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Open access

Jason P. Brandenburg, Iris A. Lesser, Cynthia J. Thomson, and Luisa V. Giles

Background: Regular physical activity and higher cardiorespiratory (CR) fitness enhance immune function, possibly reducing coronavirus disease 2019 (COVID-19) infection severity. The aim was to assess the association between physical activity and self-reported CR fitness on COVID-19 infection characteristics. Methods: Participants formerly testing positive for COVID-19 completed an online questionnaire measuring COVID-19 infection characteristics and complications, self-reported CR fitness level, physical activity, and sociodemographic and health-related characteristics. Self-reported CR fitness was determined as the pace to cover 4.8 km without becoming overly fatigued (with slow walking, brisk walking, jogging, and running corresponding to low, moderate, good, and excellent levels of fitness, respectively). Results: A total of 263 individuals completed the survey. Compared with the lowest level of self-reported CR fitness, the odds of hospitalization significantly decreased by 64% (odds ratio = 0.36; 95% confidence interval, 0.13–0.98; P = .04) in individuals reporting the ability to maintain a brisk walk. In individuals reporting the ability to maintain a jogging pace, the further reduction in hospitalization was not significant (odds ratio = 0.22; 95% confidence interval, 0.05–1.04; P = .05). For COVID-19 symptom severity and number, there were no significant associations with self-reported CR fitness or physical activity levels. Conclusions: For individuals with low self-reported CR fitness, improving CR fitness represents a strategy to reduce the risk of hospitalization from COVID-19.

Open access

Pauliina Husu, Kari Tokola, Henri Vähä-Ypyä, Harri Sievänen, Jaana Suni, Olli J. Heinonen, Jarmo Heiskanen, Kaisu M. Kaikkonen, Kai Savonen, Sami Kokko, and Tommi Vasankari

Background: Studies measuring physical activity (PA) and sedentary behavior on a 24/7 basis are scarce. The present study assessed the feasibility of using an accelerometer at the hip while awake and at the wrist while sleeping to describe 24/7 patterns of physical behavior in working-aged adults by age, sex, and fitness. Methods: The study was based on the FinFit 2017 study where the physical behavior of 20- to 69-year-old Finns was assessed 24/7 by triaxial accelerometer (UKKRM42; UKK Terveyspalvelut Oy, Tampere, Finland). During waking hours, the accelerometer was kept at the right hip and, during time in bed, at the nondominant wrist. PA variables were based on 1-min exponential moving average of mean amplitude deviation of the resultant acceleration signal analyzed in 6-s epochs. The angle for the posture estimation algorithm was used to identify sedentary behavior and standing. Evaluation of time in bed was based on the wrist movement. Fitness was estimated by the 6-min walk test. Results: A total of 2,256 eligible participants (mean age 49.5 years, SD = 13.5, 59% women) wore the accelerometer at the hip 15.7 hr/day (SD = 1.4) and at the wrist 8.3 hr/day (SD = 1.4). Sedentary behavior covered 9 hr 18 min/day (SD = 1.8 hr/day), standing nearly 2 hr/day (SD = 0.9), light PA 3.7 hr/day (SD = 1.3), and moderate to vigorous PA 46 min/day (SD = 26). Participants took 7,451 steps per day (SD = 2,962) on average. Men were most active around noon, while women had activity peaks at noon and at early evening. The low-fit tertile took 1,186 and 1,747 fewer steps per day than the mid- and high-fit tertiles (both p < .001). Conclusions: One triaxial accelerometer with a two wear-site approach provides a feasible method to characterize hour-by-hour patterns of physical behavior among working-aged adults.

Open access

Paul Mackie, Gary Crowfoot, Prajwal Gyawali, Heidi Janssen, Elizabeth Holliday, David Dunstan, and Coralie English

Background: Interrupting prolonged sitting can attenuate postprandial glucose responses in overweight adults. The dose–response effect in stroke survivors is unknown. The authors investigated the effects of interrupting 8 hours of prolonged sitting with increasingly frequent bouts of light-intensity standing-based exercises on the postprandial glucose response in stroke survivors. Methods: Within-participant, laboratory-based, dose-escalation trial. Participants completed three 8-hour conditions: prolonged sitting and 2 experimental conditions. Experimental conditions involved light-intensity standing-based exercises of increasing frequency (2 × 5 min to 6 × 5 min bouts). Postprandial glucose is reported. Results: Twenty-nine stroke survivors (aged 66 y) participated. Interrupting 8 hours of prolonged sitting with light-intensity standing-based exercises every 90 minutes significantly decreased postprandial glucose (positive incremental area under the curve; −1.1 mmol/L·7 h; 95% confidence interval, −2.0 to −0.1). In the morning (08:00–11:00), postprandial glucose decreased during the 4 × 5 minutes and 6 × 5 minutes conditions (positive incremental area under the curve; −0.8 mmol/L·3 h; 95% confidence interval, −1.3 to −0.3 and −0.8 mmol/L·3 h; 95% confidence interval, −1.5 to −0.2, respectively) compared with prolonged sitting. Conclusion: Interrupting 8 hours of prolonged sitting at least every 90 minutes with light-intensity standing-based exercises attenuates postprandial glucose in stroke survivors. During the morning, postprandial glucose is attenuated when sitting is interrupted every 60 and 90 minutes.

Open access

Nicholas M. Watanabe, Stephen Shapiro, and Joris Drayer

Big data and analytics have become an essential component of organizational operations. The ability to collect and interpret significantly large data sets has provided a wealth of knowledge to guide decision makers in all facets of society. This is no different in sport management where big data has been used on and off the field to guide decision making across the industry. As big data evolves, there are concerns regarding the use of enhanced analytic techniques and their advancement of knowledge and theory. This special issue addresses these concerns by advancing our understanding of the use of big data in sport management research and how it can be used to further scholarship in the sport industry. The six articles in this special issue each play a role in advancing sport analytics theory, producing new knowledge, and developing new inquiries. The implications discussed in these articles provide a foundation for future research on this evolving area within the field of sport management.

Full access

Gregore I. Mielke, Inacio Crochemore-Silva, Marlos Rodrigues Domingues, Mariangela Freitas Silveira, Andréa Dâmaso Bertoldi, and Wendy J. Brown

Background: Physical activity levels decrease during pregnancy, and the time course of return to prepregnancy levels is unclear. This study aimed to describe changes in leisure-time physical activity (LTPA) and sitting time from 16 to 24 weeks of pregnancy to 12, 24, and 48 months postpartum in women with different education levels in Brazil. Methods: Data from 4000 mothers of children enrolled in the 2015 Pelotas (Brazil) Birth Cohort were analyzed. The women were interviewed between 16 and 24 weeks of pregnancy and when their children were aged 12, 24, and 48 months. The LTPA and sitting time were self-reported. Results: Only 15.7% of the women reported any LTPA during pregnancy; this declined to 7.9% at 12 months postpartum; it was 16.8% at 24 months and 23.2% at 48 months. On average, participants spent a mean (SD) of 6.4 (3.9), 4.2 (3.2), 4.3 (3.3), and 4.4 (3.3) hours per day sitting during pregnancy, and at 12, 24, and 48 months after the birth, respectively. Both any LTPA and high sitting (8+ h/d) were consistently higher among women with higher education. Conclusion: After 24 months postpartum, LTPA levels had returned to or exceeded pregnancy levels, but sitting time remained lower than during pregnancy.

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Jennifer R. Pharr, Jason D. Flatt, Lung-Chang Chien, Axenya Kachen, and Babayemi O. Olakunde

Introduction: There is a positive association between exercise and improved mental health in the general population. Although there is a greater burden of psychological distress among lesbian, gay, and bisexual (LGB) people, little is known about the association between exercise and mental health in this population. The authors explored the association between exercise and poor mental health reported by LGB adults in the United States. Methods: Our analyses used data from the 2017 Behavioral Risk Factor Surveillance System survey. Multiple regression analyses were used to determine the association between exercising and mental health days adjusting for sociodemographic characteristics. Results: Data were available for 6371 LGB participants. LGB adults who participated in any exercise reported almost 1.0 day less of poor mental health in the past 30 days compared with LGB adults who did not exercise (P ≤ .01). LGB adults who met one or both of the physical activity guidelines had between 1.2 and 1.7 days less of poor mental health compared with those who did not meet the guidelines (P ≤ .01). Conclusion: Fewer days of poor mental health were reported by LGB adults who exercised. Determining whether physical activity interventions, including aerobic and strengthening exercises, could improve mental health outcomes in LGB adults should be studied.

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Victor E. Ezeugwu, Piush J. Mandhane, Nevin Hammam, Jeffrey R. Brook, Sukhpreet K. Tamana, Stephen Hunter, Joyce Chikuma, Diana L. Lefebvre, Meghan B. Azad, Theo J. Moraes, Padmaja Subbarao, Allan B. Becker, Stuart E. Turvey, Andrei Rosu, Malcolm R. Sears, and Valerie Carson

Background: Movement behaviors (physical activity, sedentary time, and sleep) established in early childhood track into adulthood and interact to influence health outcomes. This study examined the associations between neighborhood characteristics and weather with movement behaviors in preschoolers. Methods: A subset of Canadian Healthy Infant Longitudinal Development birth cohort (n = 385, 50.6% boys) with valid movement behaviors data were enrolled at age 3 years and followed through to age 5 years. Objective measures of neighborhood characteristics were derived by ArcGIS software, and weather variables were derived from the Government of Canada weather website. Random forest and linear mixed models were used to examine predictors of movement behaviors. Cross-sectional analyses were stratified by age and season (winter and nonwinter). Results: Neighborhood safety, temperature, green space, and roads were important neighborhood characteristics for movement behaviors in 3- and 5-year-olds. An increase in temperature was associated with greater light physical activity longitudinally from age 3 to 5 years and also in the winter at age 5 years in stratified analysis. A higher percentage of expressways was associated with less nonwinter moderate to vigorous physical activity at age 3 years. Conclusions: Future initiatives to promote healthy movement behaviors in the early years should consider age differences, neighborhood characteristics, and season.