Effects Of Different Frequencies Of Concurrent Training On Cardiometabolic Risk Factors In Young Adults With Overweight And Obesity: A Randomized Controlled Trial 

Effects Of Different Frequencies Of Concurrent Training On Cardiometabolic Risk Factors In Young Adults With Overweight And Obesity: A Randomized Controlled Trial | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Effects Of Different Frequencies Of Concurrent Training On Cardiometabolic Risk Factors In Young Adults With Overweight And Obesity: A Randomized Controlled Trial Yigao Wu, Jiacheng Wang, Ying Liu, Youyou Li, Yixuan Li, Yunqing zhang, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4424539/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Cardiometabolic risk factors are a significant health concern, particularly among young adults with overweight and obesity. Concurrent training, which combines aerobic and strength exercise, has been shown to improve cardiometabolic health. However, the effects of different training frequencies are not well understood. Method Forty-three participants (mean age: 19 years) were randomly assigned to either the CT-2 group (concurrent training twice per week, n = 22) or the CT-3 group (concurrent training three times per week, n = 21). The training regimen included 40 minutes of strength training followed by 40 minutes of aerobic exercises. Baseline and eight-week follow-up assessments included anthropometric measurements, body composition analysis, cardiovascular and metabolic parameters, VO2 max, and 1RM squat strength. Results Both the CT-2 and CT-3 groups showed significant improvements in body mass, body fat percentage, fat mass, android fat mass, and gynoid fat mass (p < 0.01). However, the reduction in android/gynoid fat mass ratio was significant only in the CT-3 group (p < 0.05). Additionally, fasting glucose, fasting insulin, total cholesterol, triglycerides, HDL-C, LDL-C, TC/HDL-C, HOMA-IR, HOMA-IS, and HOMA-β levels decreased significantly in both groups post-intervention (p < 0.01). Increases in VO2 max (CT-2: p < 0.05; CT-3: p < 0.01) and 1RM squat strength (CT-2: p < 0.01; CT-3: p < 0.05) were also observed. Comparing the two groups, CT-3 group demonstrated more significant improvements in HDL-C (p < 0.05) and HOMA-IS (p < 0.05). Conclusion These findings highlight the effectiveness of concurrent training in improving cardiometabolic risk factors in young adults with overweight and obesity. Both twice-weekly and three times-weekly training significantly improved these risk factors, with higher frequency training providing additional benefits. Adults Cardiometabolic risk factors Concurrent training Obesity Overweight Figures Figure 1 Figure 2 Figure 3 Introduction Recent research data indicate that cardiovascular disease (CVD) has emerged as a significant concern in China, accounting for over 40% of deaths in the nation( 1 ). Overweight and obesity, recognized as major risk factors for CVD, render individuals more susceptible to cardiometabolic risk factors(CRFs) such as high blood pressure, and high cholesterol, thereby increasing the prevalence of CVDs and mortality( 2 , 3 ). While historically CVD mainly affected the middle-aged and elderly population, there is a concerning trend of rising incidence among young adults attributed to overweight and obesity( 4 ). Improving CRFs in young adults with overweight and obesity holds practical significance in preventing and managing CVD. Research indicates that regular exercise contributes to weight and fat reduction, thus playing a pivotal role in CVD prevention and management. The American Heart Association advocates physical activity as a fundamental strategy for enhancing CRFs( 5 – 7 ). However, the efficacy of exercise-induced cardioprotection varies across different exercise modalities, necessitating a nuanced understanding of their effects( 8 – 10 ). In 1980, Professor Robert Hickson introduced concurrent training(CT) as a regimen combining aerobic and strength exercises( 11 ). CT has gained attention for its potential benefits in improving CRFs, initially within sports performance contexts and later in broader health settings( 12 – 14 ). However, CT encompasses various training variables, such as session order and frequency, which can influence its overall effectiveness( 15 , 16 ). For instance, research suggests that the sequence of strength training followed by aerobic training may offer superior benefits compared to alternative sequences( 17 ). Additionally, the frequency of CT sessions impacts training-related gains and adherence rates( 18 ). Despite the recognized benefits of CT, challenges such as adherence issues, motivation, and injury risks hinder its efficacy, particularly among young adults with overweight and obesity( 19 – 22 ). Hence, determining the optimal CT frequency is crucial for enhancing CRFs in this population. However, there is a paucity of research investigating the effects of different CT frequencies on CRFs among young adults with overweight and obesity. Previous studies primarily focused on older adults and yielded mixed results regarding the impact of CT frequency on CRFs( 23 , 24 ). To address this gap, our team designed an 8-week CT exercise intervention program to explore the effects of different CT frequencies on CRFs in young adults with overweight and obesity. We hypothesize that both twice-weekly and three times-weekly CT sessions will yield beneficial effects on CRFs, with the latter potentially being more effective. By addressing these research questions, we aim to provide evidence-based recommendations for optimizing exercise interventions in this vulnerable population. Materials and methods Research Design and Participants Our intervention study spanned eight weeks, aligning with previous studies indicating that a six-week intervention duration can effectively impact CRFs( 25 ). The study followed the Parallel Group Design of the Consolidated Standards for Trial Reporting ( 26 ) and adhered to ethical guidelines outlined in the Declaration of Helsinki, receiving clearance from the Ethics Committee of the Exercise Science Experiment. Prior to participation, all individuals provided informed consent. After an initial baseline assessment, participants were randomly assigned to either the CT-2 group, receiving two CT sessions weekly, or the CT-3 group, engaging three CT sessions per week. Randomization was achieved using computer-generated simple randomization. Eligible participants were young adults with overweight or obesity, meeting specific criteria: (a) a body mass index (BMI) exceeding 25 kg/m2, (b) maintenance of stable body weight over the previous 12 weeks, (c) absence of chronic diseases or contraindications to exercise, and (d) self-reporting as sedentary (less than 20 minutes of physical activity on fewer than three days per week). Throughout the study, participants were instructed to maintain their regular dietary habits. Procedures The initial phase of the study involved comprehensive assessments on the first day, including anthropometric assessments, body composition analysis, blood pressure checks, and fasting blood tests. On the second day, participants underwent a maximal oxygen uptake test to assess cardiovascular fitness. To ensure accuracy in the fasting blood measurements, participants were required to observe a 12-hour fasting period before the first-day evaluations. Additionally, to minimize potential confounding factors related to recovery and physiological readiness, a 48-hour interval was implemented between the initial and subsequent assessments. The experimental evaluations were conducted by experienced professionals, ensuring consistency and reliability in the data collection. To maintain methodological integrity, the same evaluator performed both baseline assessments and post-intervention measurements throughout the study. Anthropometrics and Body Composition Anthropometric measurements and body composition assessments were conducted with precision using dual-energy X-ray absorptiometry (iDxa, General Electric, USA), acknowledged as the gold standard in the field( 27 ). Waist circumference (WC) and hip circumference were meticulously recorded to the nearest 0.1 cm, employing a non-stretchable measuring tape (Acmeway, China), thus ensuring reliability and consistency in the data collection process. Blood Samples Morning blood samples were collected following a 12-hour overnight fast and analysed using automatic biochemical equipment (UniCel DxC 800, Beckman Coulter, USA) to measure fasting glucose, fasting insulin, and other relevant biomarkers. Skilled technicians conducted all measurements according to established clinical testing protocols. Homeostasis model assessments (HOMA), comprising HOMA-IR (insulin resistance), HOMA-IS (insulin sensitivity), and HOMA-β (beta-cell function), were subsequently calculated( 28 ). The calculation method is as follows: $$\begin{array}{c}HOMA-IR=\frac{\left[fastingglucose\right]plasma*\left[fastinginsulin\right]plasma}{22.5}\#\left[1\right]\end{array}$$ $$\begin{array}{c}HOMA-IS=\frac{1}{HOMA-IR}\#\left[2\right]\end{array}$$ $$\begin{array}{c}HOMA-\beta =\frac{20*\left[fastinginsulin\right]plasma}{\left[fastingglucose\right]plasma}\#\left[3\right]\end{array}$$ Blood Pressure Blood pressure measurements were taken using a validated automated monitoring device (CH-550, Citizen)( 29 ). Each measurement was performed in triplicate, with 90-second intervals between assessments, following a 15-minute rest period during which participants remained seated. Mean arterial pressure was calculated from these measurements, in accordance with the methodologies outlined in the Clinical Practice Guidelines Task Force Report by the American Heart Association (AHA)( 30 ). $$\begin{array}{c}MeanArterialBP\left(MAP\right)=\frac{SystolicBP+\left(2*DyastolicBP\right)}{3}\#\left[4\right]\end{array}$$ Concurrent Training Before initiating the CT sessions, participants underwent three familiarization sessions to adapt to the regimen. Both strength training and aerobic exercise routines were standardized for each session( 31 ). The formal training session began with a 10-minute dynamic warm-up to prepare the body. The strength training component focused on engaging major muscle groups through multi-joint movements, including targeted exercises for the upper and lower extremities, core, and back muscles. Each exercise comprised three sets of 10 repetitions, with 90-second rest intervals between sets for recovery. Aerobic training was performed at an intensity ranging from 50–80% of each participant's maximum heart rate, monitored in real-time using the BHT TEAM training telemetry system from Bohoton, China, to ensure adherence to the prescribed intensity levels. Following the training session, a 10-minute stretching routine was implemented to aid recovery. No adverse events were reported during the sessions, indicating the intervention's safety. Each session, overseen by a qualified fitness professional, was carefully designed to last approximately 100 minutes. Maximum Oxygen Uptake (VO 2max ) The experimental environment was meticulously controlled, maintaining an ambient temperature between 21–23°C and atmospheric pressure ranging from 101.1 to 102.8 KPa throughout the measurement process. Prior to commencement, all apparatus underwent calibration to guarantee measurement accuracy. To ensure measurement precision, the gas metabolism equipment (Cortex Metalyzer3BR2 system, Cortex, Germany) underwent a 30-minute warm-up period. Participant demographic data were collected, followed by a 5-minute quiescent phase. During this phase, participants were positioned with their feet on appropriate pedals (Ergomedic 839E, Monark Exercise, Sweden) and connected to the gas metabolism apparatus via a facial mask. After the resting interval, participants engaged in an incremental compliance exercise protocol, starting at a workload of 50W and increasing by 50W every three minutes. This protocol was maintained at 60–65 revolutions per minute until reaching predetermined termination criteria for maximal oxygen consumption. Subsequently, participants underwent an additional three-minute period at a workload of 50W or less to aid recovery, concluding the measurement procedure( 32 ). Surveyors were responsible for providing positive reinforcement to participants to optimize performance and ensure measurement accuracy. Additionally, clinical oversight and monitoring of the participant's physiological state were essential throughout the measurement process. One-repetition maximum squat Unlike the widely accepted 1RM squat test, which is considered the gold standard for assessing maximal strength in athletes and experienced individuals, tests involving multiple repetitions are believed to pose a lower risk of musculoskeletal injuries. Therefore, such tests are recommended for individuals without prior training experience( 33 ). Following an initial phase comprising a brief warm-up, instructions, and familiarization with the measurement protocols, participants performed a 1RM squat test according to a predetermined sequence. This assessment was conducted under the supervision of certified physiotherapists or sports therapists. The initial load for each participant was determined based on subjective feedback. Subseuently, participants aimed to complete as many repetitions as possible with the given load until failure to perform a concentric movement was observed. It was specified that the number of repetitions should not exceed six, a threshold considered appropriate for accurately predicting 1RM. If a participant exceeded six repetitions, the load was incrementally increased, and another attempt was made after a three-minute rest period. Typically, the appropriate weight was determined within a maximum of three attempts. The 1RM was calculated using the Brazycki Eq. (34): $$1RM = 100 * load rep / (102.78 - 2.78 * rep)$$ Statistical Analysis The data analysis was performed using Microsoft Excel spreadsheets and GraphPad Prism version 9.5. Descriptive statistics were reported as the mean ± standard deviation. Data normality was assessed using the Shapiro-Wilk test, while variance was evaluated using the Levene test. Within-group comparisons were conducted using the paired samples t-test. In cases where the data did not follow to a normal distribution, the Wilcoxon rank-sum test was employed. For comparisons between different groups, the independent samples t-test was utilised. Statistical significance was set at p < 0.05. Results At the outset of the trial, 78 adults with overweight and obesity were initially recruited, with 43 participants ultimately completing the trial. Figure 1 illustrates the reason for the exclusion. Participant adherence rates were 100% in CT sessions. Table 1 presents the main baseline characteristics of participants within each group. No adverse events occurred during the training sessions. Gender did not exhibit significant effects; hance the results of both males and females were pooled together in all analyses. Table 1 Baseline characteristics of all participants. CT-2 group (N = 22) CT-3 group (N = 21) Genders (M/F) Baseline 21/1 15/6 Age (years) Baseline 19.55 ± 0.72 19.50 ± 1.16 Height (cm) Baseline 172.79 ± 7.76 171.04 ± 8.62 Values are given as mean ± SD. M = males, F = females, CT-2: two times concurrent training per week; CT-3: three times concurrent training per week. Significant post-intervention differences were observed in body mass (p < 0.01), body mass index (p < 0.01), body fat percentage (p < 0.01), fat mass (p < 0.01), Android fat mass (p < 0.01), and Gynoid fat mass (p < 0.01) among participants in the CT-2 and CT-3 groups. Additionally, the A/G ratio (p < 0.05) exhibited significant difference only in the CT-3 group post-intervention. (Refer to Table 2 and Fig. 2 for a visual representation) Table 2 Changes in the anthropometric and body composition of participants. CT-2 (N = 22) CT-3 (N = 21) Body mass (kg) Baseline 100.38 ± 13.65 94.89 ± 19.89 Post 97.10 ± 14.01 ** 92.07 ± 20.40 ** Body mass index (kg/m²) Baseline 33.64 ± 4.35 32.10 ± 3.97 Post 32.53 ± 4.43 ** 31.12 ± 4.30 ** Waist circumference (cm) Baseline 105.4 ± 10.3 106.1 ± 13.0 Post 103.4 ± 8.6 99.6 ± 13.9 Hip circumference (cm) Baseline 113.0 ± 6.4 114.0 ± 8.0 Post 111.6 ± 8.2 108.9 ± 8.2 Waist-hip ratio Baseline 0.93 ± 0.07 0.93 ± 0.07 Post 0.93 ± 0.04 0.91 ± 0.07 Body fat percentage (%) Baseline 38.36 ± 4.50 37.90 ± 3.37 Post 36.26 ± 4.94 ** 35.78 ± 4.48 ** Fat mass (kg) Baseline 38.88 ± 8.45 36.19 ± 9.49 Post 35.59 ± 8.57 ** 33.31 ± 10.24 ** Lean mass (kg) Baseline 61.51 ± 6.97 58.75 ± 11.45 Post 61.51 ± 7.60 58.76 ± 11.76 Android fat mass (kg) Baseline 3.76 ± 0.88 3.42 ± 1.29 Post 3.37 ± 0.92 ** 3.02 ± 1.39 ** Gynoid fat mass (kg) Baseline 5.96 ± 1.40 5.64 ± 1.23 Post 5.40 ± 1.42 ** 5.11 ± 1.31 ** A/ G (kg) Baseline 0.64 ± 0.09 0.60 ± 0.14 Post 0.63 ± 0.08 0.58 ± 0.15 * Values are given as mean ± SD. A/G = Android fat mass / Gynoid fat mass. * (p < 0.05), ** (p < 0.01): significantly different from pre-invention. After the intervention, significant post-intervention differences were observed in the fasting glucose (p < 0.01), fasting insulin (p < 0.05), total cholesterol (p < 0.01), triglycerides (p < 0.05), HDL-C (p < 0.01), LDL-C (p < 0.01), TC/HDL (p < 0.01), LDL/HDL (p < 0.01), HOMA-IR (p < 0.01), HOMA-IS (p < 0.01), and VO 2 max (p < 0.05) among participants in the CT-2 group. Similarly, significant post-intervention differences were observed in the fasting glucose (p < 0.01), fasting insulin (p < 0.01), total cholesterol (p < 0.01), triglycerides (p < 0.05), HDL-C (p < 0.01), LDL-C (p < 0.01), TC/HDL (p < 0.05), LDL/HDL (p < 0.01), HOMA-IR (p < 0.01), HOMA-IS (p < 0.01), and VO 2 max (p < 0.01) among participants in the CT-3 group. Furthermore, in a relative comparison between the two groups, the CT-3 group displayed significant differences in HDL cholesterol levels (p < 0.05) and HOMA-IS (p < 0.05) compared to the CT-2 group. (Refer to Table 3 and Fig. 3 for a visual representation) Table 3 Changes in the CRFs of participants in the CT-2 and CT-3 groups. CT-2 (N = 22) CT-3 (N = 21) SBP (mmHg) Baseline 126.91 ± 13.64 127.14 ± 15.3 Post 128.39 ± 10.52 125.06 ± 9.90 DBP (mmHg) Baseline 73.18 ± 13.04 76.14 ± 11.28 Post 73.79 ± 8.57 76.25 ± 8.17 Mean arterial pressure (mmHg) Baseline 91.09 ± 12.29 93.14 ± 12.00 Post 91.99 ± 8.56 92.52 ± 7.60 Fasting glucose (mmol/L) Baseline 5.89 ± 0.61 5.68 ± 0.63 Post 5.11 ± 0.33** 4.98 ± 0.45** Fasting insulin (mmol/L) Baseline 118.01 ± 45.26 121.52 ± 68.13 Post 95.14 ± 46.64* 79.09 ± 63.88** Total cholesterol (mmol/L) Baseline 5.29 ± 1.01 5.52 ± 1.03 Post 3.88 ± 0.57** 4.27 ± 0.70** Triglycerides (mmol/L) Baseline 1.49 ± 0.57 1.46 ± 0.66 Post 1.20 ± 0.61* 1.12 ± 0.52* HDL-C (mmol/L) Baseline 1.19 ± 0.21 1.26 ± 0.15 Post 1.06 ± 0.12** 1.17 ± 0.14**## LDL-C (mmol/L) Baseline 3.62 ± 0.77 3.79 ± 1.00 Post 2.38 ± 0.46** 2.65 ± 0.69** TC/HDL Baseline 4.46 ± 0.69 4.42 ± 0.81 Post 3.70 ± 0.50** 3.70 ± 0.74* LDL/HDL Baseline 3.06 ± 0.63 3.05 ± 0.83 Post 2.26 ± 0.41** 2.31 ± 0.68** HOMA-IR Baseline 4.38 ± 1.90 4.41 ± 2.87 Post 3.04 ± 1.53** 2.58 ± 2.56** HOMA-IS Baseline 0.27 ± 0.12 0.34 ± 0.22 Post 0.41 ± 0.19** 0.63 ± 0.39**# HOMA-β Baseline 141.05 ± 55.20 157.28 ± 73.78 Post 166.91 ± 78.64 142.28 ± 76.78 Uric acid (µmol/L) Baseline 576.81 ± 126.24 502.35 ± 110.72 Post 559.71 ± 98.99 536.29 ± 117.09 VO 2 max (mL/min/kg) Baseline 22.95 ± 3.71 21.28 ± 4.47 Post 25.00 ± 4.38* 26.28 ± 6.44** Values are given as mean ± SD. SBP = Systolic blood pressure; DBP = Diastolic blood pressure; TC = Total cholesterol; HDL-C = High-density lipoprotein cholesterol; LDL-C = Low-density lipoprotein cholesterol. * (p < 0.05), ** (p < 0.01): significantly different from pre-invention; # (p < 0.05), ## (p < 0.01): significant difference vs CT-2 group. Significant differences were found in the 1RM squat of participants within both the CT-2 and CT-3 groups; however, there was no discernible difference between the two groups. Table 4 Changes in the 1RM squat of participants in the CT-2 and CT-3 groups. CT-2 (N = 22) CT-3 (N = 21) 1RM squat (kg) Baseline 67.96 ± 15.46 72.42 ± 17.56 Post 94.03 ± 9.67** 89.37 ± 22.44* Values are given as mean ± SD. 1RM = One-repetition maximum. * (p < 0.05), ** (p < 0.01): significantly different from pre-invention. Discussion This study aimed to assess the effect of an 8-week CT intervention on CRFs in young adults with overweight and obesity, focusing on the impact of different weekly training frequencies. Both the CT-2 and CT-3 groups exhibited notable enhancements in anthropometrics, body composition, CRFs, and 1RM squats compared to baseline. Notably, the CT-3 group, which had more frequent weekly exercises, demonstrated superior improvements in HDL-C and HOMA-IS compared to the CT-2 group. Significant reductions in body mass, fat mass, and body fat percentage were observed in both groups over the eight-week CT period. The catabolic state induced by regular CT, leading to increased energy consumption without altering dietary habits, aligns with existing literature( 35 , 36 ). The study's results, indicating improvements in participants undergoing regular CT over two months, are promising. However, it's essential to recognize that while exercise can positively impact factors associated with cardiovascular disease risk, it may not uniformly affect all measures simultaneously( 37 ). In this study, no significant changes in waist circumference, hip circumference, or waist-to-hip ratio were observed compared to baseline. These findings parallel are consistent with studies by Vispute et al( 38 ). and Kordi et al. ( 39 ), which also noted insignificant changes in waist circumference despite exercise interventions. This underscores the challenge of implementing strict dietary controls during such interventions, especially with overweight and obese individuals. Balancing dietary restrictions with exercise adherence is crucial, as overly strict requirements may negatively impact participant compliance and retention. Despite the significant decreases in body mass and body fat percentage among participants in both the CT-2 and CT-3 groups, there was no corresponding significant change in lean mass. This discrepancy could be attributed to several factors. Firstly, the strength training employed in the study primarily utilized self-weight exercises, which may be considered lower-intensity compared to traditional machine-based strength training. Consequently, these exercises might not effectively stimulate the mechanisms responsible for skeletal muscle growth( 40 ). Moreover, previous research has identified an interference phenomenon associated with concurrent training, which may impede strength development when compared to dedicated strength training alone( 18 ). Our current understanding of this inhibitory effect and its underlying mechanisms remains limited. For instance, prolonged contraction, preceded by AMPK activation, can inhibit downstream translational signaling pathways such as Akt/mTOR, while energy stress may antagonize hypertrophic responses during muscle loading contractions.( 17 , 41 ). To comprehensively elucidate these mechanisms, future research endeavors should delve deeper into investigating the complex interactions among various movement modalities and their impacts on muscle physiology. Blood pressure constitutes a crucial clinical parameter for monitoring individuals, especially those with overweight or obesity. Prior research has underscored the favorable impact of exercise interventions on blood pressure, particularly among hypertensive patients.( 42 ). Given that participants in our study initially exhibited blood pressure readings within the normal range, it is reasonable to infer that the exercise intervention administered did not produce significant alterations in blood pressure. CT has been widely acknowledged for its efficacy in improving CRFs through the management of blood glucose and lipids( 35 , 36 , 43 ). In our study, participants in the CT-2 and CT-3 groups demonstrated significant reductions in fasting glucose, fasting insulin levels, total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), TC/HDL ratio, LDL/HDL ratio, homeostatic model assessment of insulin resistance (HOMA-IR), and homeostatic model assessment of insulin sensitivity (HOMA-IS) following an 8-week concurrent training intervention. These findings are consistent with results from previous studies employing similar CT interventions( 35 , 36 , 44 – 46 ). The decrease in fasting insulin levels can be attributed to CT's ability to enhance insulin sensitivity, thereby enabling tissue cells to utilize insulin more effectively and improve blood glucose regulation( 47 , 48 ). Furthermore, CT facilitates the reduction of body fat, particularly visceral fat, which indirectly influences insulin secretion and sensitivity. Given that the HOMA index is influenced by fasting blood glucose and insulin levels, the observed changes in the HOMA index are understandable. Moreover, the CT-3 group exhibited a more pronounced improvement in HOMA-IS compared to the CT-2 group (p < 0.05), suggesting that higher frequencies of CT led to more significant enhancements in individuals with overweight and obesity. Previous studies have generated conflicting results regarding the influence of exercise on plasma triglyceride levels. While some research suggests a decrease in triglyceride levels following aerobic training, others report no significant change post-training( 49 , 50 ). In our study, the observed reduction in plasma triglyceride levels among participants may be attributed to the concurrent training (CT) intervention. Fasting low-density lipoprotein cholesterol (LDL-C) is strongly associated with an increased risk of cardiovascular disease (CVD). Kelley et al. conducted a meta-analysis and systematic review, revealing that aerobic training for more than eight weeks effectively reduced LDL-C levels and body weight in individuals with type Ⅱ diabetes mellitus, consistent with our findings( 50 ). Aerobic exercise enhances high-density lipoprotein cholesterol (HDL-C) levels by increasing lipoprotein lipase concentration and activity in skeletal muscle( 51 ). Notably, participants in the CT-2 and CT-3 groups paradoxically exhibited decreased HDL-C levels at the end of the 8-week training period. Similar decreases in HDL-C levels are commonly observed in patients taking statins, and this may be closely linked to overweight and obesity status( 52 , 53 ). Although no significant differences were found between the two groups, the combined reduction in TC/HDL and HDL/LDL ratios powerfully demonstrates that CT is an effective strategy for improving cardiovascular risk factors in adults with overweight and obesity. Is weight loss the optimal target for reducing cardiovascular disease risk associated with obesity? Indeed, the answer is no. The objective of obesity treatment should encompass modifying body composition, cardiovascular metabolic risk factors, and physical performance, rather than solely focusing on weight loss( 54 ). Numerous studies have demonstrated a correlation between cardiorespiratory capacity, muscle strength, and cardiovascular health( 55 ). Low muscle strength has been consistently associated with the development of CVD, CVD mortality, and related outcomes across diverse age groups and populations( 56 , 57 ). Associations have also been documented between measures such as the one repetition maximum (1RM) for leg or bench press exercises and the incidence of metabolic syndrome in men aged 20–80( 58 ). Furthermore, a higher maximal oxygen uptake (V̇O2max) has been validated as a negative predictor for CVD and all-cause mortality(59). Encouragingly, both groups of subjects undertaking concurrent training exhibited significantly higher 1RM deep squat and maximal oxygen uptake levels. This suggests that individuals can enhance cardiovascular risk factors by increasing muscle strength and maximal oxygen uptake during an 8-week concurrent training period. It is important to acknowledge the limitations of this study and exercise caution when interpreting the findings. Firstly, gender differences among the subjects may have influenced the study results, as the response to training could vary between genders, potentially introducing heterogeneity into the experimental data. However, it is worth noting that similar situations have been encountered in previous experiments, and they did not significantly impact the credibility of the results. Secondly, while the gold-standard high insulin glucose clamp technique was not utilized in this experiment to assess insulin resistance, the HOMA method remains a valuable tool for evaluating insulin resistance. Lastly, although severe dietary restrictions were not imposed, participants were actively encouraged to maintain their dietary habits throughout the intervention trial. Nonetheless, it is important to recognize that dietary variations could have influenced the outcomes to some extent. Conclusion In conclusion, this study emphasizes the efficacy of an 8-week concurrent training (CT) intervention in promoting weight loss, improving CRFs, and enhancing cardiorespiratory fitness among young adults who are overweight or obese. Despite the inherent limitations, the clinical significance of these findings is considerable. The trial demonstrates that CT interventions are both feasible and cost-effective for managing obesity and its associated complications. However, larger-scale studies are needed to validate these results and explore whether prolonging the intervention duration would offer additional benefits. Abbreviations CT Concurrent Training CRFs Cardiometabolic risk factors HDL-C High-density lipoprotein cholesterol LDL-C Low-density lipoprotein cholesterol TC total cholesterol TC/HDL-C total cholesterol/ High-density lipoprotein cholesterol HOMA-IR Homeostasis model assessment of insulin resistance HOMA-IS Homeostasis model assessment of insulin sensitivity HOMA-β Homeostasis model assessment of Beta-cell function VO2 max maximal oxygen uptake 1RM squat One-repetition maximum squat Declarations Ethics approval and consent to participate We confirmed that the experimental protocol was approved by Ethics Committee of the Exercise Science Experiment of Beijing Sport University, and informed consent was obtained from each participant after risks and benefits were explained. The study was conducted in accordance with the latest version of the Declaration of Helsinki. Consent for publication Not applicable. Availability of data and materials The datasets generated during and analyzed during the current study are not publicly available due to confidential information about the participants but are available from the corresponding author on reasonable request. Competing interests The authors declare no competing interests. Funding The authors acknowledge the support of the National Key Research and Development Program of China, 2018YFC2000602 and Central Special Funds of the University for Basic Scientific Research 2015SYS009. Acknowledgements Firstly, the authors thank the participants of China Agricultural University for their enthusiastic participation in this research. Finally, the authors acknowledge Yaru Huang professor of China Agricultural University, Caihui Zhao, Langlang Yin, Sheng Huang, Yaqi Wang, Xueyin Fei, Guihua Sun, and Jimin Zhou of Beijing Sport University, which facilitated data collection. References Li J-J, Liu H-H, Li S. 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Using molecular biology to maximize concurrent training. Sports Med (Auckland NZ). 2014;44(Suppl 2):S117–25. He LI, Wei WR, Can Z. Effects of 12-week brisk walking training on exercise blood pressure in elderly patients with essential hypertension: a pilot study. Clinical and Experimental Hypertension (New York, NY: 1993). 2018;40(7):673-9. Lavie CJ, Arena R, Alpert MA, Milani RV, Ventura HO. Management of cardiovascular diseases in patients with obesity. Nat Rev Cardiol. 2018;15(1):45–56. Teodoro JL, Izquierdo M, da Silva LXN, Baroni BM, Grazioli R, Lopez P, et al. Effects of long-term concurrent training to failure or not in muscle power output, muscle quality and cardiometabolic risk factors in older men: A secondary analysis of a randomized clinical trial. Exp Gerontol. 2020;139:111023. Alvarez C, Ramirez-Velez R, Ramirez-Campillo R, Lucia A, Alonso-Martinez AM, Faundez H, et al. Improvements cardiometabolic risk factors in Latin American Amerindians (the Mapuche) with concurrent training. Scand J Med Sci Sports. 2019;29(6):886–96. Amaro-Gahete FJ, De-la-O A, Jurado-Fasoli L, Martinez-Tellez B, Ruiz JR, Castillo MJ. Exercise Training as a Treatment for Cardiometabolic Risk in Sedentary Adults: Are Physical Activity Guidelines the Best Way to Improve Cardiometabolic Health? The FIT-AGEING Randomized Controlled Trial. J Clin Med. 2019;8(12). Hawley JA, Lessard SJ. Exercise training-induced improvements in insulin action. Acta Physiologica (Oxford England). 2008;192(1):127–35. Marson EC, Delevatti RS, Prado AKG, Netto N, Kruel LFM. Effects of aerobic, resistance, and combined exercise training on insulin resistance markers in overweight or obese children and adolescents: A systematic review and meta-analysis. Prev Med. 2016;93:211–8. Grandjean PW, Crouse SF, Rohack JJ. Influence of cholesterol status on blood lipid and lipoprotein enzyme responses to aerobic exercise. Journal of Applied Physiology (Bethesda, Md: 1985). 2000;89(2):472 – 80. Kelley GA, Kelley KS. Effects of aerobic exercise on lipids and lipoproteins in adults with type 2 diabetes: a meta-analysis of randomized-controlled trials. Public Health. 2007;121(9):643–55. Kelley GA, Kelley KS. Aerobic exercise and HDL2-C: a meta-analysis of randomized controlled trials. Atherosclerosis. 2006;184(1):207–15. Bora K, Pathak MS, Borah P, Das D. Association of Decreased High-Density Lipoprotein Cholesterol (HDL-C) With Obesity and Risk Estimates for Decreased HDL-C Attributable to Obesity: Preliminary Findings From a Hospital-Based Study in a City From Northeast India. J Prim Care Community Health. 2017;8(1):26–30. Hasvold P, Thuresson M, Sundström J, Hammar N, Kjeldsen SE, Johansson G, et al. Association Between Paradoxical HDL Cholesterol Decrease and Risk of Major Adverse Cardiovascular Events in Patients Initiated on Statin Treatment in a Primary Care Setting. Clin Drug Investig. 2016;36(3):225–33. Weiss EP, Jordan RC, Frese EM, Albert SG, Villareal DT. Effects of Weight Loss on Lean Mass, Strength, Bone, and Aerobic Capacity. Med Sci Sports Exerc. 2017;49(1):206–17. Ko K-J, Kang S-J, Lee K-S. Association between cardiorespiratory, muscular fitness and metabolic syndrome in Korean men. Diabetes Metabolic Syndrome. 2019;13(1):536–41. Artero EG, Lee D-c, Lavie CJ, España-Romero V, Sui X, Church TS, et al. Effects of muscular strength on cardiovascular risk factors and prognosis. J Cardiopulm Rehabil Prev. 2012;32(6):351–8. Celis-Morales CA, Welsh P, Lyall DM, Steell L, Petermann F, Anderson J, et al. Associations of grip strength with cardiovascular, respiratory, and cancer outcomes and all cause mortality: prospective cohort study of half a million UK Biobank participants. BMJ. 2018;361:k1651. Jurca R, Lamonte MJ, Barlow CE, Kampert JB, Church TS, Blair SN. Association of muscular strength with incidence of metabolic syndrome in men. Med Sci Sports Exerc. 2005;37(11):1849–55. Blomqvist CG, Saltin B. Cardiovascular adaptations to physical training. Annu Rev Physiol. 1983;45:169–89. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4424539","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":303625667,"identity":"9e5b8e7a-c873-4232-a970-b176bf741360","order_by":0,"name":"Yigao Wu","email":"","orcid":"","institution":"Beijing Sport University","correspondingAuthor":false,"prefix":"","firstName":"Yigao","middleName":"","lastName":"Wu","suffix":""},{"id":303625668,"identity":"19152067-601f-45e1-adf8-8f998cd3eeee","order_by":1,"name":"Jiacheng Wang","email":"","orcid":"","institution":"China Agricultural 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10:36:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4424539/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4424539/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":57629131,"identity":"49a5472c-93e3-4c56-8be1-ff5d3a9e49c0","added_by":"auto","created_at":"2024-06-03 14:35:47","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":49989,"visible":true,"origin":"","legend":"\u003cp\u003eStudy flow diagram.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4424539/v1/c63bf58f45bc1705472d5225.jpg"},{"id":57630209,"identity":"8ba48b29-6c50-48b5-b21a-2bb2a3e79b98","added_by":"auto","created_at":"2024-06-03 14:43:47","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":65240,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in the anthropometric and body composition of participants. * (p\u0026lt;0.05), ** (p\u0026lt;0.01): significantly different from pre-invention.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4424539/v1/754a94c99754c255431b4eb9.jpg"},{"id":57629132,"identity":"3b431092-2c86-48e5-9906-9bf39bf8ad94","added_by":"auto","created_at":"2024-06-03 14:35:47","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":57787,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in the CRFs of participants in the CT-2 and CT-3 groups. * (p\u0026lt;0.05), ** (p\u0026lt;0.01): significantly different from pre-invention.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4424539/v1/c3575b4d41ed4a5318aa07d6.jpg"},{"id":58713216,"identity":"5322bc74-adad-460f-a354-d87d68417cef","added_by":"auto","created_at":"2024-06-20 07:08:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":812365,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4424539/v1/7d3a4aef-69e5-4198-984f-92859f5a47c5.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":" Effects Of Different Frequencies Of Concurrent Training On Cardiometabolic Risk Factors In Young Adults With Overweight And Obesity: A Randomized Controlled Trial ","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRecent research data indicate that cardiovascular disease (CVD) has emerged as a significant concern in China, accounting for over 40% of deaths in the nation(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Overweight and obesity, recognized as major risk factors for CVD, render individuals more susceptible to cardiometabolic risk factors(CRFs) such as high blood pressure, and high cholesterol, thereby increasing the prevalence of CVDs and mortality(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). While historically CVD mainly affected the middle-aged and elderly population, there is a concerning trend of rising incidence among young adults attributed to overweight and obesity(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eImproving CRFs in young adults with overweight and obesity holds practical significance in preventing and managing CVD. Research indicates that regular exercise contributes to weight and fat reduction, thus playing a pivotal role in CVD prevention and management. The American Heart Association advocates physical activity as a fundamental strategy for enhancing CRFs(\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). However, the efficacy of exercise-induced cardioprotection varies across different exercise modalities, necessitating a nuanced understanding of their effects(\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn 1980, Professor Robert Hickson introduced concurrent training(CT) as a regimen combining aerobic and strength exercises(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). CT has gained attention for its potential benefits in improving CRFs, initially within sports performance contexts and later in broader health settings(\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). However, CT encompasses various training variables, such as session order and frequency, which can influence its overall effectiveness(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). For instance, research suggests that the sequence of strength training followed by aerobic training may offer superior benefits compared to alternative sequences(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Additionally, the frequency of CT sessions impacts training-related gains and adherence rates(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite the recognized benefits of CT, challenges such as adherence issues, motivation, and injury risks hinder its efficacy, particularly among young adults with overweight and obesity(\u003cspan additionalcitationids=\"CR20 CR21\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Hence, determining the optimal CT frequency is crucial for enhancing CRFs in this population. However, there is a paucity of research investigating the effects of different CT frequencies on CRFs among young adults with overweight and obesity. Previous studies primarily focused on older adults and yielded mixed results regarding the impact of CT frequency on CRFs(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo address this gap, our team designed an 8-week CT exercise intervention program to explore the effects of different CT frequencies on CRFs in young adults with overweight and obesity. We hypothesize that both twice-weekly and three times-weekly CT sessions will yield beneficial effects on CRFs, with the latter potentially being more effective. By addressing these research questions, we aim to provide evidence-based recommendations for optimizing exercise interventions in this vulnerable population.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eResearch Design and Participants\u003c/h2\u003e \u003cp\u003eOur intervention study spanned eight weeks, aligning with previous studies indicating that a six-week intervention duration can effectively impact CRFs(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). The study followed the Parallel Group Design of the Consolidated Standards for Trial Reporting (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) and adhered to ethical guidelines outlined in the Declaration of Helsinki, receiving clearance from the Ethics Committee of the Exercise Science Experiment. Prior to participation, all individuals provided informed consent.\u003c/p\u003e \u003cp\u003e After an initial baseline assessment, participants were randomly assigned to either the CT-2 group, receiving two CT sessions weekly, or the CT-3 group, engaging three CT sessions per week. Randomization was achieved using computer-generated simple randomization.\u003c/p\u003e \u003cp\u003eEligible participants were young adults with overweight or obesity, meeting specific criteria: (a) a body mass index (BMI) exceeding 25 kg/m2, (b) maintenance of stable body weight over the previous 12 weeks, (c) absence of chronic diseases or contraindications to exercise, and (d) self-reporting as sedentary (less than 20 minutes of physical activity on fewer than three days per week). Throughout the study, participants were instructed to maintain their regular dietary habits.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eProcedures\u003c/h2\u003e \u003cp\u003eThe initial phase of the study involved comprehensive assessments on the first day, including anthropometric assessments, body composition analysis, blood pressure checks, and fasting blood tests. On the second day, participants underwent a maximal oxygen uptake test to assess cardiovascular fitness. To ensure accuracy in the fasting blood measurements, participants were required to observe a 12-hour fasting period before the first-day evaluations. Additionally, to minimize potential confounding factors related to recovery and physiological readiness, a 48-hour interval was implemented between the initial and subsequent assessments.\u003c/p\u003e \u003cp\u003eThe experimental evaluations were conducted by experienced professionals, ensuring consistency and reliability in the data collection. To maintain methodological integrity, the same evaluator performed both baseline assessments and post-intervention measurements throughout the study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eAnthropometrics and Body Composition\u003c/h2\u003e \u003cp\u003eAnthropometric measurements and body composition assessments were conducted with precision using dual-energy X-ray absorptiometry (iDxa, General Electric, USA), acknowledged as the gold standard in the field(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Waist circumference (WC) and hip circumference were meticulously recorded to the nearest 0.1 cm, employing a non-stretchable measuring tape (Acmeway, China), thus ensuring reliability and consistency in the data collection process.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eBlood Samples\u003c/h2\u003e \u003cp\u003eMorning blood samples were collected following a 12-hour overnight fast and analysed using automatic biochemical equipment (UniCel DxC 800, Beckman Coulter, USA) to measure fasting glucose, fasting insulin, and other relevant biomarkers. Skilled technicians conducted all measurements according to established clinical testing protocols. Homeostasis model assessments (HOMA), comprising HOMA-IR (insulin resistance), HOMA-IS (insulin sensitivity), and HOMA-β (beta-cell function), were subsequently calculated(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). The calculation method is as follows:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\begin{array}{c}HOMA-IR=\\frac{\\left[fastingglucose\\right]plasma*\\left[fastinginsulin\\right]plasma}{22.5}\\#\\left[1\\right]\\end{array}$$\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\begin{array}{c}HOMA-IS=\\frac{1}{HOMA-IR}\\#\\left[2\\right]\\end{array}$$\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equc\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\n$$\\begin{array}{c}HOMA-\\beta =\\frac{20*\\left[fastinginsulin\\right]plasma}{\\left[fastingglucose\\right]plasma}\\#\\left[3\\right]\\end{array}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eBlood Pressure\u003c/h2\u003e \u003cp\u003eBlood pressure measurements were taken using a validated automated monitoring device (CH-550, Citizen)(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Each measurement was performed in triplicate, with 90-second intervals between assessments, following a 15-minute rest period during which participants remained seated. Mean arterial pressure was calculated from these measurements, in accordance with the methodologies outlined in the Clinical Practice Guidelines Task Force Report by the American Heart Association (AHA)(\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e).\u003cdiv id=\"Equd\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equd\" name=\"EquationSource\"\u003e\n$$\\begin{array}{c}MeanArterialBP\\left(MAP\\right)=\\frac{SystolicBP+\\left(2*DyastolicBP\\right)}{3}\\#\\left[4\\right]\\end{array}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eConcurrent Training\u003c/h2\u003e \u003cp\u003e Before initiating the CT sessions, participants underwent three familiarization sessions to adapt to the regimen. Both strength training and aerobic exercise routines were standardized for each session(\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). The formal training session began with a 10-minute dynamic warm-up to prepare the body. The strength training component focused on engaging major muscle groups through multi-joint movements, including targeted exercises for the upper and lower extremities, core, and back muscles. Each exercise comprised three sets of 10 repetitions, with 90-second rest intervals between sets for recovery.\u003c/p\u003e \u003cp\u003eAerobic training was performed at an intensity ranging from 50\u0026ndash;80% of each participant's maximum heart rate, monitored in real-time using the BHT TEAM training telemetry system from Bohoton, China, to ensure adherence to the prescribed intensity levels. Following the training session, a 10-minute stretching routine was implemented to aid recovery. No adverse events were reported during the sessions, indicating the intervention's safety.\u003c/p\u003e \u003cp\u003eEach session, overseen by a qualified fitness professional, was carefully designed to last approximately 100 minutes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eMaximum Oxygen Uptake (VO\u003csub\u003e2max\u003c/sub\u003e)\u003c/h2\u003e \u003cp\u003eThe experimental environment was meticulously controlled, maintaining an ambient temperature between 21\u0026ndash;23\u0026deg;C and atmospheric pressure ranging from 101.1 to 102.8 KPa throughout the measurement process. Prior to commencement, all apparatus underwent calibration to guarantee measurement accuracy.\u003c/p\u003e \u003cp\u003eTo ensure measurement precision, the gas metabolism equipment (Cortex Metalyzer3BR2 system, Cortex, Germany) underwent a 30-minute warm-up period. Participant demographic data were collected, followed by a 5-minute quiescent phase. During this phase, participants were positioned with their feet on appropriate pedals (Ergomedic 839E, Monark Exercise, Sweden) and connected to the gas metabolism apparatus via a facial mask.\u003c/p\u003e \u003cp\u003eAfter the resting interval, participants engaged in an incremental compliance exercise protocol, starting at a workload of 50W and increasing by 50W every three minutes. This protocol was maintained at 60\u0026ndash;65 revolutions per minute until reaching predetermined termination criteria for maximal oxygen consumption. Subsequently, participants underwent an additional three-minute period at a workload of 50W or less to aid recovery, concluding the measurement procedure(\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSurveyors were responsible for providing positive reinforcement to participants to optimize performance and ensure measurement accuracy. Additionally, clinical oversight and monitoring of the participant's physiological state were essential throughout the measurement process.\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003eOne-repetition maximum squat\u003c/h2\u003e \u003cp\u003eUnlike the widely accepted 1RM squat test, which is considered the gold standard for assessing maximal strength in athletes and experienced individuals, tests involving multiple repetitions are believed to pose a lower risk of musculoskeletal injuries. Therefore, such tests are recommended for individuals without prior training experience(\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Following an initial phase comprising a brief warm-up, instructions, and familiarization with the measurement protocols, participants performed a 1RM squat test according to a predetermined sequence. This assessment was conducted under the supervision of certified physiotherapists or sports therapists. The initial load for each participant was determined based on subjective feedback.\u003c/p\u003e \u003cp\u003eSubseuently, participants aimed to complete as many repetitions as possible with the given load until failure to perform a concentric movement was observed. It was specified that the number of repetitions should not exceed six, a threshold considered appropriate for accurately predicting 1RM. If a participant exceeded six repetitions, the load was incrementally increased, and another attempt was made after a three-minute rest period. Typically, the appropriate weight was determined within a maximum of three attempts. The 1RM was calculated using the Brazycki Eq.\u0026nbsp;(34):\u003cdiv id=\"Eque\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Eque\" name=\"EquationSource\"\u003e\n$$1RM = 100 * load rep / (102.78 - 2.78 * rep)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eThe data analysis was performed using Microsoft Excel spreadsheets and GraphPad Prism version 9.5. Descriptive statistics were reported as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. Data normality was assessed using the Shapiro-Wilk test, while variance was evaluated using the Levene test. Within-group comparisons were conducted using the paired samples t-test. In cases where the data did not follow to a normal distribution, the Wilcoxon rank-sum test was employed. For comparisons between different groups, the independent samples t-test was utilised. Statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eAt the outset of the trial, 78 adults with overweight and obesity were initially recruited, with 43 participants ultimately completing the trial. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates the reason for the exclusion. Participant adherence rates were 100% in CT sessions. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the main baseline characteristics of participants within each group. No adverse events occurred during the training sessions. Gender did not exhibit significant effects; hance the results of both males and females were pooled together in all analyses.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of all participants.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCT-2 group (N\u0026thinsp;=\u0026thinsp;22)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCT-3 group (N\u0026thinsp;=\u0026thinsp;21)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenders (M/F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21/1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15/6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e172.79\u0026thinsp;\u0026plusmn;\u0026thinsp;7.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e171.04\u0026thinsp;\u0026plusmn;\u0026thinsp;8.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eValues are given as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. M\u0026thinsp;=\u0026thinsp;males, F\u0026thinsp;=\u0026thinsp;females, CT-2: two times concurrent training per week; CT-3: three times concurrent training per week.\u003c/p\u003e \u003cp\u003eSignificant post-intervention differences were observed in body mass (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), body mass index (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), body fat percentage (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), fat mass (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), Android fat mass (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and Gynoid fat mass (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) among participants in the CT-2 and CT-3 groups. Additionally, the A/G ratio (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) exhibited significant difference only in the CT-3 group post-intervention. (Refer to Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e for a visual representation)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChanges in the anthropometric and body composition of participants.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCT-2 (N\u0026thinsp;=\u0026thinsp;22)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCT-3 (N\u0026thinsp;=\u0026thinsp;21)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody mass (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e100.38\u0026thinsp;\u0026plusmn;\u0026thinsp;13.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e94.89\u0026thinsp;\u0026plusmn;\u0026thinsp;19.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e97.10\u0026thinsp;\u0026plusmn;\u0026thinsp;14.01\u003cb\u003e**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e92.07\u0026thinsp;\u0026plusmn;\u0026thinsp;20.40\u003cb\u003e**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody mass index (kg/m\u0026sup2;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e33.64\u0026thinsp;\u0026plusmn;\u0026thinsp;4.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e32.10\u0026thinsp;\u0026plusmn;\u0026thinsp;3.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e32.53\u0026thinsp;\u0026plusmn;\u0026thinsp;4.43\u003cb\u003e**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e31.12\u0026thinsp;\u0026plusmn;\u0026thinsp;4.30\u003cb\u003e**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaist circumference (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e105.4\u0026thinsp;\u0026plusmn;\u0026thinsp;10.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e106.1\u0026thinsp;\u0026plusmn;\u0026thinsp;13.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e103.4\u0026thinsp;\u0026plusmn;\u0026thinsp;8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e99.6\u0026thinsp;\u0026plusmn;\u0026thinsp;13.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHip circumference (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e113.0\u0026thinsp;\u0026plusmn;\u0026thinsp;6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e114.0\u0026thinsp;\u0026plusmn;\u0026thinsp;8.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e111.6\u0026thinsp;\u0026plusmn;\u0026thinsp;8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e108.9\u0026thinsp;\u0026plusmn;\u0026thinsp;8.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaist-hip ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody fat percentage (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e38.36\u0026thinsp;\u0026plusmn;\u0026thinsp;4.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e37.90\u0026thinsp;\u0026plusmn;\u0026thinsp;3.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e36.26\u0026thinsp;\u0026plusmn;\u0026thinsp;4.94\u003cb\u003e**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e35.78\u0026thinsp;\u0026plusmn;\u0026thinsp;4.48\u003cb\u003e**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFat mass (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e38.88\u0026thinsp;\u0026plusmn;\u0026thinsp;8.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e36.19\u0026thinsp;\u0026plusmn;\u0026thinsp;9.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e35.59\u0026thinsp;\u0026plusmn;\u0026thinsp;8.57\u003cb\u003e**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e33.31\u0026thinsp;\u0026plusmn;\u0026thinsp;10.24\u003cb\u003e**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLean mass (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e61.51\u0026thinsp;\u0026plusmn;\u0026thinsp;6.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e58.75\u0026thinsp;\u0026plusmn;\u0026thinsp;11.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e61.51\u0026thinsp;\u0026plusmn;\u0026thinsp;7.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e58.76\u0026thinsp;\u0026plusmn;\u0026thinsp;11.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAndroid fat mass (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e3.42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003cb\u003e**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e3.02\u0026thinsp;\u0026plusmn;\u0026thinsp;1.39\u003cb\u003e**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGynoid fat mass (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5.96\u0026thinsp;\u0026plusmn;\u0026thinsp;1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e5.64\u0026thinsp;\u0026plusmn;\u0026thinsp;1.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5.40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.42\u003cb\u003e**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e5.11\u0026thinsp;\u0026plusmn;\u0026thinsp;1.31\u003cb\u003e**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA/ G (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003cb\u003e*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eValues are given as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. A/G\u0026thinsp;=\u0026thinsp;Android fat mass / Gynoid fat mass. * (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), ** (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01): significantly different from pre-invention.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAfter the intervention, significant post-intervention differences were observed in the fasting glucose (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), fasting insulin (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), total cholesterol (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), triglycerides (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), HDL-C (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), LDL-C (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), TC/HDL (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), LDL/HDL (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), HOMA-IR (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), HOMA-IS (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and VO\u003csub\u003e2 max\u003c/sub\u003e (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) among participants in the CT-2 group. Similarly, significant post-intervention differences were observed in the fasting glucose (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), fasting insulin (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), total cholesterol (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), triglycerides (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), HDL-C (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), LDL-C (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), TC/HDL (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), LDL/HDL (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), HOMA-IR (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), HOMA-IS (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and VO\u003csub\u003e2 max\u003c/sub\u003e (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) among participants in the CT-3 group. Furthermore, in a relative comparison between the two groups, the CT-3 group displayed significant differences in HDL cholesterol levels (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and HOMA-IS (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) compared to the CT-2 group. (Refer to Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e for a visual representation)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChanges in the CRFs of participants in the CT-2 and CT-3 groups.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCT-2 (N\u0026thinsp;=\u0026thinsp;22)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCT-3 (N\u0026thinsp;=\u0026thinsp;21)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e126.91\u0026thinsp;\u0026plusmn;\u0026thinsp;13.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e127.14\u0026thinsp;\u0026plusmn;\u0026thinsp;15.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e128.39\u0026thinsp;\u0026plusmn;\u0026thinsp;10.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e125.06\u0026thinsp;\u0026plusmn;\u0026thinsp;9.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e73.18\u0026thinsp;\u0026plusmn;\u0026thinsp;13.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e76.14\u0026thinsp;\u0026plusmn;\u0026thinsp;11.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e73.79\u0026thinsp;\u0026plusmn;\u0026thinsp;8.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e76.25\u0026thinsp;\u0026plusmn;\u0026thinsp;8.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean arterial pressure (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e91.09\u0026thinsp;\u0026plusmn;\u0026thinsp;12.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e93.14\u0026thinsp;\u0026plusmn;\u0026thinsp;12.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e91.99\u0026thinsp;\u0026plusmn;\u0026thinsp;8.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e92.52\u0026thinsp;\u0026plusmn;\u0026thinsp;7.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFasting glucose (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e5.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e4.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFasting insulin (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e118.01\u0026thinsp;\u0026plusmn;\u0026thinsp;45.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e121.52\u0026thinsp;\u0026plusmn;\u0026thinsp;68.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e95.14\u0026thinsp;\u0026plusmn;\u0026thinsp;46.64*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e79.09\u0026thinsp;\u0026plusmn;\u0026thinsp;63.88**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal cholesterol (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5.29\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e5.52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e4.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.70**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTriglycerides (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL-C (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14**##\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL-C (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e3.79\u0026thinsp;\u0026plusmn;\u0026thinsp;1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC/HDL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e4.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e4.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e3.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL/HDL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e3.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHOMA-IR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e4.38\u0026thinsp;\u0026plusmn;\u0026thinsp;1.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e4.41\u0026thinsp;\u0026plusmn;\u0026thinsp;2.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.04\u0026thinsp;\u0026plusmn;\u0026thinsp;1.53**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.58\u0026thinsp;\u0026plusmn;\u0026thinsp;2.56**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHOMA-IS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e0.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39**#\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHOMA-β\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e141.05\u0026thinsp;\u0026plusmn;\u0026thinsp;55.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e157.28\u0026thinsp;\u0026plusmn;\u0026thinsp;73.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e166.91\u0026thinsp;\u0026plusmn;\u0026thinsp;78.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e142.28\u0026thinsp;\u0026plusmn;\u0026thinsp;76.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUric acid (\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e576.81\u0026thinsp;\u0026plusmn;\u0026thinsp;126.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e502.35\u0026thinsp;\u0026plusmn;\u0026thinsp;110.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e559.71\u0026thinsp;\u0026plusmn;\u0026thinsp;98.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e536.29\u0026thinsp;\u0026plusmn;\u0026thinsp;117.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVO\u003csub\u003e2 max\u003c/sub\u003e (mL/min/kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e22.95\u0026thinsp;\u0026plusmn;\u0026thinsp;3.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e21.28\u0026thinsp;\u0026plusmn;\u0026thinsp;4.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e25.00\u0026thinsp;\u0026plusmn;\u0026thinsp;4.38*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e26.28\u0026thinsp;\u0026plusmn;\u0026thinsp;6.44**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eValues are given as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. SBP\u0026thinsp;=\u0026thinsp;Systolic blood pressure; DBP\u0026thinsp;=\u0026thinsp;Diastolic blood pressure; TC\u0026thinsp;=\u0026thinsp;Total cholesterol; HDL-C\u0026thinsp;=\u0026thinsp;High-density lipoprotein cholesterol; LDL-C\u0026thinsp;=\u0026thinsp;Low-density lipoprotein cholesterol. * (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), ** (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01): significantly different from pre-invention; # (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), ## (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01): significant difference vs CT-2 group.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSignificant differences were found in the 1RM squat of participants within both the CT-2 and CT-3 groups; however, there was no discernible difference between the two groups.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChanges in the 1RM squat of participants in the CT-2 and CT-3 groups.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCT-2 (N\u0026thinsp;=\u0026thinsp;22)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCT-3 (N\u0026thinsp;=\u0026thinsp;21)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1RM squat (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e67.96\u0026thinsp;\u0026plusmn;\u0026thinsp;15.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e72.42\u0026thinsp;\u0026plusmn;\u0026thinsp;17.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e94.03\u0026thinsp;\u0026plusmn;\u0026thinsp;9.67**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e89.37\u0026thinsp;\u0026plusmn;\u0026thinsp;22.44*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eValues are given as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. 1RM\u0026thinsp;=\u0026thinsp;One-repetition maximum. * (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), ** (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01): significantly different from pre-invention.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study aimed to assess the effect of an 8-week CT intervention on CRFs in young adults with overweight and obesity, focusing on the impact of different weekly training frequencies. Both the CT-2 and CT-3 groups exhibited notable enhancements in anthropometrics, body composition, CRFs, and 1RM squats compared to baseline. Notably, the CT-3 group, which had more frequent weekly exercises, demonstrated superior improvements in HDL-C and HOMA-IS compared to the CT-2 group.\u003c/p\u003e \u003cp\u003eSignificant reductions in body mass, fat mass, and body fat percentage were observed in both groups over the eight-week CT period. The catabolic state induced by regular CT, leading to increased energy consumption without altering dietary habits, aligns with existing literature(\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). The study's results, indicating improvements in participants undergoing regular CT over two months, are promising. However, it's essential to recognize that while exercise can positively impact factors associated with cardiovascular disease risk, it may not uniformly affect all measures simultaneously(\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). In this study, no significant changes in waist circumference, hip circumference, or waist-to-hip ratio were observed compared to baseline. These findings parallel are consistent with studies by Vispute et al(\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). and Kordi et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e), which also noted insignificant changes in waist circumference despite exercise interventions. This underscores the challenge of implementing strict dietary controls during such interventions, especially with overweight and obese individuals. Balancing dietary restrictions with exercise adherence is crucial, as overly strict requirements may negatively impact participant compliance and retention.\u003c/p\u003e \u003cp\u003eDespite the significant decreases in body mass and body fat percentage among participants in both the CT-2 and CT-3 groups, there was no corresponding significant change in lean mass. This discrepancy could be attributed to several factors. Firstly, the strength training employed in the study primarily utilized self-weight exercises, which may be considered lower-intensity compared to traditional machine-based strength training. Consequently, these exercises might not effectively stimulate the mechanisms responsible for skeletal muscle growth(\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Moreover, previous research has identified an interference phenomenon associated with concurrent training, which may impede strength development when compared to dedicated strength training alone(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Our current understanding of this inhibitory effect and its underlying mechanisms remains limited. For instance, prolonged contraction, preceded by AMPK activation, can inhibit downstream translational signaling pathways such as Akt/mTOR, while energy stress may antagonize hypertrophic responses during muscle loading contractions.(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). To comprehensively elucidate these mechanisms, future research endeavors should delve deeper into investigating the complex interactions among various movement modalities and their impacts on muscle physiology.\u003c/p\u003e \u003cp\u003eBlood pressure constitutes a crucial clinical parameter for monitoring individuals, especially those with overweight or obesity. Prior research has underscored the favorable impact of exercise interventions on blood pressure, particularly among hypertensive patients.(\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). Given that participants in our study initially exhibited blood pressure readings within the normal range, it is reasonable to infer that the exercise intervention administered did not produce significant alterations in blood pressure.\u003c/p\u003e \u003cp\u003eCT has been widely acknowledged for its efficacy in improving CRFs through the management of blood glucose and lipids(\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). In our study, participants in the CT-2 and CT-3 groups demonstrated significant reductions in fasting glucose, fasting insulin levels, total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), TC/HDL ratio, LDL/HDL ratio, homeostatic model assessment of insulin resistance (HOMA-IR), and homeostatic model assessment of insulin sensitivity (HOMA-IS) following an 8-week concurrent training intervention. These findings are consistent with results from previous studies employing similar CT interventions(\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan additionalcitationids=\"CR45\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). The decrease in fasting insulin levels can be attributed to CT's ability to enhance insulin sensitivity, thereby enabling tissue cells to utilize insulin more effectively and improve blood glucose regulation(\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). Furthermore, CT facilitates the reduction of body fat, particularly visceral fat, which indirectly influences insulin secretion and sensitivity. Given that the HOMA index is influenced by fasting blood glucose and insulin levels, the observed changes in the HOMA index are understandable. Moreover, the CT-3 group exhibited a more pronounced improvement in HOMA-IS compared to the CT-2 group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), suggesting that higher frequencies of CT led to more significant enhancements in individuals with overweight and obesity.\u003c/p\u003e \u003cp\u003ePrevious studies have generated conflicting results regarding the influence of exercise on plasma triglyceride levels. While some research suggests a decrease in triglyceride levels following aerobic training, others report no significant change post-training(\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e). In our study, the observed reduction in plasma triglyceride levels among participants may be attributed to the concurrent training (CT) intervention. Fasting low-density lipoprotein cholesterol (LDL-C) is strongly associated with an increased risk of cardiovascular disease (CVD). Kelley et al. conducted a meta-analysis and systematic review, revealing that aerobic training for more than eight weeks effectively reduced LDL-C levels and body weight in individuals with type Ⅱ diabetes mellitus, consistent with our findings(\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e). Aerobic exercise enhances high-density lipoprotein cholesterol (HDL-C) levels by increasing lipoprotein lipase concentration and activity in skeletal muscle(\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e). Notably, participants in the CT-2 and CT-3 groups paradoxically exhibited decreased HDL-C levels at the end of the 8-week training period. Similar decreases in HDL-C levels are commonly observed in patients taking statins, and this may be closely linked to overweight and obesity status(\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). Although no significant differences were found between the two groups, the combined reduction in TC/HDL and HDL/LDL ratios powerfully demonstrates that CT is an effective strategy for improving cardiovascular risk factors in adults with overweight and obesity.\u003c/p\u003e \u003cp\u003eIs weight loss the optimal target for reducing cardiovascular disease risk associated with obesity? Indeed, the answer is no. The objective of obesity treatment should encompass modifying body composition, cardiovascular metabolic risk factors, and physical performance, rather than solely focusing on weight loss(\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e). Numerous studies have demonstrated a correlation between cardiorespiratory capacity, muscle strength, and cardiovascular health(\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e). Low muscle strength has been consistently associated with the development of CVD, CVD mortality, and related outcomes across diverse age groups and populations(\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). Associations have also been documented between measures such as the one repetition maximum (1RM) for leg or bench press exercises and the incidence of metabolic syndrome in men aged 20\u0026ndash;80(\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e). Furthermore, a higher maximal oxygen uptake (V̇O2max) has been validated as a negative predictor for CVD and all-cause mortality(59). Encouragingly, both groups of subjects undertaking concurrent training exhibited significantly higher 1RM deep squat and maximal oxygen uptake levels. This suggests that individuals can enhance cardiovascular risk factors by increasing muscle strength and maximal oxygen uptake during an 8-week concurrent training period.\u003c/p\u003e \u003cp\u003eIt is important to acknowledge the limitations of this study and exercise caution when interpreting the findings. Firstly, gender differences among the subjects may have influenced the study results, as the response to training could vary between genders, potentially introducing heterogeneity into the experimental data. However, it is worth noting that similar situations have been encountered in previous experiments, and they did not significantly impact the credibility of the results. Secondly, while the gold-standard high insulin glucose clamp technique was not utilized in this experiment to assess insulin resistance, the HOMA method remains a valuable tool for evaluating insulin resistance. Lastly, although severe dietary restrictions were not imposed, participants were actively encouraged to maintain their dietary habits throughout the intervention trial. Nonetheless, it is important to recognize that dietary variations could have influenced the outcomes to some extent.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, this study emphasizes the efficacy of an 8-week concurrent training (CT) intervention in promoting weight loss, improving CRFs, and enhancing cardiorespiratory fitness among young adults who are overweight or obese. Despite the inherent limitations, the clinical significance of these findings is considerable. The trial demonstrates that CT interventions are both feasible and cost-effective for managing obesity and its associated complications. However, larger-scale studies are needed to validate these results and explore whether prolonging the intervention duration would offer additional benefits.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCT \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Concurrent Training\u003c/p\u003e\n\u003cp\u003eCRFs \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Cardiometabolic risk factors\u003c/p\u003e\n\u003cp\u003eHDL-C \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;High-density lipoprotein cholesterol\u003c/p\u003e\n\u003cp\u003eLDL-C \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Low-density lipoprotein cholesterol\u003c/p\u003e\n\u003cp\u003eTC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;total cholesterol\u003c/p\u003e\n\u003cp\u003eTC/HDL-C \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;total cholesterol/ High-density lipoprotein cholesterol\u003c/p\u003e\n\u003cp\u003eHOMA-IR \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Homeostasis model assessment of insulin resistance\u003c/p\u003e\n\u003cp\u003eHOMA-IS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Homeostasis model assessment of insulin sensitivity\u003c/p\u003e\n\u003cp\u003eHOMA-\u0026beta;\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Homeostasis model assessment of Beta-cell function\u003c/p\u003e\n\u003cp\u003eVO2 max\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;maximal oxygen uptake\u003c/p\u003e\n\u003cp\u003e1RM squat \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;One-repetition maximum squat\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe confirmed that the experimental protocol was approved by Ethics Committee of the Exercise Science Experiment of Beijing Sport University, and informed consent was obtained from each participant after risks and benefits were explained. The study was conducted in accordance with the latest version of the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and analyzed during the current study are not publicly available due to confidential information about the participants but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge the support of the National Key Research and Development Program of China, 2018YFC2000602 and Central Special Funds of the University for Basic Scientific Research 2015SYS009.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFirstly, the authors thank the participants of China Agricultural University for their enthusiastic participation in this research. Finally, the authors acknowledge Yaru Huang professor of China Agricultural University, Caihui Zhao, Langlang Yin, Sheng Huang, Yaqi Wang, Xueyin Fei, Guihua Sun, and Jimin Zhou of Beijing Sport University, which facilitated data collection.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLi J-J, Liu H-H, Li S. Landscape of cardiometabolic risk factors in Chinese population: a narrative review. Cardiovasc Diabetol. 2022;21(1):113.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRakhmat II, Putra ICS, Wibowo A, Henrina J, Nugraha GI, Ghozali M, et al. Cardiometabolic risk factors in adults with normal weight obesity: A systematic review and meta-analysis. Clin Obes. 2022;12(4):e12523.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeiter LA, Fitchett DH, Gilbert RE, Gupta M, Mancini GBJ, McFarlane PA et al. 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Int J Environ Res Public Health. 2020;17(17).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmaro-Gahete FJ, Ponce-Gonz\u0026aacute;lez JG, Corral-P\u0026eacute;rez J, Vel\u0026aacute;zquez-D\u0026iacute;az D, Lavie CJ, Jim\u0026eacute;nez-Pav\u0026oacute;n D. Effect of a 12-Week Concurrent Training Intervention on Cardiometabolic Health in Obese Men: A Pilot Study. Front Physiol. 2021;12:630831.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArtinian NT, Fletcher GF, Mozaffarian D, Kris-Etherton P, Van Horn L, Lichtenstein AH, et al. Interventions to promote physical activity and dietary lifestyle changes for cardiovascular risk factor reduction in adults: a scientific statement from the American Heart Association. Circulation. 2010;122(4):406\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVispute SS, Smith JD, LeCheminant JD, Hurley KS. The effect of abdominal exercise on abdominal fat. 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BMJ. 2018;361:k1651.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJurca R, Lamonte MJ, Barlow CE, Kampert JB, Church TS, Blair SN. Association of muscular strength with incidence of metabolic syndrome in men. Med Sci Sports Exerc. 2005;37(11):1849\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBlomqvist CG, Saltin B. Cardiovascular adaptations to physical training. Annu Rev Physiol. 1983;45:169\u0026ndash;89.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Adults, Cardiometabolic risk factors, Concurrent training, Obesity, Overweight","lastPublishedDoi":"10.21203/rs.3.rs-4424539/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4424539/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cb\u003eBackground\u003c/b\u003e Cardiometabolic risk factors are a significant health concern, particularly among young adults with overweight and obesity. Concurrent training, which combines aerobic and strength exercise, has been shown to improve cardiometabolic health. However, the effects of different training frequencies are not well understood.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMethod\u003c/b\u003e Forty-three participants (mean age: 19 years) were randomly assigned to either the CT-2 group (concurrent training twice per week, n\u0026thinsp;=\u0026thinsp;22) or the CT-3 group (concurrent training three times per week, n\u0026thinsp;=\u0026thinsp;21). The training regimen included 40 minutes of strength training followed by 40 minutes of aerobic exercises. Baseline and eight-week follow-up assessments included anthropometric measurements, body composition analysis, cardiovascular and metabolic parameters, VO2 max, and 1RM squat strength.\u003c/p\u003e \u003cp\u003e \u003cb\u003eResults\u003c/b\u003e Both the CT-2 and CT-3 groups showed significant improvements in body mass, body fat percentage, fat mass, android fat mass, and gynoid fat mass (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). However, the reduction in android/gynoid fat mass ratio was significant only in the CT-3 group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Additionally, fasting glucose, fasting insulin, total cholesterol, triglycerides, HDL-C, LDL-C, TC/HDL-C, HOMA-IR, HOMA-IS, and HOMA-β levels decreased significantly in both groups post-intervention (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Increases in VO2 max (CT-2: p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; CT-3: p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and 1RM squat strength (CT-2: p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; CT-3: p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were also observed. Comparing the two groups, CT-3 group demonstrated more significant improvements in HDL-C (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and HOMA-IS (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cb\u003eConclusion\u003c/b\u003e These findings highlight the effectiveness of concurrent training in improving cardiometabolic risk factors in young adults with overweight and obesity. Both twice-weekly and three times-weekly training significantly improved these risk factors, with higher frequency training providing additional benefits.\u003c/p\u003e","manuscriptTitle":" Effects Of Different Frequencies Of Concurrent Training On Cardiometabolic Risk Factors In Young Adults With Overweight And Obesity: A Randomized Controlled Trial ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-03 14:35:42","doi":"10.21203/rs.3.rs-4424539/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e17cb5b0-a345-4969-9e7e-55dcc9ebbc35","owner":[],"postedDate":"June 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-20T06:59:55+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-03 14:35:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4424539","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4424539","identity":"rs-4424539","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}