Journal of physical activity & health最新文献

Background: Finding new ways to support physical activity participation after cancer is an important challenge. This research aimed to develop a walking and running program that could support people living with and beyond cancer to participate in fun run-style events.

Methods: Mixed methods research that followed guidance for developing complex interventions was conducted in 2 phases. Phase 1 included a review of published evidence, stakeholder consultation, and co-design workshops, which were used to develop an initial program protocol. Phase 2 included iterative piloting of the program, via delivery of it prior to 3 separately sponsored fun runs, to test and refine the protocol.

Results: In Phase 1, 38 reviews, identified via systematic search, 15 stakeholders, including potential program referrers, managers or sponsors, and 8 co-design participants, including people with lived experience of cancer, and program delivery staff contributed to the initial protocol development. Protocol elements generated, included selection of location and delivery staff, tailoring of physical activity content, use of inclusive language, and strategies to support social connection. In Phase 2, 17 participants with lived experience of cancer participated in the program during iterative piloting. Protocol modifications, included expansion of the program goals beyond fun run participation, as well as the development of remote support strategies to facilitate continued engagement and further opportunities for physical activity prescription.

Conclusions: Utilizing an iterative methodological approach and being open to protocol change allowed us to address the preferences of diverse stakeholders and to optimize the practical program aspects prior to larger scale trials.

Background: Different commuting modes may contribute to overall physical activity. Additionally, the choice of commuting modes is shaped by the built environment, including transportation infrastructure which reflects the needs of the population at specific locations and times of the week. This study examines the differences in daily step counts according to commuting mode and population density, focusing on within-week variations.

Methods: We analyzed step count data collected from the smartphones of 938,568 individuals across Japan on a typical weekday and a weekend day with minimal precipitation. Personal characteristics, including commuting mode, were obtained from a questionnaire. Population density was employed as a proxy for the built environment.

Results: We found that the estimated step counts on the weekend day were generally lower than those on the weekday across all groups defined by commuting mode and population density, with the difference between the 2 days being more pronounced among public transport users than among motor vehicle users, especially in low-density areas. Despite smaller disparities among those using different commuting modes on the weekend day, the overall pattern remained consistent with the weekday, with rail and pedestrian commuters having the highest step counts and motor vehicle users the lowest.

Conclusions: These findings further support the need to address step count disparities by promoting modal shifts from motor vehicles to rail and walking. Furthermore, this study highlights the value of integrating comprehensive data sources in the ongoing assessment of population health and in guiding effective public health policies.

Background: Physical activity and leisure-time physical activity (LTPA) are crucial for maintaining overall health particularly during the COVID-19 pandemic lockdown. In this study, we aimed to identify the sociodemographic, environmental, and lifestyle factors associated with LTPA in a lower-middle-income country after the lockdown.

Method: We used secondary data from the Bolivian EH2021 National Survey with an expansion factor (N = 6,498,630) to calculate crude and adjusted Odds Ratios for performing LTPA and performing LTPA more than once a week.

Results: Performing LTPA was positively associated with being male, younger, living with fewer people, having a higher income and educational level, and performing physical activity for transportation and daily activities. Performing LTPA more than once a week was associated with sex, age, occupation, marital status, household income, and other sociodemographic and lifestyle-related variables. Environmental factors, such as neighborhood safety, usage of private paid infrastructure, green areas, and house spaces were significantly associated with LTPA performance.

Conclusions: Specific sociodemographic, lifestyle and environmental factors are associated with LTPA performance among the Bolivian population; monitoring and intervention with groups at higher risk of sedentarism based on these socioenvironmental and behavioral factors are encouraged. Our study has important implications for addressing the lack of evidence for underrepresented low- and middle-income countries and highlighting social inequalities that hinder LTPA during crisis times from an integral perspective to enhance prevention and health promotion programs based on physical activity and LTPA.

Background: Our aim was to determine adult's trajectories of meeting 150 minutes per week of physical activity (PA) and assess associations between environmental features (and changes in these) with trajectory membership.

Methods: We used data from the How Areas in Brisbane Influence HealTh and AcTivity (HABITAT) cohort study, Australia. Data on PA were assessed in 2007, 2009, 2011, 2013, and 2016 among individuals aged 45-60 years. At each survey, data on length of bike paths, area of parks, residential density, street connectivity, land use mix, and number of street lights were measured. PA trajectories were determined using group-based trajectory modeling. Group differences were analyzed based on median and interquartile range (IQR) of environmental features and associations were assessed through multinomial logistic regression.

Results: We identified 4 trajectories of meeting PA guidelines: low (14.4%), decreasing (13.7%), increasing (30.4%), and high (41.5%). Median (IQR) values of environmental features were very similar among trajectory groups (P > .05) with relatively little change between initial (2007) and final (2016) timepoints. Associations with trajectory membership were observed for bike path length among participants in the mid-tertile of the low trajectory group compared with the high trajectory (odds ratio [OR] = 0.55; 95% confidence interval [CI], 0.36-0.84); and for street connectivity in the low (OR = 0.67; 95% CI, 0.51-0.87), and increasing trajectory groups (OR = 0.76; 95% CI, 0.61-0.94).

Conclusion: In the context of this "livable city," environmental features did not thoroughly predict patterns of PA among mid-age adults. Environmental predictors of PA deserve further attention, especially in low-income and middle-income countries, as active friendly environments have important connotations for various types of PA.

Background: Physical activity research is pivotal in shaping policies and interventions that promote health. However, disparities in research contributions across authors and institutions can impact the equity and representation of evidence-based practices.

Objective: This study aimed to assess the dispersion of authors and institutions publishing research on physical activity and health within countries.

Methods: A global bibliometric analysis was conducted, including articles on physical activity and health published between 1950 and 2019. Countries with 10 or more publications were analyzed. Data on authors' names and institutions were extracted, and the Gini coefficient, a measure of inequality, was calculated using the "Descogini" command in Stata. Gini coefficients were generated for authors in 94 countries and for institutions in 98 countries.

Results: The Gini coefficient for authors ranged from 0.03 in Cuba, Bangladesh, and Lebanon (low concentration) to 0.59 in Belgium and 0.65 in Portugal (high concentration). For institutions, the lowest coefficient was 0.08 in Guatemala, and the highest was 0.84 in Belgium and Portugal. Regions such as the Americas, Europe, and the Western Pacific exhibited higher average Gini coefficients for authors and institutions. Similarly, high-income and upper middle-income countries showed greater research concentration than low-income and lower middle-income nations.

Conclusion: To promote a more equitable and impactful global research landscape, it is crucial to invest strategically in developing and multiplying high-quality research groups across regions. Supporting emerging centers of excellence will foster innovation, capacity building, and more inclusive scientific production. Future research should further explore these factors to guide effective policies and investments.

Background: Smoking is the most significant risk factor for major diseases, including cancer, respiratory diseases, and cardiovascular diseases (CVD). Extensive studies have identified physical activity (PA) and sedentary behavior (SB) as modifiable lifestyle factors that provide substantial health benefits. This study aimed to assess the effects of PA and SB on smoking-related mortality.

Methods: This study included 8542 adults from the 2014-2015 Korea National Health and Nutrition Examination Survey, with mortality follow-up data tracked through 2019. PA, SB, and smoking status were assessed using self-reported questionnaires. Cox regression was used to estimate the individual and combined effects of smoking status, PA, and SB on all-cause and CVD-related mortality. The interactions were assessed using a multiplicative scale.

Results: As of December 31, 2019, a total of 147 participants had died from all causes, including 32 deaths attributed to CVD. Both smokers (all-cause: 0.49 [0.32-0.76], CVD: 0.22 [0.06-0.76]) and nonsmokers (all-cause: 0.38 [0.21-0.68], CVD: 0.18 [0.05-0.64]) who adhered to PA guidelines exhibited significant reductions in mortality rates. Similarly, limiting daily sedentary time to <8 hours reduced mortality rates in both smokers and nonsmokers, with more pronounced effects in nonsmokers (all-cause: 0.34 [0.19-0.61], CVD: 0.12 [0.03-0.45]). Even without adhering to the sedentary guidelines, each additional hour of reduced sedentary time significantly lowered mortality rates among smokers (all-cause: P < .0001, CVD: P = .0064).

Conclusions: This study highlighted that PA and SB can attenuate the association between smoking and mortality, including all-cause and CVD-related mortality. For optimal health promotion, practicing smoking cessation, engaging in PA, and reducing SB are recommended simultaneously.

Background: Although previous studies have identified a positive relationship between physical activity (PA) participation and cognitive function in older adults, further research is needed to determine the level of PA necessary to significantly reduce the risk of Alzheimer's disease and related dementias (AD/ADRD), particularly among older adults with mild cognitive impairment.

Methods: This study used Health and Retirement Study data from 2012 to 2020 (n = 9714 Index = 5) and employed the generalized estimating equations to estimate the odds ratios (OR) of AD/ADRD across various PA levels. Covariates such as age, sex, education, and baseline cognitive function in 2012 were included in the regression model.

Results: Individuals with a PA level of 2.80 experienced a 4.6% reduction in the odds of developing AD/ADRD (B = -0.046, OR = 0.954, 95% CI, 0.946-0.964). Similar significant effects were observed at PA levels of 2.60, 2.40, and 2.20, with ORs of 0.962, 0.967, and 0.970, respectively, all within 95% CI. These findings indicate that maintaining a PA level between 2.20 and 2.80 is significantly associated with a reduced risk of AD/ADRD. Lower PA levels such as 2.00 (OR = 0.974, P = .09) and 1.80 (OR = 0.983, P = .06) showed nonsignificant trends toward risk reduction.

Conclusion: Engaging in PA (eg, walking, exercise) more than twice per week significantly reduces the risk of AD/ADRD, whereas less frequent activity showed no statistically significant benefit.

Background: Maintaining exercise behavior is important for health. Although exercising with others may be an effective strategy for maintaining this, the association between exercising with others and the maintenance of it as well as the mediators of this association remain unconfirmed. The present study examined whether exercising with others was longitudinally and positively associated with 1-year maintenance of exercise behavior, and this association was mediated by exercise motivation among workers.

Methods: This study used data of an online survey-based longitudinal cohort study on 2819 Japanese workers who performed exercise at baseline and responded to a 1-year follow-up survey. This study analyzed 1-year follow-up data of participation in exercise; baseline and 1-year follow-up data of weekly exercise time; and baseline data of exercising with others, exercise motivation, and demographic factors. Participation in exercise (model 1) and weekly exercise time (model 2) after 1 year were indices of 1-year maintenance of exercise behavior.

Results: Adjusting for demographic factors, path analyses showed that exercising with others at baseline indirectly and significantly predicted 1-year maintenance of exercise behavior, mediated by exercise motivation and weekly exercise time at baseline (standardized total associations, 0.07 in model 1 and 0.18 in model 2; standardized indirect associations, 0.06 in model 1 and 0.18 in model 2).

Conclusions: This study found that exercising with others was indirectly and positively associated with 1-year maintenance of exercise behavior, mediated by exercise motivation. Encouraging participation with others may be effective in supporting motivation and maintaining exercise behavior.