Medicine & Science in Sports & Exercise

BackgroundMaximal oxygen uptake (VO2 max), an indicator of cardiorespiratory fitness (CRF), requires exercise testing and, as a result, is rarely ascertained in large-scale population-based studies. Non-exercise algorithms are cost-effective methods to estimate VO2 max, but the existing models have limitations in generalizability and predictive power. This study aims to improve the non-exercise algorithms using machine learning (ML) methods and data from U.S. national population surveys. MethodsWe used the 1999-2004 data from the National Health and Nutrition Examination Survey (NHANES), in which a submaximal exercise test produced an estimate of the VO2max. We applied multiple supervised ML algorithms to build two models: a parsimonious model that used variables readily available in clinical practice, and an extended model that additionally included more complex variables from more Dual-Energy X-ray Absorptiometry (DEXA) and standard laboratory tests. We used Shapley additive explanation (SHAP) to interpret the new model and identify the key predictors. For comparison, existing non-exercise algorithms were applied unmodified to the testing set. ResultsAmong the 5,668 NHANES participants included in the final study population, the mean age was 32.5 years and 49.9% were women. Light Gradient Boosting Machine (LightGBM) had the best performance across multiple types of supervised ML algorithms. Compared with the best existing non-exercise algorithms that could be applied in NHANES, the parsimonious LightGBM model (RMSE: 8.51 ml/kg/min [95% CI: 7.73 -9.33]) and the extended model (RMSE: 8.26 ml/kg/min [95% CI: 7.44 -9.09]) significantly reducing the error by 15% (P <0.01) and 12% (P<0.01 for both), respectively. ConclusionOur non-exercise ML model provides a more accurate prediction of VO2 max for NHANES participants than existing non-exercise algorithms. What is KnownO_LIAlthough cardiorespiratory fitness is recognized as an important marker of cardiovascular health, it is not routinely measured because of the time and resources required to perform exercise tests. C_LIO_LINon-exercise algorithms are cost-effective alternatives to estimate cardiorespiratory fitness, but the existing models are restricted in generalizability and predictive power. C_LI What the Study AddsO_LIWe improve non-exercise algorithms for cardiorespiratory fitness prediction using advanced ML methods and a more comprehensive and representative data source from U.S. national population surveys. C_LIO_LIMore health factors that are associated with cardiorespiratory fitness are newly identified. C_LIO_LINationally representative estimates for cardiorespiratory fitness in the U.S. over the recent 20 years are generated. C_LI

ObjectiveThis study aims to evaluate the short form International Physical Activity Questionnaire (IPAQ) for use in women with chronic pelvic pain disorders (CPPDs) by comparing its scores against objectively-estimated physical activity (PA) outcomes. We investigated IPAQ components that are most consistently predictive of habitual PA behavior. MethodThe study sample included 966 weeks of data from 112 women with CPPDs who enrolled in a 14-week mHealth-based self-tracking study. Participants wore Fitbit devices and completed the IPAQ every week. We compared the IPAQ-reported minutes of walking, total activity, sitting, light-, moderate-, and vigorous intensity PA for concordance and divergence against their corresponding Fitbit estimates. We used linear mixed-effects regression models (MLMs) for all analyses and quantified the between-participant variance in the magnitude of agreement between the two methods via random slope terms. We further evaluated temporal consistency in scores using intraclass correlation coefficients (ICCs). ResultsIPAQ-reported walking minutes were strongly associated with Fitbit step counts (B = 3952.36; p = 0.006), minutes of moderate PA (B = 15.498; p = 0.0113), and moderate-to-vigorous PA (MVPA; B = 28.973; p = 0.007). IPAQ total activity minutes were associated with Fitbit minutes of vigorous PA (B = 15.183; p = 0.007) and MVPA (B = 25.658; p = 0.010). IPAQ moderate activity minutes were predictive of Fitbit vigorous PA minutes (B = 9.060; SE = 3.719; p = 0.0151). There was substantial between-individual variance in these point estimates based on the significant random-effect terms, and average weekly PA level was a significant moderator of the association between IPAQ-reported and Fitbit-estimated scores for these variables. IPAQ-reported sitting minutes were inversely associated with Fitbit step counts (B = - 3125.61; p = 0.004), and minutes of MVPA (B = -21.848; p = 0.007), vigorous AP (B = -10.854; p = 0.042), and moderate PA (B = -10.985; p = 0.004). ConclusionThese findings provide support for using IPAQ-reported walking and total activity minutes to monitor several PA domains in women with CPPDs, given their concordance with several tracker-estimated PA outcomes. However, the item on "sitting time" may not be a suitable for assessing sedentary time.

BackgroundPhysical activity is widely recognized as a key modifiable factor for reducing the risk of chronic diseases. Wearable devices such as Fitbit offer a unique opportunity to objectively measure physical activity metrics, providing insights into the association between different types of physical activity and chronic disease risk. ObjectiveThis study aims to examine the association between physical activity metrics derived from Fitbit devices and the incidence of various chronic diseases among participants from the All of Us Research Program. MethodsPhysical activity metrics included daily steps, elevation gain, and activity durations at different intensities (e.g., very active, lightly active, and sedentary). Cox proportional hazards models and multiple regression models were used to assess the relationship between these metrics and the incidence of chronic diseases represented by Phecodes. Age, sex, and body mass index (BMI) were included as covariates. ResultsA total of 15,538 participants provided Fitbit activity data, of which 9,320 also had electronic health records (EHR). Increased daily step count, elevation gain, and very active minutes were significantly associated with a reduced risk of several chronic conditions, including obesity, Type 2 diabetes, and major depressive disorder. Conversely, increased sedentary time was linked to higher risks for conditions such as obesity, Type 2 diabetes, and essential hypertension. Multiple regression analyses confirmed these associations. ConclusionOur findings highlight the beneficial effects of increased physical activity, particularly daily steps and elevation gain, on reducing the risk of chronic diseases. Conversely, sedentary behavior remains a significant risk factor for the development of several conditions. These insights may inform personalized activity recommendations aimed at reducing disease burden and improving population health outcomes.

ObjectivesThis study investigates the concurrent and construct validity of a brief, customizable exercise self-tracking item from a research mHealth App ("Phendo") for use as a measure of day-level and habitual exercise behavior in endometriosis. Study SampleStudy 1 included 52 participants who were recruited online and provided data for up to 14 days. Study 2 included 359 Phendo users who had retrospectively-collected data on the study measures. MethodsIn Study 1, we evaluated the responses on the self-tracking exercise item as estimates of day-level moderate-to-vigorous intensity exercise (MVE) and total step counts. Comparison measures included recall-based MVE minutes and accelerometry-based step counts, which were self-reported through daily surveys. In Study 2, we derived a measure of habitual exercise using each individuals longitudinal self-tracked responses. We assessed its concurrent validity using the Nurses Health Study II Physical Activity Scale (NHS-II) as the comparison measure. We assessed its discriminant validity through known-group differences analysis where the sample was dichotomized based on Health Survey Short Form-36 (SF-36) and body mass index (BMI). Data AnalysisWe assessed bivariate associations between the scores on the self-tracking and comparison measures using Kendalls rank correlations. We estimated daily MVE and step counts (Study 1), and weekly exercise (Study 2) from the self-tracking item scores through adjusted linear and polynomial regression models. We used t-tests and linear regression to conduct known-group differences analyses. ResultsIn Study 1, self-tracked exercise responses were moderately correlated with survey based MVE and step counts. Regression analyses indicated that overall exercise responses were associated with [~]17 minutes of MVE for the average participant (B=16.09, t=3.11, p=0.045). Self-tracked aerobic-type exercise was a stronger predictor of MVE minutes and step counts (B=27.561, t=5.561, p<0.0001). In Study 2, each self-tracked exercise instance corresponded to [~]19 minutes of exercise per week on the NHS-II Scale (B=19.80, t=2.1, p=0.028). Finally, there were statistically significant differences between the groups dichotomized based on SF-36 subscale scores and BMI. ConclusionThis study presents preliminary evidence on the concurrent and discriminant validity of a brief mHealth App measure for exercise self-tracking among individuals with endometriosis. These findings have implications in the context of large-scale studies that involve monitoring a diverse group of participants over long durations of time, as well as engaging and retaining research participants.

The association between higher levels of physical activity and lower cancer risk and mortality is well established. However, a causal link is yet to be proven. Recent studies showed a decrease in the proliferation rates of cultured human cancer cells when the human serum employed to stimulate them was conditioned by acute exercise. Here, we tested the hypothesis that serum mediates some of the putative benefits of exercise on cancer through alterations to the growth pattern and susceptibility to chemotherapy agents of cancer cells. To this end, human non-small cell lung cancer (NSCLC) cells were exposed to serum from two cohorts that differed significantly on their levels of physical activity and, accordingly, cardiorespiratory fitness, but were otherwise identical (master athletes and non-exercisers), collected before and after an acute exercise intervention. Serum levels of glucose, lipids, albumin, C-reactive protein and cytokines were determined and the impact of the serum responses to acute and lifelong exercise on the above-mentioned parameters were analyzed. We found that acute exercise decreased the cells proliferation rate, yet shortened the cells lag phase after detachment, whereas lifelong exercise had the opposite effects. Significantly, we showed, for the first time, that lifelong exercise increased susceptibility to a chemotherapy agent (cisplatin), which may contribute to the decreased cancer mortality rates found among those who exercise regularly. Similar to the cellular effects, changes to serum cytokine levels - several of them linked to the senescence-associated secretory phenotype - depended on whether serum was conditioned by acute or by chronic exercise. Key pointsChronic exercise increased the in vitro susceptibility of lung cancer cells to cisplatin. Acute and chronic exercise modulated the in vitro tumorigenic potential of lung cancer cells. Effects were mediated by serological changes produced by exercise. Acute and chronic exercise had distinct impacts on serological cytokine levels.

BackgroundThe global prevalence of overweight and obesity continues escalating, driven by environmental factors and lifestyle behaviors leading to cardiovascular disease, diabetes, and cancer. Digital health interventions offer scalable solutions for weight management, yet personalized artificial intelligence applications remain underexplored. Large language model chatbots present opportunities for individualized behavioral interventions, but evidence comparing personalized versus manual prompt AI-driven approaches is limited. ObjectivesThis randomized controlled trial evaluated the effectiveness of a personalized exercise and dietary prompt generator integrated with ChatGPT versus structured manual ChatGPT guidance for weight management. MethodsAdults aged 18-65 years with BMI 27.5-34.9 kg/m2 (n=160) from Greater Kuala Lumpur were randomized to NExGEN personalized prompt system with ChatGPT (NEX; n=81) or structured manual ChatGPT control (CON; n=79). The NExGEN system generated individualized prompts based on 111 assessment variables including demographics, health status, and preferences. CON participants received structured manual ChatGPT prompts. Assessments occurred at baseline, 12 weeks, and 24 weeks. Primary outcome was body weight measured using bioelectrical impedance analysis. Secondary outcomes included body composition, dietary intake, physical activity, and cardiometabolic markers. Linear mixed models analyzed intervention effects. ResultsThe NEX group achieved significantly greater weight loss than CON at 12 weeks (6.6 kg vs 3.0 kg, P<0.001) and 24 weeks (5.5 kg vs 1.7 kg, P<0.001). Fat mass decreased significantly in NEX participants (3.7 kg at 12 weeks, P<0.001) while preserving fat-free mass. Energy density, fat intake, and physical activity improved significantly in the NEX group. Cardiometabolic variables showed minimal between-group differences. ConclusionsThe personalized AI-driven intervention produced superior weight loss and body composition improvements compared with structured manual prompt guidance. Limited cardiometabolic improvements reflected the metabolically healthy study population at baseline.

BackgroundCardiorespiratory fitness (CRF) has a strong genetic component and low CRF is a major risk factor for cardiovascular morbidity and mortality. The purpose of this study was to develop and validate a polygenic score (PGS) for CRF (CRFPGS) and assess its associations with cardiovascular disease (CVD) and all-cause mortality. We hypothesized that the CRFPGS would demonstrate similar cardioprotective benefits as the CRF phenotype. MethodsEffect estimates from a genome-wide association study on directly measured CRF in the Trondelag Health Study (HUNT; n = 4 525) were used in a Bayesian regression framework to develop multiple PGSs in an independent cohort from the UK Biobank (n = 65 165). The top performing score was applied in the HUNT target cohort, excluding the discovery sample (n = 82 109). ResultsThe PGS-CRF association varied considerably as a function of model fit and phenotypic accuracy. In the target population, we observed a difference in CRF of 1.55 [95% confidence interval: 1.26, 1.84] mL{middle dot}kg-1{middle dot}min-1 between the bottom and top decile of the CRFPGS. Moreover, a high CRFPGS demonstrated cardioprotective effects, with reduced risk for CVD, myocardial infarction, hypertension, and all-cause mortality. We also found that the CRFPGS predisposed to lower risk of heart failure and hypertrophic cardiomyopathy in women. ConclusionA PGS for CRF derived from gold-standard phenotypes captures small, but potentially clinical meaningful variations in CRF, and is associated with reduced risk of cardiovascular morbidity and mortality. Heterogeneity in CRF phenotyping in large populations remains a challenge to PGS development and refinement.

BackgroundEating timing and regularity represent new contributors to metabolic health, however, the time-based aspect of eating behavior is rarely incorporated into traditional cardiometabolic risk assessment strategies. ObjectivesThe aim of this study was to create an explainable machine learning (ML) model to predict cardiometabolic risk based on anthropometric, dietary and chrono-nutritional data. MethodologyThis cross-sectional study included 300 adults for whom demographic, waist-hip ratio (WHR), Body Mass Index (BMI), blood pressure, eating timing (earliest time, latest time, meal frequency) and eating behavior observations were recorded. Nested 10-fold cross-validation and hyperparameter tuning were used to create three models (Logistic Regression (LR), Random Forest (RF), XGBoost) with interpretability established through Shapley Additive Explanations (SHAP). Discrimination was evaluated with AUC-ROC, accuracy, precision, recall, F1-score and Brier score. ResultsXGBoost was the best model compared to RF (AUC = 0.94) and LR (AUC = 0.92) (AUC-ROC = 0.98, accuracy = 93%). Later dinner timing (OR = 2.5), irregular meal timing (OR = 1.6), and reduced adherence to the recommended meal frequency (OR = 1.8) were the top independent predictors of cardiometabolic danger; conversely In contrast, an increased frequency of meals and an awareness of the significance of meal timing positively impacted cardiometabolic danger. SHAP further interpreted XGBoost to conclude that BMI and WHR were the most significant predictors in addition to meal regularity. ConclusionExplainable ML modeling from mealtimes and nutritional behaviors provide accurate and interpretable prediction of threat. Improved awareness of meal timing serves as a modifiable behavioral intervention in preventative cardiometabolic efforts.

BackgroundTo examine the association between COVID-19 vaccination status and physical activity (PA), sporting behavior, as well as barriers to PA in adults in Switzerland, Germany, and Austria. MethodsA total of 1516 adults provided complete responses to our online questionnaire sent out in August 2021. Information about self-reported PA categories, sporting behavior, barriers to PA, and COVID-19 vaccination status were gathered. Main analyses were done using multiple linear regression adjusted for relevant parameters. ResultsWe found a significant association of vaccination status with total PA (p = .011), vigorous PA (p = .015), and moderate PA (p = .001) but not transport-related PA or sedentary time. Unvaccinated adults tended to have more total and vigorous PA than those vaccinated once (ratios of geometric means: 1.34 and 1.60, respectively) or twice (1.22 and 1.09, respectively). Yet, not sufficient evidence was available to confirm this. There was no between-group difference in the contribution of leisure time, work-related, or transport-related PA to total PA. Vaccination status was not associated with sporting behavior except for jogging as the primary intensive type of sports. Finally, there were no significant differences in any of the COVID-19 specific barriers to PA between groups. ConclusionOur data showed that vaccination status is associated with PA even in summer, where the number of COVID-19 cases was low and the severity of safety measures was mild. These findings may enhance future research and improve/extend COVID-19-specific PA guidelines.

BackgroundModerate-to-vigorous physical activity (MVPA), light physical activity, sedentary behaviour and sleep have all been associated with cardiovascular disease (CVD). Due to challenges in measuring and analysing movement behaviours, there is uncertainty about how the association with incident CVD varies with the time spent in these different movement behaviours. MethodsWe developed a machine-learning model (Random Forest smoothed by a Hidden Markov model) to classify sleep, sedentary behaviour, light physical activity and MVPA from accelerometer data. The model was developed using data from a free-living study of 152 participants who wore an Axivity AX3 accelerometer on the wrist while also wearing a camera and completing a time use diary. Participants in UK Biobank, a prospective cohort study, were asked to wear an accelerometer (of the same type) for seven days, and we applied our machine-learning model to classify their movement behaviours. Using Compositional Data Analysis Cox regression, we investigated how reallocating time between movement behaviours was associated with CVD incidence. FindingsWe classified accelerometer data as sleep, sedentary behaviour, light physical activity or MVPA with a mean accuracy of 88% (95% CI: 87, 89) and Cohens kappa of 0{middle dot}80 (95% CI: 0{middle dot}79, 0{middle dot}82). Among 87,509 UK Biobank participants, there were 3,424 incident CVD events. Reallocating time from any behaviour to MVPA, or reallocating time from sedentary behaviour to any behaviour, was associated with a lower risk of CVD. For example, for a hypothetical average individual, reallocating 20 minutes/day to MVPA from all other behaviours proportionally was associated with 9% (7%, 10%) lower risk of incident CVD, while reallocating 1 hour/day to sedentary behaviour was associated with 5% (3%, 7%) higher risk. InterpretationReallocating time from light physical activity, sedentary behaviour or sleep to MVPA, or reallocating time from sedentary behaviour to other behaviours, was associated with lower risk of incident CVD. Accurate classification of movement behaviours using machine-learning and statistical methods to address the compositional nature of movement behaviours enabled these insights. Public health interventions and guidelines should promote reallocating time to MVPA from other behaviours, as well as reallocating time from sedentary behaviour to light physical activity. FundingMedical Research Council.

BackgroundAlthough the cardiovascular disease (CVD) benefits of both overall volume and intensity of physical activity (PA) are known, the role of PA intensity, over and above volume, is poorly understood. We aimed to investigate the interplay between PA volume and intensity in relation to incident CVD. MethodsData were from 88,412 UK Biobank participants without prevalent CVD (58% women) who wore an accelerometer on their dominant wrist for 7 days, from which we estimated total physical activity energy expenditure (PAEE) using population-specific validation. Cox proportional hazards regressions modelled associations between PAEE (kJ/kg/day)] and PA intensity [%MVPA; the fraction of PAEE accumulated from moderate-to-vigorous-intensity PA] with incident CVD, adjusted for potential confounders. ResultsThere were 4,068 CVD events during 584,568 person-years of follow-up (median 6.8 years). Higher PAEE and higher %MVPA (adjusted for PAEE) were associated with lower rates of incident CVD. In interaction analyses, CVD rates were 17% (95%CI: 8-26%) lower when MVPA accounted for 20% rather than 10% of 15 kJ/kg/d PAEE; equivalent to the difference between a 12-min stroll into a brisk 7-min walk. CVD rates did not differ significantly between values of PAEE when the %MVPA was fixed at 10%. However, the combination of higher PAEE and %MVPA was associated with lower CVD rates. Rates were 24% (10-35%) lower for 20 kJ/kg/d PAEE with 20% from MVPA, and 49% (23-66%) lower for 30 kJ/kg/d with 40% from MVPA (compared to 15 kJ/kg/d PAEE with 10% MVPA). ConclusionsReductions in CVD risk may be achievable through higher levels of PA volume and intensity, with the role of moderately intense PA appearing particularly important for future CVD risk. Our findings support multiple approaches or strategies to PA participation, some of which may be more practical or appealing to different individuals.

During aerobic exercise, central hemodynamics and CO2 partial pressure are central to middle cerebral artery blood velocity (MCAv) response. Still, the extent of their contribution is unknown. The purpose of this study was to characterize and utilize statistical modeling to determine the contribution of heart rate (HR), mean arterial pressure (MAP), and end-tidal CO2 (PETCO2) dynamics to MCAv dynamics. Three randomized exercise bouts were completed on a recumbent stepper at 30-40% (Low), 45-55% (Mod1), and 60-70% (Mod2) of estimated HRmax. A 90-s resting period was followed by 6-min of continuous exercise within the estimated HR ranges. HR, MAP, PETCO2, and MCAv exercise dynamics were modeled with a monoexponential curve. From this modeling, the baseline (BL), time delay (TD), time constant ({tau}), and steady-state (SS) responses were determined. Backward AIC linear regression models determined contributing dynamics. Seventeen healthy adults completed all exercise bouts (28 {+/-} 6 yrs, 8 females). The time from initiation of exercise to an exponential increase in HR (HRTD) was significantly longer for Low than Mod2 (p=0.047). The time constant for the rise in HR (HR{tau}) was significantly shorter for Low than Mod1 and Mod2 (p=0.01). The absolute change in HR from baseline to steady-state (HRSS) was significantly lower for Low than Mod1 and Mod2 (p<0.001), and Mod1 was significantly lower than Mod2 (p<0.001). MAPSS was significantly lower for Low than Mod1 (p=0.01) and Mod2 (p<0.001). Exercise intensity, HRTD, and MAPTD accounted for 17% of variation for MCAvTD (p=0.01). HRTD, PETCO2TD, and MCAvTD accounted for 21% of variation MCAv{tau} (p<0.01). MCAv{tau}, MAPSS, and PETCO2SS accounted for 60% of variation for MCAvSS (p<0.001). Throughout the MCAv dynamic response pathway central hemodynamics and end-tidal CO2 do not account for most MCAv response until the steady-state phase. Thus, other physiological factors should be considered with assessing cerebrovascular function during aerobic exercise.

BackgroundSprinting and Nordic hamstring exercise (NHE) programs are common training modalities used to reduce hamstring injury risk, but the differences in the biomechanical demands of sprinting and the NHE are unclear. The purpose of this study was to compare knee and hip joint kinematics and kinetics, and hamstrings muscle-tendon unit (MTU) length and velocity during the flight phase of sprinting and the NHE. MethodsWe collected motion capture and force data from fourteen young athletic participants (8 males and 6 females) as they ran at a range of speeds (4-8 m/s) and performed the NHE. We used this experimental data and a musculoskeletal model to compute joint angles, moments, work, and power and to estimate the hamstrings MTU length and velocity for all running speeds and the NHE. ResultsThe peak knee flexion moment at running speeds of 6 m/s and above was greater than for the NHE (p < 0.001). Peak negative knee flexion power at all running speeds was higher than during the NHE (p < 0.001). Negative knee flexion work at running speeds of 6 m/s and slower was less than during the NHE (p < 0.001). Peak hamstrings length and lengthening velocity were greater (p < 0.001) for all running speeds compared to the NHE. ConclusionSprinting puts the hamstrings at longer hamstrings lengths and higher hamstrings lengthening velocities than the NHE. The NHE requires participants to generate peak knee flexion moments that are smaller than the peak knee flexion moments generated during top speed sprinting and peak negative knee flexion powers that are less than 5% of sprinting. However, the duration of each NHE repetition is approximately 60 times longer than the hamstrings lengthening portion of the flight phase of running, resulting in comparable negative knee work. The results of this study provide necessary quantitative information to compare the biomechanical demands of sprinting and the NHE.

Exercise is effective toward delaying or preventing chronic disease, with a large body of evidence supporting its effectiveness. However, less is known about the specific healthspan-promoting effects of exercise on blood biomarkers in the disease-free population. In this work, we examine 23,237 generally healthy individuals who self-report varying weekly running volumes and compare them to 4,428 generally healthy sedentary individuals, as well as 82 professional endurance athletes. We estimate the significance of differences among blood biomarkers for groups of increasing running levels using analysis of variance (ANOVA), adjusting for age, gender, and BMI. We attempt and add insight to our observational dataset analysis via two-sample Mendelian randomization (2S-MR) using large independent datasets. We find that self-reported running volume associates with biomarker signatures of improved wellness, with some serum markers apparently being principally modified by BMI, whereas others show a dose-effect with respect to running volume. We further detect hints of sexually dimorphic serum responses in oxygen transport and hormonal traits, and we also observe a tendency toward pronounced modifications in magnesium status in professional endurance athletes. Thus, our results further characterize blood biomarkers of exercise and metabolic health, particularly regarding dose-effect relationships, and better inform personalized advice for training and performance.

ObjectiveTo investigate the effects of breaking up prolonged sedentary behavior (SB) on daily movement behavior and energy balance in adults with overweight/obesity. MethodsThirty participants (16F/14M; 34.2{+/-}7.3y; 29.5{+/-}3.2kg/m2) were randomized to either BREAK (nine hourly 5-min brisk walking bouts) or a duration-matched intervention, ONE (45-min brisk walking), both performed 5 days/week for 6 weeks. Pre- and post-intervention, daily SB and physical activity (PA; accelerometry), body composition (doubly labeled water [DLW]), total daily energy expenditure (TDEE; DLW), appetite, and fasting leptin were measured. Linear-mixed effects models tested time effects and time-by-group interactions. ResultsOnly BREAK reduced prolonged SB (-8%; interaction: p=0.043). Both groups shifted SB-PA composition toward greater moderate-to-vigorous PA with proportional reductions in SB and light PA (time: all p[&le;]0.011), which were associated with increases in TDEE (+0.67 MJ/d; time: p=0.040). Body and fat mass increased in ONE only (interaction: p=0.061 and p=0.055). No differences were noted in energy intake, appetite, or leptin levels. ConclusionsSpreading short PA bouts throughout the day increases MVPA and TDEE to the same extent as a traditional continuous PA bout. Future studies should investigate whether minor differences in body composition are driven by distinct behavioral/physiological compensations influenced by the daily pattern of PA/SB. STUDY IMPORTANCE QUESTIONSO_LIWhat is already known about this subject? O_LIAcutely, breaking up prolonged sedentary behavior (SB) with short bouts of physical activity (PA) increases energy expenditure and reduces food cravings compared to a single continuous PA bout. C_LIO_LISingle continuous PA bouts have been associated with compensatory reductions in non-exercise activities (daily living activities) in some studies, which may attenuate increases in total daily energy expenditure (TDEE) and limit effects on body mass and adiposity. C_LI C_LIO_LIWhat are the new findings in your manuscript? O_LIPerforming brisk walking either through frequent, short bouts spread across the day or as a single continuous bout over 6 weeks increases moderate-to-vigorous PA (MVPA) at the expense of SB and light PA and increases TDEE to a similar extent in adults with overweight or obesity. C_LIO_LIHowever, only the frequent, short active breaks reduced time spent in prolonged SB (>60 min), an independent cardiometabolic health risk factor. C_LIO_LIDespite no differences in energy intake, appetite, or plasma leptin concentration, the single continuous bouts were associated with a small, non-robust increase in body and fat mass, whereas these remained stable in the active breaks group, suggesting differential compensatory adaptations. C_LI C_LIO_LIHow might your results change the direction of research or the focus of clinical practice? O_LIPromoting frequent, short bouts of PA throughout the day can improve daily movement and help meet current PA/SB guidelines to a similar extent as traditional PA strategies, while also reducing prolonged sedentary time. C_LIO_LIThis strategy may help limit compensatory responses sometimes observed in response to continuous MVPA bouts, offering a new tool to manage body weight. C_LIO_LIHowever, differences in body composition outcomes were small and not robust, and future studies are needed to determine whether these patterns translate into meaningful long-term effects on energy balance and weight regulation. C_LI C_LI

BackgroundSkeletal muscle energetics decline with age, and physical activity (PA) has been shown to counteract these declines in older adults. Yet, many studies were based on self-reported PA or structured exercise interventions. We examined the associations of objective daily PA and sedentary behavior (SB) with skeletal muscle energetics and also compared with self-reported PA and SB. We also explored the extent to which PA would attenuate the associations of age with muscle energetics. MethodsAmong the Study of Muscle, Mobility and Aging (SOMMA) enrolled older adults, 810 (mean age=76{+/-}5, 58% women) had maximal muscle oxidative capacity measured ex vivo via high-resolution respirometry of permeabilized myofibers (maxOXPHOS) and in vivo by 31Phosphorus magnetic resonance spectroscopy (ATPmax). Objective PA was measured using the wrist-worn ActiGraph GT9X over 7-days to capture sedentary behavior (SB), light, and moderate-to-vigorous PA (MVPA). Self-reported SB, MVPA, and all exercise-related PA were assessed with The Community Healthy Activities Model Program for Seniors questionnaire. Linear regression models with progressive covariate adjustments evaluated the associations between SB, PA and muscle energetics, and the attenuation of the age / muscle energetic association by PA. ResultsEvery 30 minutes more objective MVPA was associated with 0.65 pmol/s*mg higher maxOXPHOS and 0.012 mM/sec higher ATPmax, after adjustment for age, site/technician and sex. More time spent in objective light+MVPA was significantly associated with higher ATPmax, but not maxOXPHOS. In contrast, every 30 minutes spent in objective SB was associated with 0.43 pmol/s*mg lower maxOXPHOS and 0.004 mM/sec lower ATPmax. Only associations with ATPmax held after further adjusting for socioeconomic status, body mass index, lifestyle factors and multimorbidities. Self-reported MVPA and all exercise-related activities, but not SB, yielded similar associations with maxOXPHOS and ATPmax. Lastly, age was only significantly associated with muscle energetics in men. Adjusting for objective time spent in MVPA attenuated the age association with ATPmax by nearly 60% in men. ConclusionMore time spent in daily PA, especially MVPA, were associated with higher muscle energetics. Interventions that increase higher intensity activity might offer potential therapeutic interventions to slow the age-related decline in muscle energetics. Our work also emphasizes the importance of taking PA into consideration when evaluating associations related to skeletal muscle energetics.

BackgroundThe Nordic hamstring exercise (NHE) and high-speed running are widely used training modalities to prevent hamstring strain injuries, yet the differences in the muscle lengths, forces, work, and power between these training modalities remain unclear. This study thus compared the dynamics of the most injured hamstrings muscle, biceps femoris long head (BFLH), for 14 participants (8 male and 6 female) performing the NHE and running between 4 and 8 m/s. MethodsWe used motion capture experiments and musculoskeletal simulation to quantify muscle fiber lengths and velocities, and muscle force, work, and power during the NHE and running. ResultsOur results show that peak muscle forces are greater during high-speed running (7.5 to 8 m/s) than the NHE, and that high-speed running also features longer muscle fiber lengths and higher muscle fiber lengthening velocities (p < 0.05). Negative muscle work was significantly greater during the NHE compared to running at all speeds (p < 0.001) because of the greater change in muscle fiber lengths during the NHE (p < 0.001). In contrast, peak negative muscle power was significantly lower during the NHE compared to running at 5 m/s and above (p < 0.01). ConclusionOur analysis reveals dramatic differences in the biomechanical demands of the NHE and running on the hamstrings muscles. Our results suggest that the two training modalities together provide complementary biomechanical stimuli to promote favorable BFLH injury prevention adaptations.

BackgroundThe problem of overweight and obesity in children and adolescents around the world is serious, and traditional intervention methods have problems such as poor compliance. Traditional ethnic sports (such as martial arts and tai chi) combined with physical and mental exercise and cultural elements may provide a new way for obesity management, but there is a lack of systematic evaluation. A systematic literature search was conducted in twelve electronic databases (PubMed, Cochrane Library, Web of Science, MEDLINE, EBSCO, CINAHL, OVID, Embase, Scopus, SPORTDiscus, CNKI, ProQuest) from inception to March 12, 2025. Randomized controlled trials of ethnic traditional sports interventions in overweight or obese students (age 7.6-23 years; BMI > 23.9 kg/m{superscript 2}) were eligible, yielding twelve RCTs (n = 520). Two reviewers independently screened studies, extracted data, and assessed risk of bias using the Cochrane RoB tool. Across 12 RCTs (n = 520), ethnic traditional sports interventions did not significantly alter body weight (WMD = -0.115 kg; 95% CI: -0.30 to 0.07; p = 0.233) or waist circumference (WMD = -0.34 cm; 95% CI: -0.82 to 0.13; p = 0.156), but yielded significant reductions in BMI (WMD = -0.33 kg/m{superscript 2}; 95% CI: -0.60 to -0.06; p = 0.016) and body fat percentage (WMD = -0.31%; 95% CI: -0.52 to -0.10; p = 0.004). In lipid profiles, high-density lipoprotein cholesterol increased (WMD = 0.33 mmol/L; 95% CI: 0.05 to 0.61; p = 0.020), whereas total cholesterol (WMD = -0.01 mmol/L; p = 0.952), triglycerides (WMD = 0.33 mmol/L; p = 0.468) and low-density lipoprotein cholesterol (WMD = 0.03 mmol/L; p = 0.828) remained unchanged. Subgroup analyses indicated that Chinese traditional exercises (e.g. Tai Chi, Kung Fu) produced more pronounced reductions in BMI and body fat than other modalities. ConclusionNational traditional sports can effectively improve the BMI, body fat rate and HDL-C level of overweight and obese students. It is a potential intervention method. In the future, it is necessary to further standardize the program and expand the research sample.

Background: This prospective cohort analysis investigated how age, sex, and body morphology modify associations of physical activity (PA) intensity, duration, and volume with cardiovascular disease (CVD) mortality. Methods: We analysed wrist-worn accelerometer data from 8,661 adults (51.9% women) in the National Health and Nutrition Examination Survey. The outcome was CVD mortality. PA intensity and volume were quantified using the intensity gradient and average acceleration, respectively. Survey-weighted Cox proportional hazards models were used to estimate associations, including interaction terms with age, sex, or body morphology (waist-to-height ratio as indicator of adiposity). Results: Median (interquartile range) follow-up was 81 (69, 94) months. All hazard ratios (HR) compare 50th with 25th percentile. Beneficial associations between CVD mortality and PA were stronger in younger than older adults for intensity (e.g., 45-year-olds: HR=0.47, 95%CI:0.29-0.75 vs 75-year-olds: HR=0.75, 95%CI:0.54-1.06), and volume (e.g., HR=0.18, 95%CI:0.07-0.71 vs 0.29, 95%CI:0.16-0.51). In women, intensity-related association were stronger than in men (HR=0.45, 95%CI:0.31-0.65 vs HR=0.79, 95%CI:0.50-1.24). Volume-related associations were stronger in men (HR=0.37, 95%CI:0.22-0.60 vs HR=0.24, 95%CI:0.11-0.51), though with earlier plateauing and greater uncertainty. Associations were observed across waist-to-height ratio levels but attenuated at higher values (intensity: waist-to-height ratio 0.5, HR=0.45, 95%CI:0.29-0.69 vs 0.6, HR=0.69, 95%CI:0.49-0.97; volume: 0.5, HR=0.07, 95%CI:0.03-0.17 vs 0.6, HR=0.28, 95%CI:0.17-0.45). Conclusion: Older adults and men may benefit more from increasing PA volume than intensity, whereas younger adults and women may benefit more from higher-intensity PA. Although benefits were observed across adiposity levels, associations were attenuated as adiposity increased, suggesting stronger benefits in individuals with low-to-moderate adiposity.

BackgroundMindfulness meditation has been reported to reduce stress and enhance well-being. However, its effects on heart rate variability (HRV) - a physiological marker of stress - remain underexplored. ObjectiveTo examine how meditation practice is associated with subjective stress, HRV, and their interaction, using mobile health (mHealth) technologies. MethodsThis three-week observational study included 90 participants: 19 meditation practitioners, 32 recreational runners, and 39 individuals without regular meditation or exercise habits. HRV was continuously recorded using Garmin smartwatches. Subjective stress and activity were assessed three times daily via a smartphone-based experience sampling method (ESM), yielding 4,557 responses; 632 meditation sessions were time-logged; questionnaires were administered at the end of the study. ResultsStress (PSS) was lower in meditation and running groups vs. controls (Kruskal-Wallis P = .024; adjusted Wilcoxon P = .048 and .040). RMSSD was higher in runners vs. controls (P < .001) but not different between meditation and controls. Higher perceived stress was associated with concurrent RMSSD reduction of -2.24 ms (95% CI -3.97 to -0.26), steeper in runners (-3.94 ms; 95% CI -7.04 to -0.74). During meditation, RMSSD increased by +4.68 ms (95% CI 2.96 to 6.38) and remained elevated for at least 30 minutes post-practice. ConclusionsAlthough daily-life HRV among meditation practitioners was not elevated overall, their ability to increase HRV at will with a prolonged residual effect may relate to stress reduction and warrants further investigation. Trial RegistrationNot applicable.