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

{"title":"Healthcare Professionals’ Insights on the Integration of Kinesiologists into Ontario’s Health System","authors":"Leslie E. Auger, Scott G. Thomas, Steve Fischer, Leanne Smith, John Armstrong, Raheel M. Dar, John Srbely","doi":"10.1249/tjx.0000000000000237","DOIUrl":"https://doi.org/10.1249/tjx.0000000000000237","url":null,"abstract":"ABSTRACT Introduction/Purpose Kinesiologists are well suited to work collaboratively or independently within the health system to improve patient/client care and well-being. This cross-sectional survey explored perceptions of the integration of registered kinesiologists (RKins) into the health system in Ontario. Methods RKins ( n = 202) and other health professionals (OHP; n = 337), including physicians, physiotherapists, nurse practitioners, etc., participated in an online survey. Results RKins reported working in diverse practice environments, and more than half reported receiving patients/clients through referrals. Of the OHP, 37.7% had ongoing professional interactions with RKins and 86.7% reported high satisfaction with these interactions; 32.6% of OHP reported referring patients/clients to RKins, primarily for exercise prescription (86.0%), treatment of clinical conditions (48.8%), and patient education (46.5%). Perceived barriers to referral included lack of awareness of the RKins’ scope of practice (81.0%), inadequate funding for services (67.1%), and low confidence in the clinical competency of RKins (61.8%). Conclusions RKins are experts in exercise-based interventions to prevent, treat, and manage many chronic lifestyle-related diseases. Initiatives to increase awareness of the RKins’ scope of practice, clinical competency, and standards of practice and to increase funding for RKin services are important next steps.","PeriodicalId":75243,"journal":{"name":"Translational journal of the American College of Sports Medicine","volume":"4 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":"135494613","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":"Lifestyle strategies after intentional weight loss: results from the MAINTAIN-pc randomized trial.","authors":"Tanya M Halliday, Molly McFadden, Maribel Cedillo, Bethany Barone Gibbs, Rachel Hess, Cindy Bryce, Gary S Fischer, Kimberly Huber, Kathleen M McTigue, Molly B Conroy","doi":"10.1249/tjx.0000000000000220","DOIUrl":"10.1249/tjx.0000000000000220","url":null,"abstract":"<p><strong>Introduction/purpose: </strong>Weight maintenance following intentional weight loss is challenging and often unsuccessful. Physical activity and self-monitoring are strategies associated with successful weight loss maintenance. However, less is known about the type and number of lifestyle strategies used following intentional weight loss. The purpose of this study was to determine the types and amounts of strategies associated with successful long-term weight loss maintenance.</p><p><strong>Methods: </strong>Data from the 24-month Maintaining Activity and Nutrition Through Technology-Assisted Innovation in Primary Care (MAINTAIN-pc) trial were analyzed. MAINTAIN-pc recruited adults (<i>n</i>=194; 53.4±12.2 years of age, body mass index (BMI): 30.4±5.9 kg/m², 74% female) with recent intentional weight loss of ≥5%, randomized to tracking tools plus coaching (i.e., coaching group) or tracking tools without coaching (i.e., tracking-only group). At baseline, 6, 12, and 24 months, participants reported lifestyle strategies used in the past 6 months, including self-monitoring, group support, behavioral skills, and professional support. General linear models evaluated changes in the number of strategies over time between groups and the consistency of strategies used over the 24-month intervention.</p><p><strong>Results: </strong>At baseline, 100% used behavioral skills, 73% used group support, 69% used self-monitoring, and 68% used professional support in the past 6 months; at 24 months, these rates were 98%, 60%, 75%, and 61%, respectively. While the number of participants utilizing individual strategies did not change significantly over time, the overall number of strategies participants reported decreased. More strategies were used at baseline and 6 months compared to 12- and 24-month follow-ups. The coaching group used more strategies at months 6 and 12 than the tracking-only group. Consistent use of professional support strategies over the 24-month study period was associated with less weight regain.</p><p><strong>Conclusion: </strong>Weight loss maintenance interventions that incorporate continued follow-up and support from healthcare professionals are likely to prevent weight regain after intentional weight loss.</p>","PeriodicalId":75243,"journal":{"name":"Translational journal of the American College of Sports Medicine","volume":"8 2","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10348773/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9830913","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":"Determinants of Dropout from and Variation in Adherence to an Exercise Intervention: The STRRIDE Randomized Trials.","authors":"Katherine A Collins, Kim M Huffman, Ruth Q Wolever, Patrick J Smith, Ilene C Siegler, Leanna M Ross, Elizabeth R Hauser, Rong Jiang, John M Jakicic, Paul T Costa, William E Kraus","doi":"10.1249/tjx.0000000000000190","DOIUrl":"10.1249/tjx.0000000000000190","url":null,"abstract":"<p><strong>Purpose: </strong>This study aimed to characterize the timing and self-reported determinants of exercise dropout among sedentary adults with overweight or obesity. We also sought to explore variations in adherence among individuals who completed a 6- to 8-month structured exercise intervention.</p><p><strong>Methods: </strong>A total of 947 adults with dyslipidemia [STRRIDE I, STRRIDE AT/RT] or prediabetes [STRRIDE-PD] were enrolled to either control or to one of 10 exercise interventions, ranging from doses of 8-23 kcal/kg/week; intensities of 50%-75% V̇O2 peak; and durations of 6-8 months. Two groups included resistance training and one included dietary intervention (7% weight loss goal). Dropout was defined as an individual who withdrew from the study due a variety of determinants. Timing of intervention dropout was defined as the last session attended and categorized into phases. Exercise training adherence was calculated by dividing weekly minutes or total sets of exercise completed by weekly minutes or total sets of exercise prescribed. General linear models were used to characterize the associations between timing of dropout and determinant category.</p><p><strong>Results: </strong>Compared to exercise intervention completers (n=652), participants who dropped out (n=295) were on average non-white (98% vs. 80%, p<0.01), had higher body mass index (31.0 kg/m² vs. 30.2 kg/m²; p<0.01), and were less fit at baseline (25.0 mg/kg/min vs. 26.7 ml/kg/min, p<0.01). Of those who dropped out, 67% did so prior to the start of or while ramping up to the prescribed exercise volume and intensity. The most commonly reported reason for dropout was lack of time (40%). Notably, among individuals who completed the ramp training period, subsequent exercise intervention adherence did not waiver over the ensuing 6-8 months of training.</p><p><strong>Conclusion: </strong>These findings are some of the first to delineate associations between the timing of dropout and dropout determinants, providing guidance to future exercise interventions to better support individuals at-risk for dropout.</p>","PeriodicalId":75243,"journal":{"name":"Translational journal of the American College of Sports Medicine","volume":"7 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9165469/pdf/nihms-1753767.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10605977","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":"Appetitive and Metabolic Responses to an Exercise versus Dietary Intervention in Adults with Obesity.","authors":"Sarah A Purcell, Kristina T Legget, Tanya M Halliday, Zhaoxing Pan, Seth A Creasy, Jennifer M Blankenship, Allison Hild, Jason R Tregellas, Edward L Melanson, Marc-Andre Cornier","doi":"10.1249/tjx.0000000000000211","DOIUrl":"10.1249/tjx.0000000000000211","url":null,"abstract":"<p><strong>Introduction/purpose: </strong>Dietary restriction (DIET) and aerobic exercise (AEX) interventions may impact energy balance differently. Our aim was to describe the effects of weight loss interventions via DIET or AEX on measures of energy balance.</p><p><strong>Methods: </strong>Adults with overweight or obesity were randomized to 12 weeks of DIET or AEX with similar calorie deficit goals. A study day was conducted before and after the intervention to assess subjective and hormonal (ghrelin, peptide-YY, glucagon-like peptide-1) appetite responses to a control meal, <i>ad libitum</i> energy intake (EI) at a single meal, and over three days of free-living conditions and eating behavior traits. Resting metabolic rate (RMR) was measured with indirect calorimetry and adjusted for body composition measured by dual X-ray absorptiometry. Non-exercise activity was measured using accelerometers.</p><p><strong>Results: </strong>Forty-four individuals were included (age: 37 ± 9 years, body mass index: 30.6 ± 3.1 kg/m²). Both interventions resulted in weight and fat mass loss. The DIET group lost fat-free mass, although differences between groups were not significant (DIET: -1.2 ± 1.7 kg, p<0.001; AEX: 0.4 ± 1.5 kg, p=0.186; p=0.095 interaction). There were no differences in RMR after body composition adjustment. Both interventions were associated with an increase in dietary restraint (DIET: 4.9 ± 1.2, AEX: 2.8 ± 0.7; p<0.001 in both groups). Hunger decreased with DIET (-1.4 ± 0.5, p=0.003), and disinhibition decreased with AEX (-1.5 ± 0.5, p<0.001), although these changes were not different between groups (i.e., no group × time interaction). No other differences in appetite, EI, or non-exercise physical activity were observed within or between groups.</p><p><strong>Conclusions: </strong>AEX did not result in compensatory alterations in appetite, <i>ad libitum</i> EI, or physical activity, despite assumed increased energy expenditure. Modest evidence also suggested that disinhibition and hunger may be differentially impacted by weight loss modality.</p>","PeriodicalId":75243,"journal":{"name":"Translational journal of the American College of Sports Medicine","volume":"7 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9635267/pdf/nihms-1817526.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9959836","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 for Promoting Exercise Is Medicine in Pregnancy—Collaboration Is Key","authors":"M. Sánchez-Polán, Taniya S. Nagpal, R. Barakat","doi":"10.1249/tjx.0000000000000222","DOIUrl":"https://doi.org/10.1249/tjx.0000000000000222","url":null,"abstract":"","PeriodicalId":75243,"journal":{"name":"Translational journal of the American College of Sports Medicine","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66085427","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":"Cross-Sectional and Individual Relationships between Physical Activity and Glycemic Variability.","authors":"Joshua R Sparks, Mark A Sarzynski, J Mark Davis, Peter W Grandjean, Xuewen Wang","doi":"10.1249/tjx.0000000000000207","DOIUrl":"10.1249/tjx.0000000000000207","url":null,"abstract":"<p><strong>Introduction/purpose: </strong>Overweight or obese adults spend more time sedentary and less time performing physical activity (PA) and are at an increased risk for developing impaired glycemic health. Free-living environments may provide insight into glycemic health in addition to clinical assessments. The purpose of this study was to examine the relationship between PA and glycemic health assessed by continuous glucose monitoring (CGM).</p><p><strong>Methods: </strong>Twenty-eight overweight or obese adults each wore an accelerometer and CGM over the same 7 consecutive days. Average daily time (minutes and metabolic-equivalent minutes (MET-minutes)) and associated energy expenditure performing light (LPA), moderate-to-vigorous (MVPA), total PA, and standard deviation (SD) across days were calculated. Average daily 24-h and waking glycemia, mean glucose concentration, glycemic variability measured as the continuous overlapping net glycemic action, mean amplitude of glycemic excursions, and mean of daily difference were assessed.</p><p><strong>Results: </strong>LPA MET-minutes per day was positively associated with 24-h and waking glycemia time-in-range and negatively associated with 24-h and waking time in hyperglycemia. Total PA time and the SD of MVPA and total PA time were negatively associated with 24-h mean glucose concentration. Individual-level analysis identified that most participants (50%-71%) expressed negative associations between LPA and MVPA time with 24-h mean glucose concentration, mean amplitude of glycemic excursion, and 4-h continuous overlapping net glycemic action.</p><p><strong>Conclusions: </strong>Expectedly, greater total PA time and intensity-specific PA time were associated with lower 24-h and waking mean glucose concentration, greater glycemia time-in-range, and less time in hyperglycemia. The relationship between glucose concentrations and PA time SD was unexpected, whereas most participants expressed hypothesized relationships, which necessitates further exploration.</p>","PeriodicalId":75243,"journal":{"name":"Translational journal of the American College of Sports Medicine","volume":"7 4","pages":"1-12"},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9460942/pdf/nihms-1834220.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9396922","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":"Effect of Weight Goals on Sitting and Moving During a Worksite Sedentary Time Reduction Intervention.","authors":"Krista S Leonard, Junia N de Brito, Miranda L Larouche, Sarah A Rydell, Nathan R Mitchell, Mark A Pereira, Matthew P Buman","doi":"10.1249/tjx.0000000000000210","DOIUrl":"10.1249/tjx.0000000000000210","url":null,"abstract":"<p><strong>Introduction/purpose: </strong>Although many US adults report trying to lose weight, little research has examined weight loss goals as a motivator for reducing workplace sitting and increasing physical activity. This exploratory analysis examined weight goals and the association with changes in workplace sitting, physical activity, and weight.</p><p><strong>Methods: </strong>Employees (<i>N</i> = 605) were drawn from worksites participating in Stand and Move at Work. Worksites (<i>N</i> = 24) were randomized to a multilevel behavioral intervention with (STAND+) or without (MOVE+) sit-stand workstations for 12 months; MOVE+ worksites received sit-stand workstations from 12 to 24 months. At each assessment (baseline and 3, 12, and 24 months), participants were weighed and wore activPAL monitors. Participants self-reported baseline weight goals and were categorized into the \"Lose Weight Goal\" (LWG) group if they reported trying to lose weight or into the \"Other Weight Goal\" (OWG) group if they did not.</p><p><strong>Results: </strong>Generalized linear mixed models revealed that within STAND+, LWG and OWG had similar sitting time through 12 months. However, LWG sat significantly more than OWG at 24 months. Within MOVE+, sitting time decreased after introduction of sit-stand workstations for LWG and OWG, although LWG sat more than OWG. Change in physical activity was minimal and weight remained stable in all groups.</p><p><strong>Conclusions: </strong>Patterns of change in workplace sitting were more favorable in OWG relative to LWG, even in the absence of notable weight change. Expectations of weight loss might be detrimental for reductions in workplace sitting. Interventionists may want to emphasize non-weight health benefits of reducing workplace sitting.</p>","PeriodicalId":75243,"journal":{"name":"Translational journal of the American College of Sports Medicine","volume":"7 4","pages":""},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9534174/pdf/nihms-1816661.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10626324","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":"Systematic Review of Fitbit Charge 2 Validation Studies for Exercise Tracking.","authors":"Crista Irwin, Rebecca Gary","doi":"10.1249/tjx.0000000000000215","DOIUrl":"10.1249/tjx.0000000000000215","url":null,"abstract":"<p><strong>Context: </strong>There are research-grade devices that have been validated to measure either heart rate (HR) by electrocardiography (ECG) with a Polar chest strap, or step count with ACTiGraph accelerometer. However, wearable activity trackers that measure HR and steps concurrently have been tested against research-grade accelerometers and HR monitors with conflicting results. This review examines validation studies of the Fitbit Charge 2 (FBC2) for accuracy in measuring HR and step count and evaluates the device's reliability for use by researchers and clinicians.</p><p><strong>Design: </strong>This registered review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The robvis (risk-of-bias visualization) tool was used to assess the strength of each considered article.</p><p><strong>Eligibility criteria: </strong>Eligible articles published between 2018 and 2019 were identified using PubMed, CINHAL, Embase, Cochran, and World of Science databases and hand-searches. All articles were HR and/or step count validation studies for the FBC2 in adult ambulatory populations.</p><p><strong>Study selection: </strong>Eight articles were examined in accordance with the eligibility criteria alignment and agreement among the authors and research librarian.</p><p><strong>Main outcome measures: </strong>Concordance correlation coefficients (CCC) were used to measure agreement between the tracker and criterion devices. Mean absolute percent error (MAPE) was used to average the individual absolute percent errors.</p><p><strong>Results: </strong>Studies that measured CCC found agreement between the FBC2 and criterion devices ranged between 26% and 92% for HR monitoring, decreasing in accuracy as exercise intensity increased. Inversely, CCC increased from 38% to 99% for step count when exercise intensity increased. HR error between MAPE was 9.21% to 68% and showed more error as exercise intensity increased. Step measurement error MAPE was 12% for healthy persons aged 24-72 years but was reported at 46% in an older population with heart failure.</p><p><strong>Conclusions: </strong>Relative agreement with criterion and low-to-moderate MAPE were consistent in most studies reviewed and support validation of the FBC2 to accurately measure HR at low or moderate exercise intensities. However, more investigation controlling testing and measurement congruency is needed to validate step capabilities. The literature supports the validity of the FBC2 to accurately monitor HR, but for step count is inconclusive so the device may not be suitable for recommended use in all populations.</p>","PeriodicalId":75243,"journal":{"name":"Translational journal of the American College of Sports Medicine","volume":"7 4","pages":"1-7"},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9881599/pdf/nihms-1826450.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9142918","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":"Program Barriers and Facilitators in Virtual Cancer Exercise Implementation: A Qualitative Analysis.","authors":"Jessica S Gorzelitz, Nour Bouji, Nicole L Stout","doi":"10.1249/tjx.0000000000000199","DOIUrl":"10.1249/tjx.0000000000000199","url":null,"abstract":"<p><strong>Introduction/purpose: </strong>Due to the coronavirus disease 2019 (COVID-19) pandemic, many in-person cancer exercise and rehabilitation programs necessarily transitioned to virtual formats to meet the needs of individuals living with and beyond cancer. The purpose of this study was to qualitatively assess program-level facilitators and barriers to virtual exercise program implementation and to identify preferred strategies to overcome implementation barriers.</p><p><strong>Methods: </strong>US-based virtual cancer exercise and rehabilitation programs were recruited from professional networks via an emailed screening questionnaire. Eligible programs identified a point of contact for a 1:1 semi-structured interview to discuss program-level barriers and facilitators to implementing virtual exercise programs. Interview transcript analysis was conducted via inductive coding techniques using NVivo software. Barriers were categorized according to the Consolidated Framework for Implementation Research and a prioritized list of strategies to support implementation was created by mapping barriers to a list of Expert Recommendations for Implementing Change.</p><p><strong>Results: </strong>Of the 41 unique responses received, 24 program representatives completed semi-structured interviews. Interviewees represented individual programs, community-based programs, and hospital-based cancer exercise/rehabilitation programs. Analysis showed high correlation between facilitators and barriers by program type, with both program- and individual-level strategies used to implement exercise programs virtually. Strategies that ranked highest to support implementation include promoting program adaptability, building a coalition of stakeholders and identifying program champions, developing an implementation blueprint, altering organizational incentives and allowances, providing education across stakeholder groups, and accessing funding.</p><p><strong>Conclusions: </strong>Learning from the transition of cancer exercise and rehabilitation programs to virtual formats due to the COVID-19 pandemic, we identify program-level barriers and facilitators encountered in the implementation of virtual programs and highlight implementation strategies that are most relevant to overcome common barriers. We present a roadmap for programs to use these strategies for future work in virtual exercise and rehabilitation program implementation.</p>","PeriodicalId":75243,"journal":{"name":"Translational journal of the American College of Sports Medicine","volume":"7 3","pages":""},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9119660/pdf/nihms-1787100.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10107690","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":"The IMAGINE Intervention: Impacting Physical Activity, Body Fat, Body Mass Index, and Dietary Inflammatory Index.","authors":"John A Bernhart,&nbsp;Gabrielle M Turner-McGrievy,&nbsp;Michael D Wirth,&nbsp;Nitin Shivappa,&nbsp;James R Hébert","doi":"10.1249/tjx.0000000000000181","DOIUrl":"https://doi.org/10.1249/tjx.0000000000000181","url":null,"abstract":"<p><strong>Background: </strong>Many behavior-change interventions focused on nutrition and physical activity (PA) have been implemented to prevent disease and promote optimal health.</p><p><strong>Purpose: </strong>This study examined changes in PA with Energy-adjusted Dietary Inflammatory Index (E-DII™) and chronic disease risk factors in participants of a multicomponent intervention.</p><p><strong>Methods: </strong>Data from the Inflammation Management Intervention (IMAGINE) were used. Participants self-selected into the intervention or control group. At baseline and 12 weeks (post-intervention), participants completed three unannounced 24-hour dietary recalls (24HR), anthropometric measures (height, weight), and a dual x-ray absorptiometry scan. PA was measured using Sensewear^® armbands. E-DII scores were calculated from the 24HR. Descriptive statistics and t-tests summarized variables and multiple regression assessed relationships between PA and body mass index (BMI), total body fat percent, and E-DII scores.</p><p><strong>Results: </strong>Intervention participants increased moderate-to-vigorous PA (MVPA) and lowered BMI, total body fat, and E-DII scores compared to controls. Every 10-minute increase in post-intervention MVPA was associated with 1.6 kg/m² lower BMI (p<0.01) and 2.4% lower body fat percent (p<0.01) among control participants, after adjusting for covariates. Every 10-minute increase in post-intervention MVPA was associated with 0.3 lower (i.e., less inflammatory) post-intervention E-DII (p=0.01) scores among intervention participants, after adjusting for covariates.</p><p><strong>Conclusion: </strong>Participants who changed dietary intake changed PA. While changes were in expected directions, this intervention's emphasis on dietary behaviors compared to PA may have attenuated the relationship between PA and study outcomes.</p>","PeriodicalId":75243,"journal":{"name":"Translational journal of the American College of Sports Medicine","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9272997/pdf/nihms-1729178.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10807828","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}