What is ‘neighborhood walkability’? How the built environment differently correlates with walking for different purposes and with walking on weekdays and weekends |
| |
| Institution: | 1. Luxembourg Institute of Socio-Economic Research, Esch/Alzette, Luxembourg;2. Centre de Recherche de l''université de Montréal (CRCHUM), Université de Montréal, QC, Canada;3. Université de Luxembourg, Esch/Alzette, Luxembourg;4. UMR Géographie-cités (CNRS, Université Paris 1, Université Paris 7), Paris, France;5. INSERM, Sorbonne Université, Institut Pierre Louis d’épidémiologie et de Santé Publique, IPLESP UMR-S1136, F75012, Paris, France;1. University of Paris 13, Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), UMR U1153 Inserm/U1125, Centre de Recherche en Epidémiologie et Biostatistiques, Sorbonne Paris Cité, Bobigny, France;2. University of Paris 8, Saint-Denis, France;3. University of Strasbourg, Laboratoire « Image Ville Environnement » UMR 7362 CNRS, Strasbourg, France;4. University of Paris Est, Lab’Urba, Urban Institute of Paris, UPEC, Créteil, France;5. CARMEN, Institut National de la Santé et de la Recherche Médicale U1060, University of Lyon 1, Institut National de la Recherche Agronomique U1235, CRNH, Rhône-Alpes, Lyon, France;6. Service de Nutrition GH Pitié-Salpêtrière (AP-HP), Pierre and Marie Curie University, Institut Cardiométabolisme et Nutrition (ICAN), Paris, France;1. Department of Geography, McGill University, 805 Sherbrooke St. West, Montreal, Quebec, Canada H3A 2K6;2. Department of Medicine, Divisions of Internal Medicine, Clinical Epidemiology, and Endocrinology and Metabolism, Montreal, Quebec, Canada H3A 1A1;3. Department of Civil, Environmental and Construction Engineering University of Central Florida, Orlando, FL 32816, USA;4. Department of Geography, Department of Epidemiology and Biostatistics, McGill University, Montreal, Quebec, Canada H3A 2K6;1. Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Denmark;2. School of Public Health, The University of Hong Kong, Hong Kong, China;3. Centre of Physical Activity and Nutrition Research, School of Exercise and Nutrition Sciences, Deakin University, Australia;4. McCaughey VicHealth Community Wellbeing Unit, The University of Melbourne, Australia;5. Center for Wireless & Population Health Systems, Department of Family Medicine & Public Health, University of California San Diego, USA;6. Centre for Research & Action in Public Health, Health Research Institute, University Canberra, Australia;7. Department of Movement and Sports Sciences, Ghent University, Belgium;8. Institute of Active Lifestyle, Palacký University, Czech Republic;9. The Human Potential Centre, Auckland University of Technology, New Zealand;10. Centre for Design Innovation, Swinburne University of Technology, Australia;11. Michael & Susan Dell Center for Healthy Living, The University of Texas Health Science Center at Houston, School of Public Health (Austin Regional Campus), USA;12. Center for Nutrition and Health Research, National Institute of Public Health, Mexico;13. Department of Public Health School of Medicine Universidad de los Andes, Bogota Colombia;14. Pontiff Catholic University of Parana, Brazil;15. Federal University of Parana, Brazil;p. School of Nutrition and Health Promotion, Arizona State University, USA;q. School of Community and Regional Planning and the School of Population and Public Health, The University of British Columbia, Vancouver, Canada;r. Department of Family Medicine and Public Health, University of California San Diego, USA;1. Department of Family Medicine and Public Health, University of California, San Diego, 3900 Fifth Avenue, Suite 310, San Diego, CA 92103, USA;2. Department of Pediatrics, University of Washington & Children?s Hospital and Regional Medical Center, 1100 Olive Way, Suite 500, Seattle, WA 98101, USA;3. Department of Family Medicine and Public Health, University of California, San Diego, 9500 Gilman Drive ? 0811, La Jolla, CA 92093, USA;4. University of Southern Denmark, Department of Sports Science and Clinical Biomechanics, Campusvej 55, 5230 Odense, Denmark;5. School of Community and Regional Planning, University of British Columbia, Vancouver BC, ?433-6333 Memorial Road, Vancouver, BC V6T 1Z2, Canada;6. Urban Design 4 Health, 353 Rockingham St., Rochester, NY 14620, USA;7. Perelman School of Medicine and School of Nursing, 801 Blockley Hall, 423 Guardian Drive, University of Pennsylvania, Philadelphia, PA 19104, USA |
| |
| Abstract: | Residential environments are associated with people's walking behavior. Transit-related, non-transit-related, and recreational walking may be differently associated with residential environments on weekdays and weekends, but empirical evidence is scarce. We therefore examined 1) to which extent these types of walking correlated with natural and built environmental characteristics of residential neighborhoods, 2) how these correlations differ for walking on weekdays and weekends, and 3) what substitution and complementarity effects between different types of walking exist. Our sample comprised 92,298 people aged ≥18 years from the pooled Dutch National Travel Survey 2010–2014. Multivariate Tobit regression models were used to assess the associations between the natural and built environment and the three types of walking (in average minutes per day). Our models accounted for cross-correlations between the walking types. Our results showed that denser residential areas encouraged both longer transit-related and non-transit-related transport walking on weekdays and weekends, whereas lower density neighborhoods were positively associated with recreational walking on weekdays. Shorter distances to public transport were only significantly associated with transit-related transport walking on weekdays. Shorter distances to daily facilities were positively associated with non-transit-related transport on weekdays. No significant associations between built environment and recreational walking were found on weekends. Additionally, some compensation effects between different types of walking seem to be at play: during weekends, recreational walking was inversely correlated with transit-related transport walking. Residential environments seem to affect walking types in a different way, suggesting that one size fits all policies might be less effective. Intervention strategies should be tailored for each walking type separately. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
