Is it Time to Rethink Our Weight Loss Paradigms?

Abstract

Strategies aiming to promote weight loss usually include anything that results in an increase in energy expenditure (exercise) or a decrease in energy intake (diet). However, the probability of losing weight is low and the probability of sustained weight loss is even lower. Herein, we bring some questions and suggestions about the topic, with a focus on exercise interventions. Based on the current evidence, we should look at how metabolism changes in response to interventions instead of counting calories, so we can choose more efficient models that can account for the complexity of human organisms. In this regard, high-intensity training might be particularly interesting as a strategy to promote fat loss since it seems to promote many physiological changes that might favor long-term weight loss. However, it is important to recognize the controversy of the results regarding interval training (IT), which might be explained by the large variations in its application. For this reason, we have to be more judicious about how exercise is planned and performed and some factors, like supervision, might be important for the results. The intensity of exercise seems to modulate not only how many calories are expended after exercise, but also where they came from. Instead of only estimating the number of calories ingested and expended, it seems that we have to act positively in order to create an adequate environment for promoting healthy and sustainable weight loss.

Full text

Biology 2020, 9, 70; doi:10.3390/biology9040070 www.mdpi.com/journal/biology
Opinion
Is it Time to Rethink Our Weight Loss Paradigms?
Paulo Gentil
1,
*, Ricardo Borges Viana
1
, João Pedro Naves
1
, Fabrício Boscolo Del Vecchio
2
,
Victor Coswig
3
, Jeremy Loenneke
4
and Claudio André Barbosa de Lira
1
1
College of Physical Education and Dance, Federal University of Goiás, Goiânia 74690-900, Brazil;
vianaricardoborges@hotmail.com (R.B.V.); jpanaves12@gmail.com (J.P.N.);
andre.claudio@gmail.com (C.A.B.L.)
2
School of Physical Education, Federal University of Pelotas, Pelotas 96055-630, Brazil;
fabricioboscolo@gmail.com
3
College of Physical Education, Federal University of Pará, Castanhal 68746-360, Brazil; vcoswig@gmail.com
4
Department of Health, Exercise Science, and Recreation Management, Kevser Ermin Applied Physiology
Laboratory, The University of Mississippi, Oxford, MS 38677-1848, USA; jploenne@olemiss.edu
* Correspondence: paulogentil@hotmail.com; Tel.: +55 62 3521-1021
Received: 22 March 2020; Accepted: 31 March 2020; Published: 2 April 2020
Abstract: Strategies aiming to promote weight loss usually include anything that results in an
increase in energy expenditure (exercise) or a decrease in energy intake (diet). However, the
probability of losing weight is low and the probability of sustained weight loss is even lower.
Herein, we bring some questions and suggestions about the topic, with a focus on exercise
interventions. Based on the current evidence, we should look at how metabolism changes in
response to interventions instead of counting calories, so we can choose more efficient models that
can account for the complexity of human organisms. In this regard, high-intensity training might be
particularly interesting as a strategy to promote fat loss since it seems to promote many
physiological changes that might favor long-term weight loss. However, it is important to recognize
the controversy of the results regarding interval training (IT), which might be explained by the large
variations in its application. For this reason, we have to be more judicious about how exercise is
planned and performed and some factors, like supervision, might be important for the results. The
intensity of exercise seems to modulate not only how many calories are expended after exercise, but
also where they came from. Instead of only estimating the number of calories ingested and
expended, it seems that we have to act positively in order to create an adequate environment for
promoting healthy and sustainable weight loss.
Keywords: interval training; resistance training; body composition; aerobic training
1. Problem Statement
Although being overweight and/or obese are associated with numerous health risks, the
prevalence of both are continuing to increase worldwide [1]. Obesity occurs when one’s energy
expenditure is less than their energy intake, which creates an imbalance in energy. Other nutritional
aspects, like the type of carbohydrates and fats as well as micronutrients, might also be considered
[2]. If sustained, body fat will begin to accumulate. The treatment would include anything that results
in an increase in energy expenditure (exercise) or a decrease in energy intake (diet). However, despite
the short-term success of both exercise and diet, neither strategy seems to be effective for sustaining
long-term changes in most individuals. The estimated weight loss for diet and/or exercise is
approximately 2 kg by the end of two years in overweight and obese people [3,4]. Consequently, the
probability of an obese individual attaining a normal weight is low and the probability of sustained
weight loss is even lower. For example, Fildes et al. [5] estimated that the probability of a man with
a body mass index between 40 and 44.9 kg × m
-2
attaining a normal weight is only 1 in 1290, or 0.08%.

Biology 2020, 9, 70 2 of 7
Although this study did not control for exercise and diet, it provides important information about
the difficulty in promoting sustainable weight loss. The objective of the present study is to present
some reflections and invite the reader to critically analyze the strategies used for promoting weight
loss. Herein, we highlight the importance of promoting the choice of exercise and supervision for
those seeking or working with those seeking to sustain long-term changes in weight status/body fat.
2. Current Support for Exercise
In a recent article published by our group [6], 49 women were randomly assigned to perform
two types of interval training (IT), high-intensity interval training (HIIT) and sprint interval training
(SIT), and found positive changes in their adiposity measures (assessed by the sum of skinfolds)
without changing their nutritional habits (assessed by 24-h dietary recalls). Here, we further explore
if the results obtained were related to the nutritional changes. We tested if the participants that had
higher decreases in caloric intake would show higher decreases in adiposity. To this purpose, we
calculated the correlations between the changes in the nutritional and anthropometric variables using
a bi-variated Pearson correlation model (Table 1). We also calculated regression models for the
dependent variables (changes in anthropometric variables) using selected independent variables
(changes in caloric ingestion). According to our results, there was no correlation between the changes
in anthropometric measures and changes in caloric intake. Therefore, the changes in anthropometric
measures could not be explained by nutritional changes.
Table 1. Correlations between changes in nutritional factors and changes in anthropometric
measures.
Variables
Δ Energy Intake
Δ Carbohydrate Intake
Δ Protein Intake
Δ Lipid Intake
r
p
r
p
r
p
r
p
Δ body weight
0.06
0.7
0.19
0.18
−0.06
0.67
−0.01
0.97
Δ Body mass index
0.06
0.66
0.20
0.16
−0.06
0.69
−0.01
0.97
Δ waist circumference
0.17
0.25
0.17
0.24
0.21
0.14
0.22
0.14
Δ sum of ST
−0.20
0.17
−0.16
0.28
−0.05
0.73
−0.23
0.11
Δ triceps ST
−0.12
0.42
−0.06
0.71
−0.10
0.49
−0.11
0.45
Δ subescapular ST
−0.22
0.12
−0.22
0.14
−0.03
0.85
−0.21
0.15
Δ suprailiac ST
−0.13
0.36
−0.07
0.63
−0.01
0.97
−0.22
0.12
Δ abdominal ST
−0.06
0.70
−0.06
0.67
−0.03
0.87
−0.14
0.35
Δ thigh ST
−0.25
0.09
−0.24
0.10
−0.08
0.61
−0.19
0.18
ST = skinfold thickness; r = Pearson correlation coefficient, p = level of significance.
By performing individual analyses, we noted that some participants increased their caloric
intake and still achieved improvements in their anthropometric measures. In addition, there were
some extreme cases like a participant that increased her caloric intake by more than 100% and
decreased the sum of skinfold thickness by 20%. Another interesting example is a participant that
increased her caloric intake by 35% and decreased the sum of skinfolds by 35%. On the other hand,
another participant decreased her caloric intake by 24% and showed a slight increase of 1% in the
sum of skinfolds.
We are aware that these analyses have some limitations such as the method used to assess caloric
intake; however, the method is widely used and has been shown to be reproductible and previously
validated [7–10]. We also do not have direct measures of the physical activity performed outside the
training sessions; however, the participants were constantly asked about their physical activity habits
throughout the experimental period to check if there were any relevant changes.
It is important to note that we were not the first group to describe decreases in the markers of
adiposity or body composition in response to IT in the absence of caloric restriction [11–14]. Whilst
some might find it intuitive that performing exercise would lead to fat loss due to the higher energy
expenditure, previous studies showed that when energy intake was controlled, the addition of
moderate-intensity exercise did not promote fat loss when compared with a control group, with [15–
17] or without dietary interventions [16,18–20]. Even when there are significant changes, the

Biology 2020, 9, 70 3 of 7
magnitude of these changes is of limited biological significance [21,22]. The reason might be in the
metabolic adaptations that occur in response to the interventions.
Some authors suggested that the metabolic changes that accompany a prolonged negative
energy balance might be an important determinant of the ability to lose body fat [23]. In line with
this, Reinhart et al. [24] reported that the success of dietary weight loss efforts is influenced by the
energy expenditure response to caloric restriction. The authors classified some people as having a
“thrifty” phenotype; that is, having large reductions in 24-h energy expenditure during fasting and
smaller increases with overfeeding, while individuals with the opposite behavior were classified as
“spendthrift”. According to the authors, greater decreases in energy expenditure during caloric
restriction predict less weight loss, indicating the presence of thrifty and spendthrift phenotypes in
obese humans. In agreement with this, Byrne et al. [25] suggested that, although lower-than-expected
weight loss is often attributed to incomplete adherence to prescribed interventions, there are other
factors that might influence the results, such as metabolic downregulation. In their study, they
reported that a progressive metabolic adaptation in response to diet and exercise resulted in weight
loss that was lower than predicted. Additionally, Fothergill et al. [26] also reported on metabolic
adaptation when accompanying people that were submitted to an extreme weight loss program, and
suggested that to obtain success in long-term weight loss, it is necessary to combat this metabolic
adaptation so to avoid the counter-effects that mitigate the efforts to reduce body weight.
Regarding physical activity specifically, Pontzer [27] suggests that the current model (called
additive or factorial) treats total energy expenditure simply as a product of body size and physical
activity without considering the potential changes in energy allocation in response to the variations
in activity levels. Therefore, the author proposes a model where energy expenditure adapts
dynamically to the variations in physical activity to maintain total energy expenditure within some
narrow physiological range.
In line with this, Westerterp et al. [28] investigated men and women that participated in a 40-
week preparation for a half-marathon. The total energy expenditure and sleeping metabolic rate were
measured at the 8th, 20th, and 40th weeks. According to the results, at the 20th and 40th weeks, total
energy expenditure leveled off in both men and women, despite increasing exercise workloads and
an increase in fat-free mass. The reductions in the sleeping metabolic rates suggest that metabolic
adaptations occurred in response to the increased physical activity. Interestingly, previous studies
found no increase in fat loss when aerobic moderate-intensity exercise was added to a diet, and
reported that the groups that performed exercise showed a reduction in their resting metabolic rates
[29,30].
So, instead of making people spend more calories through exercise, maybe we have to think on
how to promote metabolic changes in order to overcome these physiological adaptations above-
mentioned. In this case, not all exercises are equal.
In this regard, high-intensity training might be particularly interesting as a strategy to promote
fat loss [31]. Irrespective to the number of calories spent during training, higher intensity exercise
seems to promote many physiological changes that might favor long-term weight loss. For example,
previous studies have shown that IT is able to promote the upregulation of important enzymes
associated with glycolysis and beta-oxidation pathways [32–35], which occur to a greater extent than
with moderate-intensity continuous exercise [34,35]. Interestingly, previous studies showed that
some of these enzymes are under expressed in obese and ex-obese individuals [36,37], which might
be related to energy expenditure and fat oxidation during resting [38,39]. Moreover, in the hours
proceeding high-intensity exercise, there are noticeable increases in fat oxidation, which occurs either
with IT [40–43] or resistance training [44–48]. Therefore, the intensity of exercise seems to modulate
not only how many calories are expended after exercise, but also where they came from.
On the other hand, low to moderate continuous training has been shown to induce increases in
fat synthesis after its cessation [49–54]. Whilst this does not mean that low- to moderate-intensity
exercise will make people gain fat, this suggests that the metabolic adaptation to this form of exercise
might, at least partially, compensate for the fat oxidized during exercise. This, summed with the
reduction in nonphysical activity energy expenditure, might interfere with long-term fat loss.

Biology 2020, 9, 70 4 of 7
Notwithstanding, long-term effects are obviously dependent on long-term adherence. In fact,
this has been one of the main arguments to encourage low to moderate continuous training
prescription and is based mainly on affective responses [55]. However, recent evidence showed that
IT showed beneficial affective responses in both normal weight and overweight/obese people [56],
which would be even better if the wide possibilities of IT were considered in training prescriptions
to fit different people’s preferences [57]. Taken together, positive psychological and metabolic
responses may explain long-term positive effects on unsupervised IT programs [58].
3. Considerations Moving Forward
So, the question is: could IT be the magic bullet for fat loss? To answer this, we conducted a
systematic review and meta-analysis [31]. The results showed that IT promotes a greater reduction
in absolute fat mass than moderate-intensity training, and SIT might be particularly interesting in
that regard. However, it is important to recognize the controversy of the results regarding IT, which
might be explained by the large variations in its application [59]. For this reason, we have to be more
judicious about how exercise is planned and performed in order to guarantee that it will promote the
necessary metabolic changes. Interestingly, in our article, supervision was a key factor, which might
reinforce the argument that IT protocols need to be well-controlled. Moreover, it is important to
observe that supervision is not usually provided in most studies involving other forms of exercise,
which might also help to explain negative results. Based on the current evidence, it is our opinion
that we must rethink the approaches used to promote fat loss. It is necessary to revise the
mathematical model that pretends to fight overweight and obesity by simply increasing physical
activity and/or decreasing caloric ingestion, since it can lead to frustrating results and induce
unsustainable and ineffective behaviors. Based on the current evidence, we should look at how the
metabolism changes in response to interventions instead of counting calories, so we can choose more
efficient models that can account for the complexity of human organisms.
4. Conclusions
It is not our aim to present a final solution for fat loss, nor do we pretend to deny the importance
of analyzing caloric expenditure. However, it seems that the human metabolism changes in response
to what is done. Therefore, if we would like to calculate calories, it would be necessary to constantly
evaluate our metabolic state in order to calculate our dietary needs, which is unfeasible. Therefore,
instead of only estimating the number of calories ingested and expended, it seems that we have to
act positively in order to create an adequate environment for promoting healthy and sustainable
weight loss.
Author Contributions: Conceptualization, P.G. and F.B.D.V.; writing—review and editing, P.G.; R.B.V; J.P.N;
F.B.D.V; V.C; J.L.; C.A.B.L. All authors have read and agreed to the published version of the manuscript.
Funding: P.G receives a research grant from CNPq
Conflicts of Interest: The authors declare no conflict of interest.
References
1. NCD Risk Factor Collaboration. Trends in adult body-mass index in 200 countries from 1975 to 2014: A
pooled analysis of 1698 population-based measurement studies with 19·2 million participants. Lancet 2016,
387, 1377–1396, doi:10.1016/S0140-6736(16)30054-X.
2. Hernandez-Rodas, M.C.; Valenzuela, R.; Videla, L.A. Relevant Aspects of Nutritional and Dietary
Interventions in Non-Alcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2015, 16, 25168–25198.
3. Booth, H.P.; Prevost, T.A.; Wright, A.J.; Gulliford, M.C. Effectiveness of behavioural weight loss
interventions delivered in a primary care setting: A systematic review and meta-analysis. Fam. Pract. 2014,
31, 643–653, doi:10.1093/fampra/cmu064.
4. Dom;rowski, S.U.; Avenell, A.; Sniehott, F.F. Behavioural Interventions for Obese Adults with Additional
Risk Factors for Morbidity: Systematic Review of Effects on Behaviour, Weight and Disease Risk Factors.
Obes Facts 2010, 3, 377–396, doi:10.1159/000323076.

Biology 2020, 9, 70 5 of 7
5. Fildes, A.; Charlton, J.; Rudisill, C.; Littlejohns, P.; Prevost, A.T.; Gulliford, M.C. Probability of an Obese
Person Attaining Normal Body Weight: Cohort Study Using Electronic Health Records. Am. J. Public Health
2015, 105, e54–e59, doi:10.2105/AJPH.2015.302773.
6. Naves, J.P.A.; Viana, R.B.; Rebelo, A.C.S.; de Lira, C.A.B.; Pimentel, G.D.; de Oliveira, J.C.; Ramirez-
Campillo, R.; Gentil, P. Effects of High-Intensity Interval Training vs. Sprint Interval Training on
Anthropometric Measures and Cardiorespiratory Fitness in Healthy Young Women. Front. Physiol. 2018, 9,
1738, doi:10.3389/fphys.2018.01738.
7. De Keyzer. W.; Bracke, T.; McNaughton, S.A.; Parnell, W.; Moshfegh, A.J.; Pereira, R.A.; Haeng-Shin, L.;
Veer, P.V.; De Henauw, S.; Huybrechts, I. Cross-continental comparison of national food consumption
survey methods--a narrative review. Nutrients 2015, 7, 3587–3620, doi:10.3390/nu7053587.
8. Conway, J.M.; Ingwersen, L.A.; Moshfegh, A.J. Accuracy of dietary recall using the USDA five-step
multiple-pass method in men: An observational validation study. J. Am. Diet. Assoc. 2004, 104, 595–603,
doi:10.1016/j.jada.2004.01.007.
9. Salvador Castell, G.; Serra-Majem, L.; Ribas-Barba, L. What and how much do we eat? 24-hour dietary
recall method. Nutr. Hosp. 2015, 31, 46–48, doi:10.3305/nh.2015.31.sup3.8750.
10. Shim, J.S.; Oh, K.; Kim, H.C. Dietary assessment methods in epidemiologic studies. Epidemiol. Health 2014,
36, e2014009, doi:10.4178/epih/e2014009.
11. 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.
12. Racil, G.; Ben Ounis, O. Hammouda, O.; Kallel, A.; Zouhal, H.; Chamari, K.; Amri, M. Effects of high vs.
moderate exercise intensity during interval training on lipids and adiponectin levels in obese young
females. Eur. J. Appl. Physiol. 2013, 113, 2531–2540, doi:10.1007/s00421-013-2689-5.
13. Racil, G.; Zouhal, H.; Elmontassar, W.; Ben Abderrahmane, A.; De Sousa, M.V.; Chamari, K.; Amri, M.;
Coquart, J.B. Plyometric exercise combined with high-intensity interval training improves metabolic
abnormalities in young obese females more so than interval training alone. Appl. Physiol. Nutr. Metab. 2016,
41, 103–109, doi:10.1139/apnm-2015-0384.
14. Higgins, S.; Fedewa, M.V.; Fedewa, M.V.; Hathaway, E.D.; Schmidt, M.D.; Evans, E.M. Sprint interval and
moderate-intensity cycling training differentially affect adiposity and aerobic capacity in overweight
young-adult women. Appl. Physiol. Nutr. Metab. 2016, 41, 1177–1183, doi:10.1139/apnm-2016-0240.
15. van Aggel-Leijssen, D.P.; Saris, W.H.; Hul, G.B.; van Baak, M.A. Short-term effects of weight loss with or
without low-intensity exercise training on fat metabolism in obese men. Am. J. Clin. Nutr. 2001, 73, 523–531,
doi:10.1093/ajcn/73.3.523.
16. Nieman, D.C.; Brock, D.W.; Butterworth, D.; Utter, A.C.; Nieman, C.C. Reducing diet and/or exercise
training decreases the lipid and lipoprotein risk factors of moderately obese women. J. Am. Coll. Nutr. 2002,
21, 344–350.
17. Bond Brill, J.; Perry, A.C.; Parker, L.; Robinson, A.; Burnett, K. Dose-response effect of walking exercise on
weight loss. How much is enough? Int. J. Obes. Relat. Metab. Disord. 2002, 26, 1484–1493,
doi:10.1038/sj.ijo.0802133.
18. Ring-Dimitriou, S.; von Duvillard, S.P.; Paulweber, B.; Stadlmann, M.; LeMura, L.M.; Peak, K.; Mueller, E.
Nine months aerobic fitness induced changes on blood lipids and lipoproteins in untrained subjects versus
controls. Eur. J. Appl. Physiol. 2007, 99, 291–299.
19. Evans, E.M.; Saunders, M.J.; Spano, M.A.; Arngrimsson, S.A.; Lewis, R.D.; Cureton, K.J. Body-composition
changes with diet and exercise in obese women: A comparison of estimates from clinical methods and a 4-
component model. Am. J. Clin. Nutr. 1999, 70, 5–12.
20. Hardman, A.E.; Jones, P.R.M.; Norgan, N.G.; Hudson, A. Brisk walking improves endurance fitness
without changing body fatness in previously sedentary women. Eur. J. Appl. Physiol. Occup. Physiol. 1992,
65, 354–359.
21. Wilmore, J.H.; Després, J.P.; Stanforth, P.R.; Mandel, S.; Rice, T.; Gagnon, J.; Leon, A.S.; Rao, D.; Skinner,
J.S.; Bouchard, C. Alterations in body weight and composition consequent to 20 wk of endurance training:
The HERITAGE Family Study. Am. J. Clin. Nutr. 1999, 70, 346–352, doi:10.1093/ajcn/70.3.346.
22. Friedenreich, C.M.; Neilson, H.K.; Reilly, R.O.; Duha, A.; Yutaka, Y.; Morielli, A.R.; Adams, S.C.; Courneya,
K.S. Effects of a High vs Moderate Volume of Aerobic Exercise on Adiposity Outcomes in Postmenopausal
Women: A Randomized Clinical Trial. JAMA Oncol. 2015, 1, 766–776, doi:10.1001/jamaoncol.2015.2239.

Biology 2020, 9, 70 6 of 7
23. Tremblay, A.; Royer, M.M.; Chaput, J.P.; Doucet, E. Adaptive thermogenesis can make a difference in the
ability of obese individuals to lose body weight. Int. J. Obes. 2013, 37, 759–764,
doi:10.1038/ijo.2012.124ijo2012124.
24. Reinhardt, M.; Thearle, M.S.; Ibrahim, M.; Hohenadel, M.G.; Bogardus, C.; Krakoff, J.; Votruba, S.B. A
Human Thrifty Phenotype Associated With Less Weight Loss During Caloric Restriction. Diabetes 2015, 64,
2859–2867, doi:10.2337/db14-1881.
25. Byrne, N.M.; Wood, R.E.; Schutz,Y.; Hills, A.P. Does metabolic compensation explain the majority of less-
than-expected weight loss in obese adults during a short-term severe diet and exercise intervention? Int. J.
Obes. (London) 2012, 36, 1472–1478, doi:10.1038/ijo.2012.109.
26. Fothergill, E.; Guo, J.; Howard, L.; Kerns, J.C.; Knuth, N.D.; Brychta, R.; Chen, K.Y.; Skarulis, M.C.; Walter,
M.; Walter, P.J.; et al. Persistent metabolic adaptation 6 years after “The Biggest Loser” competition. Obesity
2016, 24, 1612–1619, doi:10.1002/oby.21538.
27. Pontzer, H. Constrained Total Energy Expenditure and the Evolutionary Biology of Energy Balance. Exerc.
Sport Sci. Rev. 2015, 43, 110–116, doi:10.1249/JES.0000000000000048.
28. Westerterp, K.R.; Meijer, G.A.; Janssen, E.M.E.; Saris, W.H.M.; Hoor, F.T. Long-term effect of physical
activity on energy balance and body composition. Br. J. Nutr. 1992, 68, 21–30.
29. Phinney, S.D.; LaGrange, B.M.; O’Connell, M.; Jr Danforth, E. Effects of aerobic exercise on energy
expenditure and nitrogen balance during very low calorie dieting. Metabolism 1988, 37, 758–765.
30. Heymsfield, S.B.; Casper, K.; Hearn, J.; Guy, D. Rate of weight loss during underfeeding: Relation to level
of physical activity. Metabolism 1989, 38, 215–223.
31. Viana, R.B.; Naves, J.P.A.; Coswig, V.S.; de Lira, C.A.B.; Steele, J.; Fisher, J.P.; Jentil, P. Is interval training
the magic bullet for fat loss? A systematic review and meta-analysis comparing moderate-intensity
continuous training with high-intensity interval training (HIIT). Br. J. Sports Med. 2019,
doi:10.1136/bjsports-2018-099928.
32. Rodas, G.; Ventura, J.L.; Cadefau, J.A.; Cusso, R.; Parra, J. A short training programme for the rapid
improvement of both aerobic and anaerobic metabolism. Eur. J. Appl. Physiol. 2000, 82, 480–486.
33. MacDougall, J.D.; Hicks, A.L.; MacDonald, J.R.; McKelvie, R.S.; Green, H.J.; Smith, K.M. Muscle
performance and enzymatic adaptations to sprint interval training. J. Appl. Physiol. 1998, 84, 2138–2142.
34. Tremblay, A., Simoneau, J.A.; Bouchard, C. Impact of exercise intensity on body fatness and skeletal muscle
metabolism. Metabolism 1994, 43, 814–818, doi:0026-0495(94)90259-3.
35. Tjønna, A.E.; Lee, S.J.; Rognmo, ø; Stølen, T.O.; Bye, A.; Haram, P.M.; Loennechen, J.P.; AI-Share, Q.Y.;
Skogvoll, E.; Slørdahl, S.A.; et al. Aerobic interval training versus continuous moderate exercise as a
treatment for the metabolic syndrome: A pilot study. Circulation 2008, 118, 346–354,
doi:10.1161/CIRCULATIONAHA.108.772822.
36. Raben, A.; Mygind, E.; Astrup, A. Lower activity of oxidative key enzymes and smaller fiber areas in
skeletal muscle of postobese women. Am. J. Physiol. 1998, 275, E487–E494.
37. Simoneau, J.A.; Veerkamp, J.H.; Turcotte, L.P.; Kelley, D.E. Markers of capacity to utilize fatty acids in
human skeletal muscle: Relation to insulin resistance and obesity and effects of weight loss. Faseb. J. 1999,
13, 2051–2060.
38. Zurlo, F., Nemeth, P.M.; Choksi, R.M.; Sesodia, S.; Ravussin, E. Whole-body energy metabolism and
skeletal muscle biochemical characteristics. Metabolism 1994, 43, 481–486.
39. Doucet, E.; Tremblay, A.; Simoneau, J.A.; Joanisse, D.R. Skeletal muscle enzymes as predictors of 24-h
energy metabolism in reduced-obese persons. Am. J. Clin. Nutr. 2003, 78, 430–435.
40. Whyte, L.J.; Ferguson, C.; Wilson, J.; Scott, R.A.; Gill, J.M.R. Effects of single bout of very high-intensity
exercise on metabolic health biomarkers in overweight/obese sedentary men. Metabolism 2013, 62, 212–219,
doi:10.1016/j.metabol.2012.07.019.
41. Kiens, B.; Richter, E.A. Utilization of skeletal muscle triacylglycerol during postexercise recovery in
humans. Am. J. Physiol. 1998, 275, E332–E337.
42. Islam, H., Townsend, L.K.; Hazell, T.J. Modified sprint interval training protocols. Part I. Physiological
responses. Appl. Physiol. Nutr. Metab. 2017, 42, 339–346, doi:10.1139/apnm-2016-0478.
43. Withers, R.T., Sherman, W.M.; Clark, D.G.; Esselbach, P.C.; Nolan, S.R.; Mackay, M.H.; Brinkman, M.
Muscle metabolism during 30, 60 and 90 s of maximal cycling on an air-braked ergometer. Eur. J. Appl.
Physiol. Occup. Physiol. 1991, 63, 354–362, doi:10.1007/BF00364462.

Biology 2020, 9, 70 7 of 7
44. Binzen, C.A.; Swan, P.D.; Manore, M.M. Postexercise oxygen consumption and substrate use after
resistance exercise in women. Med. Sci. Sport Exerc. 2001, 33, 932–938.
45. Melby, C.; Scholl, C.; Edwards, G.; Bullough, R. Effect of acute resistance exercise on postexercise energy
expenditure and resting metabolic rate. J. Appl. Physiol. 1993, 75, 1847–1853.
46. Osterberg, K.L.; Melby, C.L. Effect of acute resistance exercise on postexercise oxygen consumption and
resting metabolic rate in young women. Int. J. Sport Nutr. Exerc. Metab. 2000, 10, 71–81.
47. Schuenke, M.D.; Mikat, R.P.; McBride, J.M. Effect of an acute period of resistance exercise on excess post-
exercise oxygen consumption: Implications for body mass management. Eur. J. Appl. Physiol. 2002, 86, 411–
417.
48. 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, doi:10.1186/1479-5876-10-2371479-5876-10-237.
49. Kump, D.S.; Booth, F.W. Alterations in insulin receptor signalling in the rat epitrochlearis muscle upon
cessation of voluntary exercise. J. Physiol. 2005, 562, 829–838.
50. Laye, M.J.; Thyfault, J.P.; Stump, C.S.; Booth, F.W. Inactivity induces increases in abdominal fat. J. Appl.
Physiol. 2007, 102, 1341–1347.
51. Dohm, G.L.; Barakat, H.A.; Tapscott, E.B.; Beecher, G.R. Changes in body fat and lipogenic enzyme
activities in rats after termination of exercise training. Proc. Soc. Exp. Biol. Med. 1977, 155, 157–159.
52. Kump, D.S.; Booth, F.W. Sustained rise in triacylglycerol synthesis and increased epididymal fat mass
when rats cease voluntary wheel running. J. Physiol. 2005, 565, 911–925.
53. Booth, F.W.; Tseng, B.S.; Fluck, M.; Carson, J.A. Molecular and cellular adaptation of muscle in response to
physical training. Acta Physiol. Scand. 1998, 162, 343–350.
54. Askew, E.W.; Huston, R.L.; Dohm, G.L. Effect of physical training on esterification of glycerol-3-phosphate
by homogenates of liver, skeletal muscle, heart, and adipose tissue of rats. Metabolism 1973, 22, 473–480.
55. Hardcastle, S.J.; Ray, H.; Beale, L.; Hagger, M.S. Why sprint interval training is inappropriate for a largely
sedentary population. Front. Psychol. 2014, 5, 1505, doi:10.3389/fpsyg.2014.01505.
56. Oliveira, B.R.R.; Santos, T.M.; Kilpatrick, M.; Pires, F.O.; Deslandes, A.C. Affective and enjoyment
responses in high intensity interval training and continuous training: A systematic review and meta-
analysis. PLoS ONE 2018, 13, e0197124, doi:10.1371/journal.pone.0197124.
57. Del Vecchio, F.B.; Gentil, P.; Coswig, V.S.; Fukuda, D.H. Commentary: “Why Sprint interval training is
inappropriate for a largely sedentary population” The satisfaction that moves us—Sprint interval training
as an exercise method for sedentary individuals. Front. Psychol. 2015, 6, 1359, doi:10.3389/fpsyg.2015.01359.
58. Roy, M. High-intensity Interval Training in the Real World: Outcomes from a 12-month Intervention in
Overweight Adults. Med. AMP 2018, 50, 1818–1826, doi:10.1249/mss.0000000000001642.
59. Viana, R.B.; de Lira, C.A.B.; Naves, J.P.A.; Coswig, V.S.; Del Vecchio, F.B.; Ramirez-Campillo, R.; Vieira,
C.A.; Gentil, P. Can We Draw General Conclusions from Interval Training Studies? Sport Med. 2018, 48,
2001–2009.
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