Translational journal of the American College of Sports Medicine最新文献

{"title":"Hormone Fluctuations, Dietary Intake, and Daily Activity in Premenopausal Women: An 8-Week Observational Study.","authors":"Ariel J Aguiar Bonfim Cruz, Alexa J Chandler, Gena L Irwin, Malayna Schwartz, Ann Frost","doi":"10.1249/TJX.0000000000000353","DOIUrl":"10.1249/TJX.0000000000000353","url":null,"abstract":"<p><strong>Introduction: </strong>Female reproductive hormonal fluctuations may be influenced by lifestyle behaviors such as diet, physical activity (PA), and sleep. However, little is known about these interactions over time or how they may differ between naturally menstruating (NM) and hormonal contraceptive (HC) women. This 8-wk observational study examined relationships between hormone levels and dietary intake, PA, exercise, and sleep quality, and explored differences by menstrual cycle phase and contraceptive status.</p><p><strong>Methods: </strong>Sixteen premenopausal women (NM = 9, HC = 7; age: 21.2 ± 2.8) completed weekly serum blood draws, 24-h dietary recalls, Simple PA Questionnaire, and Pittsburgh Sleep Quality Questionnaire. Body composition was measured at baseline.</p><p><strong>Results: </strong>In HC participants, leptin was positively associated with dietary fat (<i>r</i> = 0.348, <i>P</i> = 0.019). In NM participants, estradiol positively predicted daily calorie intake (β = 0.134, <i>P</i> = 0.019), added sugar intake (β = 0.0028, <i>P</i> = 0.0013), and was positively associated with total fat intake (<i>r</i> = 0.427, <i>P</i> = 0.003). Progesterone positively predicted added sugar intake (β = 0.12, <i>P</i> = 0.0024). Luteinizing hormone was negatively associated with calories (<i>r</i> = -0.327, <i>P</i> = 0.029), carbohydrate (<i>r</i> = -0.406, <i>P</i> = 0.006), and added sugar (<i>r</i> = -0.380, <i>P</i> = 0.010). Sex hormone binding globulin was positively associated with added sugar (<i>r</i> = 0.427, <i>P</i> = 0.003). In NM participants, leptin was positively associated with sedentary time (β = 0.072, <i>P</i> = 0.048). No other significant associations existed between hormones or menstrual cycle phase and PA, exercise, or sleep.</p><p><strong>Conclusion: </strong>Dietary intake was more strongly linked to hormone levels in NM than HC participants. Self-reported activity and sleep quality appeared consistent across the study, suggesting limited behavior fluctuations across the menstrual cycle.</p>","PeriodicalId":75243,"journal":{"name":"Translational journal of the American College of Sports Medicine","volume":"11 2","pages":"e000353"},"PeriodicalIF":3.0,"publicationDate":"2026-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13107348/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147791605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ultrasound-Based Spatial Frequency Analysis Differentiates Patellar Tendon Quality in Tendinopathic and Healthy Participants.","authors":"Sarah L Woelfel, Samuel J Wilkins, Scott K Crawford, Adam B Rosen","doi":"10.1249/tjx.0000000000000372","DOIUrl":"10.1249/tjx.0000000000000372","url":null,"abstract":"<p><strong>Introduction: </strong>Diagnostic ultrasound is valuable in identifying patellar tendon pathologies by assessing macrostructural features such as tendon thickness. Quantitative image analysis methods, like spatial frequency analysis (SFA), allow objective assessment of tendon microstructural organization. The purpose of this study was to examine patellar tendon microstructure in individuals with clinically diagnosed patellar tendinopathy and matched healthy controls using SFA.</p><p><strong>Methods: </strong>This case-control study evaluated regional differences in patellar tendon microstructure between NCAA Division I athletes with patellar tendinopathy (n=13) and age-, sex-, sport-, height-, and mass-matched healthy controls (n=13). B-mode ultrasound images were analyzed using SFA to extract Peak Spatial Frequency Radius (PSFR), P6, and MMax%. Tendon thickness was measured at proximal and distal regions using built-in ultrasound calipers. Group differences were assessed using independent t-tests or Mann-Whitney U tests as appropriate; effect sizes were calculated using Cohen's d.</p><p><strong>Results: </strong>Tendinopathic tendons demonstrated lower proximal PSFR (p<0.01, d=1.19) compared with controls. P6 values were higher in the tendinopathic group at both proximal (p=0.04, d=0.73) and distal (p=0.03, d=0.80) regions, while distal MMax% was lower (p=0.02, d=0.82). No differences were observed for distal PSFR (p=0.21) or proximal MMax% (p=0.10). Proximal tendon thickness was greater in the tendinopathic group (p<0.01), whereas distal thickness did not differ between groups (p=0.20).</p><p><strong>Conclusion: </strong>Spatial frequency analysis identified region-specific differences in patellar tendon microstructure between tendinopathic and healthy participants, with proximal PSFR demonstrating the most robust discrimination between groups. Differences observed in P6 and MMax% should be interpreted cautiously due to greater uncertainty in their effect size estimates. These findings support further investigation of SFA, particularly PSFR, as a quantitative approach for characterizing tendon microstructural organization in research settings.</p>","PeriodicalId":75243,"journal":{"name":"Translational journal of the American College of Sports Medicine","volume":"11 3","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13588664/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149009521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pilot evaluation of a dance-based physical activity program for adults with Down syndrome.","authors":"Julianne G Clina, Anna M Rice, Joseph R Sherman, Jessica C Danon, Brian C Helsel, Amy E Bodde, Joseph E Donnelly, Lauren T Ptomey","doi":"10.1249/tjx.0000000000000362","DOIUrl":"10.1249/tjx.0000000000000362","url":null,"abstract":"<p><strong>Introduction: </strong>Adults with Down syndrome (DS) face barriers to traditional exercise modalities due in part to a lack of interest or enjoyment, desire for social connectedness during exercise, and difficulty completing traditional exercise movements because of physical limitations. Dance provides a potential alternative to conventional exercise and may address some of these barriers. The purpose of this study was to assess the feasibility, usability, safety, and energy expenditure of a 12-week dance-based exercise intervention in adults with DS.</p><p><strong>Methods: </strong>Participants completed a 12-week remotely-delivered, dance-based exercise intervention. Classes were 35 minutes each and held twice weekly. Feasibility was assessed via retention and attendance. Usability was assessed via a satisfaction survey, with all measures assessed on a 5-point Likert scale, and safety was based on the number of adverse events. Energy expenditure was assessed using indirect calorimetry.</p><p><strong>Results: </strong>Twenty participants (mean age 28.3 years, 70% female) enrolled in the intervention, and study retention was 100%. Participants attended 21.7 out of 24 sessions (90.4%). Satisfaction scores were high, with overall satisfaction rated as 4.8±0.4 (100% rating 4 or above). There were no intervention-related adverse events reported. Sixteen participants completed an assessment of energy expenditure, with the average metabolic equivalents (METs) of 4.8 ± 1.0, exceeding the threshold for moderate intensity (3.0 METs).</p><p><strong>Conclusion: </strong>Intervention retention, attendance, and satisfaction were all high and energy expenditure met the threshold for moderate intensity. Remotely-delivered dance may represent a feasible and effective exercise modality for adults with DS to increase overall exercise participation and should be tested in a larger intervention.</p>","PeriodicalId":75243,"journal":{"name":"Translational journal of the American College of Sports Medicine","volume":"11 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13166159/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147936116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Barriers and Predictors of Long-Term Physical Activity Maintenance: The STRRIDE I Reunion Cohort.","authors":"Katherine A Collins-Bennett, Leanna M Ross, Johanna L Johnson, Cris A Slentz, Kim M Huffman, William E Kraus","doi":"10.1249/TJX.0000000000000276","DOIUrl":"10.1249/TJX.0000000000000276","url":null,"abstract":"<p><strong>Introduction: </strong>This study aimed to identify barriers and predictors of self-reported physical activity (PA) maintenance 10 yr following the Studies of a Targeted Risk Reduction Intervention through Defined Exercise (STRRIDE I) randomized trial among young older adults.</p><p><strong>Methods: </strong>Participants completed a PA recall questionnaire that assessed barriers to PA maintenance. Chi-square tests assessed differences in barriers by PA maintenance tertile. Demographic and clinical measures collected at baseline and post-intervention from the STRRIDE I parent trial were included in model development to identify predictors of PA maintenance. Three models were generated using a backward bootstrap variable selection algorithm followed by multiple linear regression.</p><p><strong>Results: </strong>Participants who returned for the STRRIDE I Reunion study (<i>n</i> = 104; 63.0 ± 6.2 yr old) reported mean PA participation of 77.9 ± 76.5 min·wk^-1. Commonly reported barriers to PA maintenance included lack of self-motivation (41%), time constraints (33%), illness or injury (29%), and family obligations (23%). There was a significant association between the percentage of individuals who reported one or more barriers versus no barriers by PA maintenance tertile (frequency of PA: <i>χ</i> ² ratio = 26.1, <i>P</i> < 0.0001; amount of PA: <i>χ</i> ² ratio = 15.1, <i>P</i> = 0.0005). The baseline predictive model had an adjusted <i>R</i> ² value of 0.05, the post-intervention predictive model had an adjusted <i>R</i> ² of 0.12, and the change score (post-intervention minus pre-intervention) predictive model had an adjusted <i>R</i> ² of 0.17.</p><p><strong>Conclusions: </strong>Maintaining PA beyond a structured exercise intervention setting continues to be challenging for older adults. Compared to those who reported no barriers, young older adults who reported one or more barriers to PA maintenance were less active 10 yr following STRRIDE I. Additionally, how participants respond to a structured exercise intervention in certain clinical variables may be the most indicative of future PA maintenance.</p>","PeriodicalId":75243,"journal":{"name":"Translational journal of the American College of Sports Medicine","volume":"10 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12532306/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145330826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Call to Action: Contribute to the Development of the Third Edition of the Physical Activity Guidelines for Americans.","authors":"Katrina L Piercy, Alison Vaux-Bjerke, Malorie Polster, Janet E Fulton, Stephanie George, Kenneth M Rose, Geoffrey P Whitfield, Dana L Wolff-Hughes, Elizabeth Y Barnett","doi":"10.1249/tjx.0000000000000275","DOIUrl":"10.1249/tjx.0000000000000275","url":null,"abstract":"","PeriodicalId":75243,"journal":{"name":"Translational journal of the American College of Sports Medicine","volume":"10 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11926852/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143694757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Associations of physical and social workplace characteristics with movement behaviors at work.","authors":"Anthony J Holmes, Tyler D Quinn, Molly B Conroy, Joshua L Paley, Kimberly A Huber, Bethany Barone Gibbs","doi":"10.1249/tjx.0000000000000225","DOIUrl":"10.1249/tjx.0000000000000225","url":null,"abstract":"<p><strong>Introduction/purpose: </strong>Sedentary behavior (SB) is common in desk-based work and prolonged periods of SB are associated with negative health outcomes. This study assessed associations between workplace characteristics and setting and movement patterns during working hours.</p><p><strong>Methods: </strong>This secondary analysis used baseline data from the Reducing Sedentary Behavior to Decrease Blood Pressure (RESET BP) clinical trial which enrolled inactive, desk-based workers with elevated blood pressure (<i>n</i>=271; mean age: 45.3±11.6 years; body mass index (BMI): 30.66±7.1 kg/m²; 59.4% women). Physical and social workplace characteristics were assessed by a study-developed questionnaire and the Office Environment and Sitting Scale (OFFESS). Participants also wore an activPAL activity monitor for 7 days and reported working hours in a diary to measure SB and physical activity (PA) specifically while working. Linear regression was used to analyze cross-sectional associations between workplace characteristics and SB and PA. A stratified analysis was also conducted to assess associations among home-based and in-office desk workers separately. Analyses were adjusted for age, gender, BMI, and work wear time.</p><p><strong>Results: </strong>Participants spent 77% of working hours in SB. Public vs. private offices, working in-office vs. at home, higher local connectivity, and greater overall connectedness were associated with lower SB and/or greater PA (all p<0.05). Higher frequency of face-to-face interactions, and greater visibility and proximity to co-workers was associated with less SB and more PA (all p<0.05). For example, home-based workers had more total SB (+17.2±8.4 mins/day), more SB bouts ≥30 mins (+39.1±12.8 mins/day), and less steps (695±201 steps/day) than in-office employees. Stratification by office setting revealed differences in associations between SB and PA and workplace characteristics.</p><p><strong>Conclusions: </strong>More public, open spaces with more social interactions and physical walkways could improve SB and PA patterns during work. Home-based workers had more SB, less PA, and unique associations of these activities with workplace characteristics, suggesting a need for tailored interventions.</p>","PeriodicalId":75243,"journal":{"name":"Translational journal of the American College of Sports Medicine","volume":"8 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9937511/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10856919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Framework to Classify Physical Activity Intervention Studies for Older Adults","authors":"J. Baldwin, L. Hassett, C. Sherrington","doi":"10.1249/tjx.0000000000000230","DOIUrl":"https://doi.org/10.1249/tjx.0000000000000230","url":null,"abstract":"","PeriodicalId":75243,"journal":{"name":"Translational journal of the American College of Sports Medicine","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66085465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Biological Basis of Sex Differences in Athletic Performance: Consensus Statement for the American College of Sports Medicine","authors":"Sandra K. Hunter, Siddhartha S. Angadi, Aditi Bhargava, Joanna Harper, Angelica Lindén Hirschberg, Benjamin D. Levine, Kerrie L. Moreau, Natalie J. Nokoff, Nina S. Stachenfeld, Stéphane Bermon","doi":"10.1249/tjx.0000000000000236","DOIUrl":"https://doi.org/10.1249/tjx.0000000000000236","url":null,"abstract":"ABSTRACT Biological sex is a primary determinant of athletic performance because of fundamental sex differences in anatomy and physiology dictated by sex chromosomes and sex hormones. Adult men are typically stronger, more powerful, and faster than women of similar age and training status. Thus, for athletic events and sports relying on endurance, muscle strength, speed, and power, males typically outperform females by 10%–30% depending on the requirements of the event. These sex differences in performance emerge with the onset of puberty and coincide with the increase in endogenous sex steroid hormones, in particular testosterone in males, which increases 30-fold by adulthood, but remains low in females. The primary goal of this consensus statement is to provide the latest scientific knowledge and mechanisms for the sex differences in athletic performance. This review highlights the differences in anatomy and physiology between males and females that are primary determinants of the sex differences in athletic performance and in response to exercise training, and the role of sex steroid hormones (particularly testosterone and estradiol). We also identify historical and nonphysiological factors that influence the sex differences in performance. Finally, we identify gaps in the knowledge of sex differences in athletic performance and the underlying mechanisms, providing substantial opportunities for high-impact studies. A major step toward closing the knowledge gap is to include more and equitable numbers of women to that of men in mechanistic studies that determine any of the sex differences in response to an acute bout of exercise, exercise training, and athletic performance.","PeriodicalId":75243,"journal":{"name":"Translational journal of the American College of Sports Medicine","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135784073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Demographic, Clinical, and Psychosocial Predictors of Exercise Adherence: The STRRIDE Trials.","authors":"Katherine A Collins, Kim M Huffman, Ruth Q Wolever, Patrick J Smith, Leanna M Ross, Ilene C Siegler, John M Jakicic, Paul T Costa, William E Kraus","doi":"10.1249/tjx.0000000000000229","DOIUrl":"10.1249/tjx.0000000000000229","url":null,"abstract":"<p><strong>Purpose: </strong>To identify baseline demographic, clinical, and psychosocial predictors of exercise intervention adherence in the Studies of a Targeted Risk Reduction Intervention through Defined Exercise (STRRIDE) trials.</p><p><strong>Methods: </strong>A total of 947 adults with dyslipidemia or prediabetes were enrolled into an inactive control group or one of ten exercise interventions with doses of 10-23 kcal/kg/week, intensities of 40-80% of peak oxygen consumption, and training for 6-8-months. Two groups included resistance training. Mean percent aerobic and resistance adherence were calculated as the amount completed divided by the prescribed weekly minutes or total sets of exercise times 100, respectively. Thirty-eight clinical, demographic, and psychosocial measures were considered for three separate models: 1) clinical + demographic factors, 2) psychosocial factors, and 3) all measures. A backward bootstrapped variable selection algorithm and multiple regressions were performed for each model.</p><p><strong>Results: </strong>In the clinical and demographic measures model (<i>n</i>=947), variables explained 16.7% of the variance in adherence (p<0.001); lesser fasting glucose explained the greatest amount of variance (partial R² = 3.2%). In the psychosocial factors model (<i>n</i>=561), variables explained 19.3% of the variance in adherence (p<0.001); greater 36-Item Short Form Health Survey (SF-36) physical component score explained the greatest amount of variance (partial R² = 8.7%). In the model with all clinical, demographic, and psychosocial measures (<i>n</i>=561), variables explained 22.1% of the variance (p<0.001); greater SF-36 physical component score explained the greatest amount of variance (partial R² = 8.9%). SF-36 physical component score was the only variable to account for >5% of the variance in adherence in any of the models.</p><p><strong>Conclusions: </strong>Baseline demographic, clinical, and psychosocial variables explain approximately 22% of the variance in exercise adherence. The limited variance explained suggests future research should investigate additional measures to better identify participants who are at risk for poor exercise intervention adherence.</p>","PeriodicalId":75243,"journal":{"name":"Translational journal of the American College of Sports Medicine","volume":"8 3","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10553264/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41159710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Translational Journal of the American College of Sports Medicine: 2022 Paper of the Year","authors":"Kristin L. Campbell","doi":"10.1249/tjx.0000000000000238","DOIUrl":"https://doi.org/10.1249/tjx.0000000000000238","url":null,"abstract":"The journal publishes original research, clinical trials, systematic review articles, and meta-analysis and policy research that discuss the translational implications of basic, clinical, and policy science to everyday real-world practice. Specifically, studies that apply basic and clinical research findings that move discovery and knowledge into clinical practice and community settings will be published.","PeriodicalId":75243,"journal":{"name":"Translational journal of the American College of Sports Medicine","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66085477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}