Search Results (77)

Background: Considering that the prevalence of obesity has risen rapidly in recent decades, the aim of this study was to investigate the effects of a carbohydrate mouth rinse (CMR) on the outcomes of aerobic training among adult men with obesity, focusing particularly on the effects of repeated use on body composition and exercise performance. Methods: The intervention targeted 20 men with obesity in their 20s and 30s randomly assigned to either a CMR group (n = 10) or a placebo mouth rinse (PMR) group (n = 10). Both groups completed treadmill-based aerobic training three times per week for eight weeks. Prior to each session, participants used a mouth rinse at 60, 40, and 20 s before the start of each exercise, holding either a 6% maltodextrin solution (CMR) or purified water (PMR) in their mouths for 5 to 10 s before expectorating. Pre- and post-intervention assessments included body composition (body weight and body fat percentage), resting metabolic rate (RMR), maximal oxygen uptake (VO₂max), and exercise performance (rate of perceived exertion [RPE], exercise distance, speed, and time). Data were analyzed using 2 × 2 repeated measures analysis of variance. Results: Following the intervention, the CMR group showed significantly greater improvements than the PMR group did in body fat percentage, RMR, VO₂max, exercise distance, speed, and time (p < 0.01). However, the interaction effect for RPE was not statistically significant between the groups (p = 0.175). Overall, the repeated use of the CMR during aerobic training contributed to enhanced exercise performance and favorable physiological changes without additional caloric intake. Conclusions: A CMR may be a practical and non-caloric ergogenic aid to support exercise performance and metabolic function in individuals with obesity. Its repeated use during aerobic training appears to be effective and safe, especially when fasting while exercising, when improving endurance without compromising fat loss is essential. Full article

Background: Correct assessment of resting metabolic rate (RMR) is fundamental for estimating total energy expenditure in both clinical nutrition and sports sciences research. Various methods have been proposed for RMR determination, including predictive equations, isotopic dilution techniques, and indirect calorimetry. Over the past two decades, portable gas analyzers have emerged as promising alternatives, offering more accessible and cost-effective solutions for metabolic assessment. However, evidence regarding their validity remains inconsistent, particularly across diverse populations and varying metabolic assessment protocols. Methods: This systematic review was conducted in May 2025 using the PubMed, Web of Science, and EBSCO databases, following the PRISMA-DTA guidelines, and included observational studies with the objective of examining the available evidence regarding the validity of portable gas analyzers to determine RMR in humans. The methodological quality of each study was assessed using the NIH Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Results: From an initial pool of 230 studies, 16 met the eligibility criteria. The findings revealed notable variability in measurement validity among devices, mainly influenced by device model, population characteristics, and methodological factors. While portable analyzers such as FitMate and Q-NRG exhibited high validity, MedGem exhibited systematic biases, particularly in individuals with higher adiposity, leading to RMR overestimations. Conclusions: The main results demonstrated the critical need for rigorous validation of portable gas analyzers before their implementation in clinical and research settings to ensure their applicability across diverse populations and metabolic assessments. Full article

Resting metabolic rate (RMR) significantly impacts total daily energy expenditure, particularly on training days, and varies among trained individuals. Studies estimating RMR in this population show notable discrepancies. This study aimed to develop and validate new bioelectrical impedance analysis-based (BIA) RMR equations for young athletes, using a calibration and a validation group of 219 and 51 participants, respectively. RMR was measured via indirect calorimetry, while body composition was assessed through DXA and BIA. Correlation and agreement were evaluated by using Pearson’s correlation coefficients and Bland–Altman analysis. Multiple linear regression was applied for the estimation of RMR and a one-way ANOVA was used to compare the new BIA-based equations with other specific formulas. A significant correlation was noted between the BIA and DXA measurements. The final equation, applicable to both genders, was significantly correlated with intracellular water (ICW) and trunk fat, predicting 71.1% of RMR variance. When analyzed separately, body weight and protein displayed a moderate correlation with RMR in men (r = 0.616, p < 0.001), while ICW was correlated with the percentage of body fat in women (r = 0.579, p < 0.001). In the validation group, the values obtained through the three BIA-based equations were similar to the measured RMR, but differed significantly from those obtained through the four existing equations for trained individuals. In conclusion, the developed equations based on BIA-mediated body composition analysis provide a reliable method for estimating RMR in trained populations daily. Full article

The COVID-19 pandemic has been linked to numerous threats to public health. Of these, physical inactivity became increasingly prevalent, mainly due to the widespread closure of indoor gyms. Home-based exercise alternatives were created as potential solutions, but little research is available validating their efficacy to improve long-term health and fitness. This case study investigated the longitudinal effects of ≥three weekly exercise sessions with a smart home-based fitness platform on anthropometric, fitness, and cardiometabolic measures. Three participants were annually assessed over a five-year period spanning before and after the COVID-19 pandemic. Reductions in body fat percentage occurred simultaneously with increases in fat-free mass. Improvements in physical performance measures, including VO₂ max and both one-repetition maximum (1-RM) and 85% 1-RM for chest press and squat press, were identified. Cardiometabolic measures also demonstrated notable improvements, as borderline hypertension was reduced along with resting heart rate while resting metabolic rate (RMR) and heart rate variability (HRV) increased. Beyond these metrics, volitional exercise frequency grew without compromising exercise program adherence. Although physical activity on a global scale decreased during the COVID-19 pandemic, the long-term cardiometabolic and fitness benefits observed with this home-based exercise platform highlight its potential to improve health and fitness. Full article

Background: Tirzepatide (TZP), a unimolecular dual agonist targeting glucose-dependent insulinotropic polypeptide and glucagon-like peptide-1 receptors, is a promising weight loss agent in obesity. The preservation of metabolically active fat-free mass (FFM), muscle strength (MS), and resting metabolic rate (RMR) is essential for optimizing fat mass (FM) reduction. Although TZP is typically combined with a low-calorie diet (LCD), its impact on FFM is uncertain, and studies on MS and RMR are lacking. Evidence suggests that Low-Energy Ketogenic Therapy (LEKT) may reduce FM while preserving FFM, MS, and RMR. Therefore, this study aimed to compare the effects of an LEKT and an LCD, both combined with TZP, on body weight (BW), FM, FFM, MS, and RMR in patients with obesity. Methods: We prospectively compared the effects of TZP combined with either an LCD or LEKT in 60 patients with obesity (n = 30 per group) over 12 weeks. BW, FM, FFM, MS, and RMR were measured at baseline and after 12 weeks. Clinical parameters, an assessment of dietary compliance, and side effects were also evaluated. Results: At 12-week follow-up, both groups showed a significant BW reduction from baseline (TZP+LEKT, p = 0.0289; TZP+LCD, p = 0.0278), with no significant intergroup difference (p = 0.665). Similarly, FM decreased significantly in both cohorts (TZP+LEKT, p < 0.001; TZP+LCD, p = 0.0185), with the TZP+LEKT group achieving a greater FM loss (p = 0.042). However, the TZP+LCD group exhibited significant declines from baseline in FFM (p = 0.0284), MS (p = 0.0341), and RMR (p < 0.001), whereas we did not observe any significant changes in FFM (p = 0.487), MS (p = 0.691), and RMR (p = 0.263) in the TZP+LEKT group. Intergroup direct comparisons confirmed that the TZP+LCD group experienced significantly greater reductions in FFM (p = 0.0388), MS (p = 0.046), and RMR (p = 0.019). Conclusions: Based on the findings of these preliminary data, we are able to support the hypothesis that TZP+LEKT seems to be superior to TZP+LCD in promoting FM reduction while preserving FFM, MS, and RMR in patients with obesity. Full article

This study investigated how the DNACJ6 gene variation related to RMR alteration affects risk factors of obese environments in children with obesity aged 8–9. Methods: Over a three-year follow-up period, 63.3% of original students participated. Changes in the variables (anthropometrics, blood biochemistry, and dietary intakes) were analyzed and compared between those without obesity (non-OB) and with obesity (OB) classified at the study endpoint. Result: The average MAF of nine SNPs (D-1 to D-IX) was defined as 18.1%. The OB group showed greater increases in RMR, BMI, WC, and SBP, while the non-OB group had significantly greater increases in HDL and intakes of nutrients (e.g., total calories, vitamins B2, C, folate, A, retinol, iron, and zinc). Increased RMR, BMI, BW, and RMR/BW changes were observed with mutant allele of D-I SNP, which was also associated with a higher prevalence of obesity. Greater increases in animal fat intake, including saturated fatty acids and retinol, were noted in the minor alleles of D-VI, D-VII, D-VIII, and D-IX SNPs compared to those of the major alleles. The odds ratio for BMI risk was significantly higher in the mutant alleles of D-I (rs17127601), D-VII (rs1334880), and D-VIII (rs7354899) compared to the wild type, with increases of 2.59 times (CI; 1.068–6.274), 1.86 times (CI; 1.012–3.422), and 1.85 times (CI; 1.008–3.416), respectively. RMR was a mild risk factor in minors of the D-1, D-VII, and D-VIII; however, a higher RMR/BW ratio significantly correlated with decreased BMI risk, and this effect was found in only the major alleles of D-I, D-VII, and D-VIII SNPs, not in the minor alleles. High retinol intake appeared to reduce obesity risk in the minor alleles of the D-I, D-VII, and D-VIII SNPs, even though intake of animal fats and retinol remained higher among minors over the three years. Conclusions: These findings suggest that the RMR/BW ratio and dietary fat/retinol intake should be considered in DNACJ6-gene-based precision medicine approaches for pediatric obesity prevention, particularly for boys. Full article

Low energy availability (LEA) is common among female student-athletes and contributes to reduced bone mineral density and hormonal dysfunction. However, limited research exists on student-athletes of color, making it difficult to generalize results across populations, particularly Historically Black Colleges and Universities (HBCUs) student-athletes. Objectives: This study examined the energy needs and LEA prevalence, with or without eating disorder (ED) risk, among HBCU female student-athletes. Methods: Twenty-seven female student-athletes (age = 19 ± 1 year; height = 166.9 ± 7.6 cm; weight = 68.8 ± 11.3 kg) completed baseline measures, including the Eating Disorder Inventory-3 (EDI-3), EDI-3 symptom checklist (EDI-SC), anthropometric measures, and resting metabolic rate (RMR). Participants maintained a dietary log to measure energy intake and wore a heart rate monitor to estimate exercise energy expenditures for 7 days. LEA was defined as <30 kcal/kg of fat-free mass (FFM)/day. Results: The mean energy availability (15.9 ± 10.1 kcal/kg FFM/day) indicated 92.6% of participants (n = 25) displayed LEA; of those, 60% (n = 15) had LEA with ED risk. ED risk was identified in 59.3% of student-athletes (n = 13; EDI-3: n = 2; SC: n = 3; Both: n = 11). Interestingly, of the two student-athletes without LEA, one was identified at risk for EDs using both the EDI-3 and SC. Conclusions: HBCU female student-athletes face high risks of LEA and EDs, with most showing signs of both. This underscores the need for culturally sensitive interventions to improve EA and support mental health in this underserved group. Clinicians should focus on nutrition education and early ED identification to enhance long-term health and athletic performance. Full article

The purpose of the study was to examine differences in body fat percentage (BF%) across groups stratified by resting metabolic rate (RMR) when normalized to body weight. National Collegiate Athletic Association Division III athletes (n = 190; Age: 19.8 ± 1.4 year; Body Mass: 79.3 ± 20.2 kg; Height: 175.0 ± 9.3 cm, Body Mass Index: 25.6 ± 4.9 kg/m²) participated in this cross-sectional mixed cohort study. Body composition was assessed using air displacement plethysmography. RMR was assessed using indirect calorimetry. For each sex, tertiles were determined and used to create low, moderate, and high relative RMR groups as follows: low (M: <26 kcal/kg; F: <24 kcal/kg), moderate (M: 26.1–29.0 kcal/kg; F: 24.1–27.0 kcal/kg), and high (M: >29.1 kcal/kg; F: >27.1 kcal/kg). The mean ± standard deviation RMR for male and female athletes was 27.9 ± 3.2 and 25.9 ± 2.8 kcals/kg when expressed relative to body weight. When stratified by sex, males in the low RMR group had significantly higher BF% values than those in the moderate (mean difference, [95% confidence intervals]) (7.2, [2.4, 12.0] kcal/kg; p < 0.01) and high RMR groups (7.7, [2.9, 12.5] kcal/kg; p < 0.001). Female athletes in the moderate RMR group had higher body fat percentages than those in the high RMR group (mean difference, [95% confidence intervals]) (5.8, [2.4, 9.2] kcal/kg; p < 0.01). Female athletes in the moderate relative RMR group had higher BF% values than those in the higher relative RMR group (3.3, [−0.1, 6.7] kcal/kg; p = 0.049). Both male and female athletes with a low relative RMR had a higher BF%. Full article

Turkesterone is a naturally occurring plant steroid touted for its medicinal, pharmacological, and biological properties with no reported adverse side effects compared with traditional anabolic androgenic steroids (AAS). However, this ostensible enhancement to increase muscle protein synthesis and facilitate augmented thermogenesis remains undescribed despite uninformed and potentially haphazard consumption. To investigate whether turkesterone enhances insulin-like growth factor-1 (IGF-1) and resting metabolic rate (RMR), eleven apparently healthy males (23.3 ± 2.2) volunteered to participate in the present study with samples collected pre-, 3H post-, and 24H post-ingestion. Subsequent analyses failed to reveal any significant main condition, time, or interaction main effects for serum IGF-1, RMR, lipid, and carbohydrate metabolism (p > 0.05). However, non-significant serum IGF-1 concentrations increased with both turkesterone conditions and remained elevated when compared with placebo. Similarly, RMR remained elevated above baseline across the 3 h assessed. Although these data fail to fully support turkesterone as a potent anabolic supplement, nevertheless, our findings are foundational to persistently tease apart this supplement’s purported ergogenic effects and underscore its favorable hemodynamic and gastrointestinal tolerability profile. Future investigations should, therein, aim to assess turkesterone-mediated IGF-1 increases on long-term whole-muscle growth across several training sessions to further substantiate its efficacy on anabolism. Full article

Background/Objectives: Resting metabolic rate (RMR) is an important contributor of energy balance and displays a well-documented relationship with sex, age, race and fat-free mass (FFM) in the existing scientific literature. However, the impact of other body composition components such as fat and liver fat on RMR remains unclear. This study aims to investigate the correlation of RMR with body composition parameters in a sample of patients with overweight and obesity. Methods: Retrospective data of patients with overweight or obesity referred for magnetic resonance imaging of liver fat during the period 2018–2023 were utilized for this study. Demographic and anthropometric data were collected, including body composition parameters (body fat, muscle mass) and RMR measured by bioelectrical impedance and indirect calorimetry, respectively. Results: The final sample included 53 patients (66% male), with a mean age of 48 years (±11.2) and a mean body mass index (ΒΜΙ) of 38.5 kg/m² (32.7, 44.7). Simple correlation models revealed that RMR was separately correlated with gender, age, BMI, muscle mass, and liver fat (all p < 0.05) but not with fat mass. When multiple regression models were employed, only muscle mass retained its statistically significant influence on RMR, while total and hepatic fat did not significantly affect RMR after controlling for other parameters (gender, age, muscle mass). Conclusions: These findings confirm the known correlation between muscle mass and RMR while highlighting the lack of association between total and hepatic fat and RMR in individuals with overweight and obesity. Full article

Background: Smoking cessation is crucial for reducing complications of type 2 diabetes mellitus (T2DM), but associated weight gain can worsen glycemic control, discouraging quitting attempts. Varenicline, a partial agonist of α4β2 nicotinic receptors, aids smoking cessation. This study examines the effects of varenicline on body weight and metabolic parameters in patients with T2DM and prediabetes. Methods: Fifty-three patients were enrolled, of which 32 successfully quit smoking after a three-month course of varenicline and were examined after an additional month with no medication. Measurements taken at baseline, 2.5 months, and 4 months included body weight, blood pressure, resting metabolic rate (RMR), glycated hemoglobin (HbA1c), fasting glucose, blood lipids, C-reactive protein (CRP), appetite-related hormones, and physical activity. Results: Post-treatment, there were no significant changes in body weight, blood pressure, RMR, or glycemic control. Total (CHOL) and low-density lipoprotein (LDL-C) cholesterol decreased significantly at 4 months of the study (from 168 to 156 mg/dL, p = 0.013, and from 96 to 83 mg/dL, p = 0.013, respectively). Leptin levels increased (from 11 to 13.8 ng/dL, p = 0.004), as did glucagon-like peptide-1 (GLP-1) levels (from 39.6 to 45.8 pM, p = 0.016) at 4 months of follow-up. The percentage of participants who reported moderate-intensity activity increased from 28% to 56%, while those reporting high-intensity activity increased from 19% to 22%, respectively (p = 0.039). Conclusions: Our study showed that smoking cessation with varenicline in smokers with T2DM and prediabetes led to significant improvements in lipid profile, significant increase in plasma leptin and GLP-1 levels, and increased physical activity, without significant weight gain. Thus, smoking cessation without weight gain or deteriorated glycemic control is feasible for these smokers, with added benefits to lipid profiles, GLP-1 regulation, and physical activity. Full article

This study aimed to investigate the resting metabolic rate (RMR) in cross-training practitioners (advanced and novice) using indirect calorimetry (IC) and compare it with predictive equations proposed in the scientific literature. Methods: A cross-sectional and comparative study analyzed 65 volunteers, both sexes, practicing cross-training (CT). Anthropometry and body composition were assessed, and RMR was measured by IC (FitMate PRO^®), bioimpedance (BIA-InBody 570^®), and six predictive equations. Data normality was tested by the Kolgomorov–Smirnov test and expressed as mean ± standard deviation with 95% confidence intervals (CI), chi-square test was performed to verify ergogenic resources, and a Bland–Altman plot (B&A) was made to quantify the agreement between two quantitative measurements. One-way ANOVA was applied to body composition parameters, two-way ANOVA with Bonferroni post hoc was used to compare the RMR between groups, and two-way ANCOVA was used to analyze the adjusted RMR for body and skeletal muscle mass. The effect size was determined using Cohen’s d considering the values adjusted by ANCOVA. If a statistical difference was found, post hoc Bonferroni was applied. The significance level was p < 0.05 for all tests. Results: The main results indicated that men showed a higher RMR than women, and the most discrepant equations were Cunningham, Tinsley (b), and Johnstone compared to IC. Tinsley’s (a) equation indicated greater precision in measuring the RMR in CM overestimated it by only 1.9%, and BIA and the Harris–Benedict in CW overestimated RMR by only 0.1% and 3.4%, respectively. Conclusions: The BIA and Harris–Benedict equation could be used reliably to measure the RMR of females, while Tinsley (a) is the most reliable method to measure the RMR of males when measuring with IC is unavailable. By knowing which RMR equations are closest to the gold standard, these professionals can prescribe a more assertive diet, training, or ergogenic resources. An assertive prescription increases performance and can reduce possible deleterious effects, maximizing physical sports performance. Full article

This study aimed to develop a novel predictive equation for calculating resting metabolic rate (RMR) in women with lipedema. We recruited 119 women diagnosed with lipedema from the Angiology Outpatient Clinic at Wroclaw Medical University, Poland. RMR was assessed using indirect calorimetry, while body composition and anthropometric measurements were conducted using standardized protocols. Due to multicollinearity among predictors, classical multiple regression was deemed inadequate for developing the new equation. Therefore, we employed machine learning techniques, utilizing principal component analysis (PCA) for dimensionality reduction and predictor selection. Regression models, including support vector regression (SVR), random forest regression (RFR), and k-nearest neighbor (kNN) were evaluated in Python’s scikit-learn framework, with hyperparameter tuning via GridSearchCV. Model performance was assessed through mean absolute percentage error (MAPE) and cross-validation, complemented by Bland–Altman plots for method comparison. A novel equation incorporating body composition parameters was developed, addressing a gap in accurate RMR prediction methods. By incorporating measurements of body circumference and body composition parameters alongside traditional predictors, the model’s accuracy was improved. The segmented regression model outperformed others, achieving an MAPE of 10.78%. The proposed predictive equation for RMR offers a practical tool for personalized treatment planning in patients with lipedema. Full article

Active athletes frequently develop low energy (LEA) and protein availabilities (LPA) with consequent changes in the vital metabolic processes, especially resting metabolic rate (RMR) and substrate utilization. This study investigated the association of energy and protein intakes with RMR and substrate utilization in male and female athletes and those with LEA and LPA. Sixty athletes (35% female, 26.83 ± 7.12 y) were enrolled in this study. Anthropometric measurements and body composition analysis were reported to estimate fat-free mass (eFFM). Dietary intakes were recorded by two-day multiple-pass 24 h recall records and three-day food records and then analyzed by food processor software to calculate protein intake (PI) and energy intake (EI). Indirect calorimetry was used to measure RMR and percentages of substrate utilization. Activity–energy expenditure (AEE) was assessed by using an Actighrphy sensor for three days. Energy availability was calculated using the following formula (EA = EI − AEE/eFFM). The correlation of EI and PI with RMR and substrate utilization was tested with Pearson correlation. In the LEA group, both EI and PI correlated positively with RMR (r = 0.308, 0.355, respectively, p < 0.05). In addition, EI showed a positive correlation with the percentage of fat utilization. In the male and sufficient-PA groups, PI correlated positively with the RMR and negatively with the percentage of protein utilization. In conclusion, the percentage of LEA is markedly prevalent in our sample, with a higher prevalence among males. Athletes with LEA had lower fat utilization and lower RMR, while those with sufficient PA showed lower protein utilization with excessive PI. These findings may explain the metabolic responses in the cases of LEA and LPA. Full article

Determining resting metabolic rate (RMR) is an important aspect when calculating energy requirements for professional rugby union players. Prediction equations are often used for convenience to estimate RMR. However, the accuracy of current prediction equations for professional rugby union players remains unclear. The aims of this study were to examine the RMR of professional male rugby union players compared to nine commonly used prediction equations and develop and validate RMR prediction equations specific to professional male rugby union players. One hundred and eight players (body mass (BM) = 102.9 ± 13.3 kg; fat-free mass (FFM) = 84.8 ± 10.2 kg) undertook Dual-energy X-ray Absorptiometry scans to assess body composition and indirect calorimetry to determine RMR. Mean RMR values of 2585 ± 176 kcal∙day⁻¹ were observed among the group with forwards (2706 ± 94 kcal·day⁻¹), demonstrating significantly (p < 0.01; d = 1.93) higher RMR compared to backs (2465 ± 156 kcal·day⁻¹), which appeared to be due to their higher BM and FFM measures. Compared to the measured RMR for the group, seven of the nine commonly used prediction equations significantly (p < 0.05) under-estimated RMR (−104–346 kcal·day⁻¹), and one equation significantly (p < 0.01) over-estimated RMR (192 kcal·day⁻¹). This led to the development of a new prediction equation using stepwise linear regression, which determined that the strongest predictor of RMR for this group was FFM alone (R² = 0.70; SEE = 96.65), followed by BM alone (R² = 0.65; SEE = 104.97). Measuring RMR within a group of professional male rugby union players is important, as current prediction equations may under- or over-estimate RMR. If direct measures of RMR cannot be obtained, we propose the newly developed prediction equations be used to estimate RMR within professional male rugby union players. Otherwise, developing team- and/or group-specific prediction equations is encouraged. Full article