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Janet E. Fulton, David M. Buchner, Susan A. Carlson, Deborah Borbely, Kenneth M. Rose, Ann E. O’Connor, Janelle P. Gunn and Ruth Petersen

Physical activity can reduce the risk of at least 20 chronic diseases and conditions and provide effective treatment for many of these conditions. Yet, physical activity levels of Americans remain low, with only small improvements over 20 years. The Centers for Disease Control and Prevention (CDC) considered what would accelerate progress and, as a result, developed Active People, Healthy NationSM, an aspirational initiative to improve physical activity in 2.5 million high school youth and 25 million adults, doubling the 10-year improvement targets of Healthy People 2020. Active People, Healthy NationSM will implement evidence-based guidance to improve physical activity through 5 action steps centered on core public health functions: (1) program delivery, (2) partnership mobilization, (3) effective communication, (4) cross-sectoral training, and (5) continuous monitoring and evaluation. To achieve wide-scale impact, Active People, Healthy NationSM will need broad engagement from a variety of sectors working together to coordinate activities and initiatives.

Open access

David P. Looney, Mark J. Buller, Andrei V. Gribok, Jayme L. Leger, Adam W. Potter, William V. Rumpler, William J. Tharion, Alexander P. Welles, Karl E. Friedl and Reed W. Hoyt

ECTemp is a heart rate (HR)-based core temperature (CT) estimation algorithm mainly used as a real-time thermal-work strain indicator in military populations. ECTemp may also be valuable for resting CT estimation, which is critical for circadian rhythm research. This investigation developed and incorporated a sigmoid equation into ECTemp to better estimate resting CT. HR and CT data were collected over two calorimeter test trials from 16 volunteers (age, 23 ± 3 yrs; height, 1.72 ± 0.07 m; body mass, 68.5 ± 8.1 kg) during periods of sleep and inactivity. Half of the test trials were combined with ECTemp’s original development dataset to train the new sigmoid model while the other was used for model validation. Models were compared by their estimation accuracy and precision. While both models produced accurate CT estimates, the sigmoid model had a smaller bias (−0.04 ± 0.26°C vs. −0.19 ± 0.29°C) and root mean square error (RMSE; 0.26°C vs. 0.35°C). ECTemp is a validated HR-based resting CT estimation algorithm. The new sigmoid equation corrects lower CT estimates while producing nearly identical estimates to the original quadratic equation at higher CT. The demonstrated accuracy of ECTemp encourages future research to explore the algorithm’s potential as a non-invasive means of tracking CT circadian rhythms.

Open access

Salomé Aubert, Joel D. Barnes, Chalchisa Abdeta, Patrick Abi Nader, Ade F. Adeniyi, Nicolas Aguilar-Farias, Dolores S. Andrade Tenesaca, Jasmin Bhawra, Javier Brazo-Sayavera, Greet Cardon, Chen-Kang Chang, Christine Delisle Nyström, Yolanda Demetriou, Catherine E. Draper, Lowri Edwards, Arunas Emeljanovas, Aleš Gába, Karla I. Galaviz, Silvia A. González, Marianella Herrera-Cuenca, Wendy Y. Huang, Izzeldin A.E. Ibrahim, Jaak Jürimäe, Katariina Kämppi, Tarun R. Katapally, Piyawat Katewongsa, Peter T. Katzmarzyk, Asaduzzaman Khan, Agata Korcz, Yeon Soo Kim, Estelle Lambert, Eun-Young Lee, Marie Löf, Tom Loney, Juan López-Taylor, Yang Liu, Daga Makaza, Taru Manyanga, Bilyana Mileva, Shawnda A. Morrison, Jorge Mota, Vida K. Nyawornota, Reginald Ocansey, John J. Reilly, Blanca Roman-Viñas, Diego Augusto Santos Silva, Pairoj Saonuam, John Scriven, Jan Seghers, Natasha Schranz, Thomas Skovgaard, Melody Smith, Martyn Standage, Gregor Starc, Gareth Stratton, Narayan Subedi, Tim Takken, Tuija Tammelin, Chiaki Tanaka, David Thivel, Dawn Tladi, Richard Tyler, Riaz Uddin, Alun Williams, Stephen H.S. Wong, Ching-Lin Wu, Paweł Zembura and Mark S. Tremblay

Background: Accumulating sufficient moderate to vigorous physical activity is recognized as a key determinant of physical, physiological, developmental, mental, cognitive, and social health among children and youth (aged 5–17 y). The Global Matrix 3.0 of Report Card grades on physical activity was developed to achieve a better understanding of the global variation in child and youth physical activity and associated supports. Methods: Work groups from 49 countries followed harmonized procedures to develop their Report Cards by grading 10 common indicators using the best available data. The participating countries were divided into 3 categories using the United Nations’ human development index (HDI) classification (low or medium, high, and very high HDI). Results: A total of 490 grades, including 369 letter grades and 121 incomplete grades, were assigned by the 49 work groups. Overall, an average grade of “C-,” “D+,” and “C-” was obtained for the low and medium HDI countries, high HDI countries, and very high HDI countries, respectively. Conclusions: The present study provides rich new evidence showing that the situation regarding the physical activity of children and youth is a concern worldwide. Strategic public investments to implement effective interventions to increase physical activity opportunities are needed.

Open access

Taru Manyanga, Joel D. Barnes, Chalchisa Abdeta, Ade F. Adeniyi, Jasmin Bhawra, Catherine E. Draper, Tarun R. Katapally, Asaduzzaman Khan, Estelle Lambert, Daga Makaza, Vida K. Nyawornota, Reginald Ocansey, Narayan Subedi, Riaz Uddin, Dawn Tladi and Mark S. Tremblay

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.

Open access

Salomé Aubert, Joel D. Barnes, Nicolas Aguilar-Farias, Greet Cardon, Chen-Kang Chang, Christine Delisle Nyström, Yolanda Demetriou, Lowri Edwards, Arunas Emeljanovas, Aleš Gába, Wendy Y. Huang, Izzeldin A.E. Ibrahim, Jaak Jürimäe, Peter T. Katzmarzyk, Agata Korcz, Yeon Soo Kim, Eun-Young Lee, Marie Löf, Tom Loney, Shawnda A. Morrison, Jorge Mota, John J. Reilly, Blanca Roman-Viñas, Natasha Schranz, John Scriven, Jan Seghers, Thomas Skovgaard, Melody Smith, Martyn Standage, Gregor Starc, Gareth Stratton, Tim Takken, Tuija Tammelin, Chiaki Tanaka, David Thivel, Richard Tyler, Alun Williams, Stephen H.S. Wong, Paweł Zembura and Mark S. Tremblay

Background: To better understand the childhood physical inactivity crisis, Report Cards on physical activity of children and youth were prepared concurrently in 30 very high Human Development Index countries. The aim of this article was to present, describe, and compare the findings from these Report Cards. Methods: The Report Cards were developed using a harmonized process for data gathering, assessing, and assigning grades to 10 common physical activity indicators. Descriptive statistics were calculated after converting letter grades to interval variables, and correlational analyses between the 10 common indicators were performed using Spearman’s rank correlation coefficients. Results: A matrix of 300 grades was obtained with substantial variations within and between countries. Low grades were observed for behavioral indicators, and higher grades were observed for sources of influence indicators, indicating a disconnect between supports and desired behaviors. Conclusion: This analysis summarizes the level and context of the physical activity of children and youth among very high Human Development Index countries, and provides additional evidence that the situation regarding physical activity in children and youth is very concerning. Unless a major shift to a more active lifestyle happens soon, a high rate of noncommunicable diseases can be anticipated when this generation of children reaches adulthood.

Open access

Silvia A. González, Joel D. Barnes, Patrick Abi Nader, Dolores Susana Andrade Tenesaca, Javier Brazo-Sayavera, Karla I. Galaviz, Marianella Herrera-Cuenca, Piyawat Katewongsa, Juan López-Taylor, Yang Liu, Bilyana Mileva, Angélica María Ochoa Avilés, Diego Augusto Santos Silva, Pairoj Saonuam and Mark S. Tremblay

Background: The Global Matrix 3.0 brings together the Report Card grades for 10 physical activity indicators for children and youth from 49 countries. This study describes and compares the Global Matrix 3.0 findings among 10 countries with high Human Development Index. Methods: Report Cards on physical activity indicators were developed by each country following a harmonized process. Countries informed their Report Cards with the best and most recent evidence available. Indicators were graded using a common grading rubric and benchmarks established by the Active Healthy Kids Global Alliance. A database of grades from the countries was compiled, and letter grades were converted to numerical equivalents. Descriptive statistics and scores for groups of indicators were calculated, and correlation analyses were conducted. Results: Grades for the 10 countries clustered around “D” ranging from “F” to “B+.” Active Transportation had the highest average grade (“C”), whereas Overall Physical Activity had the lowest average grade (“D-”). Low grades were observed for both behavioral and sources of influence indicators. Conclusions: In the context of social and economical changes of high- Human Development Index countries, urgent actions to increase physical activity among children and youth are required. Surveillance and monitoring efforts are required to fill research gaps.

Open access

Natasha Schranz, Vanessa Glennon, John Evans, Sjaan Gomersall, Louise Hardy, Kylie D. Hesketh, David Lubans, Nicola D. Ridgers, Leon Straker, Michalis Stylianou, Grant R. Tomkinson, Stewart Vella, Jenny Ziviani and Tim Olds

Open access

Asaduzzaman Khan, Mohammad Abdul Kadir, Sohel Reza Choudhury, Fatema Ashraf, Mahbubur Rahman, Kazi Rumana Ahmed, K. M. Saif-Ur-Rahman, Sonia Parvin and Riaz Uddin

Open access

Dawn M. Tladi, Malebogo Monnaatsie, Sheila Shaibu, Gaonyadiwe Sinombe, Gaonyadiwe G. Mokone, Lesego Gabaitiri, Leapetswe Malete and Hubona Omphile