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Ryan Gage, Anja Mizdrak, Justin Richards, Adrian Bauman, Melissa Mcleod, Rhys Jones, Alistair Woodward, and Caroline Shaw

Background: Surveillance of domain-specific physical activity (PA) helps to target interventions to promote PA. We examined the sociodemographic correlates of domain-specific PA in New Zealand adults. Methods: A nationally representative sample of 13,887 adults completed the International PA Questionnaire–long form in 2019/20. Three measures of total and domain-specific (leisure, travel, home, and work) PA were calculated: (1) weekly participation, (2) mean weekly metabolic energy equivalent minutes (MET-min), and (3) median weekly MET-min among those who undertook PA. Results were weighted to the New Zealand adult population. Results: The average contribution of domain-specific activity to total PA was 37.5% for work activities (participation = 43.6%; median participating MET-min = 2790), 31.9% for home activities (participation = 82.2%; median participating MET-min = 1185), 19.4% for leisure activities (participation = 64.7%; median participating MET-min = 933), and 11.2% for travel activities (participation = 64.0%; median MET-min among participants = 495). Women accumulated more home PA and less work PA than men. Total PA was higher in middle-aged adults, with diverse patterns by age within domains. Māori accumulated less leisure PA than New Zealand Europeans but higher total PA. Asian groups reported lower PA across all domains. Higher area deprivation was negatively associated with leisure PA. Sociodemographic patterns varied by measure. For example, gender was not associated with total PA participation, but men accumulated higher MET-min when taking part in PA than women. Conclusions: Inequalities in PA varied by domain and sociodemographic group. These results should be used to inform interventions to improve PA.

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Fabiana Infante Smaira, Bruna Caruso Mazzolani, Ítalo Ribeiro Lemes, Rafael Pires da Silva, Ana J. Pinto, Sofia M. Sieczkowska, Nadia E. Aikawa, Sandra G. Pasoto, Ana C. Medeiros-Ribeiro, Carla G.S. Saad, Emily F.N. Yuk, Clovis A. Silva, Paul Swinton, Leonard de Vinci Kanda Kupa, Pedro C. Hallal, Hamilton Roschel, Bruno Gualano, and Eloisa Bonfa

Aim: To investigate the association between physical activity and immunogenicity among SARS-CoV-2 seropositive patients with autoimmune rheumatic diseases prior to and following a 2-dose schedule of CoronaVac (Sinovac inactivated vaccine). Methods : This was a prospective cohort study within an open-label, single-arm, phase 4 vaccination trial conducted in Sao Paulo, Brazil. In this substudy, only SARS-CoV-2 seropositive patients were included. Immunogenicity was assessed by seroconversion rates of total anti-SARS-CoV-2 S1/S2 immunoglobulin G (IgG), geometric mean titers of anti-S1/S2 IgG, frequency of positive neutralizing antibodies, and neutralizing activity before and after vaccination. Physical activity was assessed through a questionnaire. Model-based analyses were performed controlling for age (<60 or ≥60 y), sex, body mass index (<25, 25–30, and >30 kg/m2), and use of prednisone, immunosuppressants, and biologics. Results: A total of 180 seropositive autoimmune rheumatic disease patients were included. There was no association between physical activity and immunogenicity before and after vaccination. Conclusions: This study suggests that the positive association between physical activity and greater antibody responses seen in immunocompromised individuals following vaccination is overridden by previous SARS-CoV-2 infection, and does not extend to natural immunity.

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Matthew T. Stewart, Manish Verma, Alisha Rajbhandari, Cathy L. Antonakos, and Natalie Colabianchi

Background: There is currently a nationwide effort to bring parks and green spaces within a 10-minute walk of the home. We examined the association between park area within 1 km of a child’s residence and self-reported park-specific physical activity (PA) along with accelerometer-derived moderate to vigorous physical activity (MVPA). Methods: A subsample of K through eighth-grade youth (n = 493) from the Healthy Communities Study reported whether they engaged in park-specific PA during the last 24 hours and wore an accelerometer for up to 7 days. Park area was defined as the percentage of park land in a 1 km Euclidean buffer around the participant’s residence, categorized into quintiles. Analysis consisted of logistic and linear regression modeling with interaction effects that controlled for clustering within communities. Results: Regression models estimated greater park-specific PA for participants in the fourth and fifth quintiles of park land. Age, sex, race ethnicity, and family income were unrelated to park-specific PA. Accelerometer analysis indicated that total MVPA was unrelated to park area. Older children (β = −8.73, P < .001) and girls (β = −13.44, P < .001) engaged in less MVPA. Seasonality significantly predicted both park-specific PA and total MVPA. Conclusion: Increasing park area is likely to improve youth PA patterns, lending support for the 10-minute walk initiative.

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Ciarra A. Boyne, Tammie M. Johnson, Lindsay P. Toth, M. Ryan Richardson, and James R. Churilla

Background: Prescription medication usage has been used as a predictor of disease prevalence and overall health status. Evidence suggests an inverse relationship exists between polypharmacy, which is the use of 5 or more medications, and physical activity participation. However, there is limited evidence examining the relationship between sedentary time and polypharmacy in adults. The aim of this study was to examine the associations between sedentary time and polypharmacy in a large nationally representative sample of US adults. Methods: Study sample (N = 2879) included nonpregnant adult (≥20 y old) participants from the 2017–2018 National Health and Nutrition Examination Survey. Self-reported minutes per day of sedentary time were converted to hours per day. The dependent variable was polypharmacy (≥5 medications). Results: Analysis revealed that for every hour of sedentary time, there was 4% greater odds of polypharmacy (odds ratio, 1.04; 95% confidence interval, 1.00–1.07, P = .04) after adjusting for age, race/ethnicity, education, waist circumference, and the interaction term between race/ethnicity and education. Conclusion: Our findings suggest increased sedentary time is associated with an increased risk of polypharmacy among a large nationally representative sample of US adults.

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Youjie Zhang, Ruohong Cao, Cheng Li, Ziying Shi, Hui Sheng, and Yong Xu

Background: Parents play an important role in shaping youth’s lifestyle behaviors. This study aimed to investigate physical activity parenting practices (PAPP) for Chinese early adolescents and compare reporting discrepancies between parents and adolescent boys and girls. Methods: Fifty-five adolescent–parent dyads participated in 16 paired focus group interviews, and an additional 122 dyads completed questionnaire surveys with open-ended questions. Participants were recruited from 3 public middle schools in Suzhou, China. Qualitative data were analyzed inductively using an open-coding scheme. Frequencies of codes were compared by parent–child role and adolescent gender using chi-square tests. Results: Eighteen types of PAPP were identified and grouped into 6 categories: goals/control, structure, parental physical activity participation, communication, support, and discipline. These PAPP were viewed as promotive, preventive, or ineffective. Participants had mixed opinions on the effects of 11 PAPP and identified parental, adolescent, and environmental barriers for parents to promote youth physical activity. Compared with parents, adolescents were more likely to value the effects of setting expectation, scheduling, and coparticipation as well as dislike pressuring, restriction, and punishment. Girls were more likely to favor coparticipation and were more sensitive about negative communication than boys. Parents paid more attention to environmental barriers, whereas adolescents, especially girls, focused more on personal issues. Conclusions: Future studies need to address both positive and negative PAPP as well as perception discrepancies by child–parent role and adolescent gender to generate more evidence to promote parents as favorable socialization agents of youth physical activity.

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Jacqueline L. Mair, Elroy J. Aguiar, Emmanuel Stamatakis, and Sarah M. Edney

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Tao Chen, Sanmei Chen, Takanori Honda, Yu Nofuji, Hiro Kishimoto, and Kenji Narazaki

Background: To examine longitudinal changes in accelerometer-measured moderate to vigorous physical activity (MVPA) and associated factors of changes in MVPA among community-dwelling older Japanese men and women over 2 years of follow-up. Methods: In total, 601 participants (72.2 [5.4] y, 40.6% men) were included. MVPA was assessed at baseline (2011) and follow-up (2013) using triaxial accelerometers. Sex-stratified multiple linear regression models were used to identify associated factors of changes in MVPA. Results: On average, a significant decrease in MVPA over 2 years was observed only in women (P < .001). Higher baseline MVPA levels and older age were significantly associated with a decrease in MVPA over 2 years in both men and women. Men who were currently drinking (vs no) and had faster maximum gait speed showed statistically significant increases in MVPA. Women who had very poor/poor economic status (vs fair/good) and were socially isolated (vs no) showed statistically significant increases in MVPA over 2 years, while those who had fear of falling (vs no) and poor/fair self-rated health (vs good/very good) showed statistically significant decreases in MVPA over 2 years. Conclusions: Our findings showed different associated factors of changes in MVPA by sex, suggesting the importance of accounting for sex differences in terms of developing specific intervention strategies for promoting MVPA among older men and women.

Free access

Mary Njeri Wanjau, Holger Möller, Fiona Haigh, Andrew Milat, Rema Hayek, Peta Lucas, and J. Lennert Veerman

Objective: The objectives were (1) to establish the strength of the association between incident cases of osteoarthritis (OA) and low back pain (LBP), and physical activity (PA) and to assess the likelihood of the associations being causal; and (2) to quantify the impact of PA on the burden of OA and LBP in Australia. Methods: We conducted a systematic literature review in EMBASE and PubMed databases from January 01, 2000, to April 28, 2020. We used the Bradford Hill viewpoints to assess causality. We used a proportional multistate life table model to estimate the impact of changes in the PA levels on OA and LBP burdens for the 2019 Australian population (aged ≥ 20 y) over their remaining lifetime. Results: We found that both OA and LBP are possibly causally related to physical inactivity. Assuming causality, our model projected that if the 2025 World Health Organization global target for PA was met, the burden in 25 years’ time could be reduced by 70,000 prevalent cases of OA and over 11,000 cases of LBP. Over the lifetime of the current adult population of Australia, the gains could add up to approximately 672,814 health-adjusted life years (HALYs) for OA (ie, 27 HALYs per 1000 persons) and 114,042 HALYs for LBP (ie, 5 HALYs per 1000 persons). The HALY gains would be 1.4 times bigger if the 2030 World Health Organization global target for PA was achieved and 11 times bigger if all Australians adhered to the Australian PA guidelines. Conclusion: This study provides empirical support for the adoption of PA in strategies for the prevention of OA and back pain.

Open access

Jingzhi Yu, Kristopher Kapphahn, Hyatt Moore, Farish Haydel, Thomas Robinson, and Manisha Desai

Background: Clustering, a class of unsupervised machine learning methods, has been applied to physical activity data recorded by accelerometers to discover unique patterns of physical activity and health outcomes. The prediction strength metric provides a criterion to determine the optimal number of clusters for clustering methods. The aim of this study is to provide specific guidance for applying prediction strength to time series accelerometer data. Methods: For this purpose, we designed an extensive simulation study. We created a synthetic data set of accelerometer data using data from a childhood obesity management trial. We evaluated the role of a prespecified threshold of the prediction strength metric as a key input parameter. We compared the recommended threshold (between 0.8 and 0.9) with an approach we developed (Local Maxima). Results: The choice of threshold had a large impact on performance. When the noise level increased (greater overlap between true clusters), lower thresholds outperformed the recommended threshold, which tended to underestimate the true number of clusters. In addition, we found that sorting the data by magnitude of intensity in windows within the time series of interest prior to clustering alleviated sensitivity to threshold choice. Furthermore, for accelerometer data, we recommend that the Local Maxima approach be utilized together with a graphical evaluation of the prediction strength metric function over values of k. Finally, we strongly suggest sorting of the data prior to clustering if sorting retains meaning for the research question at hand. Conclusion: Our recommendations can help future researchers discover more robust patterns from accelerometer data.