabolism were more favorably improved following the low-glycemic diet. To date, there are no comprehensive studies on the effects of more prolonged high- or low-glycemic diets on insulin resistance in older obese adults.
On the other hand, there is a substantial literature showing a reversal of insulin resistance after exercise training [9,10,11,12,13,14]. Additional studies using a short-term exercise training model have shown that exercise-induced improvements in insulin sensitivity and responsiveness can be achieved independent of weight loss, and most likely manifest through enhanced insulin signaling and recruitment of the glucose transporter, GLUT-4 [15,16,17,18]. However, there are responders and nonresponders to these training programs, giving rise to heterogeneity in insulin responsiveness to exercise that is poorly understood. One likely source of the variation is an interaction between exercise training and diet composition. Studies that have combined acute exercise and low- or moderate-glycemic meals show enhanced exercise performance via a preference for lipid utilization and more efficient hepatic glucose regulation during exercise [19,20,21,22,23]. This suggests that a low-glycemic diet has the potential to complement exercise during long-term lifestyle interventions. In the context of the present report, there are no data on the possible interaction between these types of diets and exercise training. Herein we examine the effects of diet composition on insulin sensitivity in older obese adults who participated in a 12-week supervised exercise-training program. The working hypothesis was that the glycemic content of the diet would influence the magnitude of the exercise-induced improvement in insulin sensitivity.
Subjects
Eleven men and women (6 females, and 5 males) aged 60–75 years volunteered to participate in the study. All subjects were obese, with a mean body mass index (BMI) of 33.0. Subjects were excluded if they had any acute or chronic illnesses or used any medications that would interfere with exercising, weight loss, or carbohydrate or lipid metabolism. Women who had taken hormone replacement therapy in the 12 months preceding the study were also excluded. None of the subjects had been involved in any endurance exercise program for at least 12 months before the time of testing. Subjects in this study were part of a larger research trial examining the effects of exercise and diet on insulin resistance in older obese adults. The protocol was approved by the Institutional Review Board at MetroHealth Medical Center and all subjects provided written informed consent in accordance with guidelines for the protection of human subjects.
Study Design
The study was an intervention trial that consisted of 12 weeks of supervised exercise combined with a monitored eucaloric diet. All medical screening, physiological and metabolic tests were performed prior to the exercise intervention. Insulin sensitivity, exercise fitness and body composition measures were obtained at baseline and all testing was repeated after the 12-week program.
Exercise
The subjects participated in a treadmill test to determine their maximal oxygen consumption (VO2max) using a constant-speed (2–4 mph), incremental-grade (1.5–2.5% every 2 min) protocol. Measurements of VO2max and maximal heart rate (HRmax) were used to determine the appropriate exercise-training intensity. Exercise training consisted of walking on a treadmill and stationary cycling on a cycle ergometer. Subjects trained once a day, 5 days/week, 50–60 min/session, for 12 weeks. Initially subjects exercised at 55–60% of HRmax and were gradually increased over a 2- to 3-week period to 80–85% of HRmax. The test was repeated at 4-week intervals to adjust training intensity and to assure compliance with the prescribed training program. All of the exercise sessions were supervised by an exercise physiologist and were performed on site in the General Clinical Research Center.
Diet
Subjects were instructed on how to complete dietary records and were told to maintain their normal dietary intake throughout the study. All subjects completed 3-day food records during the baseline phase of the study, and this was repeated during weeks 3, 6, 9, and 12 of the program. Subjects met with a dietitian before and at 4-week intervals throughout the study. Dietary intake was assessed using Nutritionist Pro™ software (Axxya, Stafford, Tex., USA). Glycemic load was calculated by multiplying the glycemic index for the carbohydrate food by the amount of carbohydrate that was eaten. In order to assess the role of glycemic load, the average glycemic-load data from weeks 9 and 12 were combined and compared to data from the glycemic load reported for the preintervention baseline diets.
Euglycemic-Hyperinsulinemic Clamps
Insulin sensitivity was measured using the euglycemic-hyperinsulinemic clamp procedure as previously described [24,25]. Clamps were performed after a 10–12-hour overnight fast, and for postintervention testing, approximately 18 h after the last exercise bout. A polyethylene catheter was inserted into an antecubital vein for infusion of insulin (40 mU/m2/min) and glucose (5.0 mM glucose). A second catheter was inserted retrograde into a dorsal hand vein, which was warmed in a heated box for sampling of arterialized venous blood. Blood glucose was measured immediately using the glucose oxidase method (YSI 2300 STAT Plus, Yellow Springs, Ohio, USA). Blood samples for insulin measurements were centrifuged at 4°C, and the plasma was stored at ‒80°C for subsequent analysis by a double-antibody radioimmunoassay (RIA, Linco Research, St. Charles, Mo., USA). Blood lipids were analyzed by enzymatic analysis on an automated platform (Roche Modular Diagnostics, Indianapolis, Ind., USA). Plasma tumor necrosis factor-α concentrations were measured by ELISA (Quantikine HS; R&D Systems, Minneapolis, Minn., USA). Dietary intake and physical activity were controlled for 3 days prior to the euglycemic-hyperinsulinemic clamp procedure.
Body Composition
Body composition was determined at baseline and again after the 12-week exercise program. Height without shoes was measured to the nearest 1.0 cm. Body weight was measured to the nearest 0.1 kg. Body density was determined by hydrostatic weighing and percent body fat was estimated using the Siri equation as previously described [11].
Statistics
Data are presented as means ± SE. Differences between dependent variables were examined with a one-way ANOVA, ANCOVA, or paired Student t test. The relationship between insulin sensitivity measured during the clamp and changes in glycemic load was based on univariate and multivariate correlation analysis. The data were analyzed using the Statview II statistical package (Abacus Concepts, Berkeley, Calif., USA). The α-level for statistical significance was set at 0.05.
Subjects
Despite being obese (BMI 33.2 ± 2.0 kg/m2), the subjects were relatively healthy and all subjects were able to successfully complete the exercise-training program. Demographic data are presented in table table1.1. Subjects lost weight (p < 0.009), decreased their BMI (p < 0.009), and reduced their body fat (p < 0.01).
Table 1
Table 1
Participant characteristics
Exercise Responses to the Training Intervention
Physical fitness, based on VO2max testing indicated a significant improvement in aerobic capacity after completion of the intervention (table (table1).1). Compliance with the program, which was supervised, was excellent; subjects completed an average of 4.7 ± 0.2 sessions per week. Average heart rate during the training was 123 ± 2 bpm, which corresponds to 79 ± 1% of HRmax.
Effects of the Exercise Intervention on Insulin Resistance and Blood Measures
Insulin resistance assessed from the glucose disposal rate during euglycemic-hyperinsulinemic clamps revealed a marked improvement after the intervention (2.37 ± 0.37 to 3.28 ± 0.52 mg/kg/min, p < 0.004) for pre- and postintervention measurements, respectively (fig. (fig.1a).1a). Fasting insulin levels were also improved after the intervention (21.9 ± 3.5 vs. 16.0 ± 2.0 μU/ml, respectively, p < 0.01, table table1).1). Fasting plasma glucose and triglycerides were not significantly affected while total cholesterol was improved (table (table1).1). Likewise, plasma tumor necrosis factor-α was unchanged by exercise training (table (table1).1). Examination of the glucose clamp data revealed a notable heterogeneity in the magnitude of change in insulin sensitivity among subjects. Clearly, 4 of the 11 subjects demonstrated a more marked improvement in insulin sensitivity (78 ± 11%, fig. fig.1b)1b) compared to the rest of the group (1.53 ± 0.42 vs. 0.56 ± 0.23 mg/kg/min, p < 0.05). These subjects also demonstrated greater decreases in body weight (7.8 ± 1.5 vs. 1.6 ± 0.8 kg, p < 0.004) and plasma triglycerides (74.0 ± 29.2 vs. 7.7 ± 11.4 mg/dl, p < 0.01). We then examined the change in insulin sensitivity between these subgroups using body weight and plasma triglycerides as covariates. The change in insulin sensitivity between the subgroups continued to be significant (p < 0.01 using body weight, and p < 0.009 using triglycerides). Importantly, subjects in both subgroups were quite homogeneous in terms of phenotype, blood pressure, exercise capacity, fasting blood glucose and lipids, and baseline insulin sensitivity. The observations for the subset of high responders prompted us to search for possible explanations for their greater improvement in insulin sensitivity. One of the first factors considered was dietary intake.
Fig. 1
Fig. 1
Effects of exercise training and diet on insulin sensitivity. Eleven older, obese, and previously sedentary adults participated in a 12-week aerobic exercise-training intervention during which they were required to maintain a eucaloric diet (about 1,700 (more ...)
Dietary Intake and Glycemic Load
Subjects had been counseled at 4-week intervals by a dietitian and were requested to maintain their normal macronutrient and caloric intake throughout the study. Assessment of dietary intake based on 3-day diet records revealed an average caloric intake of 1,816 ± 128 kcal/day before the intervention versus 1,610 ± 100 kcal/day after the intervention, with 50% of macronutrients coming from carbohydrate, 34% from fat, and 19% from protein (table (table2).2). Postintervention macronutrient and calorie intakes were similar to preintervention intakes, indicating good compliance with this aspect of the study. Preintervention and postintervention sucrose intakes for the combined group were also similar (33.3 ± 7.6 vs. 32.3 ± 4.8 g/day, respectively), but while subgroup intakes were not different after the intervention (35.6 ± 6.7 vs. 28.2 ± 7.2 g/day, for the high- vs. low-glycemic load groups, respectively), the percent change in intakes tended to be lower in the low-glycemic load group (p = 0.08). Based on established glycemic indices for the reported foods, we estimated the dietary glycemic load [26]. Pre- to postintervention records indicated a 25 ± 10% reduction in glycemic load, which was marginally significant for the group as a whole (p = 0.03). However, the 4 subjects who had shown the greatest increase in insulin sensitivity contributed most of the reduction. These subjects reduced their glycemic load by 61 ± 8%, from 165.7 ± 10.0 to 104.9 ± 12.5 g (fig. (fig.2),2), without changing their macronutrient percentages or total calorie intakes.
Table 2
Table 2
Diet composition
Fig. 2
Fig. 2
Changes in glycemic load. Subjects were instructed to maintain a eucaloric diet, but 4 of the 11 independently changed their food selection such that they consumed a low-GL diet without changing their calorie intake. Data show a significant difference (more ...)
Effects of the Exercise Intervention and Dietary Glycemic Load on Insulin Resistance
In univariate analyses, the percent change in insulin sensitivity was strongly associated with the change in glycemic load (r = 0.84, p < 0.001; fig. fig.3)3) while the association with change in body weight showed a trend towards significance (r = 0.53, p = 0.09). Using a stepwise regression analysis model that included glycemic load, body weight, calorie intake, fiber intake, triglycerides, total cholesterol, and VO2max, the change in glycemic load was found to be a primary predictor of improved insulin sensitivity and explained >66% of the variance in the model (r = 81, p < 0.03).
Fig. 3
Fig. 3
Relationship between change in glycemic load and change in insulin sensitivity. Data represent the percent change in glycemic load and insulin sensitivity from baseline to the postintervention period for all 11 subjects. There was a significant correlation (more ...)
We proposed that exercise training would reduce insulin resistance in older obese adults, and that this response would be modulated by the glycemic content of the diet. After 12 weeks of aerobic exercise, obese men and women demonstrated a 47 ± 9% improvement in insulin sensitivity and reduced the glycemic load in their diet by 25 ± 10% without any significant change in energy intake. The decrease in insulin resistance correlated with the reduction in glycemic load. Additionally, those who made the greatest change in the glycemic content of their diet (decreased by 61 ± 8%) experienced significantly greater improvements in insulin sensitivity (78 ± 11%). These data suggest that insulin resistance can be reversed with a relatively short-term aerobic exercise-training program, but that the improvement in insulin sensitivity may be further enhanced by consuming a low-glycemic diet. The data point to a potential synergy between exercise and a low-glycemic diet as an integral treatment modality for insulin resistance and type 2 diabetes.
The prevalence of obesity, insulin resistance and type 2 diabetes has dramatically increased in older adults in the past 3 decades. Furthermore, diabetes is associated with excess morbidity and mortality across all age groups, but this is seen most frequently in the elderly [27]. The Diabetes Prevention Program provides some of the strongest data to support the role of exercise and diet in reducing the risk of developing type 2 diabetes [2]. A systematic lifestyle intervention was more than twice as effective as metformin in attenuating risk in those over the age of 60 years. The effect of exercise training alone on insulin sensitivity is well established in young obese and type 2 diabetic populations [9,10,12] although this observation is not universal [28]. Older subjects also show positive adaptations to exercise training, but these observations were not made in all studies [11,13,14,29,30]. Indeed, it was recently shown that nonobese older women only improved insulin sensitivity after high-intensity (about 80% VO2peak) exercise training [29]. In the present study, exercise intensity was set at a more modest level (about 70% VO2max) yet these older obese individuals showed positive adaptations demonstrating significant improvements in insulin sensitivity, increases in fitness, and decreases in body weight. The magnitude of the improvement in insulin sensitivity for the higher glycemic-load subgroup alone was approximately 28%, which compares favorably to other exercise studies that have demonstrated improved insulin sensitivity in overweight and obese adults [9,10,11,12,13,14]. However, one of the most novel observations from our current study was the superior response among 4 of the subjects who increased their insulin sensitivity by 78%, i.e. almost 3 times what is normally seen after similar exercise interventions. These ‘super-responders’ prompted us to probe for potential factors that might contribute to the greater increase in insulin sensitivity. While others have identified differences in gene expression profiles between those who respond and do not respond to exercise [31,32], we elected to examine the possibility that diet composition may have played a role.
While lifestyle interventions are now widely accepted as the first-line treatment for obesity, diabetes, and related metabolic problems, there is no consensus on the most appropriate diet composition for managing these conditions. Low-fat, high-carbohydrate diets have traditionally been the dietary recommendation of choice [33,34]. However, Hughes et al. [35] have shown that high-carbohydrate diets do not improve insulin sensitivity in older adults. However, this does not take into account that the metabolic response varies substantially between carbohydrates, as evidenced by different glycemic and insulinemic responses [3]. Diets that include carbohydrates with a low-glycemic response result in lower glucose and lipid levels when compared to high-glycemic diets [8,36,37]. While there are no long-term clinical trials examining the effects of high- or low-glycemic diets on insulin resistance or obesity in the elderly, two small clinical trials report greater weight loss utilizing a low-glycemic approach [8,38]. Studies conducted by our group observed improvements in insulin and glucose metabolism in insulin-resistant cirrhotic patients after a low-glycemic diet [39]. In addition, two epidemiological studies indicate that eating a high-glycemic diet is a significant independent predictor of diabetes risk [40,41]. These data suggest that low-glycemic diets may be more advantageous than high-glycemic diets in reducing obesity and insulin resistance. Data from the present study support these observations. While our subjects were not provided a specific diet, there is evidence that the subjects who selected lower-glycemic foods experienced greater improvements in insulin sensitivity. Importantly, this was achieved without significantly changing energy intake. While the glycemic content of the diet may not be the sole determinant of the markedly improved insulin sensitivity in these individuals, the data strongly suggest that reducing the glycemic load may provide a way to optimize the reversal of insulin resistance in obese subjects.
There are good reasons to think that the combined effect of exercise and reduced glycemic load might synergistically affect insulin resistance. Obesity, lipotoxicity, and low levels of chronic inflammation are among the factors that contribute to insulin resistance. Studies show that low-glycemic diets are highly effective in reducing body weight [8,38,42]. Likewise, exercise is effective in lowering body weight, particularly when performed at the level prescribed for the subjects in the current study [11]. Both exercise and low-glycemic diets have been shown separately to be highly effective in reducing circulating lipids, including low-density lipoproteins [38]. Exercise and low-glycemic diets have also been shown to separately reduce inflammation in obese and insulin-resistant adults [43,44,45,46]. Further support may be gleaned indirectly from studies that have combined acute exercise and low- or moderate-glycemic meals, resulting in enhanced performance and hepatic glucose regulation [19,20,21,22]. While these data suggest that the two interventions may be metabolically compatible during exercise, there are no data to show how the two might interact over an extended period of time. Compared to the rest of the study subjects, the subgroup of ‘super-responders’ in the current study reported a change in food choices that resulted in a shift from a high- to a low-glycemic diet. These subjects experienced substantial improvements in insulin sensitivity that were accompanied by greater weight loss, and greater improvements in circulating lipids, particularly triglycerides. In contrast, plasma tumor necrosis factor-α levels were similar for the main group and the subgroup after the intervention. The latter observation suggests that reversal of inflammation does not explain the improved insulin resistance, at least based on the limited evaluation of this outcome, while greater reductions in body weight and lowering of lipids may play a role and contribute to how a low-glycemic diet coupled with exercise can have such a dramatic effect on insulin resistance.
In summary, we have demonstrated that insulin resistance is reduced following 12 weeks of supervised aerobic exercise. These data also show that in a limited subset of subjects consuming a low-glycemic diet during the exercise intervention there is an even greater improvement in insulin sensitivity than when subjects maintain their normal moderate/high-glycemic diet. Such improvements in insulin sensitivity suggest a possible synergism between exercise and a low-glycemic diet that can be used to treat insulin resistance and type 2 diabetes in obese adults more effectively. Larger-scale clinical trials are needed to determine whether a lifestyle intervention that includes exercise and a low-glycemic diet is capable of effectively reducing the morbidity and mortality associated with insulin resistance and diabetes.
Acknowledgements
The authors would like to thank the research volunteers for their cooperation and compliance with the project, and are greatly appreciative of the dietary support provided by Alicia Thomas, RD in the GCRC Metabolic Kitchen. This project was sponsored by NIH grant RO1 AG12834, General Clinical Research Center grant R00080, and Diabetes Association of Greater Cleveland grant 467R01.
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