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JEPonline
Effects of ExerciseIntensity on Fuel Utilization and Circulating Substrate in Dyslipidemic Men
Dussanee Wongpan1,2, Panakaporn Wannanon2,3, Nantaya Krasuaythong2,4, Yupaporn Kanpettha2,4, Sermsak Sumanont2,5, Naruemon Leelayuwat2,3
1Graduate School, Khon Kaen University, Khon Kaen, 2Exercise and Sport Sciences Development and Research Group, Khon Kaen University, Khon Kaen,3Faculty of Medicine, Khon Kaen University, Khon Kaen,4Graduate School, Khon Kaen University, Khon Kaen,5Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand
ABSTRACT
WongpanD, WannanonP, KrasuaythongN, Kanpetta Y, SumanontS, Leelayuwat N. Effects of ExerciseIntensity on Fuel Utilization and Circulating Substrate in Dyslipidemic Men.JEPonline 2018;21(2):157-171. We investigated effects of exerciseintensity on fuel selection and circulating substrate in dyslipidemic subjects. Ten men randomly cycled at 25, 65, and 85% maximum oxygen consumption for 15, 10, and 10 min, respectively, and rested for 20 min,7 days apart. Expired gas was collected 5 min before exercise and at recovery. Subjects used greater carbohydrate (CHO) and fat during exercise than at rest (P<0.05). Carbohydrate use was greater during moderate- and high-intensity exercise than at low-intensity exercise; whereas, fat was used at all intensities of exercise. Subjects relied more on fat at rest and equally during low-intensity exercise and more on CHO during higher-intensity exercise. Blood glucose concentrations were the highest during high-intensity exercise and recovery. The results suggest that dyslipidemic men relied equally on fat and CHO at low-intensity exercise and relied more on CHO than fat during higher-intensity exercise. Blood glucose concentration peaked after high-intensity exercise.
Key Words: Activity, Lipid Profiles, Substrate Oxidation
INTRODUCTION
Atherogenic dyslipidemia (lipid triad) comprises a combination of high low-density lipoprotein cholesterol (LDL-C), high triglycerides (TGs), and low levels of high-density lipoprotein cholesterol (HDL-C) (10,12). It is considered a strong risk factor for independent cardiovascular disease (21)and all-cause mortality (22). Thus, treating atherogenic dyslipidemia is necessary to reduce all-cause mortality. Also, dyslipidemia may affect substrate utilization (carbohydrate and fat) of dyslipidemic individuals. One of the factors that influence substrate utilization is substrate availability in the circulation (19). Interestingly, there are no research studies that have investigated this relationship in dyslipidemic individuals.
Given that a high fitness level is effective in increasing fat utilization, it is protective against the development of atherogenic dyslipidemia(5). Thus, an exercise training program that improveslipid profiles and substrate utilization appears essential for well-being and longevity (11). But, apparently, other studies have suggested that during exercise, circulating lipoprotein-TG may account for a small fraction of total fat oxidation in humans (25,28-30). In fact, carbohydrate (CHO) and fat oxidation rates and contribution at rest and during exercise are still unclear (3,27).In addition, crossover point (COP) occurs when contribution of CHO becomes greater than lipid (6,7), while the highest lipid oxidation point (PLipoxmax) occurs at the highestpeak of fat oxidation.
Previous studies in normolipidemia reported that Western trained subjects relied more on fat at rest and low-intensity exercise and equally at moderate-intensity. They relied more on CHO at higher intensity, thus the COP and PLipoxmaxare at moderate-intensity exercise (17,24). It has been shown that exercise intensity plays role in substrate contributions (24,29). However, our previous study with untrained Thai subjects indicated that COP and PLipoxmax were at low-intensity exercise (17). Greater fitness may be the factor that influenced the discrepancy. Therefore, the substrate utilization and contributions at rest and exercise at different intensity in Thai dyslipidemia should be investigated.
There have been no studies measuring substrate utilization and circulating substrate (blood glucose and lipoprotein-TGs) during acute exercise at three separate intensities (low-, moderate-, and high-intensity) in the same dyslipidemic subjects. Only one study, which was done with untrained hypercholesterolemic men, found unchanged or increased HDL-C and decreased TGs, depending on duration of the assessment, after a single bout of exercise at high-maximal O2 consumption (80% VO2 peak) or low- (50% VO2peak) intensity exercise (9).
The present study’s crossover research design should provide reliable results that can assist in selecting the appropriate intensity of exercise for improving substrate utilization in dyslipidemic individuals. This study aimed to explore bouts of 10 to 15min exercise due to its popularity (16) and practicality for middle-aged dyslipidemic Thai men.
Thus, the purpose of this study was to evaluate the effect of exercise intensity on substrate utilization and circulating substrate (blood glucose and lipoprotein-TGs) in Thai dyslipidemic men. We hypothesized that the subjects would have different levels of substrate utilization and circulating substrate during exercise at the three intensities.
METHODS
Study design
This study used a crossover trial design. Subjects randomly performed 3 visits, each at least 7 days apart to prevent any carryover effect. All visits involved a similar procedure outside of exercise intensity. Subjects underwent exercise intensities of 25, 65, and 85%VO2max depending on the visitfor 15, 10, and 10 min, respectively, and rested for 20 min.
Subjects
Ten healthy dyslipidemic men (age,49±6.2 yrs) from Khon Kaen Province, Thailand gave written informed consent to participate in this study. Any lipid profile abnormality qualified the men for participation in this study, such as total cholesterol (TC) concentration >240 mg·dL-1, TG concentration >200 mg·dL-1, LDL-C concentration >160 mg·dL-1, or HDL-C concentration <35 mg·dL-1. None of the subjects had been taking medication.
Before each experiment, all subjects received a routine medical examination that consisted of a medical history, anthropometric measurements (height and body composition) from Dual x-ray absorptiometry (DEXA), 12-lead electrocardiograph measurements, and blood pressure measurements. Blood samples were collected for routine blood chemistry and hematology tests, which were used for screening purposes. This study was approved by the Khon Kaen University Ethical Committee, and it conformed to the standards set by the 1964 Declaration of Helsinki (HE531276).
Procedures
VO2PeakTest
One week before the first experimental trial, the subjects’ VO2peak was measured on an electromagnetically braked cycle ergometer (Corival, Lode BV, Groningen, Netherlands) during an incremental exhaustive exercise test. On the day of the assessment of VO2peak, the gas analyzer (AD Instrument, Australia) was calibrated using gases provided by Viasys: 4% CO2, 16% O2, balance N2. The test was started at a constant speed of 60 rev·min-1 with initial workloads of 40 W. The workload was increased every 3 min by 40 Wuntil the subject was fatigued. VO2peak was reached if three of the following criteria were met: (a) VO2 reached a plateau with increased workload; (b) the respiratory gas exchange ratio was >1.15; (c) heart rate (HR) reached the estimated maximum HR (calculated using the equation 220 – age); (d) maximal symptoms of dyspnea and fatigue appeared, determined using ratings of perceived exertion (RPE)on a6 to 20 scale (4); and (e)the failure to maintain a cycling speed of 60 rev·min-1 despite encouragement. Throughout the test, HR was monitored with an oscilloscope monitor (Diascope type DS 521, Simonsen and Weel, Denmark).
Diet and Physical Activity Prior to Testing
A week before each visit, the subjects were asked to keep a diet and physical activity diary for 3 days - 2 weekdays and 1 weekend day. Dietary records were analyzed using INMUCAL software (Mahidol University, Thailand) in order to estimate daily food intake and amount of physical activity.
Experimental Protocols
For every experimental day, on the evening before each visit the subjects ingested their usual meal. At 0800 hrs after an overnight fast, the subjects arrived at the laboratory. They had abstained from smoking, caffeine, alcohol, and heavy exercise for 48 hrs before the day of the study. Upon arrival, the subjects rested in a supine position for 30 min. Then, they cycled on an ergometer at a randomly chosen intensity of 25%, 65%, or 85%VO2max for 15, 10, and 10 min,respectively,and then rested for 20 min. Exercise at each intensity was separated by at least 7 days.This design is not likely to bias our results, as there is no evidence that a single bout of exercise changes the metabolic responses to a subsequent bout of exercise performed 7 days later (2), and even chronic exercise does not have such a sustainable effect on plasma TG concentrations (1,14). An electrocardiogram was recorded throughout each visit. The ambient temperature and humidity of the laboratory were 25°Cand 48±1.8%, respectively. Twelve mL blood samples were obtained from an antecubital vein immediately before exercise, immediately, and 30 min after exercise to measure glucose, insulin, TC, TGs, HDL-C, and LDL-C. All subjects completed the full resistance and endurance exercise sessions without a problem.Expired air was collected at rest and during exercise via a mask and was analyzed using a gas analyzer (ML206; AD Instruments, Bella Vista, NSW, Australia) that had been calibrated before each trial. Expired air was used to determine VO2 (L·min-1) and carbon dioxide VCO2 (L·min-1) production rates that were used to calculate substrate oxidation rates (g·min-1) (15)
Blood Analysis
Each blood sample was divided into three parts: (a) 1 mL into a sodium fluoride tube for measurement of whole blood glucose levels; (b) 1 mL into an EDTA tube for measurement of lipid profiles; and (c) 6 mL into clotting tubes for measurement of estrogen and insulin levels. Tubes were placed on ice immediately. EDTA and clotting tubes were centrifuged at 3,000 × g for 10 min at 4°C. The upper layer was transferred to a micro centrifuge tube and stored at −80°C for analysis. Blood glucose levels were measured using a YSI 2300 Stat Plus Glucose Lactate Analyzer (USA). TC, TG, and HDL-C levels were measured using a chemistry analyzer (Beckman Synchron CX4; Beckman Coulter, Inc., Brea, CA, USA), and LDL-C was calculated using the Friedewald equation (LDL-C = TC – HDL-C – 0.20 x TG). Insulin concentrations were examined using a radioimmunoassay test-kit (MP Biomedical GmbH, Germany). All blood parameters were analyzed in a chemistry laboratory at Srinagarind Hospital.
Statistical Analyses
All data are expressed as mean ± SD unless stated otherwise. A Kolmogorov-Smirnov test was used to assess the normal distribution of changes in data. For non-time-dependent variables within each subject, a paired Student’s t test was used. Changes in the dependent variables over time and exercise intensity were compared by a two-way repeated-measures analysis of variance (ANOVA). Duncan and Scheffe’s post hoc tests were applied in cases of a significant (P<0.05) F ratio in order to locate the differences. Significant interactions were tested by using ANOVA and regression analysis. A P value less than 0.05 was considered significant, and reliability of the dependent measures was shown with intra-class correlations.
Power Calculation
A gender difference in fat oxidation rate during moderate-intensity exercise after fasting, observed in a previous study, provided a rate for calculating the sample size of the present study (17). Regarding the previous study, the fat oxidation rate was 0.32 g·min-1. To meet the requirement of 80% power at a significance level of 0.05, the calculated sample size was 8 and dropout rate was set at 20%. Therefore, completion of the study required 10 subjects.
RESULTS
Subjects’ Characteristics
All subjects were healthy excluding an abnormal lipid profile (Table 1). A week before every exercise test, the subjects showed similar energy intake and expenditure (Table 2).Target relative exercise intensities of 25, 65, and 85% VO2 peak were matched experimentally with actual averageVO2 values of 30±1.7, 63±1.8, and 85±1.7%VO2 peak,respectively.
Table 1. Anthropometry, Body Composition, and Physiology of Dyslipidemic Subjects.
Mean ± SDAge (yr) / 49±6.2
Body Mass (kg) / 67.1±11.7
% Body Fat / 28.7±7.6
Fat mass (kg) / 19.1±6.3
Lean Body Mass (kg) / 47.3±8.1
Height (m) / 167.7±2.1
BMI (kg·m-2) / 23.7±2.2
Waist Circumference (cm) / 86±8.1
Hip Circumference (cm) / 95±6.1
W/H Ratio / 0.80±1.1
SBP (mmHg) / 126±7.2
DBP (mm/Hg) / 80±13.1
MAP (mm/Hg) / 96±0.0
HR (L·min-1) / 77±1.2
HR Peak (L·min-1) / 152±17.9
VO2 Peak (mL·kg-1·min-1) / 23.0±8.7
FPG (mg·dL-1) / 84.2 ±4.13
TC (mg·dL-1) / 197.5 ±14.7
TG (mg·dL-1) / 105.4 ±33.7
HDL-C (mg·dL-1) / 53.4 ±15.2
LDL-C (mg·dL-1) / 109.9 ±29.5
Insulin (µIU·mL-1) / 13.10 ±3.05
Data are expressed as mean ± SD (N = 10 men).BMI =Body Mass Index; SBP =Systolic Blood Pressure; DBP =Diastolic Blood Pressure; MAP =Mean Arterial Blood Pressure; HR =Heart Rate; HRPeak =Peak Exercise Heart Rate; VO2 Peak =Peak Oxygen Consumption; FPG= Fasting Plasma Glucose; TC = Total Cholesterol; TG =Triglycerides;HDL-C =High Density Lipoprotein Cholesterol; LDL-C =Low Density Lipoprotein Cholesterol
Physiological and Metabolic Parameters
Heart rate, RPE, and oxygen uptake increased from resting values during exercise at low-, moderate-, and high-intensities, with the highest values being at high intensity (P<0.01 at high-intensity and P<0.05 at lower intensities) (Table 3). Similarly, energy expenditure also increased from resting values during exercise, but there was no difference between moderate-and high-intensities (Table 3).
Table 2. Dietary Composition, Total EI, and EE of Dyslipidemic Subjects.
Mean ± SDCarbohydrate (g·d-1) / 267.3±28.1
% Carbohydrate (%total EI) / 52.0±19.2
Fat (g·d-1) / 67.6±7.9
%Fat (%total EI) / 18.2±9.0
Protein (g·d-1) / 94.6±1.8
% Protein (%total EI) / 28.8±13.5
Total EI (kJ·d-1) / 7,527.0±509.1
Total EE (kJ·kg-1BM·d-1) / 7,400.8±615.5
Data are expressed as mean ± SD (N = 10 men); EI =Energy Intake; EE =Energy Expenditure
Table 3. Physiological and Metabolic Parameters at Rest and During Exercise at Different Intensities of Dyslipidemic Subjects (N = 10 men).
Intensity / Mean±SEHeart Rate (L·min-1) / Rest / 71±1.3
25% / 89±6.5*
65% / 136±7.6*@
85% / 179±6.6*@$
Rating of Perceived Exertion (RPE) / Rest / 6
25% / 7±0.6
65% / 15±0.7*@
85% / 19±0.4*@$
Oxygen Uptake (mL·kg-1·min-1) / Rest / 4.5±0.4
25% / 10.6±2.1*
65% / 21.6±1.9*@
85% / 28.45±1.9*@$
Energy Expenditure (kJ·kg-1·min-1) / Rest / 0.04±0.01
25% / 0.28 ±0.07*
65% / 0.53 ±0.02@*
85% / 0.79 ±0.04@$
*Significantly different from at rest (P<0.05); @Significantly different from during exercise at low-intensity (P<0.05);#Significantly different from carbohydrate contribution at the same condition (P<0.05); $Significantly different from moderate-intensity exercise at the same condition (P<0.05)
Interaction
There was significant interaction between intensity and time in substrate oxidation rates, substrate contribution and plasma glucose concentration (P<0.01).
Substrate Utilization
Carbohydrate oxidation rates during exercise were significantly greater than baseline values at all intensities (baseline: 0.08±0.01 g·min-1; low-intensity: 0.35 ±0.04 g·min-1; moderate-intensity: 0.84 ±0.03 g·min-1; high-intensity: 1.00 ±0.03 g·min-1, P<0.05) and showed a significant return to baseline values at recovery (0.09 ±0.01 g·min-1, P<0.05) (Figure 1A).
Fat oxidation rates during exercise were also greater than baseline values at all intensities (rest: 0.035 ±0.002 g·min-1; low-intensity: 0.12 ±0.01 g·min-1; moderate-intensity: 0.20 ±0.03 g·min-1; high-intensity: 0.22 ±0.02 g·min-1, P<0.05) and showed a significant return to baseline values at recovery (P<0.05) (Figure 1B).
Carbohydrate use was greater during moderate- and high-intensity exercise than low-intensity exercise (P<0.05); whereas, fat was used similarly during all intensities of exercise. Furthermore, the subjects relied more on fat as energy sources at rest (58 vs. 42%), equally on fat and CHO as energy sources during low-intensity exercise (52 vs. 48%) and relied more on CHO during exercise at higher intensities (carbohydrate vs. fat: 76 vs. 24% at moderate-intensity; 80 vs. 20% at high-intensity, P<0.05).
Figure 1.Carbohydrate (A) and Fat (B) Oxidation Rates Before (Baseline), Immediately (Exercise), and 20-Min After (Recovery) Exercise at Low, Moderate, and High Intensities in Dyslipidemic Subjects. The data are expressed as mean ± SE, (n = 10 men). *Significantly different from at rest (P<0.05); @Significantly different from during exercise at low-intensity (P<0.05); #Significantly different from carbohydrate contribution at the same condition (P<0.05)
Figure 2.Percent of Substrate Contribution at Rest and During Exercise at Low, Moderate, and High Intensities in Dyslipidemic Men. Data are expressed as mean (N = 10 men). *Significantly different from at rest (P<0.05); @Significantly different from during exercise at low-intensity (P<0.05); #Significantly different from carbohydrate contribution at the same condition (P<0.05)
All subjects relied similarly on fat and carbohydrate as energy sources at rest (carbohydrate vs. fat: 42 vs. 58%) and during low-intensity exercise (carbohydrate vs. fat: 52 vs. 48%) and relied more on carbohydrate during exercise at higher intensities (carbohydrate vs. fat: 76 vs. 24% at moderate-intensity; 80 vs. 20% at high-intensity, P<0.05) (Figure2).
Plasma Glucose Concentration
Immediately after high-intensity exercise and at the end of recovery from the exercise, plasma glucose concentrations were higher than during the same points at low- and moderate-intensity exercise (Table 4). Plasma glucose concentrations did not change from resting values during exercise at any of intensities.
Serum Insulin Concentration
There were no changes in serum insulin concentrations from resting values during exercise at any of the exercise intensities (Table 4).
Plasma Lipid Profile
Plasma lipid profiles showed no significant change at rest or during exercise at any intensity (Table 4).
DISCUSSION
This is the first study exploring fuel selection and circulating substrate at rest and during exercise at different intensities within dyslipidemic subjects. The major findings from this study demonstrate that dyslipidemic men use more carbohydrate and fat during all intensities of exercise than at rest. Carbohydrate utilization increased from low- to moderate- and high- intensity. In contrast, increases in fat utilization were independent of exercise intensity. Furthermore, the subjects relied more on fat at rest and equally on both substrates during low-intensity exercise and more on CHO than fat during exercise at higher intensities. Blood glucose concentrations peaked during and after the high-intensity exercise. However, lipid profiles and insulin concentrations were not altered by exercise intensity.
These results partially support our hypothesis, specifically the prediction that CHO utilization would be affected by exercise intensity. Carbohydrate utilization increased from low- to moderate- and high-intensity exercise. Although the increased CHO oxidation rate was similar between the moderate- and high-intensity exercises, the highest effort induced by the high-intensity exercise was indicated by physiological and metabolic parameters (refer to Table 3). This is comparable with the highest blood glucose concentration, which occurred immediately after high-intensity exercise and lasted at least 20 min. The role of increased gluconeogenesis resulting from increased substrate, e.g., lactate induced by high-intensity exercise, implies an increased acidity of blood during high-intensity exercise, which would increase the functions of the cardiovascular and respiratory systems (as determined by HR, VO2, and RPE). Although we did not analyze blood lactate concentration, these relationships have been well supported by previous research review (13,23).
An explanation for why carbohydrate utilization during moderate-intensity exercise was not different from high-intensity exercise may be understood in the similar total energy expenditure of both exercise intensities. The shorter duration of the high-intensity exercise relative to the moderate-intensity exercise seemed to cause a bias, which is a limitation of our study. However, we set a shorter exercise duration for the high-intensity exercise, as our subjects were middle-aged Thai men who would not be able to perform exercise at such high-intensity for a long duration, i.e., longer than 5 min. Realistically, subjects of this age do not perform exercise at this intensity.