Journal of physical activity & health最新文献

{"title":"Smartphone Google Location History: A Novel Approach to Outdoor Physical Activity Research.","authors":"Ofer Amram, Olufunso Oje, Andrew Larkin, Kwadwo Boakye, Ally Avery, Assefaw Gebremedhin, Bethany Williams, Glen E Duncan, Perry Hystad","doi":"10.1123/jpah.2024-0360","DOIUrl":"https://doi.org/10.1123/jpah.2024-0360","url":null,"abstract":"<p><strong>Background: </strong>Outdoor physical activity (PA) is an important component of overall health; however, it is difficult to measure. Passively collected smartphone location data like Google Location History (GLH) present an opportunity to address this issue.</p><p><strong>Objectives: </strong>To evaluate the use of GLH data for measuring outdoor PA.</p><p><strong>Methods: </strong>We collected GLH data for 357 individuals from the Washington State Twin Registry. We first summarized GLH measurements relevant to outdoor PA. Next, we compared accelerometer measurements to GLH classified PA for a subset of 25 participants who completed 2 weeks of global positioning system and accelerometer monitoring. Finally, we examined the association between GLH measured walking and obesity.</p><p><strong>Results: </strong>Participants provided a mean (SD) average 52 (18.8) months of GLH time-activity data, which included a mean (SD) average of 2421 (1632) trips per participant. GLH measurements were classified as the following: 79,994 unique walking trips (11.6% of all trips), 564,558 (81.8%) trips in a passenger vehicle, 11,974 cycling trips (1.7%), and 890 running trips (0.1%). Sixty-two percent of these trips had location accuracy >80%. In the accelerometry evaluation, GLH walking trips had a corresponding mean vector magnitude of 3150 counts per minute, compared with 489 counts per minute for vehicle trips. In adjusted cross-sectional analyses, we observed an inverse association between both walking minutes and trips per month and the odds of being obese (odds ratio = 0.78; 95% CI, 0.60-0.96, and odds ratio = 0.91; 95% CI, 0.82-0.98, respectively).</p><p><strong>Conclusions: </strong>GLH data provide a novel method for measuring long-term, retrospective outdoor PA that can provide new opportunities for PA research.</p>","PeriodicalId":16812,"journal":{"name":"Journal of physical activity & health","volume":" ","pages":"1-9"},"PeriodicalIF":2.9,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142813528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Evidence Is Clear, Exercise Is Not Better Than Antidepressants or Therapy: It Is Crucial to Communicate Science Honestly.","authors":"Nicholas Fabiano, David Puder, Brendon Stubbs","doi":"10.1123/jpah.2024-0743","DOIUrl":"https://doi.org/10.1123/jpah.2024-0743","url":null,"abstract":"","PeriodicalId":16812,"journal":{"name":"Journal of physical activity & health","volume":" ","pages":"1-2"},"PeriodicalIF":2.9,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142813529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Billing for Exercise Is Medicine: An Analysis of Reimbursement Trends for Physical Activity-Related Billing Codes.","authors":"Lucas J Carr, Britt Marcussen, Tyler Slayman, Yin Wu, Dale S Bond","doi":"10.1123/jpah.2024-0499","DOIUrl":"https://doi.org/10.1123/jpah.2024-0499","url":null,"abstract":"<p><strong>Background: </strong>Physical inactivity is a significant health risk factor linked to chronic diseases and premature death. To address this, initiatives like Exercise is Medicine® aim to promote physical activity in health care systems. However, integrating physical activity counseling into clinical practice faces barriers such as limited reimbursement. Understanding billing practices and reimbursement rates for physical activity counseling is crucial for its integration into health care.</p><p><strong>Methods: </strong>This study used 12 months of billing data from a large midwestern US hospital. Variables included charges, charge amounts, primary payors, reimbursement rates, and denial rates associated with International Classification of Diseases-10 diagnosis codes, and Evaluation and Management billing codes for physical activity counseling. Logistic regression analysis identified factors associated with denial rates.</p><p><strong>Results: </strong>Over 12 months, 19,366 lifestyle-related charges were submitted, totaling $7,842,845. Of these, 5.28% were denied, amounting to $414,446. The most common International Classification of Diseases-10 codes were \"obesity\" (38.8%) and \"sedentary lifestyle\" (32.6%), while the most common Evaluation and Management codes were for established outpatient office visits. Charges were mainly submitted to employer-paid insurance (43.5%), Medicaid (22.2%), and Medicare (21.9%). Higher odds of denial were associated with newer patients, shorter visit lengths, and the sedentary lifestyle code.</p><p><strong>Conclusion: </strong>This study provides novel data on the use, reimbursement, and denial rates of physical activity counseling billing codes in a large health care system. Physical activity counseling-related charges are rarely denied by third-party payors. Further research is needed to determine if these findings are generalizable to other US health care systems.</p>","PeriodicalId":16812,"journal":{"name":"Journal of physical activity & health","volume":" ","pages":"1-6"},"PeriodicalIF":2.9,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142807177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Socioeconomic Status and Patterns of Physical Activity and Sedentary Behavior: A Cross-Sectional Analysis of the J-SHINE.","authors":"Munehiro Matsushita, Daisuke Takagi, Masamitsu Kamada","doi":"10.1123/jpah.2023-0138","DOIUrl":"https://doi.org/10.1123/jpah.2023-0138","url":null,"abstract":"<p><strong>Background: </strong>This study aimed to examine the association between socioeconomic status (SES) and optimal movement behaviors including sufficient moderate-to-vigorous physical activity (PA), regular leisure-time PA, and less sedentary behavior.</p><p><strong>Methods: </strong>We used data from the Japanese Study on Stratification, Health, Income, and Neighborhood conducted in 2012. Activity patterns and SES were measured using International Physical Activity Questionnaire Short-Version and other self-administered questionnaires. Activity pattern outcomes assessed were sufficient total volume of moderate-to-vigorous PA (≥150 min/wk), regular leisure-time PA (≥1 d/wk), less sedentary time (≤4 h/d), and optimal movement behaviors (meeting all criteria). SES variables were equivalized annual income, educational attainment, and occupation. Logistic regression analysis adjusted for confounders.</p><p><strong>Results: </strong>We included 731 men and 852 women. Lower income levels were associated with less leisure-time PA among men and women (men, odds ratio [OR]: 0.60 and 0.65 for Q2 and Q1 [lowest], respectively; women, OR: 0.53 and 0.56 for Q2 and Q1 [lowest]). Lower SES groups associated with less sedentary time (men, OR: 1.82 for blue-collar; women, OR: 1.44 for Q1 income level, 1.61 and 1.53 for junior college, technical school, and high school/junior high school, respectively; 1.89 for unemployed). SES was not significantly associated with optimal movement behavior in both sexes (in men, OR for those with high school or junior high school education vs those with university or graduate school education = 0.81 [0.43-1.53]).</p><p><strong>Conclusion: </strong>Activity patterns varied by SES, with lower income associated with less leisure-time PA and white-collar workers associated with more prevalent sedentary behavior among both sexes.</p>","PeriodicalId":16812,"journal":{"name":"Journal of physical activity & health","volume":" ","pages":"1-8"},"PeriodicalIF":2.9,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142807183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Temporal Decomposition Analysis of Noncommunicable Disease Burden: The Interplay of Population Aging, Population Growth, and Low Physical Activity, 2010-2019.","authors":"Ming Lu, Bin Lu, Le Wang","doi":"10.1123/jpah.2024-0201","DOIUrl":"https://doi.org/10.1123/jpah.2024-0201","url":null,"abstract":"<p><strong>Background: </strong>To analyze global trends in the noncommunicable diseases (NCDs) burden attributable to low physical activity, considering the impacts of population aging and growth.</p><p><strong>Method: </strong>Based on the Global Burden Disease 2019 Study, the NCDs-related death and disability-adjusted life years attributable to low physical activity (defined as <3000 metabolic equivalent-min/wk) were obtained from 2010 to 2019. The average annual percent change was calculated using the joinpoint analysis. Decomposition analysis was applied to assess the separated contributions of 3 components (population aging, population growth, and death change due to all other factors) on the overall change in NCDs death attributed to low physical activity.</p><p><strong>Results: </strong>From 2010 to 2019, the average annual percent change of age-standardized rates of NCDs due to low physical activity was -0.09% for death and -0.06% for disability-adjusted life years. However, the global absolute number of deaths from NCDs attributable to low physical activity increased from 672,215 to 831,502, and disability-adjusted life years rose from 12,813,793 to 15,747,938. This rise was largely driven by population aging and growth, contributing to a 13.0% and 14.7% increase, respectively. The most significant impact of population aging on NCD deaths was observed in high-middle socio-demographic index countries (17.6%), whereas population growth had the greatest effect in low socio-demographic index countries (24.3%).</p><p><strong>Conclusions: </strong>The reduction in NCDs death rates attributed to low physical activity is insufficient to counteract the effects of population aging and growth. Targeted interventions for physical activity promotion should focus on the older population with special attention to diseases most sensitive to physical inactivity.</p>","PeriodicalId":16812,"journal":{"name":"Journal of physical activity & health","volume":" ","pages":"1-10"},"PeriodicalIF":2.9,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142807124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Erratum. Gender Gap for Accelerometry-Based Physical Activity Across Different Age Groups in 5 Brazilian Cohort Studies.","authors":"","doi":"10.1123/jpah.2024-0822","DOIUrl":"https://doi.org/10.1123/jpah.2024-0822","url":null,"abstract":"","PeriodicalId":16812,"journal":{"name":"Journal of physical activity & health","volume":" ","pages":"1"},"PeriodicalIF":2.9,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142801220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Erratum. Sitting, Standing, and Physical Activity in Australian Passenger Rail Drivers: On the Right Track for Better Health?","authors":"","doi":"10.1123/jpah.2024-0817","DOIUrl":"https://doi.org/10.1123/jpah.2024-0817","url":null,"abstract":"","PeriodicalId":16812,"journal":{"name":"Journal of physical activity & health","volume":" ","pages":"1"},"PeriodicalIF":2.9,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142739816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Geographic and Grade-Level Disparities in Student Access to School-Based Physical Education and Physical Activity Opportunities Across 25 US States.","authors":"Chad M Killian, Ben D Kern, Wesley J Wilson, Hans van der Mars","doi":"10.1123/jpah.2024-0340","DOIUrl":"https://doi.org/10.1123/jpah.2024-0340","url":null,"abstract":"<p><strong>Background: </strong>Most US children and adolescents do not meet recommended daily physical activity (PA) guidelines. Determinants of PA are complex; however, access to opportunities precedes actual PA engagement. Schools are well positioned to support student PA through the provision of physical education (PE) and before, during, and after school PA opportunities through comprehensive (ie, expanded) school PA programming. Monitoring access to school PE and PA opportunities is an essential function of public health. However, there are limited comprehensive data across K-12 settings. Therefore, the purpose of this study was to evaluate students' access to PE and expanded recreation time before, during, and after school PA opportunities in K-12 schools across 25 US states.</p><p><strong>Methods: </strong>The US Physical Education and Physical Activity Policy questionnaire was completed by 4845 K-12 PE teachers across 25 states, representing diverse geographical regions, with responses standardized across varying academic calendars. Descriptive statistics were used to illustrate access to PE and PA opportunities.</p><p><strong>Results: </strong>Access to PE and PA varied, with elementary schools generally providing more opportunities than middle and high schools. There was an overall misalignment with national PE and recess recommendations. Limited before and after school PA opportunities were also reported.</p><p><strong>Discussion: </strong>The relative dearth of access to PE and expanded PA opportunities currently available to students in relation to national guidelines shows a need for states to prioritize expanding access to PE and recreational PA to reduce disparities. To ensure more equitable student access, collaborative efforts among educators, policymakers, and stakeholders are essential.</p>","PeriodicalId":16812,"journal":{"name":"Journal of physical activity & health","volume":" ","pages":"1-10"},"PeriodicalIF":2.9,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142739818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Movement Mediates the Relationship Between Socioeconomic Position and Socioemotional Outcomes in Youth.","authors":"Katrina Wilhite, Michael Noetel, Borja Del Pozo Cruz, Chris Lonsdale, Taren Sanders","doi":"10.1123/jpah.2024-0114","DOIUrl":"https://doi.org/10.1123/jpah.2024-0114","url":null,"abstract":"<p><strong>Background: </strong>Youth from lower socioeconomic positions tend to have poorer socioemotional outcomes, be less physically active, have poorer sleep, and engage in more screen time than their peers from higher socioeconomic positions. The objective of this study was to test the hypothesis that movement behaviors (ie, physical activity, sedentary behavior, and sleep) and changes in combinations of movement behaviors over time (movement trajectories) mediate the relationship between socioeconomic position and socioemotional outcomes in youth.</p><p><strong>Methods: </strong>This study used socioeconomic position data, scores from Strengths and Difficulties Questionnaires, and time-use diaries from 980 females and 1014 males (2% Australian Indigenous) aged 10-14 from the Longitudinal Study of Australian Children from 2014 to 2018.</p><p><strong>Results: </strong>Movement trajectories did not mediate the relationship between socioeconomic position and socioemotional outcomes. Least absolute shrinkage and selection operator-based mediation analyses found males from lower socioeconomic positions participated in less moderate- to vigorous-intensity physical activity than their peers from high socioeconomic positions, partially explaining (7%) more peer problems. Youth from lower socioeconomic positions participated in more recreational screen activities than their peers from higher socioeconomic positions, partially explaining (1%-3%) worse total socioemotional outcomes and conduct (females) and emotional problems (males).</p><p><strong>Conclusions: </strong>Future qualitative research should be considered to identify the best ways for youth from lower socioeconomic positions to decrease screen time and increase opportunities to participate in moderate- to vigorous-intensity physical activity in the community, at school, and at home. Other mediators explaining differences in socioemotional outcomes should be explored.</p>","PeriodicalId":16812,"journal":{"name":"Journal of physical activity & health","volume":" ","pages":"1-11"},"PeriodicalIF":2.9,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142693232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the Efficacy of Sport-Based Physical Education on Children's Activity Behaviors: A Randomized Controlled Trial.","authors":"Aliye B Cepni, David W Walsh, Hanjoe Kim, Cynthia Y Yoon, Sheryl O Hughes, Tracey A Ledoux, Craig A Johnston","doi":"10.1123/jpah.2024-0243","DOIUrl":"https://doi.org/10.1123/jpah.2024-0243","url":null,"abstract":"<p><strong>Background: </strong>Children from low-income and racial/ethnic minority backgrounds are more prone to insufficient physical activity and heightened sedentary behaviors. This study aims to increase moderate to vigorous physical activity and decrease sedentary behaviors among high-risk children through an inclusive and transformative sport skill development physical education (PE) intervention.</p><p><strong>Methods: </strong>Elementary school-aged children were recruited from 3 public schools located in underserved communities in Houston, TX. Classrooms were randomly assigned to a sport-based PE class (intervention, 12 classrooms, n = 124) or a standard PE class (control, 13 classrooms, n = 133). The intervention was implemented at school by teachers over 10 weeks, whereas at home, the intervention group received equipment, virtual classes, and parent trainings. Activity behaviors were assessed using accelerometry (ActiGraph GT3X+) at baseline and post intervention. Multilevel linear mixed-effects models were conducted to examine changes in activity behaviors between the study conditions.</p><p><strong>Results: </strong>Participants were 9.33 (0.68) years old, and 46% were females, who identified as either Hispanic/Latino (48%) and/or Black (38%). The difference in minutes of weekend sedentary behavior change was 32 minutes between study conditions (P = .012). Specifically, intervention girls decreased weekend sedentary behavior by 37 minutes, whereas girls in the control condition increased by 8 minutes (P < .01). Despite the direction of change in overall, weekday, or weekend moderate to vigorous physical activity and overall or weekday sedentary behaviors in favor of the intervention, these effects did not reach the statistically significant level compared to the control condition.</p><p><strong>Conclusions: </strong>Sport-based PE intervention can be an important strategy to decrease child sedentary behaviors during out-of-school periods, particularly among girls.</p>","PeriodicalId":16812,"journal":{"name":"Journal of physical activity & health","volume":" ","pages":"1-11"},"PeriodicalIF":2.9,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142676147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}