Next Article in Journal
Research and Publication Ethics in Journal of Functional Morphology and Kinesiology
Previous Article in Journal
Secondary Scoliosis as a Complication of Acute Transverse Myelitis in a Child
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
JFMK
Volume 5
Issue 2
10.3390/jfmk5020041
jfmk-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The Effects of Short-Term High-Intensity Interval Training and Moderate Intensity Continuous Training on Body Fat Percentage, Abdominal Circumference, BMI and VO2max in Overweight Subjects

by
Luca Russomando
1,†,
Vincenzo Bono
1,†,
Annamaria Mancini
1,2,
Alessia Terracciano
1,
Francesca Cozzolino
1,
Esther Imperlini
3,
Stefania Orrù
1,2,
Andreina Alfieri
1,2,* and
Pasqualina Buono
1,2,*
1
Dipartimento di Scienze Motorie e del Benessere, Università degli Studi di Napoli Parthenope, 80133 Naples, Italy
2
CEINGE-Biotecnologie avanzate, 80131 Naples, Italy
3
IRCCS SDN, 80143 Naples, Italy
*
Authors to whom correspondence should be addressed.
†
These authors equally contributed to this work.
J. Funct. Morphol. Kinesiol. 2020, 5(2), 41; https://doi.org/10.3390/jfmk5020041
Submission received: 10 April 2020 / Revised: 4 June 2020 / Accepted: 5 June 2020 / Published: 10 June 2020
(This article belongs to the Section Physical Exercise for Health Promotion)
Browse Figure
Review Reports Versions Notes

Abstract

:
We aimed to compare the effects of a personalized short-term high-intensity interval training (HIIT) vs. standard moderate intensity continuous training (MICT) on body fat percentage, abdominal circumference, BMI and maximal oxygen uptake (VO2max) in overweight volunteers. Twenty overweight sedentary volunteers (24.9 ± 2.9y; BMI: 26.1 ± 1 kgm−2) were randomly assigned to 2 groups, HIIT or MICT. HIIT trained 6 weeks (3-days/week), 40-min sessions as follows: 6-min warm-up, 20-min resistance training (RT) at 70% 1-RM, 8-min HIIT up to 90% of the predicted Maximal Heart Rate (HRmax), 6-min cool-down. MICT trained 6 weeks (3-days/week) 60-min sessions as follows: 6-min warm-up, 20-min RT at 70% 1-RM, 30-min MICT at 60–70% of the predicted HRmax, 4-min cool-down. Two-way ANOVA was performed in order to compare the efficacy of HIIT and MICT protocols, and no significant interaction between training x time was evidenced (p > 0.05), indicating similar effects of both protocols on all parameters analyzed. Interestingly, the comparison of Δ mean percentage revealed an improvement in VO2max (p = 0.05) together with a positive trend in the reduction of fat mass percentage (p = 0.06) in HIIT compared to MICT protocol. In conclusion, 6 weeks of personalized HIIT, with reduced training time (40 vs. 60 min)/session and volume of training/week, improved VO2max and reduced fat mass percentage more effectively compared to MICT. These positive results encourage us to test this training in a larger population.

1. Introduction

Obesity represents one of the most important cardiovascular (CV) risk factors [1,2]. A lot of epidemiological and trial-based evidences suggest a direct link between body weight and health [3,4]. In Italy, more than one third of the adult population (35.5%) is overweight, whereas more than 10% of subjects is obese (10.4%): overall, 45.9% of people aged ≥18 years are overweight [5]. The American College of Sports Medicine (ACSM) in a recent position stand recommends aerobic physical activity 150 min/week for a modest weight loss (2–3 kg), 225–420 min/week for a considerable weight loss (5–7.5 kg), 200–300 min/week are indicated for the management of body weight after the weight loss [6]. However, due to lack of time, many people are often unable to reach the minimum level of recommended daily physical activity (PAL). According to ISTAT data, approximately 39.2% of Italian people do not attend any kind of sport and do not engage in physical activity in their free time [5]. In order to reduce sedentary lifestyle and to counteract overweight and obesity, research is recently focusing on the effectiveness of different short-term and high-intensity training protocols, that could represent a useful strategy for the management of body composition and the reduction of waist circumference [7]. In this context, MICTs are traditionally the most suitable protocols used for achieving these goals also in absence of food restriction in overweight subjects, and only recently, RT training has been included [8,9,10,11,12,13].
HIIT is considered a new-type of training, most popular among physically active individuals [14]: HIIT enhances 2–4% the performance in athletes improving both anaerobic and aerobic capacity [15,16,17,18]. More recently HIIT training has been proposed as an alternative protocol to MICT in order to improve physical fitness and body composition in healthy subjects [6,19]. Long-term (at least 12 weeks) High Intensity Interval Resistance Training (HIRT) improved resting energy expenditure and respiratory ratio to a greater extent than traditional MICT training also in non-dieting subjects [20].
Furthermore, the HIIT training is considered the first choice for healthy subjects who frequently dropped-out from gym training sessions due to lack of time. To date, there are no universally accepted guidelines reporting the length of the high-intensity session and the recovery time; a growing body of evidence suggests that HIIT protocols, i.e., 0.5–4 min bout of vigorous exercise interspersed by period of passive or active recovery, are a more-time efficient exercise strategy, also being perceived as more enjoyable in term of adherence [20,21,22,23].
Only few studies analyzed the effects of short-term HIIT protocols on body composition in different subjects, often providing conflicting results, so far [24,25,26]. Accordingly, the aim of the present study was to compare the effects of 6 weeks, 3 times/week, personalized supervised short-term HIIT (HIIT) vs. standard MICT protocol on BMI, body fat percentage, abdominal circumference and VO2max in young overweight, sedentary subjects.

2. Materials and Methods

2.1. Study Design and Participant Recruitment

In this randomized control trial, young volunteers were randomly assigned to HIIT or MICT group to perform 6 weeks (3 days/week) of HIIT or MICT training, respectively. Anthropometry (height, weight, BMI), Body Fat mass percentage (%), abdominal circumference, together with VO2max were evaluated at baseline (T0) and after 6 weeks (T1) of HIIT or MICT training protocols. Muscular fitness, 1-RM, was also evaluated at baseline, in all participants.
Twenty young, healthy, overweight, sedentary (performing less than 60 min, 1–2 times for week of exercise) subjects volunteered to participate in this study (24.9 ± 2.9y; height: 1.67 ± 0.1 (m); weight: 72.6 ± 9.1 (kg); BMI: 26.1 ± 1 (kg m−2); fat mass percentage: 25.8 ± 2.9 (%); abdominal circumference: 90.2 ± 5.8 cm; VO2max: 38.1 ± 2.2 (mL kg−1 min−1). The volunteers stated that they had a Mediterranean-type diet with no food-restrictions. The participants were asked to report any changes in lifestyle, including nutritional habits, or if they were taking any drugs during the study. Participants were randomly assigned to 2 different groups: 10 subjects (3 males and 7 females) to the HIIT group and 10 subjects (4 males and 6 females) to the MICT group, respectively. Participants were asked to refrain from consuming caffeine and alcohol and to not perform any physical activity for 24 h before each evaluation. Furthermore, in the seven days before the baseline assessment, participants completed a familiarization training session. Although ethics committee permission was not required prior to the beginning of the study [27], all participants were informed of the research aims and gave their written informed consent for participation in the study. The study was conducted nevertheless in accordance with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

2.2. Measurements

2.2.1. Anthropometric Evaluation

Height and weight were recorded using the SECA 756 (Mechanical Column Scale) with SECA 224 (Telescopic Measuring Rod for SECA column scales, respectively (SECA, Precision for health, 2017). The Body Fat percentage (%) was measured according to the Girth Method based on three girth measurements [28]; the measurement was approximately 0.1 cm.
Girth measurement sites are reported in Table 1; reference equations to predict Body Fat percentage are reported in Table 2.

Estimated VO2max

The estimation of VO2max was performed using the single-stage treadmill Walking Test as described below [29]. Briefly, subjects first performed a 4-min warm-up at comfortable walking speed, based on the participant’s gender, age and fitness level, without slope, allowing the HR to reach the 50–70% of the predicted HRmax. Then, participants continued at the same speed for additional 4 min at a 5% grade allowing to reach the Steady State HR (SS HR). The HR was recorded in the final 2 min, if the HR differed by more than 5 bpm, they continued the test for another 1 min and the new SS was recorded in the final 30-sec of the last 2 min. A cool down (2–5 min) was performed at the end of the test. The SS HR value will be used in the following equation to estimate the VO2max (mL kg−1 min−1): 15.1 + (21.8 × speed in mph) – 0.327 (SS HR in bpm) – 0.263 (speed × age in y) + 0.00504 (SS HR in bpm × age in y) + 5.98 (gender: female = 0, male = 1) [29].

2.2.2. 1-RM Estimation

1-RM evaluation was estimated by Brzycki’ s regression equation, 1-RM = Kg/(1.0278 − (RM × 0.0278)) [30].

2.3. RT Protocol

All participants performed a 6-min warm-up and 20 min of the RT 3 times per week for 6 weeks as follows: 3 sets of 12 reps (at ~70% 1-RM); 1-min rest periods between sets. The RT training was performed using isotonic machines, i.e., leg press, lat machine, chest press, crunch machine. After 20 min of RT protocol, the subjects performed HIIT or MICT training protocol, respectively.

2.4. HIIT Protocol

A YMCA adapted fitness protocol [31] was used in order to determine the work rate corresponding to the 85% of HRmax for each recruited subject. Briefly, all participants performed the 1st stage, 3 min at a work rate of 150 kg/min. According to the HR measured at the end of the 1st stage, indicated in the rows of Table 3, subjects continued the YMCA protocol by performing the 2nd up to the 5th (if required) stages (each of 3 min) at the workload reported in the corresponding columns (see Table 3). HR was measured during the final 15–30 s of the second and third minute; the work rate continued for an additional minute if the HR values varied more than 5 beats/min between the second and the third minute. The protocol was interrupted when the HR reached the 85% of the predicted HRmax. HRmax was evaluated by Tanaka equation: 208 − (0.7 × age) [32]. At the end of the test, the workload (kgm/min) and HR were recorded, representing the starting point for the personalized HIIT setting protocol.
A Jump box (SportPlus, PLYO, Hamburg, Germany) with adjustable height from 31 to 51 cm for the high-intensity phases and a stepper (Mirafit Stepper deluxe, Norfolk, UK) with height adjustable from 10 to 30 cm for recovery phases were used, respectively.
Starting from the results of YMCA test, HIIT protocol was personalized as follows: 4 steps, 120 s each, composed of 30 s at 140% of the maximum workload (kgm/min) leading to the increase of HR up to 90% of the predicted HRmax and 90 s of active recovery performed at 25% of the maximum workload (kgm/min) allowing to reduce the HR up to 60% of the predicted HRmax. The intensity (kgm/min) was increased by 5% every 2 weeks.

2.5. MICT Protocol

After the RT section, the MICT protocol proceeds for additional 30 min with a continuous cardiovascular training session performed at 60–70% of the predicted HRmax, using a treadmill.

2.6. Data Analysis

Two-way ANOVA was carried-out to compare the effects of HIIT and MICT after the training (T1) on BMI, Fat mass percentage, Abdominal Circumference and VO2max, vs. baseline (T0) in all subjects. Delta (Δ) values percentage were obtained calculating the percentage change at T1 vs. T0 as follows (T1/T0 × 100) − 100 percent. Then the mean Δ values obtained for MICT and HIIT were compared using one-way ANOVA; p-value ≤ 0.05 was considered significant. Data were reported as mean ± SE; data were analyzed using Statview statistical software (version 5.0.1.0; SAS Institute).

3. Results

Seventeen subjects completed the training program; three subjects (1 male and 2 females) belonging to MICT group dropped-out after 2 weeks of sessions. None of the recruited subjects reported any training-related injury.
The HIIT and MICT groups did not differ significantly at baseline either in anthropometric characteristics or in VO2max (Table 4). Subjects belonging to the HIIT or the MICT group participated in 17.6 ± 0.5 and 17.1 ± 0.7 sessions, respectively (p = 0.103), on a total of 18 scheduled sessions.
In order to compare the effects of HIIT vs. MICT protocol on body composition and VO2max in overweight volunteers, we conducted a two-way ANOVA with repeated measures (Figure 1, A1–A4) that revealed improvements in all tested parameters, irrespective to the protocol used. Moreover, two-way ANOVA did not show a significant interaction between training and time (training × time interaction, p > 0.05 for all parameters analyzed), indicating that both training protocols provided similar positive effects on the variables analyzed.
Furthermore, to verify if the two protocols gave different performances, we compared the (Δ, T1−T0) mean percentage for each parameter between HIIT and MICT using the one-way ANOVA (see Table 5). A more effective improvement in the VO2max (p = 0.05) together with a positive trend in fat mass percentage reduction (p = 0.06) in HIIT compared to MICT protocol, was evidenced.

4. Discussion

The main goal of the present study was to compare the effect of a short-term supervised personalized high-intensity interval training (HIIT) vs. standard moderate intensity continuous training (MICT) on body fat percentage, abdominal circumference, BMI and maximal oxygen uptake (VO2max) in young overweight volunteers. In summary, we demonstrated that 6 weeks of HIIT, with reduced training time (40 vs. 60 min)/session and volume of training/week improved VO2max and reduced fat mass percentage more effectively compared to MICT.
The greater VO2max improvement in HIIT group vs. MICT suggests that exercise intensity, more than volume, is a critical aspect of training adaptations [33]. Our findings are in line with previous studies reporting that HIIT training led to a greater improvement in VO2max when compared to traditional circuit training [34] and similarly to that obtained with MICT protocols [35,36,37].
Few and conflicting results on the positive effects of HIIT on the reduction of Body Fat percentage compared to standard MICT protocols have been provided [33,38,39]; other studies showed no significant reduction in Body Fat percentage or improvement in the fat distribution after HIIT protocols in overweight subjects [25,26,33]. Furthermore, a recent meta-analysis, investigating the efficacy of HIIT compared to MICT training protocol on body composition improvement, highlighted that HIIT protocol reduced fat mass percentage, similarly to that obtained using MICT protocol [40].
Finally, the length of intervention time (weeks) is an important factor correlated to the effectiveness of HIIT protocol: in a meta-analysis study, in fact, Batacan et al. [21] assessed that at least 12 weeks of HIIT protocol are needed to achieve significant improvement in cardio-metabolic parameters and in body composition both in normal-weight and obese subjects. Here, we suggested that 6 weeks of personalized HIIT protocol are enough to induce a more effective improvement in VO2max compared to MICT.
Furthermore, our results contribute to the growing evidence reporting that HIIT training turns to be as effective but more time-efficient when compared to MICT protocols [41]. Such newer elements are important given that they are the most commonly existing drawback to regular exercise participation [42].
A limit of the study is the small number of subjects investigated, but the positive results encourage us to test this training in a larger population. Another aspect that should be evaluated is the adherence to the HIIT protocols; in fact, to date, there is still debate about the adherence level to HIIT protocols in different studies [43,44]. Further, the association between HIIT and compliance should represent the starting point of future studies aimed to identify the minimum effective dose of HIIT to improve health status. Such efforts would be important to increase the public health impact of HIITs.

5. Conclusions

Our findings suggest that 6 weeks of personalized HIIT protocol (40 min/session) represent a valid alternative to the standard moderate physical activity training (MICT) (60min/session) in order to improve health-related parameters: BMI, fat mass percentage, abdominal circumference and VO2max in overweight young sedentary subjects. We demonstrated that 6 weeks of personalized HIIT, with reduced training time (40 vs. 60 min)/session and volume of training/week, improved VO2max and reduced fat mass percentage more effectively compared to MICT. A limit of this study is the low number of participants. The positive results encourage us to test this training in a larger population including non-communicable disease patients, in order to better understand the effectiveness of this personalized HIIT protocol on cardio-metabolic parameters and its compliance.

Author Contributions

Conceptualization, L.R.; data curation, A.M. and Andreina Alfieri; formal analysis, A.M. and A.A.; funding acquisition, P.B.; investigation, L.R. and V.B.; methodology, L.R., V.B., A.T. and F.C.; resources, P.B.; supervision, E.I. and S.O.; writing—original draft, A.A.; writing—review and editing, S.O. and P.B. All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded by the grant “Bando di Ateneo per il sostegno alla partecipazione ai bandi di ricerca competitiva per l’anno 2016 (quota C)” from the University of Naples Parthenope, 2016 and by PRIN 2017 cod. RS5M44 UO. 1-P. Buono.

Acknowledgments

The authors are pleased to acknowledge Daniela Vitucci (CEINGE-Biotecnologie avanzate, Naples, Italy) who contributed to perform the statistical analysis of data.

Conflicts of Interest

The authors declared no potential conflict of interest with respect to the research, authorship, and/or publication of this article.

Abbreviations

VO2maxMaximal oxygen uptake
HIITHigh-Intensity Interval Training
MICTModerate-Intensity Continuous Training
BMIBody mass index

References

  1. Gómez-Hernández, A.; Beneit, N.; Díaz-Castroverde, S.; Escribano, O. Differential Role of Adipose Tissues in Obesity and Related Metabolic and Vascular Complications. Int. J. Endocrinol. 2016, 2016, 1216783. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Campbell, W.W.; Kraus, W.E.; Powell, K.E.; Haskell, W.L.; Janz, K.F.; Jakicic, J.M.; Troiano, R.P.; Sprow, K.; Torres, A.; Piercy, K.L.; et al. High-Intensity Interval Training for Cardiometabolic Disease Prevention. Med. Sci. Sports Exerc. 2019, 51, 1220–1226. [Google Scholar] [CrossRef] [PubMed]
  3. American College of Sports Medicine Position Stand. Appropriate Physical Activity Intervention Strategies for Weight Loss and Prevention of Weight Regain for Adults. Med. Sci. Sports Exerc. 2009, 41, 459–471. [Google Scholar] [CrossRef] [PubMed]
  4. Kelsey, M.M.; Zaepfel, A.; Bjornstad, P.; Nadeau, K.J. Age-related consequences of childhood obesity. Gerontology 2014, 60, 222–228. [Google Scholar] [CrossRef] [PubMed]
  5. Annuario statistico italiano: Dati istat 2017. Available online: https://www.istat.it/it/archivio/annuario+statistico+italiano (accessed on 20 November 2019).
  6. American College of Sports Medicine Position Stand. Quantity and Quality of Exercise for Developing and Maintaining Cardiorespiratory, Musculoskeletal, and Neuromotor Fitness in Apparently Healthy Adults: Guidance for Prescribing Exercise. Med. Sci. Sports Exerc. 2011, 43, 1334–1359. [Google Scholar] [CrossRef] [PubMed]
  7. Maillard, F.; Pereira, B.; Boisseau, N. Effect of High-Intensity Interval Training on Total, Abdominal and Visceral Fat Mass: A Meta-Analysis. Sports Med. 2018, 48, 269–288. [Google Scholar] [CrossRef] [PubMed]
  8. Martins, C.; Kazakova, I.; Ludviksen, M.; Mehus, I.; Wisloff, U.; Kulseng, B.; Morgan, L.; King, N. High-Intensity Interval Training and Isocaloric Moderate-Intensity Continuous Training Result in Similar Improvements in Body Composition and Fitness in Obese Individuals. Int. J. Sport Nutr. Exerc. Metab. 2016, 26, 197–204. [Google Scholar] [CrossRef] [PubMed]
  9. Ramos, J.S.; Dalleck, L.C.; Tjonna, A.E.; Beetham, K.S.; Coombes, J.S. The impact of high-intensity interval training versus moderate intensity continuous training on vascular function: A systematic review and meta-analysis. Sports Med. 2015, 45, 679–692. [Google Scholar] [CrossRef] [PubMed]
  10. Wewege, M.; van den Berg, R.; Ward, R.E.; Keech, A. The effects of high-intensity interval training vs.moderate-intensity continuous training on body composition in overweight and obese adults: Asystematic review and meta-analysis. Obes. Rev. 2017, 18, 635–646. [Google Scholar]
  11. Zhang, H.; Tong, T.K.; Qiu, W.; Wang, J.; Nie, J.; He, Y. Effect of high-intensity interval training protocol on abdominal fat reduction in overweight Chinese women: A randomized controlled trial. Kinesiology 2015, 47, 57–66. [Google Scholar]
  12. Alansare, A.; Alford, K.; Lee, S.; Church, T.; Jung, H.C. The Effects of High-Intensity Interval Training vs. Moderate-Intensity Continuous Training on Heart Rate Variability in Physically Inactive Adults. Int. J. Environ. Res. Public Health 2018, 15, 1508. [Google Scholar] [CrossRef] [Green Version]
  13. Bianco, A.; Bellafiore, M.; Battaglia, G.; Paoli, A.; Caramazza, G.; Farina, F.; Palma, A. The Effects of Indoor Cycling Training in Sedentary Overweight Women. J. Sports Med. Phys. Fit. 2010, 50, 159–165. [Google Scholar]
  14. Bartlett, J.D.; Close, G.L.; MacLaren, D.P.; Gregson, W.; Drust, B.; Morton, J.P. High-intensity interval running is perceived to be more enjoyable than moderate-intensity continuous exercise: Implications for exercise adherence. J. Sports Sci. 2011, 29, 547–553. [Google Scholar] [CrossRef] [PubMed]
  15. Monks, L.; Seo, M.W.; Kim, H.B.; Jung, H.C.; Song, J.K. High-intensity interval training and athletic performance in Taekwondo athletes. Int. J. Sports Med. 2019, 40, 503–510. [Google Scholar]
  16. Hatle, H.; Støbakk, P.K.; Mølmen, H.E.; Brønstad, E.; Tjønna, A.E.; Steinshamn, S.; Skogvoll, E.; Wisløff, U.; Ingul, C.B.; Rognmo, Ø. Effect of 24 sessions of high-intensity aerobic interval training carried out at either high or moderate frequency, a randomized trial. PLoS ONE 2014, 9, e88375. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  17. Wells, C.; Edwards, A.; Fysh, M.; Drust, B. Effects of high-intensity running training on soccer-specific fitness in professional male players. Appl. Physiol. Nutr. Metab. 2014, 39, 763–769. [Google Scholar] [CrossRef] [PubMed]
  18. Laursen, P.B.; Shing, C.M.; Peake, J.M.; Coombes, J.S.; Jenkins, D.G. Interval training program optimization in highly trained endurance cyclists. Med. Sci. Sports Exerc. 2002, 34, 1801–1807. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  19. Milanovic, Z.; Sporis, G.; Weston, M. Effectiveness of high intensity interval training (HIT) and continuous endurance training for VO2max improvements: A systematic review and meta-analysis of controlled trials. Sports Med. 2015, 45, 1469–1481. [Google Scholar] [CrossRef] [PubMed]
  20. Paoli, A.; Moro, T.; Marcolin, G.; Neri, M.; Bianco, A.; Palma, A.; Grimaldi, K. High-Intensity Interval Resistance Training (HIRT) Influences Resting Energy Expenditure and Respiratory Ratio in Non-Dieting Individuals. J. Transl. Med. 2012, 10, 237–244. [Google Scholar] [CrossRef]
  21. Batacan, R.B., Jr.; Duncan, M.J.; Dalbo, V.J.; Tucker, P.S.; Fenning, A.S. Effects of high intensity interval training on cardiometabolic health: A systematic review and meta-analysis of intervention studies. Br. J. Sports Med. 2017, 51, 494–503. [Google Scholar] [CrossRef] [PubMed]
  22. Jelleyman, C.; Yates, T.; O’Donovan, G.; Gray, L.J.; King, J.A.; Khunti, K.; Davies, M.J. The effects of high intensity interval training on glucose regulation and insulin resistance: A meta-analysis. Obes. Rev. 2015, 16, 942–961. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Kessler, H.S.; Sisson, S.B.; Short, K.R. The potential for high-intensity interval training to reduce cardiometabolic disease risk. Sports Med. 2012, 42, 489–509. [Google Scholar] [CrossRef] [PubMed]
  24. Foster, C.; Farland, C.V.; Guidotti, F.; Harbin, M.; Roberts, B.; Schuette, J.; Tuuri, A.; Doberstein, S.T.; Porcari, J.P. The Effects of High Intensity Interval Training vs. Steady State Training on Aerobic and Anaerobic Capacity. J. Sports Sci. Med. 2015, 14, 747–755. [Google Scholar] [PubMed]
  25. Caldeira, R.S.; Panissa, V.L.G.; Inoue, D.S.; Campos, E.Z.; Monteiro, P.A.; Giglio, B.M.; Pimentel, G.D.; Hofmann, P.; Lira, F.S. Impact to short-term high intensity intermittent training on different storages of body fat, leptin and soluble leptin receptor levels in physically active non-obese men: A pilot investigation. Clin. Nutr. ESPEN 2018, 28, 186–192. [Google Scholar] [CrossRef] [PubMed]
  26. Keating, S.E.; Machan, E.A.; O’Connor, H.T.; Gerofi, J.A.; Sainsbury, A.; Caterson, I.D.; Johnson, N.A. Continuous exercise but not high intensity interval training improves fat distribution in overweight adults. J. Obes. 2014, 2014, 834865. [Google Scholar] [CrossRef] [PubMed]
  27. Winter, E.M.; Maughan, R.J. Requirements for ethics approvals. J. Sports Sci. 2009, 27, 985. [Google Scholar] [CrossRef] [PubMed]
  28. Katch, F.I.; Katch, V.L.; McArdle, E.D. Evaluation of Body Composition; Fitness Technologies: Santa Barbara, CA, USA, 2000. [Google Scholar]
  29. Ebbeling, C.B.; Ward, A.; Puleo, E.M.; Widrick, J.; Rippe, J.M. Development of a single-stage submaximal treadmill walking test. Med. Sci. Sports Exerc. 1991, 23, 966–973. [Google Scholar] [CrossRef] [PubMed]
  30. Brzycki, M. A Practical Approach to Strength Training; McGraw-Hill: New York, NY, USA, 1998. [Google Scholar]
  31. Golding, L.A. YMC Fitness Testing and Assessment Manual, 4th ed.; Human Kinetics: Champaign, IL, USA, 2000. [Google Scholar]
  32. Tanaka, H.; Monahan, K.D.; Seals, D.R. Age-predicted maximal heart rate revisited. J. Am. Coll. Cardiol. 2001, 37, 153–156. [Google Scholar] [CrossRef] [Green Version]
  33. Macpherson, R.E.K.; Hazell, T.J.; Olver, T.D.; Paterson, D.H.; Lemon, P.W.R. Run Sprint Interval Training Improves Aerobic Performance but Not Maximal Cardiac Output. Med. Sci. Sports Exerc. 2011, 43, 115–122. [Google Scholar] [CrossRef] [PubMed]
  34. Birkett, S.T.; Nichols, S.; Sawrey, R.; Gleadall Siddall, D.; McGregor, G.; Ingle, L. The effects of low volume high intensity interval training and circuit training on maximal oxygen uptake. Sport Sci. Health 2019, 15, 443–451. [Google Scholar] [CrossRef] [Green Version]
  35. Sawyer, B.J.; Tucker, W.J.; Bhammar, D.M.; Ryder, J.R.; Sweazea, K.L.; Gaesser, G.A. Effects of high-intensity interval training and moderate-intensity continuous training on endothelial function and cardiometabolic risk markers in obese adults. J. Appl. Physiol. 2016, 121, 279–288. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  36. Baekkerud, F.H.; Solberg, F.; Leinan, I.M.; Wisloff, U.; Karlsen, T.; Rognmo, O. Comparison of three popular exercise modalities on VO2max in overweight and obese. Med. Sci. Sports Exerc. 2016, 48, 491–498. [Google Scholar] [CrossRef] [PubMed]
  37. McKay, B.R.; Paterson, D.H.; Kowalchuk, J.M. Effect of short term high-intensity interval training vs. continuous training on O2 uptake kinetics, muscle deoxygenation, and exercise performance. J. Appl. Physiol. 2009, 107, 128–138. [Google Scholar] [CrossRef] [PubMed]
  38. Panissa, V.L.G.; Julio, U.F.; Hardt, F.; Kurashima, C.; Lira, F.S.; Takito, M.Y.; Franchini, E. Effect of exercise intensity and mode on acute appetite control in men and women. Appl. Physiol. Nutr. Metab. 2016, 41, 1083–1091. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  39. Trapp, E.G.; Chisholm, D.J.; Freund, J.; Boutcher, S.H. The effects of high- intensity intermittent exercise training on fat loss and fasting insulin levels of young women. Int. J. Obes. 2008, 32, 684–691. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  40. Keating, S.E.; Johnson, N.A.; Mielke, G.I.; Coombes, J.S. A systematic review and meta-analysis of interval training versus moderate-intensity continuous training on body adiposity. Obes. Rev. 2017, 18, 943–964. [Google Scholar] [CrossRef] [PubMed]
  41. Helgerud, J.; Hoydal, K.; Wang, E.; Karlsen, T.; Berg, P.; Bjerkaas, M.; Simonsen, T.; Helgesen, C.; Hjorth, N.; Bach, R.; et al. Aerobic High-Intensity Intervals Improve VO2max More Than Moderate Training. Med. Sci. Sports Exerc. 2007, 39, 665–671. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Gibala, M.J.; Little, J.P.; Macdonald, M.J.; Hawley, J.A. Physiological adaptations to low-volume, high-intensity interval training in health and disease. J. Physiol. 2012, 590, 1077–1084. [Google Scholar] [CrossRef] [PubMed]
  43. Vella, C.A.; Taylor, K.; Drummer, D. High-intensity interval and moderate-intensity continuous training elicit similar enjoyment and adherence levels in overweight and obese adults. Eur. J. Sport Sci. 2017, 17, 1203–1211. [Google Scholar] [CrossRef] [PubMed]
  44. Reljic, D.; Lampe, D.; Wolf, F.; Zopf, Y.; Herrmann, H.J.; Fischer, J. Prevalence and predictors of dropout from high-intensity interval training in sedentary individuals: A meta-analysis. Scand. J. Med. Sci. Sports 2019, 29, 1288–1304. [Google Scholar] [CrossRef] [PubMed]
Jfmk 05 00041 g001 550
Figure 1. Effects of moderate intensity continuous training (MICT) and HIIT protocol on BMI, Abdominal Circumference (AC), Fat mass percentage and VO2max. (A1–A4): Line charts report two-way ANOVA with repeated measures at baseline (T0) and after 6 weeks of training (T1) with BMI (A1), Body Fat mass percentage (A2), Abdominal circumference, AC (A3) and VO2max (A4) as dependent variables. All values are expressed as the mean ± SE. No significant interaction (p > 0.05) between training and time (training × time interaction) for all parameters analyzed were found.
Figure 1. Effects of moderate intensity continuous training (MICT) and HIIT protocol on BMI, Abdominal Circumference (AC), Fat mass percentage and VO2max. (A1–A4): Line charts report two-way ANOVA with repeated measures at baseline (T0) and after 6 weeks of training (T1) with BMI (A1), Body Fat mass percentage (A2), Abdominal circumference, AC (A3) and VO2max (A4) as dependent variables. All values are expressed as the mean ± SE. No significant interaction (p > 0.05) between training and time (training × time interaction) for all parameters analyzed were found.
Jfmk 05 00041 g001
Table
Table 1. Girth measurement sites according to age and gender.
Table 1. Girth measurement sites according to age and gender.
Age (y)GenderSite ASite BSite C
18–26MalesRight upper armAbdomenRight forearm
18–26FemalesAbdomenRight thighRight forearm
27–50MalesButtocksAbdomenRight forearm
27–50FemalesAbdomenRight thighRight calf
Table
Table 2. Age and gender-specific equations to predict body fat percentage.
Table 2. Age and gender-specific equations to predict body fat percentage.
Age (y)GenderEquations
18–26MalesConstant A + Constant B − Constant C − 10.2
18–26FemalesConstant A + Constant B − Constant C – 19.6
27–50MalesConstant A + Constant B − Constant C – 15
27–50FemalesConstant A + Constant B − Constant C – 19.6
Table
Table 3. YMCA adapted fitness protocol used for setting personalized HIIT protocol.
Table 3. YMCA adapted fitness protocol used for setting personalized HIIT protocol.
1st Stage 150 kgm/min for 3 min
HR: <80 bpmHR: 80-89 bpmHR: 90-100 bpmHR: >100 bpm
2nd stage750 kgm/min600 kgm/min450 kgm/min300 kgm/min
3rd stage900 kgm/min750 kgm/min600 kgm/min450 kgm/min
4th stage1050 kgm/min900 kgm/min750 kgm/min600 kgm/min
5th stage1200 kgm/min1050 kgm/min900 kgm/min750 kgm/min
Table
Table 4. Baseline characteristics of the two groups of volunteers participating in HIIT or MICT protocols.
Table 4. Baseline characteristics of the two groups of volunteers participating in HIIT or MICT protocols.
ParametersHIITMICT
Gender (M/F)3M/7F4M/6F
Age (y)24 ± 326 ± 2
Height (m)1.65 ± 0.121.68 ± 0.09
Weight (kg)71.6 ± 10.973.7 ± 7.4
BMI (kg m−2)26.1 ± 1.125.9 ± 0.9
Body Fat percentage (%)26.3 ± 325.2 ± 2.9
Abdominal circumference (cm) 92.1 ± 6.788.2 ± 4.3
VO2max (mL kg−1 min−1)38.6 ± 2.337.6 ± 2.1
Values were represented as mean ± SD. No significant differences between groups at baseline were evidenced. BMI= Body Mass Index.
Table
Table 5. Comparison of Δ (T1−T0) mean percentage between MICT and HIIT for BMI, Fat mass %, Abdominal Circumference and VO2max. Analysis was performed using one-way ANOVA; for each parameter, we indicated the mean percentage (Δ Mean percentage), the Standard Error (SE) and p value. * p-value ≤ 0.05.
Table 5. Comparison of Δ (T1−T0) mean percentage between MICT and HIIT for BMI, Fat mass %, Abdominal Circumference and VO2max. Analysis was performed using one-way ANOVA; for each parameter, we indicated the mean percentage (Δ Mean percentage), the Standard Error (SE) and p value. * p-value ≤ 0.05.
TrainingΔ Mean PercentageSEpValue
BMI (Kg/m2)MICT
HIIT		−4.3
−3.4		0.9
0.3		0.28
Fat mass %MICT
HIIT		−5.7
−8.2		0.7
0.9		0.06
Abdominal Circumference (cm)MICT
HIIT		−1.6
−1.1		0.3
0.4		0.30
VO2max (mL/Kg/min)MICT
HIIT		+3.2
+5.7		0.5
0.9		0.05 *

Share and Cite

MDPI and ACS Style

Russomando, L.; Bono, V.; Mancini, A.; Terracciano, A.; Cozzolino, F.; Imperlini, E.; Orrù, S.; Alfieri, A.; Buono, P. The Effects of Short-Term High-Intensity Interval Training and Moderate Intensity Continuous Training on Body Fat Percentage, Abdominal Circumference, BMI and VO2max in Overweight Subjects. J. Funct. Morphol. Kinesiol. 2020, 5, 41. https://doi.org/10.3390/jfmk5020041

AMA Style

Russomando L, Bono V, Mancini A, Terracciano A, Cozzolino F, Imperlini E, Orrù S, Alfieri A, Buono P. The Effects of Short-Term High-Intensity Interval Training and Moderate Intensity Continuous Training on Body Fat Percentage, Abdominal Circumference, BMI and VO2max in Overweight Subjects. Journal of Functional Morphology and Kinesiology. 2020; 5(2):41. https://doi.org/10.3390/jfmk5020041

Chicago/Turabian Style

Russomando, Luca, Vincenzo Bono, Annamaria Mancini, Alessia Terracciano, Francesca Cozzolino, Esther Imperlini, Stefania Orrù, Andreina Alfieri, and Pasqualina Buono. 2020. "The Effects of Short-Term High-Intensity Interval Training and Moderate Intensity Continuous Training on Body Fat Percentage, Abdominal Circumference, BMI and VO2max in Overweight Subjects" Journal of Functional Morphology and Kinesiology 5, no. 2: 41. https://doi.org/10.3390/jfmk5020041

APA Style

Russomando, L., Bono, V., Mancini, A., Terracciano, A., Cozzolino, F., Imperlini, E., Orrù, S., Alfieri, A., & Buono, P. (2020). The Effects of Short-Term High-Intensity Interval Training and Moderate Intensity Continuous Training on Body Fat Percentage, Abdominal Circumference, BMI and VO2max in Overweight Subjects. Journal of Functional Morphology and Kinesiology, 5(2), 41. https://doi.org/10.3390/jfmk5020041

Article Metrics

Back to TopTop