Search Results

Background: We used nationally representative data to explore associations among location of residence (rural/urban) and perceived barriers to physical activity (PA) in Canadian youth. Methods: We analyzed the 2017 Canadian Community Health Survey, Barriers to Physical Activity Rapid Response data for 12- to 17-year-old youth. Nine items from the survey assessing perceived barriers to PA were combined into 3 barrier domains: resources, motivational, and socioenvironmental. The likelihood of reporting barriers to PA based on rural–urban location was examined using survey-weighted binary logistic regression following a model fitting approach. Sociodemographic factors were modeled as covariates and tested in interaction with location. For each barrier domain, we derived the best-fitting model with fewest terms. Results: There were no location-specific effects related to reporting any barrier or motivation-related PA barriers. We found a sex by location interaction predicting the likelihood of reporting resource-related barriers. Rural boys were less likely to report resource-related barriers compared with urban boys (odds ratio [OR] = 0.42 [0.20, 0.88]). Rural girls were more likely to report resource-related barriers compared with boys (OR = 3.72 [1.66, 8.30]). Regarding socioenvironmental barriers, we observed a significant body mass index by location interaction demonstrating that rural youth with body mass index outside the “normal range” showed a higher likelihood of reporting socioenvironmental barriers compared with urban youth (OR = 2.38 [1.32, 4.30]). For urban youth, body mass index was unrelated to reporting socioenvironmental barriers (OR = 1.07 [0.67, 1.71]). Conclusion: PA barriers are not universal among Canadian youth. Our analyses highlight the importance of testing interactions in similar studies as well as considering key sociodemographic characteristics when designing interventions.

Background: We examined recent global secular trends in 5 indicators of child and adolescent physical activity and sedentary behavior (Overall Physical Activity, Organized Sport and Physical Activity, Active Play, Active Transportation, and Sedentary Behavior) and 4 influences on these (Family and Peers, School, Community and Environment, and Government). Methods: Active Healthy Kids Global Alliance letter grades (A+ to F) were assigned numbers from 15 to 2, with 0 assigned for missing/incomplete grades. Trends from Active Healthy Kids Global Alliance Global Matrices 1.0 (2014) to 4.0 (2022) were analyzed using linear mixed-effects models with level of economic development and gender inequity considered as potential moderators. Results: Report card grades were generally relatively stable. Trends generally did not differ significantly by level of economic development (except for Active Transportation and Active Play), but gender inequality did significantly moderate trends for most of the indicators, with higher gender inequality associated with more adverse changes in grades. The number of “incomplete” grades decreased over time, but this did not reach statistical significance. Conclusions: While trends varied within and between countries, physical activity and sedentary behaviors, and the influences on these behaviors globally, were relatively stable over the past decade or so, albeit at undesirable levels.

Background: This brief report provides an overview of the Active Healthy Kids Global Alliance (AHKGA); an introduction to the Global Matrix 4.0; an explanation of the value and opportunities that the AHKGA efforts and assets provide to the physical activity research, policy, practice, and advocacy community; an outline of the series of papers related to the Global Matrix 4.0 in this issue of the Journal of Physical Activity and Health; and an invitation for future involvement. Methods: The AHKGA was formed to help power the global movement to get kids moving. In 2019–2021, we recruited countries to participate in the Global Matrix 4.0, a worldwide initiative to assess, compare, and contrast the physical activity of children and adolescents. Results: A total of 57 countries/jurisdictions (hereafter referred to as countries for simplicity) were recruited. The current activities of the AHKGA are summarized. The overall findings of the Global Matrix 4.0 are presented in a series of papers in this issue of the Journal of Physical Activity and Health. Conclusions: The Global Matrix 4.0 and other assets of the AHKGA are publicly available, and physical activity researchers, practitioners, policy makers, and advocates are encouraged to exploit these resources to further their efforts.

Background: The aim of this study was to explore the associations between the 10 key indicators of the Global Matrix 4.0 project and human development index (HDI) at a national level according to sex, age, area of residence, and ability levels. Methods: Information from the 57 countries/localities included in the Global Matrix 4.0 project was compiled and presented according to the HDI of each country/locality for each of the 10 key indicators. Grades were assigned based on the benchmarks of the Global Matrix 4.0 project ranged between “A+” (best performance) and “F” (worst performance). Results: The population subgroups of females, children, rural residents, with/without disabilities from countries/localities with higher HDI performed better in the organized sport and physical activity indicator than their peers from countries/localities with lower HDI. Children and adolescents living in rural areas of countries/localities with higher HDI showed better performance for active play, and children and adolescents living in urban areas of countries/localities with lower HDI showed better performance for the active transportation. Countries/localities with higher HDI showed better grades for sources of influence than the countries/localities with lower HDI. Conclusions: Physical activity patterns in some population subgroups of children and adolescents differed according to the development level of countries/localities.

Background: Macrolevel factors such as economic and climate factors can be associated with physical activity indicators. This study explored patterns and relationships between economic freedom, climate culpability, and Report Card grades on physical activity-related indicators among 57 countries/jurisdictions participating in the Global Matrix 4.0. Methods: Participating countries/jurisdictions provided Report Card grades on 10 common indicators. Information on economic freedom and climatic factors were gathered from public data sources. Correlations between the key variables were provided by income groups (ie, low- and middle-income countries/jurisdictions and high-income countries/jurisdictions [HIC]). Results: HIC were more economically neoliberal and more responsible for climate change than low- and middle-income countries. Annual temperature and precipitation were negatively correlated with behavioral/individual indicators in low- and middle-income countries but not in HIC. In HIC, correlations between climate culpability and behavioral/individual and economic indicators were more apparent. Overall, poorer grades were observed in highly culpable countries/jurisdictions in the highly free group, while in less/moderately free groups, less culpable countries/jurisdictions showed poorer grades than their counterparts in their respective group by economic freedom. Conclusions: Global-level physical activity promotion strategies should closely evaluate different areas that need interventions tailored by income groups, with careful considerations for inequities in the global political economy and climate change.

Background: This study compares results of physical activity report cards from 9 countries with low to medium human development indices, participating in the Global Matrix 3.0 initiative. Methods: Country-specific report cards were informed by relevant data and government policy documents, reporting on 10 core indicators of physical activity for children and youth. Data were synthesized by report card working groups following a harmonized process. Grade assignments for each indicator utilized a standard grading rubric. Indicators were grouped into one of 2 categories: daily behaviors and settings and sources of influence. Descriptive statistics (average grades) were computed after letter grades were converted into interval variables. Spearman’s rank correlation coefficients were calculated for all correlation analyses. Results: Mean grades for daily behaviors were higher (C) than those for settings and sources of influence (D+). Twenty-nine out of the possible 90 grades were assigned an incomplete. There were moderate to strong positive and negative relationships between different global indices and overall physical activity, organized sport and physical activity, active play, family, community and environment, and government. Conclusions: Findings demonstrate an urgent need for high-quality data at the country level in order to better characterize the physical activity levels of children and youth in countries with low to medium human development indices.