Browse

You are looking at 21 - 30 of 508 items for :

  • Sport and Exercise Science/Kinesiology x
  • User-accessible content x
Clear All
Full access

Emily J. Tomayko, Katherine B. Gunter, John M. Schuna Jr. and Paul N. Thompson

Background: Use of 4-day school weeks (FDSWs) as a cost-saving strategy has increased substantially as many US school districts face funding declines. However, the impacts of FDSWs on physical activity exposure and related outcomes are unknown. This study examined physical education (PE) exposure and childhood obesity prevalence in 4- versus 5-day Oregon schools; the authors hypothesized lower PE exposure and higher obesity in FDSW schools, given reduced school environment exposure. Methods: The authors utilized existing data from Oregon to compare 4- versus 5-day models: t tests compared mean school-level factors (PE exposure, time in school, enrollment, and demographics) and complex samples weighted t tests compared mean child-level obesity data for a state representative sample of first to third graders (N = 4625). Results: Enrollment, time in school, and student–teacher ratio were significantly lower in FDSW schools. FDSW schools provided significantly more PE, both in minutes (120 vs 101 min/wk in 4- vs 5-d schools, P < .01) and relative to total time in school (6.9% vs 5.0%, P < .0001). Obesity prevalence did not differ significantly between school models. Conclusion: Greater PE exposure in FDSW schools was observed, and it remains unknown whether differences in PE exposure contributed to obesity prevalence in this sample of students. Efforts to better understand how FDSWs impact physical activity, obesity risk, and related factors are needed.

Open access

Martin Buchheit

Full access

Erin K. Howie, Justin M. Guagliano, Karen Milton, Stewart A. Vella, Sjaan R. Gomersall, Tracy L. Kolbe-Alexander, Justin Richards and Russell R. Pate

Background: Sport has been identified as one of the 7 best investments for increasing physical activity levels across the life span. Several questions remain on how to effectively utilize youth sport as a strategy for increasing physical activity and improving health in youth. The purpose of this paper is to identify the main research priorities in the areas of youth sport and physical activity for health. Methods: An international expert panel was convened, selected to cover a wide spectrum of topics related to youth sport. The group developed a draft set of potential research priorities, and relevant research was scoped. Through an iterative process, the group reached consensus on the top 10 research priorities. Results: The 10 research priorities were identified related to sport participation rates, physical activity from sport, the contribution of sport to health, and the overall return on investment from youth sport. For each research priority, the current evidence is summarized, key research gaps are noted, and immediate research needs are suggested. Conclusion: The identified research priorities are intended to guide researchers, policymakers, and practitioners to increase the evidence base on which to base the design, delivery, and policies of youth sport programs to deliver health benefits.

Open access

Kristin Suorsa, Anna Pulakka, Tuija Leskinen, Jaana Pentti, Andreas Holtermann, Olli J. Heinonen, Juha Sunikka, Jussi Vahtera and Sari Stenholm

Background: The accuracy of wrist-worn accelerometers in identifying sedentary time has been scarcely studied in free-living conditions. The aim of this study was to compare daily sedentary time estimates between a thigh-worn accelerometer, which measured sitting and lying postures, and a wrist-worn accelerometer, which measured low levels of movement. Methods: The study population consisted of 259 participants (M age = 62.8 years, SD = 0.9) from the Finnish Retirement and Aging Study (FIREA). Participants wore an Axivity AX3 accelerometer on their mid-thigh and an Actigraph wActiSleep-BT accelerometer on their non-dominant wrist simultaneously for a minimum of 4 days in free-living conditions. Two definitions to estimate daily sedentary time were used for data from the wrist-worn accelerometer: 1) the count cutpoint, ≤1853 counts per minute; and 2) the Euclidean Norm Minus One (ENMO) cutpoint, <30 mg. Results: Compared to the thigh-worn accelerometer, daily sedentary time estimate was 63 min (95% confidence interval [CI] = −53 to −73) lower by the count cutpoint and 50 min (95% CI = 34 to 67) lower by the ENMO cutpoint. The limits of agreement in daily sedentary time estimates between the thigh- and cutpoint methods for wrist-worn accelerometers were wide (the count cutpoint: −117 to 243, the ENMO cutpoint: −212 to 313 min). Conclusions: Currently established cutpoint-based methods to estimate sedentary time from wrist-worn accelerometers result in underestimation of daily sedentary time compared to posture-based estimates of thigh-worn accelerometers. Thus, sedentary time estimates obtained from wrist-worn accelerometers using currently available cutpoint-based methods should be interpreted with caution and future work is needed to improve their accuracy.

Open access

Andreas M. Kasper, S. Andy Sparks, Matthew Hooks, Matthew Skeer, Benjamin Webb, Houman Nia, James P. Morton and Graeme L. Close

Rugby is characterized by frequent high-intensity collisions, resulting in muscle soreness. Players consequently seek strategies to reduce soreness and accelerate recovery, with an emerging method being cannabidiol (CBD), despite anti-doping risks. The prevalence and rationale for CBD use in rugby has not been explored; therefore, we recruited professional male players to complete a survey on CBD. Goodness of fit chi-square (χ2) was used to assess CBD use between codes and player position. Effects of age on use were determined using χ2 tests of independence. Twenty-five teams provided 517 player responses. While the majority of players had never used CBD (p < .001, V = 0.24), 26% had either used it (18%) or were still using it (8%). Significantly more CBD use was observed in rugby union compared with rugby league (p = .004, V = 0.13), but player position was not a factor (p = .760, V = 0.013). CBD use increased with players’ age (p < .001, V = 0.28), with mean use reaching 41% in the players aged 28 years and older category (p < .0001). The players using CBD primarily used the Internet (73%) or another teammate (61%) to obtain information, with only 16% consulting a nutritionist. The main reasons for CBD use were improving recovery/pain (80%) and sleep (78%), with 68% of players reporting a perceived benefit. These data highlight the need for immediate education on the risks of CBD, as well as the need to explore the claims regarding pain and sleep.

Full access

William Boyer, James Churilla, Amy Miller, Trevor Gillum and Marshare Penny

Background: The effects of aerobic physical activity (PA) and muscular strengthening activity (MSA) on all-cause mortality risk need further exploration among ethnically diverse populations. Purpose: To examine potential effect modification of race-ethnicity on meeting the PA guidelines and on all-cause mortality. Methods: The study sample (N = 14,384) included adults (20–79 y of age) from the 1999–2006 National Health and Nutrition Examination Survey. PA was categorized into 6 categories based on the 2018 PA guidelines: category 1 (inactive), category 2 (insufficient PA and no MSA), category 3 (active and no MSA), category 4 (no PA and sufficient MSA), category 5 (insufficient PA and sufficient MSA), and category 6 (meeting both recommendations). Race-ethnic groups examined included non-Hispanic white, non-Hispanic black, and Mexican American. Cox-proportional hazard models were used. Results: Significant risk reductions were found for categories 2, 3, and 6 for non-Hispanic white and non-Hispanic black. Among Mexican American, significant risk reductions were found in category 6. Conclusion: In support of the 2018 PA guidelines, meeting both the aerobic PA and MSA guidelines significantly reduced risk for all-cause mortality independent of race-ethnicity. The effects of aerobic PA alone seem to be isolated to non-Hispanic white and non-Hispanic black.

Full access

Jessica G. Hunter, Alexander M.B. Smith, Lena M. Sciarratta, Stephen Suydam, Jae Kun Shim and Ross H. Miller

Studies of running mechanics often use a standardized lab shoe, ostensibly to reduce variance between subjects; however, this may induce unnatural running mechanics. The purpose of this study was to compare the step rate, vertical average loading rate, and ground contact time when running in standardized lab shoes versus participants’ normal running shoes. Ground reaction forces were measured while the participants ran overground in both shoe conditions at a self-selected speed. The Student’s t-test revealed that the vertical average loading rate magnitude was smaller in lab shoes versus normal shoes (42.09 [11.08] vs 47.35 [10.81] body weight/s, P = .013), while the step rate (170.92 [9.43] vs 168.98 [9.63] steps/min, P = .053) and ground contact time were similar (253 [25] vs 251 [20] ms, P = .5227) and the variance of all outcomes was similar in lab shoes versus normal shoes. Our results indicate that using standardized lab shoes during testing may underestimate the loads runners actually experience during their typical mileage.

Open access

Benjamin J. Narang, Greg Atkinson, Javier T. Gonzalez and James A. Betts

The analysis of time series data is common in nutrition and metabolism research for quantifying the physiological responses to various stimuli. The reduction of many data from a time series into a summary statistic(s) can help quantify and communicate the overall response in a more straightforward way and in line with a specific hypothesis. Nevertheless, many summary statistics have been selected by various researchers, and some approaches are still complex. The time-intensive nature of such calculations can be a burden for especially large data sets and may, therefore, introduce computational errors, which are difficult to recognize and correct. In this short commentary, the authors introduce a newly developed tool that automates many of the processes commonly used by researchers for discrete time series analysis, with particular emphasis on how the tool may be implemented within nutrition and exercise science research.