Metabolic syndrome is characterized by central obesity, elevated blood pressure, high fasting glucose and triglyceride levels, and low HDL levels. Regular physical activity can improve the metabolic profile and reduce the risks of cardiovascular diseases and premature mortality. However, the optimal training regime to treat metabolic syndrome and its associated cardiovascular abnormalities remains undefined. Forty-three participants with metabolic syndrome were randomized to one of the following groups: aerobic interval training (AIT; n = 11), strength training (ST; n = 11), a combination of AIT and ST (COM; n = 10) 3 times/wk for 12 wk, or control (n = 11). Risk factors comprising metabolic syndrome were evaluated before and after the intervention. Waist circumference (in cm) was significantly reduced after AIT [95% confidence interval (CI): −2.5 to −0.04], COM (95% CI: −2.11 to −0.63), and ST (95% CI: −2.68 to −0.84), whereas the control group had an increase in waist circumference (95% CI: 0.37–2.9). The AIT and COM groups had 11% and 10% increases in peak O2 uptake, respectively. There were 45% and 31% increases in maximal strength after ST and COM, respectively. Endothelial function, measured as flow-mediated dilatation (in %), was improved after AIT (95% CI: 0.3–3), COM (95% CI: 0.3–3), and ST (95% CI: 1.5–4.5). There were no changes in body weight, fasting plasma glucose, or HDL levels within or between the groups. In conclusion, all three training regimes have beneficial effects on physiological abnormalities associated with metabolic syndrome.
- oxygen uptake
- endothelial function
physical inactivity and being overweight are strongly associated with an increased risk for developing metabolic syndrome (31, 32). Four major components identify metabolic syndrome: central obesity, dyslipidemia, elevated blood pressure, and elevated plasma glucose levels (1, 15, 28). These major components are often associated with decreased insulin sensitivity (31), impaired endothelial function (16), unhealthy body composition (35), a prothrombotic state (28), and a low level of physical fitness (12).
In the Western world, ∼25% of young to middle-aged adults have metabolic syndrome (18, 24). There seem to be a strong age dependence in the prevalence of metabolic syndrome, but the incidence rises rapidly within adolescents and middle-aged groups and follows the development of obesity in the general population (15). Metabolic syndrome increases the risk of coronary heart disease, cardiovascular disease, and premature death (13, 21, 23); therefore, effective and affordable strategies to combat the syndrome would be of great individual and social importance.
Despite the general agreement that moderate-intensity physical activity for a minimum of 30 min for 5 days/wk or vigorous-intensity aerobic physical activity for a minimum of 20 min for 3 days/wk promote and maintain health (17), the optimal training regime to treat metabolic syndrome and its associated cardiovascular abnormalities remains uncertain. Previous studies (19, 36) have compared different aerobic training intensities in people with metabolic syndrome, but little is known about the effect of strength training (ST) versus aerobic training in this patient group. Physicians do not often recommend ST for patients with cardiovascular disease, in fear of the hemodynamic responses. However, several clinical studies (3, 33, 34) have shown that ST can improve risk factors associated with cardiovascular disease.
The aim of the present study was to evaluate the effects of aerobic interval training (AIT) versus ST and a combination of these regimes (COM) on factors comprising metabolic syndrome to find the most effective exercise regime for patients with metabolic syndrome.
MATERIALS AND METHODS
Forty-three patients (26 men and 17 women, age: 50.2 ± 9.5 yr) with metabolic syndrome were included in this study, which took place at the Norwegian University of Science and Technology in Trondheim, Norway. Metabolic syndrome was defined according to the International Diabetes Federation and comprised central obesity, elevated systolic blood pressure (SBP) and diastolic blood pressure (DBP), high plasma glucose and triglyceride levels, and low levels of HDL-cholesterol (HDL-C) (1). Patients were selected from a large pool of individuals that responded to a local advertisement asking for volunteers. Exclusion criteria included unstable angina pectoris, uncompensated heart failure, myocardial infarction during the past 4 wk, complex ventricular arrhythmias, and kidney failure. After receiving written and oral information about the experimental protocol and procedures, the participants provided written consent to participate. One person from the ST group and one person from the control group refused to complete the training. One subject from the COM group withdrew because of rheumatic pain.
Participants were randomized (stratified by sex and age) to either the AIT group (n = 11), ST group (n = 11), COM group (n = 10), or control group (n = 11). Randomization was performed using a random number generator computer program to select a random permuted block. The Applied Clinical Research Unit of the Norwegian University of Science and Technology carried out all randomization procedures to secure complete blinded randomization. The Regional Committee for Medical Research Ethics approved the study, and the study was conducted in accordance with the Declaration of Helsinki.
All participants were instructed to continue their current medications during the study. Two of the participants in this study were taking β-blockers, which are known to lower heart rate (HR). According to Chaloupka et al. (5), the percent peak HR (HRpeak) can be used to determine exercise training intensity in patients treated with β-blockers. One of the men in the control group had to increase the levels of statins 3 wk before the posttest. Baseline participant characteristics and use of medications are shown in Table 1.
Exercise groups followed a supervised training program consisting of training 3 times/wk for 12 wk. All training sessions were carefully supervised by an exercise physiologist. Participants were required to complete at least 80% of the exercise sessions. No major complications or cardiac events occurred during the study period.
The AIT group performed interval training as treadmill walking or running (self-selected). The training started with a 10-min warmup period at ∼70% of HRpeak followed by four intervals of 4 min at 90–95% of HRpeak. There was a 3-min active recovery period at ∼70% of HRpeak between each interval. Each session ended with a 5-min cooldown period, giving a total exercise time of 43 min. The AIT group performed interval training 3 times/wk.
The strength training session started with a warmup period using commercial resistance training equipment, where the participants performed 2 sets of 15–20 repetitions at ∼40–50% of one repetition maximum (1-RM). During the first week of training, the resistance was set at ∼60% of each individual's 1-RM. After the first week, the resistance training program consisted of three sets at ∼80% of 1-RM (corresponding to a maximum of 8–12 repetitions). ST consisted of two different programs including different muscle groups. The following exercises were performed twice weekly (program 1): low row, bench press, and hack lift. An alternative program was performed once each week (program 2): deltoid exercise (lateral raise exercise), triceps pulldown, biceps curl, and low-row and core exercises (plank exercise). The total exercise time was ∼40 and 50 min for programs 1 and 2, respectively. The number of repetitions and the weight used for each exercise session were recorded. The ST groups performed the training 3 times/wk.
The COM group performed AIT twice a week and ST once a week (program 1).
The control group was instructed not to change their dietary patterns or physical activity levels during the study period. After 12 wk, all control participants were offered a supervised training program at a local fitness center.
The order of the testing and protocols were identical for each patient at baseline and posttests.
Peak O2 uptake and submaximal exercise.
Peak O2 uptake (V̇o2 peak) was measured using an individualized treadmill ramp protocol. After a 10-min warmup period, belt speed and inclination were set to a constant submaximal level. O2 uptake (in ml·kg−1·min−1) and HR during the submaximal work rate were measured as reflections of work economy. After submaximal work, the belt speed was adjusted to a constant individual level, and the inclination was increased by 2% after O2 uptake stabilization at each workload. The exercise test was maintained until exhaustion. The mean of the three highest measurements was used as V̇o2 peak. HR was measured during the test (Polar type 610, Polar Electro), and the highest HR value obtained during the test was noted (HRpeak). At posttest, V̇o2 peak measurements were taken between 48 and 72 h since the last exercise bout.
Maximal strength was determined by the 1-RM in a Eurosport hack lift machine (Impulse Inray Group, Qingdao, China). 1-RM was defined as the maximal load the participant could lift through the full range of motion with knee joints at 90° for one repetition.
Resting metabolic rate.
Resting metabolic rate (RMR) was measured with indirect calorimetry (Deltatrac II metabolic monitor, Datex-Ohmeda Division, Helsinki, Finland). Participants were asked to refrain from vigorous physical activity for 96 h before the test. The determination of RMR was performed after a 12-h fast and 24 h without the consumption of alcohol or caffeine. Participants who were taking β-blockers were instructed to take their dose of medication at least 2 h before the test. Participants rested in the supine position on a comfortable bed with their head enclosed in a Plexiglas canopy for 35 min. RMR was recorded using a computerized, open-circuit, indirect calorimetric system with a ventilated canopy for the last 15 min to allow for acclimatization. The room was quiet and dimly lit. Women who were eumenorrheic were tested during the same part of the menstrual cycle at baseline and posttest.
Body weight and height were measured using a standard scale and stadiometer and set to the nearest 0.1 kg and cm, respectively. Body mass index (BMI; in kg/m2) was determined using body weight and height. Waist circumference (over the navel) was measured to the nearest 0.1 cm using a plastic tape measure. Participants rested for at least 15 min before SBP and DBP were measured using a Durashock hand-held aneroid sphygmomanometer (Welch Allyn). The average of the last two of three measurements was used to report the mean SBP and DBP.
Dual-energy X-ray absorptiometry.
Dual-energy X-ray absorptiometry scanning (HologicDiscovery-A) was used to measure fat mass, bone mineral content (BMC), and lean body mass (LBM) (29). The subjects underwent a whole body scan that gave the regional distributions of fat mass, BMC, and LBM.
The participants were asked to refrain from vigorous exercise the last 48 h before the test. After a 12-h fast, the participants arrived at the laboratory, and a blood sample was obtained from an arm vein. Serum triglycerides, glucose, HDL-C, total cholesterol, glycosylated hemoglobin (HbA1c), and C-peptide were measured immediately using standard procedures at St. Olav's University Hospital (Trondheim, Norway). The intra-assay coefficient variation for the different measurement was 4.2% for triglycerides, 2.3% for glucose, 2.1% for HDL, 2.3% for total cholesterol, 2.1% for HBA1c, and 7.1% for C-peptide. The laboratory at the hospital is under Labquality's quality system; program and quality assurances are therefore performed frequently. Citrated and EDTA-treated plasma were centrifuged at 3,000 rpm for 10 min at 4°C. Aliquots of plasma were stored at −80°C for later analysis. The homeostasis assessment model (HOMA) was used to estimated the overall insulin sensitivity (39).
Participants were asked to refrain from vigorous physical activity for 96 h before the test. Endothelial function was measured as flow-mediated dilatation (FMD) using high-resolution ultrasound (Vivid 7 system, GE Vingmed Ultrasound, Horten, Norway) according to previously described methods (7, 33). All measurements were taken at the brachial artery. Artery diameter was measured every 30 s for 2 min after the cuff release, and peak blood flow was recorded 10 s after the release. Shear rate was calculated as blood flow velocity divided by the diameter 1 min after the cuff release, as previously described (30). Because FMD is influenced by estrogen levels (11), women were evaluated during the same part of their menstrual cycle at baseline and posttest. The ultrasound images were analyzed using EchoPACtm (GE Vingmed Ultrasound).
Quality of life.
Quality of life was measured using the generic questionnaire SF-36 (26, 40) and was administered the week before and the last week of the intervention. Eight dimensions explored health using nine multiple-item scales. Only the dimensions that explored physical health (physical functioning, role limitation, general health, and health transition) were used in this study.
All four groups were ask to continue their habitually lifestyle during the intervention. Total energy and macronutrient intake were assessed using the food-frequency questionnaire previously described by Andersen et al. (2). The registration of food intake was done the week before and the last week of the intervention. The food-frequency questionnaire included questions about how often and how much was eaten of ∼180 foods and dishes.
Results are reported as means ± SD. The mean change in each group was reported as the estimated margin of the mean (EMM), as assessed by 95% confidence intervals (CI). Within-group differences were considered significantly when the 95% CI did not include zero (14). Covariance analysis, with the Bonferroni adjustment, was used to test differences between groups, with the difference/Δ-value as the dependent factor, group variable as the fixed factor, and baseline values as covariates (37). P values of <0.05 were considered significant. All statistical evaluations were performed using SPSS (version 14.0).
Endothelial function measured as FMD was improved after AIT (EMM: 2%, 95% CI: 0.3–3), COM (EMM: 2%, 95% CI: 0.3–3), and ST (EMM: 3%, 95% CI: 1.5–4.5), and there were no differences between the training groups (Fig. 1). There were no differences in shear rate (data not shown) either within or between the groups after the interventions.
Risk Factors Comprising Metabolic Syndrome
The control group had an increase in waist circumference, whereas all three training groups had a reduction in waist circumference. Only the AIT and ST groups had a reduction in waist circumference compared with the control group (P = 0.01 for both the AIT and ST groups; Table 2). There were no differences between the groups in triglycerides, HDL, or fasting glucose (Table 2). Although not significantly, the AIT group had an estimated reduction in SBP of −5.5 mmHg (95% CI: −11.4 to 0.4) and in DPB of −4.1 mmHG (95% CI: −8.3 to 0.12; Table 2), which indicated a tendency toward an effect. The estimated mean changes of the six risk factors defining metabolic syndrome are shown as a percentage of the prevalue in Fig. 2.
The AIT and ST groups had a 7% and 6% reduction in fat mass, respectively (Table 3). LBM (in kg) increased in both the control (95% CI: 0.07–1.9) and COM (95% CI: 0.36–2.41) groups. The AIT group had a small reduction in C-peptide levels (95% CI: −0.60 to −0.06; Table 3). There were no differences in weight, BMI, RMR, HbA1c, insulin sensitivity, or total cholesterol in any of the groups.
Work Economy, Maximal O2 Uptake, and Maximal Strength
There was 11% and 10% increases in V̇o2 peak after AIT and COM , respectively (Table 4). Both the AIT and COM groups improved work economy, as demonstrated by a decrease in HR (10% for both groups) and O2 consumption (15% and 10% for the AIT and COM groups, respectively) during the standardized submaximal workload (Table 4). There was a 31% increase in maximal strength in the hack lift machine after COM (EMM: 34 kg, 95% CI: 19–48), which was significant compared with the AIT group (P = 0.04). Additionally, the ST group had a 45% increase in maximal strength in the hack lift machine (EMM: 54 kg, 95% CI: 40–67), and this increase was significant compared with the change in the AIT and control groups (P < 0.01 for both; Table 4).
Questionnaires: Quality of Life and Food Registration
Health transition was increased with AIT (95% CI: 6–25) and ST (95% CI: 5–21; data not shown). There were no significant differences in general health, physical function, or role limitations after the intervention in any of the groups. Total energy intake (in kcal) and macronutrient intake did not change during the interventions for any of the groups (data not shown).
To our knowledge, this is the first clinical study to compare ST with AIT and a combination between the two training regimes (COM) in patients with established metabolic syndrome.
Previously, Katzmarzyk et al. (22) showed that aerobic exercise can be beneficial for patients with metabolic syndrome, but it has been debated whether high-intensity training (36) or moderate-intensity training (19) is more advantageous. The results from the present study support the findings of Tjønna et al. (36), who reported that high-intensity interval training is effective in improving risk factors related to metabolic syndrome. The present study also showed that ST is beneficial for people with metabolic syndrome. Furthermore, it is notable that none of the participants in the ST group experienced any problems during the training period.
Recently, there has been an increased focus on the accumulation of excess fat in the abdominal region, and it has been proposed that waist circumference is a better indicator of the risk of developing cardiovascular diseases than either BMI or the waist-to-hip ratio (8). Increased waist circumference is considered the main inclusion criteria for metabolic syndrome (according to the International Diabetes Federation), and in the present study, the AIT, ST, and COM groups had a significant reduction of waist circumference.
The AIT group had a clear tendency toward a reduction in SBP and DBP; only one person had an increase after the training period. The estimated mean reduction of ∼6 mmHg for SBP and ∼4 mmHg for DBP in the AIT group are of clinical importance, as it has been assumed that 10- and 5-mmHg decreases in SBP and DBP, respectively, could decrease the long-term risk of death by ischemic heart diseases by ∼40% (25).
The changes in HDL-C seen after exercise training are often associated with a change in body weight and/or fat mass. There were no changes in HDL-C, total cholesterol, or triglycerides in any of the groups in the present study, although the AIT and ST groups had a reduction in total body fat. According to Durstine et al. (10), almost no change in HDL-C related to exercise occurs when the exercise training program is shorter than 12 wk, but when training programs last longer than 12 wk, increased HDL-C levels are more likely to be reported. One person in the control group increased the use of statins during the study. The adjustment of medication in the control group might have influenced the result leading to lower mean levels of triglycerides and total cholesterol at posttest.
Metabolic syndrome is commonly termed as insulin resistance syndrome, and resistance to insulin-mediated glucose disposal and compensatory hyperinsulinemia are considered the central defects of the syndrome (31). The AIT group had a small estimated mean reduction in C-peptide. The initial level of C-peptide was normal, and because plasma glucose, HbA1c, and insulin sensitivity (HOMA2-S) did not change, it cannot be postulated that AIT had a significant effect on glucose metabolism. It might be that a reduction in body weight is needed to obtain a change in glucose metabolism, especially when the volume and length of the training programs is as low as in the present study (∼120 min exercise/wk for 12 wk). Our results are in line with those of Banz et al. (3), who reported that neither resistance nor aerobic training for 10 wk had an effect on fasting insulin or glucose measurements in individuals exhibiting at least two classical cardiovascular risk factors associated with metabolic syndrome. A 2001 meta-analysis (4) concluded that exercise should be viewed as beneficial on its own and not merely as an avenue to weight loss. However, many of the studies evaluated in this meta-analysis lasted longer than 12 wk, and some included a change in diet. One of the studies (9) found a change in the area under the insulin curve after 8 wk of circuit weight training but no changes in fasting glucose, insulin, or HbA1c. Thus, it might be that more than 3 exercise sessions/wk are required to see a change in glucose metabolism in this patients group after 12 wk.
It has been claimed that low aerobic capacity is a stronger predictor of cardiovascular diseases and mortality than other established risk factors (27). We found that AIT and COM significantly improved aerobic capacity, measured as submaximal HR and V̇o2 peak. According to Wisløff et al. (41), the link between reduced aerobic capacity and cardiovascular diseases might be impaired mitochondrial function. Mitochondrial function was not measured in our study. Maximal strength was increased in both the ST and COM groups. Increasing maximal strength may be important for increasing general physical activity, and a study (20) has shown that muscular strength is inversely associated with the prevalence of metabolic syndrome.
Surprisingly, ST did not increase LBM even though we aimed for muscular hypertrophy. The lack of change in LBM for the ST group is probably due to one person who had a quite large decrease in LBM. We do not have an explanation for this large decrease, but when this person was taken out of the analysis, the ST group had a significant increase in LBM. Both the COM and control group increased LBM. It is possible that the control group increased their activity unconsciously because they were made aware that they had metabolic syndrome, and, if so, this might have influenced the results. As LBM did not change with ST and AIT, increased muscle mass could not explain the reduction in total fat seen in these groups.
Results from previous studies have indicated that both ST (6) and aerobic training (36) may improve endothelial function. However, our study is the first to show that ST and AIT, as well as a combination of these, are equally effective in improving endothelial function in patients with metabolic syndrome. Our results support the findings of Vona et al. (38), who showed that exercise training, independent of the type of training, improved endothelial function (38). Because endothelial dysfunction is thought to be an important factor for developing atherosclerosis, hypertension, and cardiovascular disease, the potential reversibility of endothelial dysfunction is a clinically significant finding.
The number of patients in our study was small; therefore, larger multicenter studies are encouraged to reinforce our findings. The variation in age as well as the fact that men and women were pooled can explain the large variation in some of the results. The COM and ST groups were on more medications than the other two groups. This difference in medication use might have influenced the result by making theses groups more or less susceptible to the adaptation to training. The progressive nature could not be matched between the groups because the number of AIT and ST sessions differs between the groups. Consequently, the AIT and ST groups performed more of the specific training form than the COM group. The COM group performed AIT twice a week and ST once a week; thus, the strength components of the training was low in this study. This distribution of aerobic training and ST was believed to be the most appropriate and advantageous form of combined training when the total amount per week was three training sessions. Alternatively, we could have changed each week so that the same numbers of sessions were done for AIT and ST. Metabolic syndrome is characterized by a cluster of risk factors, but not all patients have all risk factors. In future studies, it might be informative to group the participants according to their battery of risk factors.
The present study showed that ST, AIT, and COM training have beneficial effects on physiological abnormalities associated with metabolic syndrome. There was a strong tendency toward a decrease in SBP and DBP after AIT; thus, our data may indicate that AIT for 12 wk is more effective than both ST and COM training in improving risk factors defining metabolic syndrome. The effect of longer training interventions needs to be studied in the future, especially for combination training regimes that require both resistance and aerobic adaptations.
This work was supported by the Liaison Committee between the Central Norway Regional Health Authority and the Norwegian University of Science and Technology.
The authors confirm that the manuscript has been read and approved and that they qualify for authorship. The authors report no conflicts of interest.
The authors thank Ragnhild Røsbjørgen and Trine Skoglund for excellent technical assistance.
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