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.
Mark S. Tremblay, Joel D. Barnes, Iryna Demchenko, Silvia A. Gonzalez, Javier Brazo-Sayavera, Jakub Kalinowski, Peter T. Katzmarzyk, Taru Manyanga, John J. Reilly, Stephen Heung Sang Wong, and Salomé Aubert
Diego Augusto Santos Silva, Salomé Aubert, Kwok Ng, Shawnda A. Morrison, Jonathan Y. Cagas, Riki Tesler, Dawn Tladi, Taru Manyanga, Silvia A. González, Eun-Young Lee, and Mark S. Tremblay
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.
Eun-Young Lee, Patrick Abi Nader, Salomé Aubert, Silvia A. González, Peter T. Katzmarzyk, Asaduzzaman Khan, Wendy Y. Huang, Taru Manyanga, Shawnda Morrison, Diego Augusto Santos Silva, and Mark S. Tremblay
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.
Salomé Aubert, Joel D. Barnes, Iryna Demchenko, Myranda Hawthorne, Chalchisa Abdeta, Patrick Abi Nader, José Carmelo Adsuar Sala, Nicolas Aguilar-Farias, Susana Aznar, Peter Bakalár, Jasmin Bhawra, Javier Brazo-Sayavera, Mikel Bringas, Jonathan Y. Cagas, Angela Carlin, Chen-Kang Chang, Bozhi Chen, Lars Breum Christiansen, Candice Jo-Anne Christie, Gabriela Fernanda De Roia, Christine Delisle Nyström, Yolanda Demetriou, Visnja Djordjic, Arunas Emeljanovas, Liri Findling Endy, Aleš Gába, Karla I. Galaviz, Silvia A. González, Kylie D. Hesketh, Wendy Yajun Huang, Omphile Hubona, Justin Y. Jeon, Danijel Jurakić, Jaak Jürimäe, Tarun Reddy Katapally, Piyawat Katewongsa, Peter T. Katzmarzyk, Yeon-Soo Kim, Estelle Victoria Lambert, Eun-Young Lee, Sharon Levi, Pablo Lobo, Marie Löf, Tom Loney, José Francisco López-Gil, Juan López-Taylor, Evelin Mäestu, Agus Mahendra, Daga Makaza, Marla Frances T. Mallari, Taru Manyanga, Bojan Masanovic, Shawnda A. Morrison, Jorge Mota, Falk Müller-Riemenschneider, Laura Muñoz Bermejo, Marie H. Murphy, Rowena Naidoo, Phuong Nguyen, Susan Paudel, Željko Pedišić, Jorge Pérez-Gómez, John J. Reilly, Anne Kerstin Reimers, Amie B. Richards, Diego Augusto Santos Silva, Pairoj Saonuam, Olga L. Sarmiento, Vedrana Sember, Mohd Razif Shahril, Melody Smith, Martyn Standage, Gareth Stratton, Narayan Subedi, Tuija H. Tammelin, Chiaki Tanaka, Riki Tesler, David Thivel, Dawn Mahube Tladi, Lenka Tlučáková, Leigh M. Vanderloo, Alun Williams, Stephen Heung Sang Wong, Ching-Lin Wu, Paweł Zembura, and Mark S. Tremblay
Background: The Global Matrix 4.0 on physical activity (PA) for children and adolescents was developed to achieve a comprehensive understanding of the global variation in children’s and adolescents’ (5–17 y) PA, related measures, and key sources of influence. The objectives of this article were (1) to summarize the findings from the Global Matrix 4.0 Report Cards, (2) to compare indicators across countries, and (3) to explore trends related to the Human Development Index and geo-cultural regions. Methods: A total of 57 Report Card teams followed a harmonized process to grade the 10 common PA indicators. An online survey was conducted to collect Report Card Leaders’ top 3 priorities for each PA indicator and their opinions on how the COVID-19 pandemic impacted child and adolescent PA indicators in their country. Results: Overall Physical Activity was the indicator with the lowest global average grade (D), while School and Community and Environment were the indicators with the highest global average grade (C+). An overview of the global situation in terms of surveillance and prevalence is provided for all 10 common PA indicators, followed by priorities and examples to support the development of strategies and policies internationally. Conclusions: The Global Matrix 4.0 represents the largest compilation of children’s and adolescents’ PA indicators to date. While variation in data sources informing the grades across countries was observed, this initiative highlighted low PA levels in children and adolescents globally. Measures to contain the COVID-19 pandemic, local/international conflicts, climate change, and economic change threaten to worsen this situation.
Cindy Sit, Salomé Aubert, Catherine Carty, Diego Augusto Santos Silva, José Francisco López-Gil, Piritta Asunta, Yves Palad, Roselle Guisihan, Jeongmin Lee, Kelly P. Arbour Nicitopoulos, Leigh M. Vanderloo, Heidi Stanish, Justin Haegele, Piotr K. Urbański, Jurate Pozeriene, Yeshayahu Hutzler, and Kwok Ng
Background: Physical inactivity among children and adolescents with disabilities (CAWD) is a global public health issue. Policy efforts to promote physical activity (PA) among CAWD have increased. This study summarizes the international policy trend for promoting PA among CAWD, with behavioral and policy insights specific to CAWD from country/regional indicators from the Active Healthy Kids Global Alliance Matrix on Physical Activity for Children and Adolescents to determine policy translation into practice. Methods: International and national PA policy documents on CAWD were assessed. Data from the Global Matrix Para Report Cards on the behavioral and government indicators from 14 countries or regions (grouped by human development index) were reviewed and compared. Results: Policy instruments began promoting PA for CAWD in 1989 via the Convention on the Rights of the Child. International policy has been advocating PA specifically for CAWD recently. In 2020, the World Health Organization published specific PA guidelines for CAWD. Data from the 14 Para Report Car found 14 grades on the average behavioral indicator and 12 on the government indicator. A gap between the average behavioral indicator (D−) and the government indicator (C+) was found in the Para Report Card data. Conclusions: Although international policies are consistent in their attention to the needs of CAWD, national/regional policies vary. Coverage ranges from nonexistent to embedded in broader inclusion concepts. A gap in policies to promote PA of CAWD is prevalent and is more prominent in countries or regions with a lower human development index ranking.
John J. Reilly, Joel Barnes, Silvia Gonzalez, Wendy Y. Huang, Taru Manyanga, Chiaki Tanaka, and Mark S. Tremblay
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.
Therese Lockenwitz Petersen, Jan C. Brønd, Eva Benfeldt, and Randi Jepsen
Background: Tape-mounted Axivity AX3 accelerometers are increasingly being used to monitor physical activity of individuals, but studies on the integrity and performance of diffe1rent attachment protocols are missing. Purpose: The purpose of this paper was to evaluate four attachment protocols with respect to skin reactions, adhesion, and wear time in children and adults using tape-mounted Axivity AX3 accelerometers and to evaluate the associated ease of handling. Methods: We used data from the Danish household-based population study, the Lolland-Falster Health Study. Participants were instructed to wear accelerometers for seven consecutive days and to complete a questionnaire on skin reactions and issues relating to adhesion. A one-way analysis of variance was used to examine differences in skin reactions and adhesion between the protocols. A Tukey post hoc test compared group means. Ease of handling was assessed throughout the data collection. Results: In total, 5,389 individuals were included (1,289 children and 4,100 adults). For both children and adults, skin reactions were most frequent in Protocols 1 and 2. Adhesion problems were most frequent in Protocol 3. Wear time was longest in Protocol 4. Skin reactions and adhesion problems were more frequent in children compared to adults. Adults achieved longest wear time. Discussion: Covering the skin completely with adhesive tape seemed to cause skin reactions. Too short pieces of fixation tape caused accelerometers to fall off. Protocols necessitating removal of remains of glue on the accelerometers required a lot of work. Conclusion: The last of the four protocols was superior in respect to skin reactions, adhesion, wear time, and ease of handling.
Mia S. Tackney, Daniel Stahl, Elizabeth Williamson, and James Carpenter
In studies that compare physical activity between groups of individuals, it is common for physical activity to be quantified by step count, which is measured by accelerometers or other wearable devices. Missing step count data often arise in these settings and can lead to bias or imprecision in the estimated effect if handled inappropriately. Replacing each missing value in accelerometer data with a single value using the Expectation–Maximization (EM) algorithm has been advocated in the literature, but it can lead to underestimation of variances and could seriously compromise study conclusions. We compare the performance in terms of bias and variance of two missing data methods, the EM algorithm and Multiple Imputation (MI), through a simulation study where data are generated from a parametric model to reflect characteristics of a trial on physical activity. We also conduct a reanalysis of the 2019 MOVE-IT trial. The EM algorithm leads to an underestimate of the variance of effects of interest, in both the simulation study and the reanalysis of the MOVE-IT trial. MI should be the preferred approach to handling missing data in accelerometer, which provides valid point and variance estimates.
Linda Yin-king Lee, Rebecca Cho-kwan Pang, and Mimi Mei-ha Tiu
The aim of this study was to estimate older adults’ physical activity level in all types and categories of physical activities and calculate their total physical activity level. This cross-sectional descriptive study estimated the physical activity level of older adults on a quota sample of 500 physically independent older adults living in a densely populated city (in this case, Hong Kong). It used the Physical Activity Questionnaire (Hong Kong version) to assess participants’ physical activity level. Based on the frequency, duration, and intensity of each type of physical activity being performed by the participants, their physical activity level in terms of energy expenditure (in kilocalories per day) for all types and categories of physical activities and the total physical activity level were calculated. Independent t test or analysis of variance, whatever appropriate, was used to examine the difference in the total physical activity level between participants with different individual characteristics. Linear regression analysis was conducted to determine the contribution of individual characteristics to the total physical activity level (p < .05). Results indicated that the participants mostly engaged in leisurely sitting, watching television, listening to radio, and leisurely walking. They spent the greatest amount of energy on the category of “leisure activity” (710.77 kcal/day). Their total physical activity level was 1,727.09 kcal/day, which was much less than previously reported. Linear regression indicates that age accounted for 3.1% of the variance of the total physical activity level (p = .001) with senior older adults warranting additional support. Future research is suggested to confirm the role of specific neighborhood-level factors on the physical activity performance of older adults.