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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.

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.

The academic literature reports mixed evidence on how social media platform and message impact consumer engagement. We investigated the effects of three platforms (Facebook, Instagram, and Twitter) and three message themes (sales, informational, and relationship building) on six consumer engagement actions (comment, like, search, share, talk about, and purchase) in a lab experiment. College students responded to social media posts featuring their National Collegiate Athletic Association Division I women’s basketball team. Results for platform show that participants were more likely to comment on Facebook and Twitter (vs. Instagram) and more likely to purchase on Twitter (vs. Instagram). Results for message theme show that participants were more likely to comment, like, and share informational and relationship building posts and more likely to purchase after sales posts. Results for message theme vary by gender for search and talk about (with others). These results can help sport marketers develop social media content that drives specific engagement actions.

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.

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.

There has been a paucity of literature discussing how to address consent procedures as part of ethics, practitioner development, and best practice in applied sport psychology. Several researchers have addressed ethical challenges (e.g., out-of-session contact, overidentification, time, and space). However, none have substantially considered the sport-specific issues related to consent, which sits at the heart of best practice. The scarcity of discussing consent is limiting sport psychology’s potential to establish itself as a more recognized profession. This article highlights some contextual issues that challenge the idea and efficacy of informed consent. It proposes adapting consent procedures in the collaboration between sport psychology practitioners and clients to better address the current contextual challenges in applied sport psychology. In doing so, the current paper introduces Empowered Consent, which is specifically designed to empower athletes and address challenges related to choosing interventions, contractual obligations, visibility in the environment, and staff trying to gain insights into confidential information. The author offers a model to enhance applied practice for those collaborating with athletes and other clients in sport.

Background: We aimed to estimate the prevalence of physical inactivity in all districts of Iran and the disparities between subgroups defined by various measures. Methods: Small area estimation method was employed to estimate the prevalence of physical inactivity in districts based on the remaining districts in which data on the level of physical inactivity were available. Various comparisons on the estimations were done based on socioeconomic, sex, and geographical stratifications to determine the disparities of physical inactivity among districts of Iran. Results: All districts of Iran had a higher prevalence of physical inactivity compared with the world average. The estimated prevalence of physical inactivity among all men in all districts was 46.8% (95% uncertainty interval, 45.9%–47.7%). The highest and lowest estimated disparity ratio of physical inactivity were 1.95 and 1.14 in males, and 2.25 and 1.09 in females, respectively. Females significantly had a higher prevalence of 63.5% (62.7%–64.3%). Among both sexes, the poor population and urban residents significantly had higher prevalence of physical inactivity than rich population and rural residents, respectively. Conclusions: The high prevalence of physical inactivity among Iranian adult population suggests the urgent need to adopt population-wide action plans and policies to handle this major public health problem and avert the probable burden.