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

{"title":"Diet and Physical Activity Behaviors in Primary Care Patients with Recent Intentional Weight Loss.","authors":"Bethany Barone Gibbs, Dana Tudorascu, Cindy L Bryce, Diane Comer, Gary S Fischer, Rachel Hess, Kimberly A Huber, Kathleen M McTigue, Laurey R Simkin-Silverman, Molly B Conroy","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Purpose: </strong>Lifestyle habits of primary care patients with recent, intentional weight loss are unclear and need to be better understood to aid in translational health promotion efforts. We aimed to characterize diet and exercise habits in primary care patients with recent, intentional weight loss, comparing those with greater (≥10%) vs. lesser (5 to <10%) weight loss.</p><p><strong>Methods: </strong>This was a cross-sectional analysis of baseline data from a randomized trial comparing weight loss maintenance interventions. The study included primary care patients, 18-75 years old, with ≥5% intentional weight loss via lifestyle change in the past 2 years. Participants (74% female, 87% white) had mean age 53 (12) years, body mass index 30.4 (5.9) kg/m², and recent weight loss of 11 (8)%. Dietary habits were measured by the Diet Habits Survey. Physical activity and sedentary behavior were measured by self-report and objectively by pedometer.</p><p><strong>Results: </strong>On average, participants reported high fruits and vegetables intake (5 servings/day), and low intake of fried foods (1 serving/week), desserts (1 serving/week) and sugar-sweetened beverages (0 servings/week). Those with greater vs. lesser weight loss had higher intake of fruits and vegetables (p=0.037) and low fat foods or recipes (p=0.019). Average self-reported moderate-vigorous physical activity was 319 (281) minutes/week, with significant differences between greater (374 (328) minutes/week) vs. lesser (276 (230) minutes/week) weight loss groups (p=0.017). By pedometer, 30% had ≥7,500 steps/day; the proportion was higher in greater (43%) vs. lesser (19%) weight loss groups (p=0.005).</p><p><strong>Conclusions: </strong>For weight loss, clinical patients typically employ simple strategies such as 5+ fruits and vegetables per day, fried foods and desserts ≤1 per week, elimination of sugary drinks, choosing low fat foods/recipes, and physical activity 45-60 min/day.</p>","PeriodicalId":75243,"journal":{"name":"Translational journal of the American College of Sports Medicine","volume":"2 18","pages":"114-121"},"PeriodicalIF":0.0,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5679021/pdf/nihms886884.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35545995","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":"A Comparative Effectiveness Trial of Three Walking Self-monitoring Strategies.","authors":"Caroline R Richardson,&nbsp;David E Goodrich,&nbsp;Angela R Larkin,&nbsp;David Ronis,&nbsp;Robert G Holleman,&nbsp;Laura J Damschroder,&nbsp;Julie C Lowery","doi":"10.1249/TJX.0000000000000017","DOIUrl":"https://doi.org/10.1249/TJX.0000000000000017","url":null,"abstract":"<p><strong>Purpose: </strong>Walking programs improve health outcomes in adults at risk for cardiovascular disease and self-monitoring strategies can improve adherence to such programs. The objective of this study was to determine if a six-month internet-based walking program using web-enhanced pedometers results in more weight loss than walking programs based on time or simple pedometer-step count goals in adults with or at risk for cardiovascular disease (CVD).</p><p><strong>Methods: </strong>This was a multi-site, randomized controlled trial of 255 male Veterans who were ambulatory, insufficiently active, BMI ≥ 28, and who reported 1 ≥ CVD risk factors. Participants were randomized to one of three self-monitoring strategies to increase walking: (1) time-based walking goals; (2) simple pedometer-based walking goals; and (3) web-enhanced pedometer feedback goals with Internet-mediated feedback. All participants also attended five individual weight loss sessions with a dietitian. The main outcome measure was change in weight at six months (kg) and secondary outcomes were change in accelerometer-measured physical activity (min) and change in health-related quality of life at six months.</p><p><strong>Results: </strong>The 255 participants had a mean age of 56.3 years (SD = 10.0), BMI=36.3 (SD = 5.3) with a mean of 5.2 (SD = 2.3) medical comorbidities. Dropouts were distributed evenly across the three groups and 72% of participants completed the program. At six months, participants in the web-enhanced pedometer arm lost significantly more weight (-1.9 kg, 95% CI=-2.7, -1.1) than those in the time-based group (-0.7 kg, 95% CI=-1.5, 0.0; p = 0.04) and simple pedometer group (-0.6 kg, 95% CI=-1.4, 0.2; p = 0.02).</p><p><strong>Conclusion: </strong>Internet-enhanced pedometers result in greater weight loss in Veterans than walking programs using time-based walking goals or simple pedometers.</p>","PeriodicalId":75243,"journal":{"name":"Translational journal of the American College of Sports Medicine","volume":"1 15","pages":"133-142"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/99/79/tjx-1-133.PMC5435380.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35015776","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":"Factors Influencing Implementation of Youth Physical Activity Interventions: An Expert Perspective—Corrigendum","authors":"","doi":"10.1249/tjx.0000000000000021","DOIUrl":"https://doi.org/10.1249/tjx.0000000000000021","url":null,"abstract":"LE 3. elihood ratios and diagnostic power scores for each factor-level. Likelihood Ratios for Each Factor-Level ctors High Moderate Low Diagnostic Power Scores rganizational characteristics . Leadership motivation and engagement c, d 8.75/1 1/1.05 1/8.63 17.38 . Physical activity culture 4.69/1 1.07/1 1/6.56 11.34 . Available facilitates and equipment d 4/1 1/1.12 1/5.09 9.09 . Available space 3.05/1 1.19/1 1/3.53 6.58 . Available staff d 5/1 1/1.17 1/5 10 . Communication c, d 2.55/1 1.05/1 1/3.31 5.86 . Competing programs within the organization 1.77/1 1.19/1 1/2.63 4.4 plementation processes . Needs assessment 7.75/1 1/1.23 1/5 12.75 . Goal setting 4.31/1 1.12/1 1/4.55 8.86 0. Engaging intervention staff c 5.57/1 1.08/1 1/10.67 16.24 . Engaging youths c 3.16/1 1.17/1 1/4.46 7.62 2. Engaging program champion c 4.43/1 1/1.15 1/4.67 9.1 3. Training c, d 3.39/1 1/1 1/4.91 8.32 4. Technical assistance c, d 3.85/1 1.27/1 1/4.75 8.6 5. Reflecting and evaluating 4.92/1 1.44/1 1/4.67 9.59 6. Sustainability plans 2.23/1 1.36/1 1/3.61 5.84 rovider characteristics 7. Provider belief and motivation d 4.54/1 1.13/1 1/4.27 8.81 8. Provider knowledge and skills about the intervention c, d 5.16/1 1.03/1 1/7.43 12.59","PeriodicalId":75243,"journal":{"name":"Translational journal of the American College of Sports Medicine","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66085306","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":"Physical Activity Levels in a Community Lifestyle Intervention: A Randomized Trial.","authors":"Yvonne L Eaglehouse,&nbsp;Bonny Rockette-Wagner,&nbsp;M Kaye Kramer,&nbsp;Vincent C Arena,&nbsp;Rachel G Miller,&nbsp;Karl K Vanderwood,&nbsp;Andrea M Kriska","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Background: </strong>A behavioral lifestyle intervention program with goals of increasing physical activity (PA) and losing weight was shown to be efficacious for preventing type 2 diabetes and decreasing risk for cardiovascular disease in the U.S. Diabetes Prevention Program (DPP). Modified versions of the DPP lifestyle intervention are being translated into diverse community settings and have been successful in decreasing weight and improving metabolic markers. However, comprehensive evaluations of PA levels within these community translation intervention efforts are rare.</p><p><strong>Purpose: </strong>To evaluate the effectiveness of a DPP-based community lifestyle intervention for improving PA levels.</p><p><strong>Methods: </strong>223 overweight adults at-risk for type 2 diabetes and/or cardiovascular disease were randomized (immediate or 6-month delayed-start) to a 12-month DPP-based lifestyle intervention. Past-month PA level was assessed at baseline and post-intervention with the Modifiable Activity Questionnaire. Simple and mixed-effects regression models were used to determine changes in PA level between and within groups over time.</p><p><strong>Results: </strong>The between-group mean difference for change in PA levels from baseline to 6 months indicated significantly greater improvement in the intervention compared to the delayed-start group [+6.72 (SE=3.01) MET-hrs/week; <i>p</i>=0.03]. Examining combined within-group change from baseline to post-intervention, mean PA levels significantly increased by +14.69 (SE=1.43) and +9.50 (SE= 1.40) MET-hrs/week at 6 and 12 months post-intervention, respectively. This PA change offset to approximately +10 MET-hrs/week at both 6 and 12 months after adjusting for baseline PA level and season (all; <i>p</i><0.01). Other than season, sex impacted on change in PA level.</p><p><strong>Conclusions: </strong>This community-based lifestyle intervention significantly increased PA levels among overweight adults at risk for type 2 diabetes and cardiovascular disease, even after adjusting for key variables.</p><p><strong>Clinicaltrialsgov identifier: </strong>NCT01050205.</p>","PeriodicalId":75243,"journal":{"name":"Translational journal of the American College of Sports Medicine","volume":"1 5","pages":"45-51"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4991779/pdf/nihms775914.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34328482","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":"Leveraging Citizen Science and Information Technology for Population Physical Activity Promotion.","authors":"Abby C King, Sandra J Winter, Jylana L Sheats, Lisa G Rosas, Matthew P Buman, Deborah Salvo, Nicole M Rodriguez, Rebecca A Seguin, Mika Moran, Randi Garber, Bonnie Broderick, Susan G Zieff, Olga Lucia Sarmiento, Silvia A Gonzalez, Ann Banchoff, Juan Rivera Dommarco","doi":"","DOIUrl":"","url":null,"abstract":"<p><strong>Purpose: </strong>While technology is a major driver of many of society's comforts, conveniences, and advances, it has been responsible, in a significant way, for engineering regular physical activity and a number of other positive health behaviors out of people's daily lives. A key question concerns how to harness information and communication technologies (ICT) to bring about positive changes in the health promotion field. One such approach involves community-engaged \"citizen science,\" in which local residents leverage the potential of ICT to foster data-driven consensus-building and mobilization efforts that advance physical activity at the individual, social, built environment, and policy levels.</p><p><strong>Method: </strong>The history of citizen science in the research arena is briefly described and an evidence-based method that embeds citizen science in a multi-level, multi-sectoral community-based participatory research framework for physical activity promotion is presented.</p><p><strong>Results: </strong>Several examples of this citizen science-driven community engagement framework for promoting active lifestyles, called \"Our Voice\", are discussed, including pilot projects from diverse communities in the U.S. as well as internationally.</p><p><strong>Conclusions: </strong>The opportunities and challenges involved in leveraging citizen science activities as part of a broader population approach to promoting regular physical activity are explored. The strategic engagement of citizen scientists from socio-demographically diverse communities across the globe as both assessment as well as change agents provides a promising, potentially low-cost and scalable strategy for creating more active, healthful, and equitable neighborhoods and communities worldwide.</p>","PeriodicalId":75243,"journal":{"name":"Translational journal of the American College of Sports Medicine","volume":"1 4","pages":"30-44"},"PeriodicalIF":0.0,"publicationDate":"2016-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4978140/pdf/nihms768544.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34308208","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}