James F Sallis1, Ester Cerin2, Terry L Conway3, Marc A Adams4, Lawrence D Frank5, Michael Pratt6, Deborah Salvo7, Jasper Schipperijn8, Graham Smith9, Kelli L Cain3, Rachel Davey10, Jacqueline Kerr3, Poh-Chin Lai11, Josef Mitáš12, Rodrigo Reis13, Olga L Sarmiento14, Grant Schofield15, Jens Troelsen8, Delfien Van Dyck16, Ilse De Bourdeaudhuij16, Neville Owen17. 1. Department of Family Medicine and Public Health, University of California, San Diego, CA, USA. Electronic address: jsallis@ucsd.edu. 2. The University of Hong Kong, Hong Kong, China; Institute for Health and Ageing, Australian Catholic University, Melbourne, VIC, Australia. 3. Department of Family Medicine and Public Health, University of California, San Diego, CA, USA. 4. School of Nutrition and Health Promotion and Global Institute of Sustainability, Arizona State University, Tempe, AZ, USA. 5. Health and Community Design Lab, Schools of Population and Public Health and Community and Regional Planning, University of British Columbia, Vancouver, Canada. 6. Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA. 7. Michael and Susan Dell Center for Healthy Living, The University of Texas Health Science Center at Houston, School of Public Health, Austin Regional Campus, Austin, TX, USA; Center for Nutrition and Health Research, National Institute of Public Health of Mexico, Cuernavaca, Mexico. 8. Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark. 9. Institute for Environment, Sustainability and Regeneration, Staffordshire University, Stoke-on-Trent, UK. 10. Centre for Research and Action in Public Health, University of Canberra, Bruce, ACT, Australia. 11. Department of Geography, The University of Hong Kong, China. 12. Institute of Active Lifestyle, Faculty of Physical Culture, Palacky University, Olomouc, Czech Republic. 13. Pontiff Catholic University of Parana, Curitiba, Brazil; Federal University of Parana, Curitiba, Brazil. 14. School of Medicine, Universidad de los Andes, Bogota, Colombia. 15. Auckland University of Technology, Auckland, New Zealand. 16. Department of Movement and Sport Sciences, Ghent University, Ghent, Belgium. 17. Baker IDI Heart and Diabetes Institute, Melbourne, VIC, Australia.
Abstract
BACKGROUND: Physical inactivity is a global pandemic responsible for over 5 million deaths annually through its effects on multiple non-communicable diseases. We aimed to document how objectively measured attributes of the urban environment are related to objectively measured physical activity, in an international sample of adults. METHODS: We based our analyses on the International Physical activity and Environment Network (IPEN) adult study, which was a coordinated, international, cross-sectional study. Participants were sampled from neighbourhoods with varied levels of walkability and socioeconomic status. The present analyses of data from the IPEN adult study included 6822 adults aged 18-66 years from 14 cities in ten countries on five continents. Indicators of walkability, public transport access, and park access were assessed in 1·0 km and 0·5 km street network buffers around each participant's residential address with geographic information systems. Mean daily minutes of moderate-to-vigorous-intensity physical activity were measured with 4-7 days of accelerometer monitoring. Associations between environmental attributes and physical activity were estimated using generalised additive mixed models with gamma variance and logarithmic link functions. RESULTS: Four of six environmental attributes were significantly, positively, and linearly related to physical activity in the single variable models: net residential density (exp[b] 1·006 [95% CI 1·003-1·009]; p=0·001), intersection density (1·069 [1·011-1·130]; p=0·019), public transport density (1·037 [1·018-1·056]; p=0·0007), and number of parks (1·146 [1·033-1·272]; p=0·010). Mixed land use and distance to nearest public transport point were not related to physical activity. The difference in physical activity between participants living in the most and least activity-friendly neighbourhoods ranged from 68 min/week to 89 min/week, which represents 45-59% of the 150 min/week recommended by guidelines. INTERPRETATION: Design of urban environments has the potential to contribute substantially to physical activity. Similarity of findings across cities suggests the promise of engaging urban planning, transportation, and parks sectors in efforts to reduce the health burden of the global physical inactivity pandemic. FUNDING: Funding for coordination of the IPEN adult study, including the present analysis, was provided by the National Cancer Institute of National Institutes of Health (CA127296) with studies in each country funded by different sources.
BACKGROUND: Physical inactivity is a global pandemic responsible for over 5 million deaths annually through its effects on multiple non-communicable diseases. We aimed to document how objectively measured attributes of the urban environment are related to objectively measured physical activity, in an international sample of adults. METHODS: We based our analyses on the International Physical activity and Environment Network (IPEN) adult study, which was a coordinated, international, cross-sectional study. Participants were sampled from neighbourhoods with varied levels of walkability and socioeconomic status. The present analyses of data from the IPEN adult study included 6822 adults aged 18-66 years from 14 cities in ten countries on five continents. Indicators of walkability, public transport access, and park access were assessed in 1·0 km and 0·5 km street network buffers around each participant's residential address with geographic information systems. Mean daily minutes of moderate-to-vigorous-intensity physical activity were measured with 4-7 days of accelerometer monitoring. Associations between environmental attributes and physical activity were estimated using generalised additive mixed models with gamma variance and logarithmic link functions. RESULTS: Four of six environmental attributes were significantly, positively, and linearly related to physical activity in the single variable models: net residential density (exp[b] 1·006 [95% CI 1·003-1·009]; p=0·001), intersection density (1·069 [1·011-1·130]; p=0·019), public transport density (1·037 [1·018-1·056]; p=0·0007), and number of parks (1·146 [1·033-1·272]; p=0·010). Mixed land use and distance to nearest public transport point were not related to physical activity. The difference in physical activity between participants living in the most and least activity-friendly neighbourhoods ranged from 68 min/week to 89 min/week, which represents 45-59% of the 150 min/week recommended by guidelines. INTERPRETATION: Design of urban environments has the potential to contribute substantially to physical activity. Similarity of findings across cities suggests the promise of engaging urban planning, transportation, and parks sectors in efforts to reduce the health burden of the global physical inactivity pandemic. FUNDING: Funding for coordination of the IPEN adult study, including the present analysis, was provided by the National Cancer Institute of National Institutes of Health (CA127296) with studies in each country funded by different sources.
Authors: Peter James; Jaime E Hart; J Aaron Hipp; Jonathan A Mitchell; Jacqueline Kerr; Philip M Hurvitz; Karen Glanz; Francine Laden Journal: Cancer Epidemiol Biomarkers Prev Date: 2017-02-14 Impact factor: 4.254
Authors: Wenfei Zhu; Yuliang Sun; Jonathan Kurka; Carrie Geremia; Jessa K Engelberg; Kelli Cain; Terry Conway; James F Sallis; Steven P Hooker; Marc A Adams Journal: Landsc Urban Plan Date: 2017-07-14 Impact factor: 6.142
Authors: Deborah Salvo; Olga L Sarmiento; Rodrigo S Reis; Adriano A F Hino; Manuel A Bolivar; Pablo D Lemoine; Priscilla B Gonçalves; Michael Pratt Journal: Prev Med Date: 2016-09-05 Impact factor: 4.018