Interindividual variability in energy intake and expenditure during a weight loss intervention.

INTRODUCTION: Behavioral compensations may occur as a response to a negative energy balance. The aim of this study was to explore the associations between changes in energy intake (EI) and changes in physical activity (PA, min/day; kcal/d) as a response to a weight loss (WL) intervention and to understand if interindividual differences occur in EI and energy expenditure (EE). METHODS: Eighty-one participants [mean (SD): age = 42.8 (9.4)y, BMI = 31.2 (4.4)kg/m2, 37% females] divided in intervention (IG, n = 43) and control group (CG, n = 38) were included. The IG underwent a moderate energy restriction (300-500 kcal/d). EI was measured through the intake-balance method. Non-exercise PA (NEPA) and exercise (through logbook) were assessed by accelerometery. The EE in NEPA (NEAT) and in exercise (EiEE) was calculated by applying the Freedson Combination'98 algorithm over the time spent in these activities. Pearson correlations were performed in IG to examine associations between EE components, EI and body composition. To understand if interindividual differences were observed, the SD of individual response (SDIR) and the smallest worthwhile change (SWC, SDbaselineCG×0.2) were calculated. RESULTS: Changes in EI [Δ EI, (kcal/d)] was negatively associated with Δ exercise (min/d:r = -0.413, p = 0.045; %:r = -0.846, p = 0.008) and with Δ EiEE (kcal/d:r = -0.488, p = 0.016; %:r = -0.859, p = 0.006). A negative correlation was found between Δ sedentary time and Δ NEPA (min/d:r = -0.622, p = 0.002; %:r = -0.487, p = 0.018). An interindividual variability was found for EI(SDIR = 151.6, SWC = 72.3) and EE (SDIR = 165, SWC = 134). CONCLUSIONS: Decreases in EI were not associated to compensatory responses such as decreases in PA and/or increases in sedentary time. Interindividual variability was found for EI and EE. Nevertheless, behavioral compensations and the interindividual variability should be considered when implementing WL interventions, to increase the likelihood of achieving sustainable results. (clinicaltrials.gov ID: NCT03031951).

Body Size, Fatness and Skeletal Age in Female Youth Soccer Players.

Growth and maturation are central concerns in the organization of training and competitions in youth sports. This study examined maturity-associated variation in body size and adiposity among adolescent girls participating in competitive age group youth soccer. The sample included 441 players 10.08-16.73 years of age. Stature and body mass were measured and body composition was predicted. The Fels method was used to estimate skeletal age. Skeletally maturity status (late, average or early maturing) was based on the difference between chronological and skeletal age for each player. Mean stature approximated the 50th percentiles of the general population in all competitive age groups, while mean weight fluctuated between 50th and 75th percentiles. Age- and maturity-specific means for estimated fat mass ranged between 18.0% and 28.2%. The number of players classified as skeletally mature increased with competitive age groups (under-13: 0%; under-15: 8%; under-17: 49%). In general, early maturing girls tended to be heavier than their age group peers and especially when compared to late maturing players.

Effects of a 4-month active weight loss phase followed by weight loss maintenance on adaptive thermogenesis in resting energy expenditure in former elite athletes.

PURPOSE: Despite adaptive thermogenesis (AT) being studied as a barrier to weight loss (WL), few studies assessed AT in the resting energy expenditure (REE) compartment after WL maintenance. The aim of this study was twofold: (1) to understand if AT occurs after a moderate WL and if AT persists after a period of WL maintenance; and (2) if AT is associated with changes in body composition, hormones and energy intake (EI). METHODS: Ninety-four participants [mean (SD); BMI, 31.1(4.3)kg/m2; 43.0(9.4)y; 34% female] were randomized to intervention (IG, n = 49) or control groups (CG, n = 45). Subjects underwent a 1-year lifestyle intervention, divided in 4 months of an active WL followed by 8 months of WL maintenance. Fat mass (FM) and fat-free mass (FFM) were measured by dual-energy X-ray absorptiometry and REE by indirect calorimetry. Predicted REE (pREE) was estimated through a model using FM, FFM. EI was measured by the "intake-balance" method. RESULTS: For the IG, the weight and FM losses were - 4.8 (4.9) and - 11.3 (10.8)%, respectively (p < 0.001). A time-group interaction was found between groups for AT. After WL, the IG showed an AT of -85(29) kcal.d-1 (p < 0.001), and remained significant after 1 year [AT = - 72(31)kcal.d-1, p = 0.031]. Participants with higher degrees of restriction were those with an increased energy conservation (R = - 0.325, p = 0.036 and R = - 0.308, p = 0.047, respectively). No associations were found between diet adherence and AT. Following a sub-analysis in the IG, the group with a higher energy conservation showed a lower WL and fat loss and a higher initial EI. CONCLUSION: AT in REE occurred after a moderate WL and remained significant after WL maintenance. More studies are needed to better clarify the mechanisms underlying the large variability observed in AT and providing an accurate methodological approach to avoid overstatements. Future studies on AT should consider not only changes in FM and FFM but also the FFM composition.

Adaptive thermogenesis after moderate weight loss: magnitude and methodological issues.

PURPOSE: The aim of this study was (1) to assess AT through 13 different mathematical approaches and to compare their results; and (2) to understand if AT occurs after moderate WL. METHODS: Ninety-four participants [mean (SD); BMI, 31.1 (4.3) kg/m2; age, 43.0 (9.4) years; 34% females] underwent a 1-year lifestyle intervention (clinicaltrials.gov ID: NCT03031951) and were randomized to intervention (IG, n = 49) or control groups (CG, n = 45), and all measurements were made at baseline and after 4 months. Fat mass (FM) and fat-free mass (FFM) were measured by dual-energy X-ray absorptiometry and REE by indirect calorimetry. AT was assessed through 13 different approaches, varying in how REE was predicted and/or how AT was assessed. RESULTS: IG underwent a mean negative energy balance (EB) of 270 (289) kcal/day, p < 0.001), resulting in a WL of - 4.8 (4.9)% and an FM loss of - 11.3 (10.8)%. Regardless of approach, AT occurred in the IG, ranging from ~ - 65 to ~ - 230 kcal/day and three approaches showed significant AT in the CG. CONCLUSIONS: Regardless of approach, AT occurred after moderate WL in the IG. AT assessment should be standardized and comparisons among studies with different methodologies to assess AT must be avoided.

Effectiveness of a lifestyle weight-loss intervention targeting inactive former elite athletes: the Champ4Life randomised controlled trial.

OBJECTIVES: Many athletes struggle in managing the end of their career, often gaining weight and adopting unhealthy lifestyles. Lifestyle programmes targeting former athletes who have gained substantial fat mass (FM) postsports career are lacking. We studied the effects of the Champ4Life programme on body composition and other health-related outcomes in former elite athletes with overweight or obesity. METHODS: Ninety-four former athletes(42.4±7.3 y, 34.0% female) were recruited and randomly assigned to either an intervention group (IG; n=49) or a control group (CG; n=45). The IG attended 12 educational sessions addressing physical activity, weight management and nutrition. They also had a nutrition appointment aimed to prescribe a moderate caloric deficit(~300-500 kcal/day). Dual-energy X-ray absorptiometry was used to assess body composition. The Short-Form Health Survey-36 questionnaire was used to measure general health-related quality of life. Blood samples were collected to assess cardiometabolic health parameters. RESULTS: At 12 months, the IG lost more weight (estimated difference (ED)=-5.3 kg; -6.9 to -3.8), total FM (ED=-4.1 kg; -5.4 to -2.8) and abdominal FM (ED=-0.49 kg; -0.64 to -0.33) than did the CG (p's<0.001). Cardiometabolic health markers also improved significantly (p<0.05) more in the IG at 12 months (insulin (ED=-4.9 µU/mL;-8.0 to -1.8); homoeostatic model assessment (ED=-1.2; -2.1 to -0.4); total cholesterol (ED=-21.8 mg/dL; -35.4 to -8.2); low-density lipoprotein (ED=18.2 mg/dL;-29.2 to -7.1)), as did quality-of-life dimensions (physical functioning (ED=11.7; 6.5 to 16.9); physical role (ED=17.6; 2.1 to 33.0); general health (ED=19.4; 11.4 to 27.4); vitality (ED=13.3; 5.3 to 21.3) and mental health (ED=12.3; 4.1 to 20.6)). CONCLUSIONS: The Champ4Life programme was effective in substantially reducing total and abdominal FM while preserving fat-free mass and improving health-related markers. These findings will enable evidence-based decisions when implementing lifestyle interventions targeting retired elite athletes. TRIAL REGISTERATION NUMBER: NCT03031951.

Energy Availability Over One Athletic Season: An Observational Study Among Athletes From Different Sports.

During the athletic season, changes in body composition occur due to fluctuations in energy expenditure and energy intake. Literature regarding changes of energy availability (EA) is still scarce. The aim was to estimate EA of athletes from nonweight and weight-sensitive sports during the athletic season (i.e., preparatory and competitive phase). Eighty-eight athletes (19.1 ± 4.2 years, 21.8 ± 2.0 kg/m2, 27% females, self-reported eumenorrheic) from five sports (basketball [n = 29]; handball [n = 7]; volleyball [n = 9]; swimming [n = 18]; and triathlon [n = 25]) were included in this observational study. Energy intake and exercise energy expenditure were measured through doubly labeled water (over 7 days and considering neutral energy balance) and metabolic equivalents of tasks, respectively. Fat-free mass (FFM) was assessed through a four-compartment model. EA was calculated as EA = (energy intake - exercise energy expenditure)/FFM. Linear mixed models, adjusted for sex, were performed to assess EA for the impact of time by sport interaction. Among all sports, EA increased over the season: basketball, estimated mean (SE): 7.2 (1.5) kcal/kg FFM, p < .001; handball, 14.8 (2.9) kcal/kg FFM, p < .001; volleyball, 7.9 (2.8) kcal/kg FFM, p = .006; swimming, 8.7 (2.0) kcal/kg FFM, p < .001; and triathlon, 9.6 (2.0) kcal/kg FFM, p < .001. Eleven athletes (12.5%) had clinical low EA at the preparatory phase and none during the competitive phase. During both assessments, triathletes' EA was below optimal, being lower than basketballers (p < .001), volleyballers (p < .05), and swimmers (p < .001). Although EA increased in all sports, triathlon's EA was below optimal during both assessments. Risk of low EA might be seasonal and resolved throughout the season, with higher risk during the preparatory phase. However, in weight-sensitive sports, namely triathlon, low EA is still present.

Validity of water compartments estimated using bioimpedance spectroscopy in athletes differing in hydration status.

We aimed to validate bioelectrical impedance spectroscopy (BIS), compared with tracer dilution measurements, for assessing total body water (TBW), intracellular water (ICW), and extracellular water (ECW) in athletes differing in hydration status. A total of 201 athletes participated. Reference TBW and ECW were determined by deuterium and bromide dilution methods, respectively; ICW was calculated as TBW-ECW. Water compartments were estimated by BIS. Urine specific gravity (USG) classified athletes into well-hydrated (WH) (USG < 1.023), euhydrated (EH) (USG:1.024-1.026), and dehydrated (DH) (USG>1.027). No significant differences were found between BIS and the reference methods for WH, EH, and DH athletes for TBW, ICW nor ECW (p>0.05). Concordance of TBW and its compartments by method was significant (p < 0.001) with coefficients of determination ranging by hydration classification [EH:52-96%;DH:56-98%;WH:71-96%]. Bland-Altman analyses showed no trend for TBW and its compartments with the exception of ICW in the WH athletes. The 95% confidence BIS intervals for the WH group ranged from -3.08 to 2.68 kg for TBW, -4.28 to 4.14 kg for ICW, and -3.29 to 3.02 kg for ECW. For the EH athletes, the 95% confidence intervals ranged from -2.78 to 2.24 kg for TBW, -4.10 to 3.94 kg for ICW, and -3.44 to 3.06 kg for ECW. In DH group, TBW ranged between -1.99 and 2.01 kg, ICW between -3.78 and 6.34 kg, and ECW between -6.22 and 3.74 kg. These findings show that BIS is useful at a group level in assessing water compartments in athletes differing in hydration status. However, the usefulness of BIS is limited at an individual level, especially in dehydrated athletes.

Usefulness of Reflection Scanning in Determining Whole-Body Composition in Broadly Built Individuals Using Dual-Energy X-ray Absorptiometry.

Whole-body composition analysis by dual-energy X-ray absorptiometry (DXA) requires subjects to fit within the width limits of the DXA bed. To overcome this limitation, the aim of this study was to validate a partial scanning technique at which the upper left limb is deliberately left unscanned and measurements are "reflected" from the right-side upper limb. A Hologic Explorer-W densitometer was used in a sample of 189 participants, including athletes and nonathletes, ranging from underweight to obese (body mass index: 17.0-40.1 kg/m2). A whole-body scan was analyzed as the reference procedure to determine bone mineral content (BMC), lean soft tissue (LST), and fat mass (FM), and reanalyzed using a partial reflection scanning (RS) technique. RS estimates of BMC were associated with athletic status and differed significantly from reference estimates (p < 0.05). Also, the RS estimates of LST and FM were different (p < 0.05) from those of the reference whole-body scan, although differences were small (0.17 kg, -0.02 kg, and -0.10% for BMC, LST, and FM, respectively). The alternative procedure explained more than 99% of the reference scan variance with low limits of agreement (BMC: -13.8 to 23.9 g [athletes] and -6.3 to 18.0 g [nonathletes]; LST: -0.11 to 0.45 kg; FM: -0.22 to 0.17 kg). Regardless of body mass index, athletic status, and gender, RS is a useful and simple solution to be used in individuals wider than the DXA scan area. However, individual errors for BMC may be higher in athletes engaged in lateral dominant sports practice.

A cross-sectional and prospective analyse of reallocating sedentary time to physical activity on children's cardiorespiratory fitness.

Cardiorespiratory fitness (CRF) is associated with health benefits in children, improving cardiac morphology, cardiovascular disease risk factors, and biological outcomes. This study aimed to examine the substitution effects of displaying a fixed duration of sedentary time with a fixed duration of physical activity (PA) at different intensities on children's CRF. A total of 315 children (136 boys) were assessed (age: 10.6 ± 0.6 years old). Outcomes at baseline and follow-up (16-months) were CRF determined using a maximal cycle test and sedentary time and PA measured with accelerometers. Data were analysed by isotemporal substitution analyses estimating the effect of reallocating 30 min/day of sedentary time by light (LPA), moderate (MPA) and vigorous physical activity (VPA) on CRF. VPA was positively and significantly associated with CRF cross-sectional (ß = 0.026, p < 0.001) and prospectively (ß = 0.010, p < 0.001). Reallocating 30 min/day of sedentary time into VPA was positively cross-sectionally (ß = 0.780, p < 0.001) and prospectively (ß = 0.303, p < 0.05) associated with CRF. Conversely, relocating 30-minutes of sedentary time into 30 minutes of LPA and MPA was not associated with CRF. These results suggest that reallocating an equal amount of time from sedentary into VPA is cross-sectional and prospectively associated with a favourable CRF.

Characterization and Comparison of Nutritional Intake between Preparatory and Competitive Phase of Highly Trained Athletes.

Background and objective: For a high level athlete, it is essential to ensure optimal energy as well as macro- and micro-nutrient and fluid intakes, in order to improve their performance during training and competition. Protein intake should be 1.2⁻2.1 g/kg/d, whereas the requirements for carbohydrate and fat intakes should be >5g/kg/d and 20⁻35% of energy, respectively. The micronutrient and fluid intakes in athletes were compared to the Dietary Reference Intake (DRI) and European Food Safety Authority (EFSA) recommendations, respectively. This study aimed to characterize and compare the nutritional habits of athletes at the preparatory and competitive phase, and to test if their nutritional intakes were in accordance with the recommendations. Materials and methods: A total of 276 professional athletes were assessed. To evaluate their nutritional intake, the athletes completed a 7 days food record. Under reporting was defined using a ratio of energy intake to basal metabolic rate (BMR) of 1.1. Body composition was assessed using dual energy X-ray absorptiometry (DXA). Results: Almost half (49%) of the athletes from the final sample reported lower measured intakes of carbohydrates and 27% reported a higher consumption of proteins than what was recommended. In both the preparatory and competitive phases, the micronutrients with a higher mismatch between the actual and recommended intakes were vitamins D and E, magnesium, folate, calcium, and zinc for both sexes, and iron intake for females. A large proportion of athletes reported a lower water intake. Compared to the recommendations, males reported a higher intake of carbohydrates, lipids, vitamins E, calcium, and magnesium (p <0.05) in the competitive phase, while females reported a lower ingestion of water, vitamins A and D, and calcium (p <0.05) in the preparatory phase. Conclusions: Overall, in the preparatory and competitive phases of the season, athletes reported a macro- and micro-nutrient intake below the recommendations, especially in the female athletic population. Dietary intakes in athletes need to be optimized and adjusted to their requirements, according to sex and sport, so as to avoid compromising health and performance.

Suitability of Bioelectrical Based Methods to Assess Water Compartments in Recreational and Elite Athletes.

OBJECTIVE: It is important for highly active individuals to easily and accurately assess their hydration level. Bioelectrical impedance (BIA) can potentially meet these needs but its validity in active individuals is not well established. We aim to validate total body water (TBW), extracellular water (ECW), and intracellular water (ICW) estimates obtained from 50 kHz BIA, bioelectrical impedance spectroscopy (BIS), and BIA-based models against dilution techniques in 2 populations: active adults and elite athletes. METHODS: Active males (N = 28, 20-39 years) involved in recreational sports and elite athletes (females: N = 57, 16-35 years; males: N = 127, 16-38 years) participated in this study. TBW and ECW were assessed with deuterium and bromide dilution, respectively. ICW was assessed as their difference. Body water compartments were also assessed by BIA (BIA-101), BIS (model 4200), and BIA-based equations. RESULTS: Small but significant differences were observed between alternative methods and the criterion in all subsamples. In female athletes, r(2) > 0.69, r(2) > 0.57, and r(2) > 0.65 were observed between methods in the TBW, ECW, and ICW estimates. In males, r(2) > 0.75, r(2) > 0.65, and r(2) > 0.68 were found between alternative and reference methods in the TBW, ECW, and ICW estimates, respectively, whereas for male recreational exercisers, r(2) > 0.58, r(2) > 0.73, and r(2) > 0.75 were observed. Pure errors ranged between 0.19 to 3.32 kg for TBW, 0.64 to 1.63 for ECW, and 1.98 to 2.64 in ICW. The highest limits of agreement (LoA) were observed in Van Loan and Mayclin equation and the BIA method, respectively, for TBW and ECW assessment and the lowest LoA were observed in BIS for both TBW and ECW estimates. CONCLUSIONS: The higher accuracy of BIS in predicting individual TBW, ECW, and ICW highlights its utility in water assessment of recreational and elite athletes.

Body composition phenotypes and carotid intima-media thickness in 11-13-year-old children.

UNLABELLED: Early detection of impairment in vascular structure is an important clinical pursuit. However, it is unknown which measure of body composition best predicts vascular wall changes. We assess the differences in body composition among intima-media thickness (IMT) tertiles and determined which measures of body composition are associated with IMT in 385 children aged 11-13 years (196 girls). In this cross-sectional study, body mass index (BMI), waist circumference (WC), body fat mass (BFM), and trunk fat mass (TFM) from dual-energy radiographic absorptiometry and IMT through high-resolution ultrasonography were collected. Differences in body composition measures among IMT tertiles [low IMT (LIMT), ≤ 0.46 mm; middle IMT, 0.46-0.53 mm; higher IMT (HIMT), ≥0.53 mm] were assessed with ANOVA/ANCOVA after categorization. Regression analysis was used to assess the relationships between body composition and IMT. The groups were similar for sex, age, and maturity (p > 0.05). As compared with LIMT group, subjects with HIMT had higher mean values of BMI, BFM, TFM, and WC (p < 0.05). Significant differences were found for WC even when controlling for BMI (p < 0.05). Combining all subjects, IMT was significantly correlated to BMI, BFM, TFM, and WC (p < 0.05). In multiple regression, WC was the only predictor of IMT (ß = 0.22, p < 0.001). CONCLUSION: Differences exist in body composition variables among IMT tertiles. In the overall model, WC was the only obesity-related predictor of increased IMT in 11-13-year-old children.

The impact of body composition on the degree of misreporting of food diaries.

BACKGROUND/OBJECTIVES: Accurate assessments of energy intake (EI) are needed in lifestyle interventions to guarantee a negative energy balance (EB), thereby losing weight. This study aimed (1) to compare objectively measured and self-reported EI and (2) to determine the predictors of underreporting divided by sex, adiposity and BMI category. METHODS: Seventy-three participants [mean (SD): 43.7 (9.2) years, BMI = 31.5 (4.5) kg/m2, 37% females] of the Champ4Life intervention were included in this study. EI was measured using the "intake-balance method" and self-reported through 3-day food records. Fat mass (FM) and fat-free mass (FFM) were measured by dual-energy X-ray absorptiometry. Bland-Altman analysis was performed to compare both EI assessments. RESULTS: Self-reported EI was lower than measured EI during both neutral (-355 kcal/d) and negative EB (-570 kal/day). While no significant trends were observed for EI evaluation in either neutral (p = 0.315) or negative EB (p = 0.611), limits of agreement were wide (-1720 to 1010 and -1920 to 779 kcal/day, respectively). In females, the degree of misreporting (kcal/day and %) was predicted by weight (p = 0.032 and p = 0.039, respectively) and FM (p = 0.029 and p = 0.037, respectively). In males, only BMI (p = 0.036) was a predictor of misreporting (kcal/day). CONCLUSION: Self-reported EI did not agree with measured EI. Our results show that larger body size was associated with higher levels of underestimation for EI (females only). Nevertheless, misreporting EI is a complex issue involving more associations than merely body composition. A deeper understanding could inform counseling for participants filling out food records in other to reduce misreporting and improve validity.

Body composition in taller individuals using DXA: A validation study for athletic and non-athletic populations.

Dual energy X-ray absorptiometry (DXA) cannot be used to evaluate participants taller than the scan area. We aimed to analyse the accuracy of bone mineral content, fat mass, and lean mass assessed with DXA whole-body scan and from the sum of two scans (head and trunk plus limbs). Participants were 31 athletes (13 males and 18 females) and 65 non-athletes (34 males and 31 females), that fit within the DXA scan area. Three scans were performed using a Hologic Explorer-W fan-beam densitometer: a whole-body scan used as the reference; a head scan; and a trunk and limbs scan. The sum of the head scan and the trunk and limbs scan was used as the alternative procedure. Multiple regression and agreement analysis were performed. Non-significant differences between methods were observed for fat mass (0.06 kg) and lean mass (-0.07 kg) while bone mineral content from the alternative procedure differed from the reference scan (0.009 kg). The alternative procedure explained > 99% of the variance in the reference scan and low limits of agreement were observed. Precision analysis indicated low pure errors and the higher coefficients of variation were found for fat mass (whole-body: 3.70%; subtotal: 4.05%). The method proposed is a valid and simple solution to be used in individuals taller than the DXA scan area, including athletes engaged in sports recognised for including very tall competitors.

Total energy expenditure assessment in elite junior basketball players: a validation study using doubly labeled water.

An accurate assessment of total energy expenditure (TEE) during a competitive season is required. We aimed to validate TEE estimated by self-reported energy intake (EI) and the dietary reference intake (DRI) method in 19 elite basketball players (aged 16-18 years) using doubly labeled water (DLW) as the reference method. The DRI models and EI from dietary records over a 7-day period were simultaneously assessed for TEE estimation. Resting energy expenditure was assessed by indirect calorimetry. Fat and fat-free mass (FFM) were determined by a 4-compartment model (body volume by air displacement plethysmography, bone mineral by DXA, and water by deuterium dilution). Fat and FFM ranged from 4 to 19 kg and from 47 to 81 kg, respectively. The physical activity level ranged from 2.2 to 3.7 with a mean value of 2.8 ± 0.4. Total energy expenditure from DLW (17,598 ± 3,298 kJ·d) was significantly underestimated by EI (11,274 ± 2,567 kJ·d), whereas no differences were found using DRI (17,008 ± 3,206 kJ·d). The EI and DRI methods explained TEE from DLW by 34% (p = 0.057) and 44% (p = 0.002), respectively, and wide limits of agreement were observed. Our findings suggested that EI is not a valid tool for TEE assessment. The DRI method may be valid at a group level but inaccurate for estimating individual TEE in young players during a demanding competitive season period.

Interindividual variability in metabolic adaptation of non-exercise activity thermogenesis after a 1-year weight loss intervention in former elite athletes.

Lack of efficacy of weight loss(WL) interventions is attributed in-part to low adherence to dietary/physical activity(PA) recommendations. However, some compensation may occur in PA as a response to energy restriction such as a decrease in non-exercise PA(NEPA) or non-exercise activity thermogenesis(NEAT). The current study aim was (1) to investigate whether adaptive thermogenesis(AT) in NEAT occurs after WL, and (2) to understand the associations of these compensations with WL. Ninety-four former athletes [mean±SD, age: 43.0±9.4y, BMI: 31.1±4.3 kg/m2, 34.0% female] were recruited and randomly assigned to intervention or control groups (IG, CG). The IG underwent a one-year lifestyle WL-intervention; no treatments were administered to the CG. PA was measured using accelerometery and NEAT was predicted with a model including sample baseline characteristics. AT was calculated as measuredNEAT4mo/12mo(kcal/d)-predictedNEAT4mo/12mo(kcal/d)-measuredNEATbaseline(kcal/d)-predictedNEATbaseline(kcal/d). Dual-energy x-ray absorptiometry was used to assess fat-free mass and fat mass. No differences were found in the IG for NEAT or NEPA after WL. Considering mean values, AT was not found for either group. The SD of individual response (SDIR) for AT was -2(4-months) and 24(12-months) (smallest worthwhile change = 87kcal/d), suggesting that the interindividual variability regarding AT in NEAT is not relevant and the variability in this outcome might reflect a large within-subject variability and/or a large degree of random measurement error. No associations were found between AT in NEAT and changes in body composition. Further studies are needed to clarify the mechanisms behind the large variability in AT observed in NEAT and related changes in NEPA to better implement lifestyle-induced WL interventions.HighlightsNo significant differences were found for non-exercise activity thermogenesis (NEAT) or non-exercise physical activity (NEPA) after the weight loss (WL) intervention;Although a large variability was found for NEAT and NEPA, the interindividual variability regarding these outcomes is not relevant. The variability in these outcomes might reflect a large within-subject variability and/or a large degree of random measurement error;Although no energy conservation was observed in NEAT after moderate WL (mean values), further studies are needed to clarify the mechanisms behind the large variability in adaptive thermogenesis observed in NEAT and related changes in NEPA to better implement lifestyle-induced WL interventions.Trial registration: ClinicalTrials.gov identifier: NCT03031951.

Effect of Time-Restricted Eating and Resistance Training on High-Speed Strength and Body Composition.

This study examined the effects of four weeks of resistance training combined with time-restricted eating (TRE) vs. habitual diet on fat and fat-free mass as well as maximum and explosive force production in healthy, trained participants (18 males, aged 23.7 ± 2.6 years). The order of dieting was randomized and counterbalanced, and the participants served as their own controls. TRE involved an 8-h eating window and non-TRE involved a habitual meal pattern. Participants completed performance strength tests and body composition scans at baseline and post-intervention. The participants followed a structured training routine during each dietary intervention (four sets of maximum repetitions at 85% 1RM in five dynamic exercises, three times/week). Both interventions elicited deceases in fat mass (p < 0.05) but not in fat-free mass. After training (controlling for baseline values as covariates), non-TRE was compatible with better lower body jump performance than TRE (p < 0.05). Conversely, training with TRE elicited higher values in terms of peak force and dynamic strength index at the level of the upper body (p < 0.05). Thus, it can be concluded that there were no differences in fat mass and fat-free mass changes between interventions in already trained young males. Additionally, while the combination of TRE and resistance training might be beneficial for individuals focusing on developing high-speed strength performance at the upper body level, this is not applicable to those focusing on training the lower body.

Changes in regional body composition explain increases in energy expenditure in elite junior basketball players over the season.

We aimed to analyze the association between changes in total and regional fat (FM) and fat-free mass (FFM) over a season with resting (REE) and total energy expenditure (TEE) in elite basketball players. At the beginning of the pre-season and at the final of the competitive period, measures of total and regional FM, FFM, lean soft tissue (LST), and bone mineral estimated by DXA and REE by indirect calorimetry were obtained in eight males and nine females of the Portuguese basketball team (16-17 years). TEE was assessed by doubly labeled water. Handgrip and a vertical-jumping were used to assess strength and power. Changes were expressed as a percentage from the baseline values. Resting energy expenditure and TEE increased by 13.2 ± 12.6 and 13.3 ± 12.7% (p < 0.01), respectively. Increases in FFM (3.6 ± 2.2%) and reductions in relative FM (-4.0 ± 6.6%) were observed (p < 0.01). The strength and power increased by 14.4 ± 9.9 and 9.8 ± 10.6%, respectively (p < 0.001). Alone, FFM and arms LST differences explained 25 and 23% of the total variance in REE alteration. These variables remained associated after adjusting for gender and baseline values (ß = 0.536, p = 0.042; and ß = 2.023, p = 0.016, respectively). Over the season, the REE increase was explained by changes in FFM. The increase in REE along with the strength and power improvement may suggest that a qualitative change in the metabolic active tissues occurred. Furthermore, these findings highlight the regional LST contribution, specifically located at the upper limbs, as a key component for the higher REE occurred over the season in junior basketball players.

Effect of a 16-week multi-level classroom standing desk intervention on cognitive performance and academic achievement in adolescents.

The replacement of traditional classroom desks for active-permissive desks has been tested to reduce sitting time during classes. However, their impact on other domains is still unclear. We aimed to verify the potential effects of a classroom standing desk intervention on cognitive function and academic achievement in 6th-grade students. This was a controlled trial conducted with two classes [intervention (n = 22) and control (n = 27)] from a public school in Lisbon, Portugal. The intervention was carried out for 16 weeks and consisted of multi-level actions (students, parents, and teachers) centered on the implementation of standing desks in the intervention classroom. The control group had traditional classes with no use of standing desks or any other interference/action from the research team. Pre- and post-assessments of executive functions (attention, inhibitory function, memory, and fluid intelligence) and academic achievement were obtained. No differences between groups were found at baseline. Both groups improved (time effect) academic achievement (p < 0.001), memory span (p < 0.001), and inhibitory function (p = 0.008). Group versus time interactions were observed regarding operational memory (intervention: + 18.0% and control: + 41.6%; p = 0.039) and non-verbal fluid intelligence (intervention: - 14.0% and control: + 3.9%; p = 0.017). We concluded that a 16-week classroom standing desk intervention did not improve cognitive performance or academic achievement more than the traditional sitting classes.Trial registration: ClinicalTrials.gov Identifier (NCT03137836) (date of first registration: 03/05/2017).

Body image change and improved eating self-regulation in a weight management intervention in women.

BACKGROUND: Successful weight management involves the regulation of eating behavior. However, the specific mechanisms underlying its successful regulation remain unclear. This study examined one potential mechanism by testing a model in which improved body image mediated the effects of obesity treatment on eating self-regulation. Further, this study explored the role of different body image components. METHODS: Participants were 239 overweight women (age: 37.6 ± 7.1 yr; BMI: 31.5 ± 4.1 kg/m²) engaged in a 12-month behavioral weight management program, which included a body image module. Self-reported measures were used to assess evaluative and investment body image, and eating behavior. Measurements occurred at baseline and at 12 months. Baseline-residualized scores were calculated to report change in the dependent variables. The model was tested using partial least squares analysis. RESULTS: The model explained 18-44% of the variance in the dependent variables. Treatment significantly improved both body image components, particularly by decreasing its investment component (f² = .32 vs. f² = .22). Eating behavior was positively predicted by investment body image change (p < .001) and to a lesser extent by evaluative body image (p < .05). Treatment had significant effects on 12-month eating behavior change, which were fully mediated by investment and partially mediated by evaluative body image (effect ratios: .68 and .22, respectively). CONCLUSIONS: Results suggest that improving body image, particularly by reducing its salience in one's personal life, might play a role in enhancing eating self-regulation during weight control. Accordingly, future weight loss interventions could benefit from proactively addressing body image-related issues as part of their protocols.