The Effects of Two Different Orders of Concurrent Training on the Interindividual Variability of Health Markers of Metabolic Syndrome and Fitness in Severe/Morbidly Obesity Women. A Randomized Control Trial
Phase: NA
Conditions: Morbid Obesity, Sports Physical Therapy
Sponsor: Cristian Alvarez

The effects of two different orders of concurrent training on the interindividual 
variability of health markers of metabolic syndrome and fitness in severe/morbidly 
obesity women. A randomized control trial 
ID: RP08042020 
 
Date: Apri1 10th, 2019 
 
Study documents 
Scientific background: Morbid obesity, defined as a body mass index (BMI) of 
40 kg/m2 (class III obesity), is a chronic disease with life-threatening cardiometabolic 
consequences such as elevated blood pressure (systolic [SBP] or diastolic BP [DBP]), 
fasting plasma glucose (FPG), triglycerides (Tg), and low high-density lipoprotein 
cholesterol (HDL-c), all summarised as metabolic syndrome (MetS) (Baffi, Wood et al. 
2016), increasing substantially the rates of total mortality, with most of the excess deaths 
due to heart disease, cancer, diabetes, and important life expectancy reductions in 
compared with normal weight (Kitahara, Flint et al. 2014). Moreover, morbid obesity has 
been associated with impairments of cardiorespiratory fitness and muscle strength, 
limiting the capacity to perform activities of daily living (Pazzianotto-Forti, Moreno et 
al. 2020) Additionally, this fact increases the economic costs associated with healthcare 
in this population (Espallardo, Busutil et al. 2017).  
Due to the multi-factorial aetiology of morbid obesity, such as the genetic load (e.g. the 
FTO gen), and other environmental factors, including mainly lifestyle determinants such 
as physical activity/exercise training participation, and diet as main modulators, the 
application of lifestyle strategies have been proposed prior to alternative surgical 
intervention in these populations (Bächler, Papamargaritis et al. 2013, Espallardo, Busutil 
et al. 2017). In this sense, exercise training as the resistance training (RT), defined as any 
exercise that causes voluntary skeletal muscle contraction by using external weights 

including dumbbells and metal bars (Schoenfeld, Grgic et al. 2017), is a known non-
pharmacotherapy strategy for improving muscle strength and functional capacity in obese 
patients undergoing bariatric surgery (Huck 2015). Similarly, high intensity interval 
training (HIIT), defined as several and brief bouts of high-intensity effort usually by 
cycling/running, interspersed by recovery periods (Gibala, Little et al. 2012, Delgado-
Floody, Izquierdo et al. 2020), has produced strong evidence for the improvement of 
cardiometabolic risk factors for type 2 diabetes mellitus, arterial hypertension, central 
arterial stiffness, vascular function, and cardiorespiratory fitness (Ramírez-Vélez, 
Hernández-Quiñones et al. 2019). Thus, HIIT might have protective effects against the 
development of cardiometabolic diseases including populations with poor glucose control 
and high blood pressure in comparison to moderate-intensity continuous training (MICT) 
(Campbell, Kraus et al. 2019). Thus, following RT or HIIT alone, there have been 
described unique physiological adaptations for improving for example muscle strength, 
the endurance performance by walking test, as well as beneficial metabolic improvements 
at MetS markers including fasting glucose reductions, increases at HDL-c, and decreases 
in Tg in populations with higher adiposity. 
Thus, in individuals with morbid obesity for example, exercise training has 
proven to be effective for inducing clinically significant weight loss (5–10%) (Gerber, 
Anderin et al. 2015), and for the reduction of cardiovascular risk (Delgado-Floody, 
Alvarez et al. 2019), in accordance with the standard recommendations for these cohorts 
prior to bariatric surgical. Additionally, there are also other benefits such as the increase 
of skeletal muscle mass, the reduction of body fat, and better glucose control by the 
lowering of fasting plasma glucose (FPG), and lipids regulation (i.e., increases of HDL-
c, and decreases of Tg) (Han and Lean 2016). Briefly, 12 weeks of concurrent training 
(CT), defined as a combination of both MICT / plus RT, decreased body weight (by ~7.3 

kg), blood pressure, and FPG in this cohort (Marc-Hernández, Ruiz-Tovar et al. 2019). 
In addition, part of our preliminary findings have shown that 20 weeks of RT decreases 
MetS risk factors in morbidly obese patients, showing a low inter-individual variability 
those patients with greater adiposity, revealing that with more adiposity alteration, the 
benefits of RT are also more visible (Delgado-Floody, Alvarez et al. 2019). However, 
some inconsistences have been described after CT, that are directly related with the 
‘order’ (i.e. starting the CT session with MICT followed by RT, or vice versa) of the CT 
session. For example, some literature reports that by starting the exercise session with 
RT, participants can get more benefits and improve their physical fitness markers (i.e. 
increases of upper body strength and neuromuscular markers) (Murlasits, Kneffel et al. 
2018). However, in contrast, other studies have reported that starting CT with MICT/or 
HIIT does not alter physiological adaptations in similar outcomes (Wilhelm, Rech et al. 
2014). Other evidence shows that starting CT with firstly RT exercises clearly promotes 
greater lower-body strength gains and neuromuscular economy (Cadore, Izquierdo et al. 
2013). By contrast, other reports claim no more benefits by starting with MICT/HIIT or 
RT to physical fitness markers in populations of athletes (Eddens, van Someren et al. 
2018), and additionally, no additional benefits for decreasing body fat using one or 
another exercise modality when starting the CT session (Cadore, Izquierdo et al. 2012). 
However, little is known about the interindividual variability of exercise training (IVET) 
in relation to different order session of CT in morbidly obese populations, and in health-
related outcomes, such as MetS markers. Briefly, IVET means that some subjects achieve 
benefits after training, and are termed responders (Rs), while others exhibit a worsened 
or unchanged response, that are commonly known as nonresponders (NRs) (Bouchard, 
Blair et al. 2012). With regard to the causes of IVET, genetic (Stephens, Xie et al. 2015), 
and environmental factors including the mode of exercise training (Alvarez, Ramirez-

Campillo et al. 2017), have been described. In addition, considering the health-related 
benefits of CT including MICT/or HIIT plus RT in terms of physical fitness, and the 
metabolic markers in different populations, as well as taking into account the previous 
discrepancies of the order session in relevant literature, it is necessary to investigate the 
exercise modalities interaction as a precision medicine for improving MetS markers. This 
study will follow the CONSORT guidelines for randomised trials, will be developed in 
accordance with the Declaration of Helsinki (2013), and has been approved by the Ethical 
Committee of the Universidad de La Frontera, Temuco, Chile (DI18-0043 Project). 
Design: An experimental, and randomized control clinical study. Methods: This study is 
a parallel-group randomised controlled trial in which 43 women with morbid obesity that 
will be randomly allocated to one of the two similar CT exercise programmes. The 
exercises will be applied in different session order by the two groups (HIIT+RT, n=17), 
and resistance training plus high-intensity interval training (RT+HIIT, n=17). All 
volunteers will read and signed an informed consent. The inclusion criteria will be; (i) 
being a candidate for bariatric surgery, (ii) aged between 18 and 60 years, (iii) being 
medically authorised, and (iii) with a body mass index (BMI) ≥40 kg/m2 or ≥35 kg/m2 
with additional comorbidities (i.e. diabetes, hypertension, insulin resistance) controlled 
by pharmacotherapy according to the Chilean requirements for morbidly obese patients 
in order to be a candidate for bariatric surgery. The exclusion criteria will be; (i) having 
physical limitations preventing the performance of exercise (e.g. restricting injuries of the 
musculoskeletal system), (ii) having exercise-related dyspnoea or respiratory alterations, 
(iii) having chronic heart disease with any worsening in the last month, and (iv) adhering 
to less than 80% of the total interventions (these results were excluded from the statistical 
analyses). 
 

REFERENCES 
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after 10 Weeks of High-Intensity Interval Training in Adult Women with Higher and 
Lower Insulin Resistance." Front Physiol 8(479): 479. 
 
 
Bächler, T., et al. (2013). "Treatment of Morbid Obesity: Intensive Lifestyle Intervention 
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Baffi, C. W., et al. (2016). "Metabolic Syndrome and the Lung." Chest 149(6): 1525-
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Bouchard, C., et al. (2012). "Adverse metabolic response to regular exercise: is it a rare 
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Cadore, E. L., et al. (2012). "Strength prior to endurance intra-session exercise sequence 
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Cadore, E. L., et al. (2013). "Neuromuscular adaptations to concurrent training in the 
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Campbell, W. W., et al. (2019). "High-intensity interval training for cardiometabolic 
disease prevention." Medicine and science in sports and exercise 51(6): 1220. 
 
 
Delgado-Floody, P., et al. (2019). "Preventing metabolic syndrome in morbid obesity 
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Delgado-Floody, P., et al. (2020). "Effect of High-Intensity Interval Training on Body 
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Exercise Among Prehypertensive and Hypertensive Patients With Excessive Adiposity." 
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Kitahara, C., et al. (2014). "Association between class III obesity (BMI of 40–59 kg/m 2) 
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Marc-Hernández, A., et al. (2019). "Impact of exercise on body composition and 
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Murlasits, Z., et al. (2018). "The physiological effects of concurrent strength and 
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Ramírez-Vélez, R., et al. (2019). "Effectiveness of HIIT compared to moderate 
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Statistical Analysis Plan (SAP): We will apply 2 main forms of statistical 
analyses a) to report the pre-post changes in mean terms, and b) to report the results 
according with the inter-individual responses based on the technical error criteria, where 
according with the error calculated in the three previous measurements registered by the 
sample that was voluntary. Graph pad Prisma statistical software 8.0 (San Diego, CA, 
USA) will be used. The normal distribution of all the variables were tested using the 
Shapiro-Wilk test. Data will be presented as the mean and (95%CI) in tables, as mean 

with (±) standard error in Figures 1, 2, and 3, and as individual delta in Figure 4 for 
identification of Rs and NRs. Normality and homoscedasticity assumptions for all data 
were analysed using the Shapiro–Wilk and Levene’s test, respectively. In the HIIT+RT 
group, the Tg outcome, as well as in the RT+HIIT group, LDL-c, and lean mass outcomes 
were analysed by the Wilcoxon non-parametric test. For training-induced changes, the 
student’s t test was used to identify differences at baseline, while a repeated measure two-
way ANOVA was applied to assess the occurrence of an actual training effect; namely, p 
< 0.05 for the interaction (time x group) on the main MetS (WC, SBP, DBP, FPG, HDL, 
and Tg, as well as to the secondary outcomes). A Sidack’s post hoc test was used for 
multiple comparisons. Additionally, the Eta partial squared for interaction (Time x 
Group) was assessed by η2 obtained from the ANCOVA with small (η2=0.01), medium 
(η2=0.06), and large (η2=0.14) effects defined according to (Lakens, 2013). The 
prevalence of NRs was described using the comparisons by percentage between both 
experimental groups using a Chi square test X2. All statistical analyses were performed 
with SPSS statistical software version 23.0 (SPSSTM Inc., Chicago, IL). The alpha level 
was set at p < 0.05 for statistical significance.