Effect of Different Modes of High Intensity Interval Training on Appetite‐Related Hormones, Appetite Perception, and Anthropometric Measures in Overweight and Obese Men: A Randomized Controlled Trial

ABSTRACT

Background and Aims

This research aimed to assess the effectiveness of high‐intensity interval training (HIIT) and high‐intensity functional training (HIFT) on appetite‐related hormones (Ghrelin, peptide tyrosine–tyrosine (PYY), and glucagon‐like peptide‐1(GLP‐1)), appetite perception, and anthropometric measures in overweight and obese young men.

Methods

Thirty male participants (age: 22.6 ± 1.7 years; weight: 101.4 ± 7.4 kg; body mass index (BMI): 31.1 ± 2.3 kg/m²) were randomly allocated into HIIT (n = 10), HIFT (n = 10), and control groups (con) (n = 10). The intervention groups received supervised training three times a week for 8 weeks, including running‐based HIIT based on maximal aerobic speed (MAS) or HIFT (six bodyweight exercises). Training intensity in both groups was monitored using BORG‐CR10 perceived exertion scale (RPE). Measurements were taken at baseline and after an 8‐week training period. A mixed ANOVA analysis was used to analyze the data.

Results

HIIT and HIFT protocols significantly increased plasma levels of PYY, GLP‐1, feeling of hunger, and improved body fat percentage (BF%), waist and hip circumference, VO_₂max, and vVO₂max compared to the control (p < 0.05). However, there were no significant changes in ghrelin levels (p = 0.53), appetite ratings (fullness (p = 0.48), satiety (p = 0.72), and desire to eat (p = 0.20), weight (p = 0.14), and fat‐free mass(FFM) (p = 0.11). Additionally, BMI, and fat mass (FM) decreased significantly in the HIFT group, compared with the control (p < 0.05).

Conclusion

Overall, the findings of this study indicated that HIIT and HIFT increased fasting levels of GLP‐1 and PYY, heightened hunger perception, and improved body composition and performance. HIIT showed relatively greater percent changes in PYY, GLP‐1, feeling of hunger, and performance, while HIFT had larger percent changes in anthropometric outcomes.

Trial Registration: IRCT20191207045644N2. Registration date: 2024/03/04. URL:https://www.irct.ir/search/result?query=IRCT20191207045644N2 https://www.irct.ir/search/result?query=IRCT20191207045644N2.

Summary

• The first study to evaluate the effect of HIFT on appetite.

• GLP‐1, PYY and hunger perception significantly increased in HIIT and HIFT groups compared to the control. However, no significant changes in ghrelin or appetite perception, including fullness, satiety, and desire to eat.

• Both intervention groups significantly improved anthropometric measures and performance.

1. Introduction

Obesity is a global health concern, affecting individuals across all ages and socioeconomic backgrounds. The World Health Organization (WHO) categorizes obesity as a pathological condition, attributing it to a complex interplay of biological, psychological, behavioral, and environmental factors [1]. It is estimated that over 2.5 billion adults are overweight, with more than 890 million of them being obese [2]. Obesity is associated with an elevated risk of multiple morbidities, including metabolic dysfunction, mood disorders, osteoarthritis, and certain cancers, and imposes a significant burden on global health economics [3]. At its core, obesity is attributed to a systemic energy imbalance, where energy intake exceeds energy expenditure [1, 4]. Energy expenditure includes basal metabolism, postprandial thermogenesis, and physical activity, while energy intake captures all energy‐containing food, supplements, and drinks consumed [1, 5].

While multiple factors and peptides controlling appetite and energy intake are released in the brain, circulating peptides released from peripheral tissues such as the gastrointestinal system and adipose tissue can also influence the brain's appetite centers [1, 6, 7]. These hormones can be categorized into anorectic (appetite‐suppressing) and orexigenic (appetite‐stimulating) factors, including ghrelin (orexigenic), glucagon‐like peptide 1 (GLP‐1; anorectic), peptide YY (PYY; anorectic), pancreatic polypeptide, and leptin [8, 9, 10].

Given the significant personal and medical costs associated with overweight and obesity, public health policymakers are focused on implementing effective interventions [11]. A pathology of obesity involves the dysregulated secretion of appetite hormones, leading to uncontrolled food intake [8]. Physical activity—and exercise more specifically—is critical in managing energy balance [12, 13], and offers a non‐pharmacological and non‐surgical means of obesity prevention and treatment [14]. However, a large variability in the exercise‐induced body mass loss suggests compensatory changes in appetite and energy intake [15]. Conversely, physical inactivity can induce positive energy balance, subsequent weight gain, and disruption of appetite regulation mechanisms [16, 17].

Despite the benefits of exercise, the majority of individuals with overweight and obesity cannot participate in exercise due to a lack of time [11, 18, 19], with only 1.5%–3% achieving the recommended 150 min of weekly moderate‐vigorous intensity exercise [20]. High‐intensity interval training (HIIT) has become popular as a time‐efficient alternative to traditional training styles [11], proving to reduce FM, improve metabolic status, and body composition more effectively than moderate‐intensity continuous training (MICT) in overweight and obese adults [11, 21]. Moreover, HIIT increases concentrations of anorectic peptides more than MICT [22]. However, combining resistance training with HIIT is considered even more beneficial for positive health outcomes [23].

High‐intensity functional training (HIFT) has gained popularity in the sports and fitness industry [24]. Unlike HIIT, which is usually focused on one motor ability, HIFT integrates cardiovascular, neuromotor, and muscular efforts through various whole‐body exercises, fast movement execution, and scalable weights [24, 25]. Functionally, HIFT improves body composition factors, glucose regulation, and cognitive function [25]. However, only a few studies have adopted clinical patients, and to the best of our knowledge, no study has investigated the effects of HIFT on appetite‐regulating hormones. Therefore, this study assessed the effectiveness of an 8‐week HIIT and HIFT training program on appetite‐related hormones, appetite perception, and anthropometry in a group of men with overweight and obesity. The findings of this study could provide valuable insights into effective and enjoyable training options for managing appetite and anthropometric measures in overweight and obese individuals.

2. Materials and Methods

2.1. Study Subjects

Thirty overweight and obese males (age: 22.6 ± 1.7 years; weight: 101.4 ± 7.4 kg; BMI: 31.1 ± 2.3 kg/m²) were recruited through posters and social media advertisements. Inclusion criteria include sedentary men, defined as less than 1 h of physical activity per week over the past 12 months, aged 20–30 years, with a BMI over 25 kg/m², not diagnosed with chronic diseases (e.g., diabetes, cardiovascular disease, and hypertension), non‐smokers, not undertaking hormonal or mental health therapy, and not drinking alcohol. Exclusion criteria were any exercise injuries or discomfort, missing exercise for more than two sessions, and using supplements and medications that impact the muscle or adipose tissue metabolism, such as amino acids, corticosteroids, beta‐agonists, beta‐blockers, and calcium channel blockers. Inclusion criteria were evaluated by a physician using the medical health/history questionnaires, along with the Physical Activity Readiness Questionnaire. All participants completed an informed consent form. The study was approved by the research and ethics committee of the University of Tabriz (ethics code: IR.TABRIZU.REC.1402.042), conducted according to the latest revision of the Declaration of Helsinki, and registered with the Iranian registry of clinical trials (IRCT) IRCT20191207045644N2. A schematic overview of the study is presented in Figure 1.

Figure 1.

Schematic overview of study timeline (CONSORT flow diagram).

2.2. Study Design

Participants were randomly allocated to three groups: HIIT (n = 10), HIFT (n = 10), and control (n = 10) using a computer‐generated random sequence with allocation concealed in sealed opaque envelopes. Outcome assessors and laboratory staff were blinded to group allocation. The required number of participants to detect a medium‐to‐large effect ( f = 0.3) in each group was estimated as n = 10 using G*Power software for Repeated measures (rejection criterion of 0.05; power: 0.80 (1 − beta) power). One participant was lost to follow‐up from each group due to personal and job‐related reasons, and 27 participants completed the study (Table 1). Before baseline measurements, all participants were familiarized with the testing protocols. Outcome measurements were completed at two time points: 48 h prior to the preparatory phase and 48 h after the final training session, both at the same time of the day (within ~1 h). Moreover, two briefing sessions were held to familiarize the subjects with food groups distribution and meal ingredients, including sugars, proteins, fats, and fibers. Participants were instructed to maintain their regular dietary habits throughout the study.

Table 1.

Anthropometric and physiologic characteristics of participants.

Group	Age (years)	Height (m)	Body mass (kg)		BMI (kg/m2)		SBP (mmHg)		DBP (mmHg)
			Pre	Post	Pre	Post	Pre	Post	Pre	Post
HIIT	21.9 ± 1.6	1.84 ± 0.05	102.6 ± 8.9	101.3 ± 9	30.5 ± 2.3	30 ± 2.4	122 ± 5.4	118.3 ± 5.6	77.5 ± 4.2	76.1 ± 5.5
HIFT	23. 7 ± 1.7	1.79 ± 0.02	100.5 ± 6.9	98.3 ± 7.6	31.4 ± 1.9	30.6 ± 2.1	119.5 ± 6	117.8 ± 6.2	78 ± 4.2	76.7 ± 5.6
CON	22.3 ± 1.5	1.80 ± 0.04	101.03 ± 7.2	100.3 ± 7.5	31.4 ± 2.7	31.2 ± 2.8	122.5 ± 5.9	121.1 ± 5.5	80 ± 4.1	77.8 ± 5.7

Note: Data are presented as mean ± SD.

2.3. Test Procedures

The initial measurement battery consisted of height (stadiometer, Seca 213, Germany), body mass (digital weighing scales, Seca 769, Germany), calculation of the BMI (kg/m²), waist and hip circumference (tape measure), and systolic and diastolic blood pressure (sphygmomanometer, Riester, Germany). On the same day, the participants completed a body composition analysis (Anea BIA, Iran) to assess BF%, FM, and FFM.

The following day, the participants performed the 1‐mile Rockport walking test to estimate V̇O₂ max [26]. After a warm‐up, the subjects walked as quickly as possible for a mile (1609 m) with a heart rate monitor. Cardiovascular fitness was estimated using the following formula:

V̇O₂ max (mL.kg⁻¹.min^{− 1}) = 132.853 − (0.0769 * weight) − (0.3877 * age) + (6.315 * gender) − (3.2649 * mile walk time) − (0.1565 * ending heart rate).

The next day, the Maximal Aerobic Speed (MAS) assessment (vV̇O2 max) was performed by running the maximum distance in 5 min on the track. Throughout the test, a sound signal was given every minute, and participants received verbal encouragement to perform to their maximum ability. The maximal aerobic velocity (vV̇O₂ max(5) (kilometers/hour)) was calculated by multiplying the running distance (d) by 12: vV̇O₂ max(5) = 12 d (km run in 5 min) [27]. The tests were repeated 48 h after the training intervention period, respectively.

2.4. Training Protocol

Participants of each training group performed 1 week of supervised MICT (50%–60% MAS for 20 min), consisting of three sessions prior to the 8‐week training intervention, to boost baseline fitness. All training sessions lasted 45–50 min of supervised exercise, including a 10‐min warm‐up, a 25–30‐min exercise phase, and a 10‐min cool‐down. The HIIT training was running‐based, with the intensity based on the percentages from MAS; while the HIFT group performed six exercises: push‐ups, high knees, squats, mountain climbing, burpees, and jumping jacks. Training intensity for HIFT was personalized based on participants' records, and both groups used the BORG‐CR10 perceived exertion scale to monitor intensity [28] (Table 2).

Table 2.

Training protocol.

Group	Variables	Weeks 1–2	Weeks 1–4	Weeks 5–6	Weeks 7–8
HIIT	Set (N)	3	3	4	4
	Rep (N)	6	6	6	6
	Work time (s)	30	25	20	15
	Rest time (s)	60	50	40	30
	Work intensity	130%–140% MAS	140%–150% MAS	150%–160% MAS	160%–170% MAS
	RPE	7–8/10	7–8/10	8–9/10	8–9/10
	Rest intensity	20%–30% MAS	20%–30% MAS	Passive	Passive
	Between set rest (s)	150	150	150	150
	Training time (min)	29	25	29	23.5
HIFT	Set (N)	3	3	4	4
	Rep (N)	6	6	6	6
	Work time (s)	30	25	20	15
	Rest time (s)	60	50	40	30
	Work intensity	70%–75% record	75%–80% record	80%–85% record	85%–90% record
	RPE	7–8/10	7–8/10	8–9/10	8–9/10
	Rest intensity	20%–30% MAS	20%–30% MAS	Passive	Passive
	Between set rest (s)	150	150	150	150
	Training time (min)	29	25	29	23.5

2.5. Hormonal Analysis

A 5 mL blood sample was collected from the antecubital vein using ethylenediaminetetraacetic (EDTA) tubes following overnight fasting at the same time of day (8:00 a.m.), with a maximum variation of ~30 min, before and after the training intervention (~48 h before and after the intervention). Samples were immediately centrifuged (4°C, 1000×g) for 15 min after collection to isolate plasma and were then stored at −70° C. Total ghrelin (Elabscience, United States, Cat no: E‐EL‐H1919): sensitivity 0.09 ng/mL, intraassay coefficients of variability (CV) 6% and the inter‐assay CV 6%), GLP‐1 (Elabscience, United States, Cat No: E‐EL‐H6025: sensitivity 0.94 pg/mL, intraassay CV 5.45% and the inter‐assay CV 5.44%), total PYY (Elabscience, United States, Cat No: E‐EL‐H1237: sensitivity = 18.75 pg/mL, intraassay CV 5.43% and the inter‐assay CV 5.78%), concentration were analyzed by ELISA.

2.6. Nutrient Intake and Habitual Energy Expenditure

Three‐day food records (2 weekdays and 1 weekend day) were collected before, during (Week 4), and after the study, to track dietary intake changes. Total energy intake and the macronutrient contributions were calculated using Diet Analysis Plus version 10 (Cengage, Boston, MA, United States). Total energy expenditure (TEE) consists of basal metabolic rate (BMR), activity energy expenditure (AEE), and the thermic effect of food (TEF) [29]. BMR was estimated using the Katch–McArdle equation, which uses lean body mass [30]. To assess the participants' physical activity, we used the long‐form International Physical Activity Questionnaire (IPAQ‐L, 27 items) at pre‐test, Week 4, and post‐test, considering a reference period of the past 7 days. Weekly MET minutes were calculated by multiplying MET value (walking = 3.3, moderate activity = 4, vigorous activity = 8) by the activity duration in minutes and frequency [31]. The TEF is estimated at 5%–10% of the daily TEE [29, 32]. In addition, fasting appetite perception (hunger, fullness, satiety, and desire to eat) was assessed using the visual analog scale (VAS) 48 h before and after the training period [33].

2.7. Statistical Analysis

Data are presented as mean ± standard deviation (mean ± SD). Data normality (Shapiro–Wilk test) and homogeneity (Levene's test) were assessed before ANOVA testing. One‐way ANOVA and Tukey's post‐hoc tests compared baseline data among the three groups. A mixed ANOVA (repeated‐measures ANOVA) evaluated the main and interaction effects of time and group. Where significant, planned pairwise comparisons were employed. For energy expenditure, RM‐ANCOVA was applied. Additionally, it is important to note that intention‐to‐treat analysis was performed.

To quantify the effect size (ES), the partial eta‐squared (ƞ ²) was calculated and reported. Statistical significance levels were set at p ≤ 0.05. All analyses were conducted using SPSS software (Version 24.0; SPSS Inc., Chicago, IL).

3. Results

The assumptions of data normality (Shapiro–Wilk's test) and homogeneity of variance (Levene's test) were confirmed. One‐way ANOVA results demonstrated no differences between groups across any of the variables at baseline (All p > 0.05).

The time × group interaction analysis revealed significant effects for all anthropometric factors, with the exception of weight and FFM, as well as for performance, hunger perception, and circulating GLP‐1 and PYY (p < 0.05; Tables 3, 4, 5).

Table 3.

Anthropometric and performance variables before and after interventions.

Variable	Group	M ± SD		% Changes	Time	Group	Time * group interaction	Partial eta squared	Effect size
		Pre (N = 10)	Post (N = 9)
Body mass (kg)	HIIT	102.6 ± 8.9	101.3 ± 8.9	−1.3	*< 0.001	0.80	0.14	0.153	0.43
	HIFT	100.5 ± 6.9	98.3 ± 7.6*	−2.2
	Con	101 ± 6.7	100.3 ± 7.5	−0.7
BMI (kg/m2)	HIIT	30.5 ± 2.3	30 ± 2.4*	−1.7	*< 0.001	0.65	a0.03	0.249	0.58
	HIFT	31.4 ± 1.9	30.6 ± 2.1*	−2.5
	Con	31.4 ± 2.7	31.2 ± 2.8	−0.6
Waist circumference (cm)	HIIT	104.3 ± 8.7	98.4 ± 7.6*	−5.6	*< 0.001	0.51	a0.001	0.430	0.87
	HIFT	103.8 ± 7.6	97.9 ± 7.3*	−5.7
	Con	105.9 ± 9.9	105 ± 11.4	−0.8
Hip circumference (cm)	HIIT	117.3 ± 4.5	113.3 ± 3.9*	−3.4	*< 0.001	0.05	a0.002	0.397	0.81
	HIFT	113.4 ± 5.7	107.9 ± 4.9*	−4.9
	Con	117.2 ± 5.2	116 ± 5.7	−1
BF (%)	HIIT	31.1 ± 3.8	30.2 ± 3.4*	−2.9	*< 0.001	0.67	a, b<0.001	0.579	1.17
	HIFT	30.7 ± 4.8	28.6 ± 4.5*	−6.8
	Con	31.3 ± 4.4	31.7 ± 4.7*	1.3
FM (kg)	HIIT	31.9 ± 5.2	30.6 ± 4.3*	−4.1	*< 0.001	0.68	a0.001	0.440	0.89
	HIFT	30.8 ± 6	28.4 ± 6.2*	−7.8
	Con	32 ± 6.3	32.1 ± 6.6	0.3
FFM (kg)	HIIT	70.6 ± 6.9	70.8 ± 7.4	0.3	0.35	0.73	0.11	0.170	0.45
	HIFT	69.8 ± 4.3	69.9 ± 4.7	0.1
	Con	69.2 ± 2.8	68.3 ± 3.5*	−1.3
VO2max (mL/kg.min)	HIIT	39.4 ± 2.9	43.7 ± 2.9*	10.9	*< 0.001	0.36	a, b< 0.001	0.710	1.56
	HIFT	39.8 ± 3.4	41.4 ± 3.3*	4
	Con	39.7 ± 2.8	39.2 ± 3.2*	−1.2
vVO2max (m/s)	HIIT	2.5 ± 0.2	2.8 ± 0.2*	12	*< 0.001	0.74	a< 0.001	0.519	1.04
	HIFT	2.6 ± 0.3	2.8 ± 0.3*	7.7
	Con	2.7 ± 0.2	2.7 ± 0.3	0

Note: Data presented as mean ( ± SD).

Abbreviations: BF%, Body fat percentage; BMI, Body mass index; Con, Control; FFM, Free fat mass; FM, Fat mass; HIFT, High intensity functional training; HIIT, High intensity interval training.

^aSignificant differences from the control group (p < 0.05).

^bSignificant differences between training protocols (p < 0.05).

^*Significant differences from the pre‐test (p < 0.05).

Table 4.

Nutritional intake and energy expenditure values in 3 phases (pre, week 4th, and post).

Variable	Group	M ± SD			Time	Group	Time * group interaction	Effect size
		1	2	3
Energy (kcal/d)	HIIT	2332 ± 177	2330 ± 188	2352 ± 191	0.55	0.86	0.48	0.26
	HIFT	2308 ± 187	2298 ± 174	2287 ± 143
	Con	2316 ± 190	2293 ± 129	2286 ± 141
CHO (g/d)	HIIT	299 ± 32.2	298 ± 32.5	301 ± 33.8	0.82	0.99	0.91	0.14
	HIFT	299 ± 16	298 ± 16.5	296 ± 19.3
	Con	298 ± 37.8	296 ± 31	296 ± 33.6
Protein (g/d)	HIIT	101 ± 17.6	103 ± 15.8	103 ± 16.4	0.79	0.84	0.57	0.23
	HIFT	99 ± 9.7	99 ± 9.3	101 ± 10.2
	Con	100 ± 12.9	98 ± 10.6	98 ± 11.4
Fat (g/d)	HIIT	82 ± 12	81 ± 7	81 ± 7.4	0.44	0.88	0.96	0.10
	HIFT	80 ± 13.2	79 ± 10.6	78 ± 8.8
	Con	81 ± 13.4	80 ± 12.4	79 ± 13.2
Energy Expenditure (kcal/d)	HIIT	2250 ± 155	2388 ± 161	2565 ± 170	0.18	* <0.001	a <0.001	3.28
	HIFT	2259 ± 118	2416 ± 125	2604 ± 133
	Con	2283 ± 70	2314 ± 63	2315 ± 72

Note: Data presented as mean (± SD).

Abbreviations: Con, control; CHO, carbohydrate g/d, gram(s)/day; HIFT, high intensity functional training; HIIT, high intensity interval training.

^a Significant differences from the control group (p < 0.05).

^*Significant differences between groups (p < 0.05).

Table 5.

Appetite assessed using visual analog scale (VAS).

Variable	Group	M ± SD		% Changes	Time	Group	Time * group interaction	Partial eta squared	Effect size
		Pre (N = 10)	Post (N = 9)
Hunger (mmVAS)	HIIT	44.4 ± 10.6	52.2 ± 12*	17.6	*0.001	0.31	a 0.008	0.333	0.71
	HIFT	43.3 ± 11.5	50 ± 11.1*	15.5
	Con	41.1 ± 10	40 ± 11.1	−2.7
Fullness (mmVAS)	HIIT	47.7 ± 10.3	44.4 ± 8.8	−6.9	> 0.99	0.85	0.48	0.060	0.25
	HIFT	47.7 ± 10.3	48.9 ± 7.8	2.5
	Con	46.6 ± 9.4	48.9 ± 10.5	4.9
Satiety (mmVAS)	HIIT	48.8 ± 10	46.6 ± 8.6	−4.5	0.83	0.99	0.72	0.027	0.17
	HIFT	46.6 ± 9.4	47.8 ± 9.7	2.6
	Con	47.7 ± 9.2	47.8 ± 9.7	0.2
Desire to eat (mmVAS)	HIIT	40 ± 9.4	50 ± 10*	25	*0.009	0.95	0.20	0.124	0.37
	HIFT	42.2 ± 10.3	47.8 ± 10.9	13.3
	Con	43.3 ± 9.4	44.4 ± 8.8	2.5

Note: Data presented as mean (± SD).

Abbreviations: Con, control; HIFT, high intensity functional training; HIIT, high intensity interval training; mmVAS, millimeter visual analog scale.

^aSignificant differences from the control group (p < 0.05).

^*Significant differences from the pre‐test (p < 0.05).

Results demonstrated no significant differences in weight between groups (F = 2.17 p = 0.14, η _p ²:0.153; Table 3). The BMI was significantly decreased in HIFT (F = 3.97, p = 0.03, η _p ²:0.249) compared to the control, while waist and hip circumference were significantly reduced in both training groups (Waist F = 9.06, p = 0.001, η _p ²:0.430, Hip F = 7.90, p = 0.002, η _p ²:0.397) compared to the control. We observed significant differences between groups for BF% (F = 16.53, p < 0.001, η _p ²:0.579), with the greatest decrease observed after HIFT. Accordingly, only the HIFT intervention resulted in a significant decrease in fat mass (F = 9.42, p < 0.001, η _p ²:0.440) compared to control, but no significant changes were noted in FFM (F = 2.46, p = 0.11, η _p ²:0.170). Significant improvements were seen in V̇O2 max in both HIIT and HIFT (F = 29.31, p < 0.001, η _p ²:0.710), which corresponded with the vV̇O2 max data, showing significant improvements in both intervention groups compared to the control group (F = 12.95, p < 0.001, η _p ²:0.519).

Within‐group analyses identified consistent improvements in all anthropometric and performance parameters in the HIFT group, except FFM (Table 3). With the exception of body mass, the HIIT group also displayed similar trends, albeit with lower percent‐change scores in anthropometric variables and higher scores in performance variables.

Regarding energy intake, there were no significant main effects of time (F = 0.51, p = 0.55, η _p ²:0.021), group (F = 0.16, p = 0.86, η _p ² 2:0.013), or interaction effect (F = 0.84, p = 0.48, η _p ²:0.065). Similarly, for carbohydrates, there was no significant main time (F = 0.2, p = 0.82, η _p ²:0.008), group (F = 0.02, p = 0.99, η _p ²:0.001), and interaction effect (F = 0.24, p = 0.91, η _p ²:0.020). We also did not observe significant main group (F = 0.18 p = 0.84, η _p ²:0.015), time (F = 0.14 p = 0.79, η _p ²:0.006) and interaction effects (F = 0.65 p = 0.57, η _p ²:0.051) for protein. For fat intake, the results indicated no significant main time (F = 0.77, p = 0.44, η _p ²:0.031), group (F = 0.13, p = 0.88, η _p ²:0.010), and interaction effects (F = 0.11, p = 0.96, η _p ²:0.009). However, the intervention did lead to a significant main group (F = 103.1, p < 0.001, η _p ²:0.900) and interaction effect (F = 124, p < 0.001, η _p ²:0.915) on energy expenditure, though no significant time effect (F = 1.9, p = 0.181, η _p ²:0.076) was found. Overall, the energy expenditure was increased in both intervention groups compared to the control (Table 4).

Findings on appetite ratings (Table 5) indicated that after 8 weeks of training, the HIIT group experienced a significant increase in hunger and desire to eat, while the HIFT group showed a significant increase only in hunger (p < 0.05 There was a significant difference in hunger levels comparing both interventions to the control (F = 6.00, p = 0.008, η _p ²:0.333). On the other hand, fullness and satiety results showed no within‐ and between‐group changes (p > 0.05).

Finally, regarding appetite‐related hormones (Table 6 and Figure 2), no significant changes observed in Ghrelin levels within or between the groups (p > 0.05). However, both the HIIT and HIFT groups showed significant increases in GLP‐1 (F = 3.86, p = 0.04, η _p ²:0.243) and PYY (F = 4.12, p = 0.03, η _p ²:0.256) compared to the control. No significant differences were observed between the two exercise groups.

Table 6.

Pre‐ and post‐training values for appetite‐related hormones.

Variable	Group	M ± SD		% Changes	Time	Group	Time * group interaction	Partial eta squared	Effect size
		Pre (N = 10)	Post (N = 9)
Ghrelin(ng/mL)	HIIT	0.59 ± 0.2	0.66 ± 0.16	12	0.08	0.78	0.53	0.052	0.23
	HIFT	0.60 ± 0.16	0.71 ± 0.19	18
	Con	0.60 ± 0.16	0.61 ± 0.14	2
GLP‐1(pg/mL)	HIIT	9.22 ± 1.6	11.35 ± 2.1*	23	*0.002	0.81	a0.04	0.243	0.57
	HIFT	9.10 ± 2	11.05 ± 2.3*	21
	Con	9.81 ± 2.1	9.61 ± 2.1	−2
PYY (pg/mL)	HIIT	106.3 ± 11.2	131.2 ± 24.9*	23	*0.005	0.27	a0.03	0.256	0.59
	HIFT	106 ± 15.6	128.5 ± 26.5*	21
	Con	109 ± 16.2	104.7 ± 21.2	−4

Note: Data presented as mean ( ± SD),

Abbreviations: Con, control; GLP‐1, glucagon‐like peptide‐1; HIFT, high intensity functional training; HIIT, high intensity interval training; PYY, peptide YY.

^aSignificant differences from the control group (p < 0.05).

^*Significant differences from the pre‐test (p < 0.05).

Figure 2.

Pre‐ and post‐training values for (A) Ghrelin, (B) glucagon‐like peptide‐1, and (C) peptide YY in HIIT, HIFT, and control groups. *Significant differences from the pre‐test (p < 0.05); (a) Significant differences from the control group (p < 0.05).

4. Discussion

The findings of this study demonstrated improvements across a range of anthropometric (BMI; waist and hip circumference; FM; BF%) and performance (V̇O2 max; vV̇O2 max) measures in response to both training interventions. Our findings showed that the increase in fasted GLP‐1, PYY levels, and hunger perception was significantly greater than in the control group following the 8 weeks of HIIT and HIFT. However, no change was found in the fasting plasma level of ghrelin. Interestingly, the within‐group analyses revealed an increased desire to eat only in the HIIT group. To the best of our knowledge, this is the first randomized controlled trial examining the effects of HIFT and HIIT on appetite hormones in overweight and obese males.

Appetite control is a complex physiologic interaction between gastrointestinal factors, multiple tissues (i.e., adipose and muscle tissue), and systems (i.e., nervous, immune, and endocrine systems), which communicate information about energy intake and energy needs to the brain [34, 35]. Previous research has shown that gastrointestinal peptides Ghrelin, GLP‐1, and PYY play crucial roles in regulating appetite [36, 37]. GLP‐1 and PYY are released from intestinal l‐cells in response to nutrient intake and act synergistically via discrete mechanisms to suppress appetite [35]. As the only orexigenic peptide amongst these, ghrelin is crucial in stimulating hunger and the desire to eat. Ghrelin circulates in the blood in acyl and non‐acyl forms and exerts its orexigenic action via the growth hormone secretagogue receptor (GHS‐R). The acylated form affects appetite, while non‐acyl ghrelin regulates lipogenesis and aids in peripheral glucose metabolism [38, 39]. During fasting, the circulating ghrelin levels rise and decrease after eating [36, 37].

Only a limited number of studies have investigated the impact of chronic HIIT on appetite perception and appetite‐related hormones in overweight or obese individuals. Martins et al. compared a HIIT program to an isocaloric MICT protocol, finding an increase in fasting hunger [40]. However, no significant effect of exercise intervention was found on the plasma concentrations of acylated ghrelin, PYY_3‐36, and GLP‐1, or fasting perception of fullness and desire to eat following a 12‐week training period. These results are in contrast to earlier research conducted by that group, which showed not only the increased acylated ghrelin levels and perception of hunger in fasting, but also improvements in the satiety response to a meal [41]. Differences in these results are attributed to the differences in training volume, with the earlier work requiring a 500‐kcal deficit per session, while the subsequent study required only a 250‐kcal deficit [40]. Irrespective, the finding of a higher fasted hunger perception following the HIIT and HIFT and desire to eat only in HIIT in the current study is consistent with those observed by Martins et al.

Some studies have reported no changes in ghrelin concentrations (total or acylated ghrelin) after HIIT (Khademosharie et al.; Sheikholeslami‐Vatani et al.; Horner et al.; Heiston et al.; Sim et al.), consistent with our findings in obese and overweight men [21, 22, 38, 42, 43]. Conversely, other studies have indicated decreases (Afrasyabi et al.) [36] or increases (Ataeinosrat et al.) [2] in ghrelin levels among obese or overweight participants. This inconsistency may primarily be explained by the differences in the achieved weight loss and training interventions, such as training duration, intensity, and modalities (e.g., running, walking, or cycling) [2, 40]. Additionally, the increase in ghrelin levels in overweight or obese individuals (Ataeinosrat et al.) may reflect the short‐term compensatory effect of appetite stimulation to greater weight loss compared to our findings (−6.7 vs. −2.2 kg) [2].

The initiation of fullness following a meal is partly mediated by GLP‐1, an incretin hormone that slows gastric emptying, enhances satiety, and facilitates insulin secretion [38, 44, 45, 46]. GLP‐1 stimulates insulin secretion from pancreatic β cells [47, 48] and increases the hydrolysis of triglyceride in adipose tissue [48], which may both indirectly alter appetite perceptions [49]. Prior research has indicated that lean and healthy individuals tend to have higher levels of incretin hormones (e.g., GLP‐1) than those with obesity [1, 36]. While individuals with obesity displayed similar profiles in GLP‐1 following weight loss due to exercise [1, 50, 51].

In addition, an increase in certain inflammatory factors like interleukin‐6 (IL‐6) can impact the secretion of appetite‐regulating peptides, enhancing GLP‐1 production from intestinal L cells and pancreatic alpha cells [52, 53]. Our findings regarding significant differences between training groups and control align with the findings of Ataeinosrat et al., who indicated that 12 weeks of interval resistance training increased fasting GLP‐1 levels [2]. In contrast, Martins et al. reported no significant differences in GLP‐1 between HIIT and MICT, and a lower‐volume HIIT group [40]. Moreover, Heiston et al. noted a slight reduction in fasting GLP‐1 levels within the HIIT group after 2 weeks of training [38].

Several studies have indicated that obese people have attenuated postprandial PYY responses, leading to uncontrolled food intake and a positive energy balance [1, 54, 55]. Peptide YY is also released in response to exercise training, with Sheikholeslami‐Vatani et al. reporting that HIIT increased PYY levels in sedentary individuals with overweight, supporting our findings of elevated PYY herein [21]. Several studies have suggested that physical exercise might have a dampening effect (decreased neural activity) on the brain's food reward systems, which aligns with lower overall food palatability, diminished anticipation for eating, and reduced food intake [22, 56]. Crabtree et al. found that high‐intensity exercises reduced neural responses to high‐calorie foods [56]. Additionally, regular exercise training could improve appetite regulation by altering substrate metabolism, especially the increased oxidation of fatty acids, which may lead to decreased energy intake by affecting vagal afferent activity that transmits satiety signals to the appetite centers in the brain [22, 57]. Additionally, regular exercise may lead to changes in individuals' psychological approaches toward food [22].

In contrast, studies have shown unchanged fasting plasma PYY following a 12‐week training period [22, 40] ¸and a 2‐week interval training program with a low‐calorie diet in women with obesity [58]. This lack of change may be due to modest weight loss in those studies, with averages of −1.2, −0.7, and −1.6 kg, compared to −2.2 kg in our study. Moreover, Ataeinosrat et al. noted that 12 weeks of different modes of resistance training decreased PYY levels [2]. The reasons for these discrepancies remain unclear, and further studies are required to shed light on how participants' body mass and fat may influence appetite‐related hormones following exercise training.

The findings of this study showed that overweight and obese men had a significant improvement in BMI, waist and hip circumference, BF%, FM, V̇O₂max, and vV̇O₂max after an 8‐week of HIIT and HIFT training. A meta‐analysis by wang et al. confirmed that HIIT was the most effective in reducing waist circumference, BF%, serum triglycerides, and fasting blood glucose, and improving V̇O₂max in overweight and obese adults [11]. Another meta‐analysis by Khodadadi et al. also demonstrated significant reductions in FM and BF% with HIIT modes [59]. Previous studies have shown that HIFT improves body composition factors, glucose regulation [25, 60], and is associated with increased production of the myokines IGF‐1, IRISIN, and BDNF, which may influence appetite regulation [60].

In contrast, body weight, FFM, feeling of fullness, satiety, and desire to eat remained unchanged compared to the control group in our study. It is important to note that Changes in appetite‐related hormones do not always align with the appetite perception and calorie expenditure. This inconsistency represents the complexity of appetite regulation and highlights the influence of various physiological and psychological factors [21, 61].

This study had multiple strengths, including the multiple outcomes assessed, the two training groups involved in the program, and the recruitment of participants with overweight and obesity. However, it is also important to acknowledge some limitations when interpreting the findings. First, the sample size was relatively small (n = 30), comprising only men in a narrow age range, limiting generalizability, particularly to women. Second, the gut hormones are known to demonstrate the greatest changes during the postprandial phase and in response to acute exercise, while these were measured at rest in the fasting state, suggesting the results reflect chronic intervention effects. Additionally, total levels of these hormones were measured rather than cleaved neuropeptide forms (e.g., PYY3‐36). Finally, we did not measure other myokines and adipokines that may regulate appetite or influence weight loss.

We suggest that future studies investigate the panel of gut hormones, including total and active hormone isoforms, at fasting and postprandial phases, with more diverse samples.

5. Conclusion

Overall, the findings of this study indicated that HIIT and HIFT increased fasting levels of GLP‐1 and PYY, heightened hunger perception, and improved body composition and performance. Considering the combined outcomes, HIFT emerges as an effective alternative to other forms of HIIT methods for managing body mass. However, further studies are required to elucidate the physiological appetite mechanisms supporting body mass and fat changes following HIFT.

Author Contributions

Vahid Fekri‐Kourabbaslou: conceptualization, data curation, formal analysis, investigation, methodology, software, writing – original draft, writing – review and editing. Ramin Amirsasan: conceptualization, methodology, formal analysis, supervision, validation, writing – review and editing. Saeid Dabbagh‐Nikoukheslat: methodology, formal analysis, supervision, validation, writing – review and editing.

Funding

The authors have nothing to report.

Ethics Statement

The study was approved by the Research and Ethics Committee of the University of Tabriz (ethics code: IR.TABRIZU.REC.1402.042) and performed in accordance with the latest revision of the Declaration of Helsinki. In addition, this research was registered in the Iranian Registry of Clinical Trials (IRCT) with registration number IRCT20191207045644N2.

Consent

All participants completed an informed consent form.

Conflicts of Interest

The authors declare no conflicts of interest.

1. Data Availability Statement

The data sets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Transparency Statement

The corresponding author, Ramin Amirsasan, affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.