The energy expenditure and substrate oxidation of treadmill running and cycle ergometer exercise in normal-weight and obese men

Abstract

Background

The purpose of the study was to assess energy expenditure and substrate oxidation to treadmill running (TR) and cycle ergometer (CE) exercise in normal-weight (NW) and obese (OB) men.

Methods

27 NW (BMI: 21.2 ± 1.2 kg/m²) and 25 OB (BMI: 27.2 ± 1.3 kg/m²) men were recruited in this study. Each participant completed resting metabolic rate and energy expenditure tests during the fixed absolute workloads (TR at 7 and 8 km/h and CE at 50 and 100 W) by indirect calorimetry.

Results

Gross VO₂ (L/min) was higher for OB during CE at 100 W (p < 0.05), and TR at 7 and 8 km/h (both p < 0.01), no difference was found when the values were adjusted for FFM, but lower gross (all p < 0.01) and net VO₂ (all p < 0.05) when the values were adjusted for body mass. While net energy expenditure (kcal/min) was greater for OB group during TR at 7 and 8 km/h (both p < 0.01), but similar in both groups during CE at 50 and 100 W. For CE, gross efficiency was significantly lower in OB during CE at 50 and 100 W (both p < 0.01), but no difference was found in net efficiency. A higher fat oxidation rate was found during CE at 50 and 100 W (both p < 0.05) for OB than NW. For both NW and OB subjects, fat contribution was greater during CE at 50 W than CE at 100 W (both p < 0.01). Obesity significantly affected gross and net VO₂ and fat oxidation but showed no significant main effect on CHO oxidation, however, a significant obesity × type interaction was found in CHO oxidation (F = 10.325, p = 0.002, partial η² = 0.171). While exercise type and intensity appear to have a significant effect on CHO oxidation (with type × intensity interaction), only exercise type appears to have a significant effect on fat oxidation (without interaction with intensity).

Conclusions

These findings suggested that OB showed the higher energy cost than NW during CE at higher intensity and TR. CE without weight burden resulted in a greater fat oxidation rate and higher fat oxidation contribution in OB than NW. For cycling, net efficiency does not differ between NW and OB subjects. Exercise type and intensity are both factors influencing substrate oxidation during exercise. It is concluded that the exercise type and intensity have to be taken into account when prescribing for obese subjects. Future studies should apply equal relative physiological intensities to interpret the energy expenditure and substrate oxidation differences between normal and obese subjects.

Introduction

The increasing trend in obesity has become a public health issue in China and throughout the world [1, 2]. Obesity is associated with cardiovascular diseases, type 2 diabetes mellitus, metabolic diseases, and cancer, leading to an increased risk of death [3–5]. The critical driver of obesity is an imbalance between energy intake and energy expenditure. Physical activity and exercise play an important role in managing and losing weight [6–8]. However, many studies revealed that one of the most important contributors to the maintenance of obesity is that obese individuals tend to have more sedentary behavior or insufficient PA [9, 10]. Effective weight management requires an accurate exercise prescription of exercise type and intensity, energy expenditure, and substrate metabolism during exercise, and mechanical efficiency characteristics for obese populations.

While treadmills and cycle ergometer exercises are popular, convenient, and relatively safe types of exercise, these two modes are commonly used in exercise testing and clinical settings. There is a fundamental difference between these two modes of exercise, cycling is a weight-independent exercise and not influenced by balance and gait issues, which can easily be performed by most people; while treadmill running is weight-dependent and influenced by balance and gait. Several differences in physiological responses to treadmill exercise and cycle ergometer exercise are investigated in normal weight subjects [11, 12], and few in overweight and obese individuals [13], and rarely including comparison between treadmill running and cycle ergometer exercise.

In addition, the gross energy cost and net energy cost have been found to be higher in obese individuals during different movements by several researchers [13–15], due to the effect of the greater body mass involved in the physical activity [13, 16] or a lower mechanical efficiency [17, 18]. Nevertheless, the difference between obese and normal-weight subjects is greatly reduced when the metabolic rate is adjusted for total body weight [19], which suggests that total body weight may play a role in the energy cost of physical activity. The greater body mass may lead to the reduction of the exercise effectiveness in weight loss programs, further contributing to the maintenance of obesity.

It is well known that the dominant fuels oxidized during exercise are carbohydrates (CHO) and free fatty acids, and that the CHO contribution and fat contribution are influenced by exercise type, intensity, as well as duration [20, 21]. Maunder et al. showed that obese subjects were found to perform lower maximal rates of fat oxidation during exercise than that of lean counterparts [22]. Previous studies have shown that [23, 24] fat utilization rate is maximal during low intensity exercise (lower than 50%VO_2MAX) in untrained subjects. Therefore, how to achieve the maximal fat oxidation is also important in the process of body weight management in obesity.

Consequently, it is necessary to understand the differences and the degree of differences of physiological response and energy expenditure in different exercises in obese subjects and normal-weight subjects, which is important for appropriate exercise prescriptions or PA programs for obese subjects. The primary purpose of this study was to compare the energy metabolism (energy cost and substrate oxidation) between normal-weight and obese men. A secondary purpose of this study was to determine the characteristics of energy metabolism during treadmill running and cycle ergometer to provide guidance in the exercise programs or PA prescriptions in clinical for obesity.

Materials and methods

Experimental approach to the problem

To analyze the effects of obesity, exercise type, and intensity on energy expenditure and substrate oxidation, two groups (normal-weight and obese subjects) were recruited. All participants underwent anthropometric data collection, RMR at rest, and energy expenditure testing during CE (50 and 100 W) and TR (7 and 8 km/h). The gross and net metabolic rate, substrate oxidation, and gross and net efficiency data during the same exercise type and intensity were compared between NW and OB groups to identify the effect of obesity on energy expenditure. The gross and net metabolic rate, substrate oxidation, and gross and net efficiency during different exercise types and intensities were compared in NW and OB to identify the effect of exercise type and intensity on energy expenditure.

Subjects

27 Normal-weight (age: 28.3 ± 2.3 years, BMI: 21.2 ± 1.2 kg/m²) and 25 obese men (age: 28.9 ± 2.1 years, BMI: 27.2 ± 1.3 kg/m²) participated in this study. The total sample size needed using power analysis was 73, taking into account the effect size (0.5) seen in similar studies. We recruited 64 male subjects in total, however, 5 normal and 7 obese did not complete all tests. Specifically, 4 obese and 3 normal participants were unable to perform treadmill running due to insufficient treadmill experience and movement adaptation; 2 additional obese participants could not finish the prescribed treadmill running at 8 km/h owing to difficulty tolerating the fixed absolute running workload; and 3 participants (1 obese, 2 normal) withdrew voluntarily during testing due to acute physical discomfort during all exercises. No participants dropped out during the cycling trials. All participants were healthy, free of cardiovascular, respiratory, and metabolic diseases and did not have regular physical activity in daily life that could affect their energy metabolism. Inclusion criteria for obese subjects were BMI ≥ 25 kg/m² and 18.5–23 kg/m² for NW subjects (participants were screened using a threshold of BMI ≥ 23 kg/m²; no participants with BMI 23.0–24.9 kg/m² were enrolled, yielding an effective analytical OB threshold of BMI ≥ 25.0 kg/m²), which were in accordance with the WHO classification for Asians [25]. The physical characteristics of all subjects (Mean ± SD) are shown in Table 1.

Table 1.

Physical characteristics of normal-weight and obese subjects

	NW (n = 27)	OB (n = 25)
Age (years)	28.3 ± 2.3	28.9 ± 2.1
Height (cm)	174.2 ± 5.0	174.3 ± 6.5
Weight (kg)	64.3 ± 4.8**	82.8 ± 7.4
BMI (kg/m2)	21.2 ± 1.2**	27.2 ± 1.3
Body Fat Percentage (%)	16.8 ± 2.5**	26.8 ± 4.4
RMR (kcal/day)	1877.1 ± 258.1**	2185.0 ± 226.9

BMI Body Mass Index, RMR Resting Metabolic Rate

^∗∗p <0.01

Procedures

All measurements were performed during May to July 2022. All subjects were asked to arrive at the laboratory in a fasted state before 8:00 am on the test day. Before the exercise energy expenditure measurements, every participant underwent anthropometric measurements and Resting Metabolic Rate (RMR) measurements. All testers involved in this study received professional training, and each test project was independently completed by the same tester. All participants were asked to wear the same comfortable clothes and shoes during each testing session and were encouraged to complete all exercise tests.

Anthropometric measures

Standing height (m) and body mass (kg) were assessed according to international standards for anthropometric assessment. To evaluate height and body mass, the Su Heng Health Scale (RGZ-120, Jiangsu, China) with precisions of 0.1 cm and 0.1 kg were used, respectively. The BMI was calculated (kg/m²). A bioelectrical impedance analysis composition analyzer (Inbody 770, Biospace Corp., Korea) was used to determine body composition.

RMR measurement

After the anthropometric measurements, participants rested supine for 10 min prior to RMR data collection. Steady-state RMR was measured by using indirect calorimetry (Cortex Metamax 3B-R2 metabolic system, Germany) in the supine position for 30 min in a semi-darkened, quiet and controlled environment temperature (22–25 ℃) and humidity (40–50%) room. Based on the data from each experimental condition, we confirm that the mean RER values consistently remained at or below 1.00 (RER ≤ 1.00) throughout the steady‑state measurement period. Therefore, the assumption for applying non‑protein respiratory quotient equations to calculate substrate oxidation rates (i.e., no net lactate buffering contribution to CO₂ production) is satisfied for all conditions included in the analysis. Any trial showing an RER > 1.00 was excluded from substrate oxidation calculations. The RMR was calculated by using the VO₂ and VCO₂ of the steady periods for about 20 min according to the Weir [26] formula.

Exercise energy-expenditure tests

Measures of exercise energy metabolic rate were performed during TR (7 and 8 km/h) (Rodby RL3500E, Sweden) and CE exercise (50 and 100 W) (Wattbike, England), maintained for 6 min each exercise, by indirect calorimetry (Cortex Metamax 3B-R2 metabolic system, Germany). The system (Cortex Metamax 3B-R2, Germany) was calibrated before each test with standard gases of known oxygen and carbon dioxide concentration. An initial steady state at 5 km/h and 20 W for 3 min was allowed for warming. The treadmill and ergometer were set to operate at a constant speed of 7 and 8 km/h with 0% gradient and power of 50 and 100 Watts at the cadence of 60 rpm, respectively. The participants were instructed to perform these exercises according to the workloads of treadmill and ergometer. The saddle and hand bar positions during the ergometer exercise were individually adjusted. Participants were not permitted to hold handrails during all treadmill running. Heart rate (HR) was continuously monitored by a wireless heart rate (HR) monitor (Polar H7, Finland). Each exercise test was performed in a randomized order and separated by rest between trials until their HR recovered to a level ± 5% of their resting HRs (average 8–10 min). Gross VO₂ and VCO₂ output were measured breath-by-breath and averaged over the last 3 steady-state minutes of each test. To identify the presence of steady-state, linear regression of VO₂ over time was performed using data from the final three minutes of each exercise bout. Any session in which the resulting beta coefficient yielded a positive (β > 0) and statistically significant slope (p < 0.05) was subsequently excluded from data analysis. Maximal HR was calculated by equation HR_max= 220-age(yr). The net metabolic rate was obtained by subtracting the resting metabolic rate from the gross metabolic rate. Fat and CHO oxidation were calculated from VO₂ and VCO₂ according to equations assuming a nonprotein respiratory quotient. CHO and fat oxidation contributions were estimated by using the following formulas [27]:

Mechanical efficiency during CE at different workloads was calculated as gross efficiency and net efficiency as defined by Gaesser and Brooks [28].

Statistical analyses

Statistical analysis was performed by using SPSS software version 27.0 (IBM Corp., Armonk, NY, USA). All data are presented as mean ± SD. Data were checked for normality using the Kolmogorov-Smirnov test. Differences between NW and OB subjects (group differences) in physical characteristics and energy expenditure data were investigated using independent Student’s t tests. To control the false discovery rate (FDR) for the all-independent t-tests, we applied the Benjamini‑Hochberg procedure with an FDR of 0.05. Only comparisons with a Benjamini‑Hochberg adjusted q‑value < 0.05 were considered statistically significant. A repeated measure ANOVA was used to examine how obesity, different exercise type and exercise intensity affected gross VO₂, net VO₂, CHO and fat oxidation rate. Effect size was estimated for main effects and interaction by calculating partial eta squared (η²) values. Effect size for comparisons between NW and OB was assessed with Cohen’s d using the pooled standard deviation of the two means compared. Effect sizes were classified as small (0.2), medium (0.5) and large (≥ 0.8). For all tests, the significance level was set at p < 0.05.

Results

Table 2 shows the cardiorespiratory and energy expenditure data of NW and OB groups during cycle ergometer exercise and treadmill running. Gross VO₂ (L/min) and Net VO₂ (L/min) during CE 50 were similar between two groups (both p > 0.05); gross VO₂ (L/min) and gross energy expenditure (kcal/min) of OB during cycle ergometer at 100 W, treadmill running at 7 and 8 km/h were greater than those of the NW group (both p < 0.05, both p < 0.01, both p < 0.01) respectively, whereas no statistically significant difference in HR and RER was detected between the two groups during any exercise. Furthermore, normalization of VO₂ to body weight (ml/kg/min) resulted in obese subjects having a lower gross (all p < 0.01) and net metabolic rates (all p < 0.05) compared to normal-weight subjects during all exercises. However, when this data is evaluated to amount of FFM, no differences can be distinguished between two groups. The net VO₂ (L/min) (Table 2), and energy expenditure (kcal/min) (Fig. 1B) were greater for the OB group in treadmill running at 7 and 8 km/h compared with their normal-weight counterparts (both p < 0.01). However, there were no significant differences in net VO₂ (L/min) (Table 2) and net energy expenditure (kcal/min) (Fig. 1B) in the cycle ergometer at 50 and 100 W between the NW and OB groups, indicating that the body-weight involved in running movements may be responsible for the higher energy cost for OB subjects. The HR, gross VO₂ (L/min), net VO₂ (L/min), gross and net VO₂ (ml/kg/min), gross and net VO₂ (ml/kg FFM/min), and gross and net energy expenditure (kcal/min) increased with increasing power output from 50 to 100 W and running speed from 7 to 8 km/h in both NW and OB groups (Fig. 1). Intensity and type of exercise both have a significant effect on the HR, gross and net VO₂ (L/min), gross and net VO₂ (ml/kg/min), gross and net VO₂ (ml/kg FFM/min), and gross and net energy expenditure (kcal/min) in the NW and OB groups.

Table 2.

Cardiorespiratory and energy expenditure (EE) data of normal-weight and obese subjects

		NW (n = 27)	OB (n = 25)	Cohen’s d	95% CI
Cycle ergometer at 50 W	HR (b/min)	120.1 ± 15.8aa	120.3 ± 17.5bb	-0.01	-0.552 to 0.536
	Intensity (%HRmax)	62.7 ± 8.1aa	62.9 ± 9.0bb	-0.03	-0.574 to 0.514
	Gross VO2 (L/min)	1.07 ± 0.15aa	1.15 ± 0.16bb	-0.54	-1.090 to 0.018
	Net VO2 (L/min)	0.79 ± 0.15aa	0.84 ± 0.15bb	-0.24	-0.788 to 0.304
	RER	0.832 ± 0.064aa	0.805 ± 0.05bb	0.47	-0.081 to 1.023
	Gross VO2 (ml/kg/min)	16.6 ± 2.0**aa	14.0 ± 2.4bb	1.20	0.599 to 1.784
	Gross VO2 (ml/kg FFM/min)	20.0 ± 2.7aa	19.2 ± 3.7bb	0.26	-0.291 to 0.802
	Net VO2 (ml/kg/min)	12.4 ± 2.1**aa	10.2 ± 2.2bb	1.06	0.472 to 1.636
	Net VO2 (ml/kg FFM/min)	15.0 ± 2.8aa	14.0 ± 3.3bb	0.33	-0.217 to 0.878
Cycle ergometer at 100 W	HR (b/min)	141.5 ± 20.3	137.0 ± 17.5	0.24	-0.311 to 0.781
	Intensity (%HRmax)	73.8 ± 10.5	71.7 ± 9.2	0.21	-0.333 to 0.758
	Gross VO2 (L/min)	1.59 ± 0.18*	1.71 ± 0.18	-0.64	-1.189 to -0.074
	Net VO2 (L/min)	1.32 ± 0.18	1.39 ± 0.18	-0.39	-0.938 to 0.161
	RER	0.897 ± 0.065	0.864 ± 0.064	0.52	-0.038 to 1.069
	Gross VO2 (ml/kg/min)	24.9 ± 3.2**	20.8 ± 2.9	1.35	0.740 to 1.949
	Gross VO2 (ml/kg FFM/min)	29.9 ± 4.0	28.5 ± 4.6	0.33	-0.220 to 0.876
	Net VO2 (ml/kg/min)	20.7 ± 3.2**	16.9 ± 2.7	1.25	0.652 to 1.845
	Net VO2 (ml/kg FFM/min)	24.9 ± 4.1	23.2 ± 4.2	0.39	-0.161 to 0.938
Treadmill running at 7 km/h	HR (b/min)	147.5 ± 21.3cc	151.4 ± 16.0dd	-0.21	-0.749 to 0.341
	Intensity (%HRmax)	76.9 ± 11.0cc	79.2 ± 8.4dd	-0.23	-0.775 to 0.317
	Gross VO2 (L/min)	1.84 ± 0.17**cc	2.19 ± 0.22dd	-1.79	-2.432 to -1.138
	Net VO2 (L/min)	1.57 ± 0.17**cc	1.87 ± 0.21dd	-1.58	-2.200 to -0.949
	RER	0.843 ± 0.069	0.846 ± 0.051	-0.05	-0.594 to 0.494
	Gross VO2 (ml/kg/min)	28.7 ± 2.9**cc	26.5 ± 2.2dd	0.88	0.303 to 1.443
	Gross VO2 (ml/kg FFM/min)	34.6 ± 3.7cc	36.3 ± 3.8dd	-0.45	-1.002 to 0.101
	Net VO2 (ml/kg/min)	24.5 ± 3.0*cc	22.7 ± 2.1dd	0.74	0.169 to 1.294
	Net VO2 (ml/kg FFM/min)	29.6 ± 3.8cc	31.1 ± 3.4dd	-0.41	-0.962 to 0.138
Treadmill running at 8 km/h	HR (b/min)	155.5 ± 20.2	159.4 ± 17.1	-0.21	-0.751 to 0.340
	Intensity (%HRmax)	81.1 ± 10.5	83.4 ± 9.0	-0.23	-0.777 to 0.315
	Gross VO2 (L/min)	2.02 ± 0.24**	2.40 ± 0.20	-1.72	-2.357 to -1.077
	Net VO2 (L/min)	1.76 ± 0.25**	2.09 ± 0.19	-1.5	-2.114 to -0.877
	RER	0.847 ± 0.057	0.852 ± 0.057	-0.08	-0.625 to 0.464
	Gross VO2 (ml/kg/min)	31.6 ± 3.8**	29.1 ± 2.3	0.77	0.200 to 1.329
	Gross VO2 (ml/kg FFM/min)	38.0 ± 5.0	39.9 ± 4.3	-0.41	-0.956 to 0.144
	Net VO2 (ml/kg/min)	27.4 ± 4.0*	25.3 ± 2.2	0.64	0.080 to 1.196
	Net VO2 (ml/kg FFM/min)	33.3 ± 5.2	34.7 ± 3.9	-0.37	-0.919 to 0.179

^*p < 0.05 compared with the same data between NW and OB; ^**p < 0.01 compared with the same data between NW and OB; ^aa p < 0.01 CE at 50 vs. 100 W in NW group; ^bb p < 0.01 CE at 50 vs. 100 W in OB group; ^cc p < 0.01 TR at 7 vs. 8 km/h in NW group; ^dd p < 0.01 TR at 7 vs. 8 km/h in OB group

Fig. 1.

Gross (Figure A) and net (Figure B) energy expenditure during cycle ergometer exercise and treadmill running in NW and OB subjects. ^*p < 0.05 compared with the same data between NW and OB; ^**p < 0.01 compared with the same data between NW and OB; ^aa p < 0.01 CE at 50 vs. 100 W in NW group; ^bb p < 0.01 CE at 50 vs. 100 W in OB group; ^cc p < 0.01 TR at 7 vs. 8 km/h in NW group; ^dd p < 0.01 TR at 7 vs. 8 km/h in OB group

The results of the repeated-measures ANOVA are shown in Table 3 for the energy expenditure data and substrate oxidation. Obesity has significant effects on gross and net VO₂ (F = 22.771, p < 0.001, partial η² = 0.313; F = 17.42, p < 0.001, partial η² = 0.258), and fat oxidation rate (F = 4.355, p = 0.042, partial η² = 0.08). However, obesity does not appear to have a significant effect on CHO oxidation rate, a significant obesity × type interaction was detected for CHO oxidation rate (F = 10.325, p = 0.002, partial η² = 0.171). While exercise type and intensity both appear to have a significant effect on gross and net VO₂ (F = 800.628, p < 0.001, partial η² = 0.941; F = 383.042, p < 0.001, partial η² = 0.885) and CHO oxidation rate (F = 48.047, p < 0.001, partial η² = 0.49; F = 114.781, p < 0.001, partial η² = 0.697), exercise type and intensity exhibit a significant interactive effect on gross VO₂ and CHO oxidation rate (F = 129.071, p < 0.001, partial η² = 0.721; F = 41.765, p < 0.001, partial η² = 0.455). Furthermore, only exercise type seems to have a significant effect on fat oxidation rate (F = 86.353, p < 0.001, partial η² = 0.633; without any interactions with other factors).

Table 3.

Effect of obesity, exercise type and intensity on energy expenditure and substrate oxidation

	df	Error df	F-ratio	p	partial η²
Gross VO2 (ml/kg/min)
Between subjects
Obesity	1	50	22.771	< 0.001	0.313
Within subjects
Exercise type	1	50	800.628	< 0.001	0.941
Exercise intensity	1	50	383.042	< 0.001	0.885
Type×intensity	1	50	129.071	< 0.001	0.721
Obesity×type	1	50	2.112	0.152	0.041
Obesity×intensity	1	50	2.509	0.12	0.048
Obesity×type×intensity	1	50	2.229	0.142	0.043
Net VO2 (ml/kg/min)
Between subjects
Obesity	1	50	17.42	< 0.001	0.258
Within subjects
Exercise type	1	50	800.628	< 0.001	0.941
Exercise intensity	1	50	383.042	< 0.001	0.885
Type×intensity	1	50	129.071	< 0.001	0.721
Obesity×type	1	50	2.112	0.152	0.041
Obesity×intensity	1	50	2.509	0.12	0.048
Obesity×type×intensity	1	50	2.229	0.142	0.043
Fat oxidation rate (g/min)
Between subjects
Obesity	1	50	4.355	0.042	0.08
Within subjects
Exercise type	1	50	86.353	< 0.001	0.633
Exercise intensity	1	50	0.637	0.429	0.013
Type×intensity	1	50	1.747	0.192	0.034
Obesity×type	1	50	0.186	0.668	0.004
Obesity×intensity	1	50	0.517	0.475	0.01
Obesity×type×intensity	1	50	0.527	0.471	0.01
CHO oxidation rate (g/min)
Between subjects
Obesity	1	50	0.353	0.555	0.007
Within subjects
Exercise type	1	50	48.047	< 0.001	0.49
Exercise intensity	1	50	114.781	< 0.001	0.697
Type×intensity	1	50	41.765	< 0.001	0.455
Obesity×type	1	50	10.325	0.002	0.171
Obesity×intensity	1	50	0.007	0.934	0.0001
Obesity×type×intensity	1	50	0.341	0.562	0.007

Figure 2 shows the substrate oxidation during cycle ergometer exercise and treadmill running. The OB participants showed a significantly greater fat utilization rate during cycle ergometer exercise at 50 and 100 W (both p < 0.05) than the NW participants. CHO oxidation rate increased significantly with increasing power output in both NW and OB participants (both p < 0.01), but CHO oxidation rate increased significantly with increasing running speed only in OB participants (p < 0.01).

Fig. 2.

Fat oxidation (Figure A) and CHO oxidation (Figure B) during cycle ergometer exercise and treadmill running in NW and OB subjects. *p < 0.05 compared with the same data between NW and OB; ^aa p < 0.01 CE at 50 vs. 100 W in NW group; ^bb p < 0.01 CE at 50 vs. 100 W in OB group; ^cc p < 0.01 TR at 7 vs. 8 km/h in OB group

Figure 3 shows the fat and carbohydrate (CHO) contribution during cycle ergometer exercise and treadmill running. For both NW and OB subjects, fat contribution (%) was greater during CE exercise at 50 W than CE exercise at 100 W. There was no significant difference in fat contribution (%) between TR at 7 and 8 km/h for both NW and OB subjects. There was no significant difference in CHO contribution (%) between NW and OB subjects for any exercise.

Fig. 3.

Fat and carbohydrate (CHO) contribution during cycle ergometer exercise and treadmill running in NW and OB subjects. ^aa p < 0.01 CE at 50 vs. 100 W in NW group; ^bb p < 0.01 CE at 50 vs. 100 W in OB group

Figure 4 shows the gross efficiency and net efficiency during cycle ergometer exercise for NW and OB subjects. Gross efficiency for CE at 50 and 100 W was significantly higher in the NW group compared to the OB group (both p < 0.05) (Fig. 4A). Net efficiency for CE at 50 and 100 W did not differ between groups (both p > 0.05) (Fig. 4B).

Fig. 4.

Gross efficiency (Figure A) and net efficiency (Figure B) during cycle ergometer exercise in NW and OB subjects. ^*p < 0.05 compared with the same data between NW and OB

Discussion

The main findings from the present study demonstrated that obese subjects exhibited a higher gross metabolic rate (L/min) during CE 100 W and TR exercises than normal-weight individuals, which is in agreement with most findings in different types of exercise [13, 29]. Previous studies have indicated that total body weight is the primary determinant of the energy cost of physical activity and that exercise could be more expensive for obese due to the more body fat carried during exercise [19, 30]. The results of this study also showed that when gross and net metabolic rates were expressed per unit of FFM, OB subjects presented similar values to NW subjects in all CE and TR exercises; when gross and net metabolic rates were expressed per unit of body weight, OB subjects presented lower values than NW subjects in all CE and TR exercises. DeLany et al. [31] indicated a lower activity energy expenditure per body weight in obese individuals and Elbelt et al. [32] showed a lower body weight-adjusted activity energy expenditure in higher degrees of obesity, which is consistent with our findings. However, there are several studies suggesting that obese have a higher relative net metabolic rate (ml/kg/min) for treadmill walking than normal-weight adults [19, 33]. Primavesi et al. [34] suggested that the energy cost and mechanics of walking appear to be affected by the class of obesity. The OB subjects in this study were in a BMI range of greater than 24.9, and were obese class I (with a mean BMI of 27.2) according to the WHO Asian classification [25]. Therefore, it is possible that the differences in activity energy expenditure were reduced due to the obesity levels. The similar results (no differences between the NW and OB participants) in values of activity energy expenditure expressed per unit of body weight (kg) were reported by LeCheminant et al. [35].

Lafortuna et al. [13] have found that the net metabolic rate was higher in OB than NW during both treadmill walking and cycle ergometer exercise, which differed from our results showing that the net energy expenditure (kcal/min) was higher for the OB group during TR rather than CE exercise. Several studies have suggested that subjects perform more complex movement work involving many body segments during treadmill exercise than during cycling, which mainly uses the legs, leading to differences in workload and movement patterns between the two exercise modes [36, 37]. This would explain that when subtracting the RMR, the net energy expenditure of TR exercise appeared significantly different between OB and NW subjects, since CE exercise is a non-weight-bearing activity. Additionally, the present study supports existing studies that the mode and intensity of exercise significantly influence the cardiovascular response [13, 38], gross energy expenditure, and net energy expenditure [13, 39] for obese and normal-weight individuals.

Fat oxidation is important in the prevention and treatment of obesity and is influenced by exercise intensity [21, 40]. Different from the finding of lower fat oxidation rate in OB [22], the present study found that exercise at a lower intensity (CE 50 W, 63%HR_max) resulted in a higher fat oxidation rate in OB than NW subjects. One possible explanation was that short duration low-intensity exercise triggered more plasma free fatty acids oxidation of OB than NW [40]. Besides that, we found a greater fat oxidation contribution in OB and NW subjects during intensities of CE at 50 W and 100 W. Consistent with our hypotheses, obesity served as an independent physiological determinant of both gross and net VO₂ and fat oxidation rate, indicating that body composition status fundamentally alters whole-body oxygen utilization and metabolic responses during exercise. Bogdanis et al. [23] found that peak fat oxidation was observed in overweight men and women at the intensity of lower than 40% VO_2max. Lefai et al. found that 8 weeks (1 h of cycling per session, 4 times per week) low-intensity cycling improved fat oxidation by ~ 30% in overweight and obese adults [41]. Van Aggel-Leijssen et al. [42] have shown that a high-intensity training with about 70% VO_2max did not affect fat oxidation during exercise. Interestingly, our study found that only exercise type has a significant effect on fat oxidation without interactions with exercise intensity. Several findings suggest that training ≥ 65%VO_2max will not increase fat oxidation potential [43], one might predict that the intensities of CE at 100 W and TR at 7 and 8 km/h all exceed 70% of HRmax, no significant effects of exercise intensity on fat oxidation were found consequently.

Interestingly, obesity does not appear to have a significant effect on CHO oxidation. However, a significant obesity × type interaction effect was found on CHO oxidation, which is driven by the results that CHO oxidation increased significantly with running speed in OB participants but not in NW participants, whereas no analogous group asymmetry is present for cycling conditions. It indicates that between-group differences in carbohydrate utilization were dependent on exercise type. Several possible reasons have been suggested to explain the different oxidation rates during different exercise types are related to the specific type of muscle activation patterns, lower limb loading magnitudes and metabolic strain [44–45]. First, the elevated carbohydrate oxidation with increasing running speed only in obese participants is primarily attributed to high lower limb loading induced type‑II‑fiber recruitment and impaired oxidative function of type‑I fibers caused by accumulated intermuscular adipose tissue in obese individuals [44]. Second, the seated posture during cycling reduces mechanical stress and improves peripheral perfusion, resulting in comparable carbohydrate‑oxidation responses across two groups. Additionally, the magnitude of changes in gross VO₂ and CHO oxidation rate induced by exercise intensity was also type-dependent, indicating that exercise type reshapes the intensity–metabolism dose–response relationship for carbohydrate utilization and gross oxygen cost. The key point we could get from previous studies and the present study is that when we make an exercise prescription for obesity, the exercise type is a key factor we need to consider to achieve the greater fat oxidation. Moreover, we could select a relatively lower exercise intensity with a longer time rather than a high exercise intensity with a shorter time to the same energy expenditure goal because relatively lower exercise intensities facilitate a higher proportionate fat contribution for satisfying lower energy demands.

Several studies have suggested that gross efficiency seems to be the best indicator for mechanical efficiency and net efficiency seems to describe how well individual has adapted to a cycling movement [46]. Normal-weight subjects appeared to have a higher gross cycling efficiency than obese subjects. Several studies have shown that obese subjects appear to have a lower mechanical efficiency [17, 18], which is generally consistent with our findings. When exercising at lower intensities, the proportion of energy required for basal metabolism is relatively higher than at higher intensities, resulting in lower gross efficiency [47], and oxygen consumption was greater in obese than in lean counterparts, resulting in lower efficiency in obese subjects [48]. Chen et al. found that there was a negative correlation between the efficiency of walking and body fatness [49], meaning that the more body fat, the lower the gross efficiency. Our results also indicate that net efficiency was not impaired during CE in OB subjects. Thus, we can speculate that obesity may not contribute to reduce the muscular efficiency and change adaption to CE while exercising. Rosenbaum et al. reported that work efficiency during cycle ergometry could be predicted by weight change [50]. Consequently, we can speculate that weight change or fat change could not be associated with net efficiency.

Considering that exercise and PA are one of key means to treat obesity and to make exercise prescription more scientific, effective, and targeted for obese individuals, more research should be done on the effects of age, sex, and obesity class on the energy cost and mechanics of more different exercise modes with different exercise intensities and characteristics.

Practical applications

This study shows that obesity appears to have a significant effect on energy cost and fat substrate oxidation. Based on cardiovascular responses and metabolic measurements obtained from our study, low-power cycling presents distinct short-term substrate metabolism characteristics in OB during exercise. The results suggest that cycling with less physical burden at a low power output may promote high rates and more contribution of fat oxidation for OB than NW subjects. However, these observations are limited exclusively to acute physiological responses under laboratory conditions. No longitudinal data are available to support long-term weight management or fat loss effects. Future longitudinal studies are warranted to systematically explore the long-term efficacy and clinical value of relevant exercise prescriptions for weight management and fat loss.

Strengths and limitations of the study

Treadmill running and cycle ergometer are two common exercise modalities used for exercise and leisure. Though several researches have reported physiological responses to these two exercise modalities, few focused on obese group and energy expenditure comparison between the TR and CE. To our knowledge, this is among the first study to report population-specific data in a young Chinese male cohort, and make energy cost and substrate oxidation comparison between TR and CE for NW and OB, which is important in exploring the relationship between energy expenditure and substrate oxidation of physical activity and body weight regulation. The results could help in prescribing for in obese population and further studies in assessing different physiological responses in different level obese populations during different exercise modalities, effects of different physical activities.

In the present study, there were several limitations. First, the present study is the application of same absolute workloads across NW and OB groups with distinct body mass profiles and unassessed baseline aerobic fitness levels. This constraint may induce discrepancies with relative exercise intensity and group-specific metabolic differences. Second, the final valid sample included in the statistical analysis was 52 participants, which was lower than the intended target sample of 73 participants determined prior to data collection. This failure to reach the planned sample size may compromise the statistical power of the study and induce potential biases in the interpretation of research findings. Third, there may be biomechanical differences between NW and OB individuals that affect EE during treadmill running and economy of running. As our study did not assess these biomechanical variables, we cannot determine the effect of biomechanical factors on EE and substrate oxidation. Last, another limitation relates to the study is the design of consecutive same-day testing. Although randomization balances carry‑over effects across the group average, it does not remove bias for the later condition within each individual. Gradual accumulation of fatigue, elevated circulating metabolites and incomplete physiological recovery may have distorted metabolic data for later trials, potentially reducing the accuracy of between-condition comparisons.

Conclusion

We conclude that, obese men consumed more energy during CE at higher intensity and TR than normal weight men, the differences disappeared when energy costs were adjusted for FFM. Our results suggest that CE without weight burden resulted in a greater fat oxidation rate and higher fat oxidation contribution in obese subjects. For cycling, net efficiency does not differ between NW and OB subjects. Energy cost is affected by obesity, exercise type and intensity. Exercise type is an important determinant of fat oxidation, independent of the exercise intensity. Exercise type and intensity are both factors influencing CHO oxidation during exercise. Future studies should apply equal relative physiological intensities to interpret the energy expenditure and substrate oxidation differences between normal and obese subjects.

Abbreviations

BMI

Body mass index

CE

Cycle ergometer

CHO

Carbohydrates

EE

Energy expenditure

HR

Heart rate

NW

Normal-weight

OB

Obese

PA

Physical activity

RMR

Resting metabolic rate

RER

Respiratory exchange ratio

TR

Treadmill running

VO₂

Oxygen consumption

VCO₂

Carbon dioxide production

Authors’ contributions

JJ. X and SL performed the experiment, JJ. X completed statistical analysis and wrote the manuscript; TT. S participated to analysis and interpretation of the data.SL and KJ. ZH reviewed the manuscript; PH designed the study and reviewed the manuscript. All the authors read and approved the manuscript.

Funding

All data collection of this study was completed in 2022 under the 2016 authorization (CISSIRD-201604); the statistical analysis and publication cost of this work was supported by the Key Research and Development Project of Hainan Province (Grant No. ZDYF2025(LALH)004).

Data availability

The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

All procedures were followed in accordance with the Helsinki Declaration and were approved by the ethics committee for human research of the China Institute of Sport Science (Ethical code: CISSIRD-201604); informed consent was obtained from all participants prior to participation.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.