Evi Dons1, David Rojas-Rueda2, Esther Anaya-Boig3, Ione Avila-Palencia2, Christian Brand4, Tom Cole-Hunter5, Audrey de Nazelle3, Ulf Eriksson6, Mailin Gaupp-Berghausen7, Regine Gerike8, Sonja Kahlmeier9, Michelle Laeremans10, Natalie Mueller2, Tim Nawrot11, Mark J Nieuwenhuijsen2, Juan Pablo Orjuela3, Francesca Racioppi12, Elisabeth Raser7, Arnout Standaert13, Luc Int Panis10, Thomas Götschi9. 1. Centre for Environmental Sciences, Hasselt University, Martelarenlaan 42, 3500 Hasselt, Belgium; Flemish Institute for Technological Research (VITO), Boeretang 200, 2400 Mol, Belgium. Electronic address: evi.dons@uhasselt.be. 2. ISGlobal, C/Dr. Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), C/Dr. Aiguader 88, 08003 Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), C/Monforte de Lemos 3-5, 28029 Madrid, Spain. 3. Centre for Environmental Policy, Imperial College London, Exhibition Road, South Kensington Campus, SW7 2AZ London, UK. 4. Transport Studies Unit, University of Oxford, South Parks Road, Oxford OX1 3QY, UK. 5. ISGlobal, C/Dr. Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), C/Dr. Aiguader 88, 08003 Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), C/Monforte de Lemos 3-5, 28029 Madrid, Spain; Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO, USA. 6. Trivector Traffic, Barnhusgatan 16, Stockholm, Sweden. 7. University of Natural Resources and Life Sciences Vienna, Institute for Transport Studies, Peter-Jordan-Straße 82, 1190 Vienna, Austria. 8. Dresden University of Technology, Chair of Integrated Transport Planning and Traffic Engineering, 01062 Dresden, Germany. 9. Physical Activity and Health Unit, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Seilergraben 49, 8001 Zurich, Switzerland. 10. Flemish Institute for Technological Research (VITO), Boeretang 200, 2400 Mol, Belgium; Transportation Research Institute (IMOB), Hasselt University, Wetenschapspark 5/6, 3590 Diepenbeek, Belgium. 11. Centre for Environmental Sciences, Hasselt University, Martelarenlaan 42, 3500 Hasselt, Belgium; Environment & Health Unit, University of Leuven, Herestraat 49, box 706, 3000 Leuven, Belgium. 12. World Health Organization Regional Office for Europe, Denmark. 13. Flemish Institute for Technological Research (VITO), Boeretang 200, 2400 Mol, Belgium.
Abstract
BACKGROUND: In the fight against rising overweight and obesity levels, and unhealthy urban environments, the renaissance of active mobility (cycling and walking as a transport mode) is encouraging. Transport mode has been shown to be associated to body mass index (BMI), yet there is limited longitudinal evidence demonstrating causality. We aimed to associate transport mode and BMI cross-sectionally, but also prospectively in the first ever European-wide longitudinal study on transport and health. METHODS: Data were from the PASTA project that recruited adults in seven European cities (Antwerp, Barcelona, London, Oerebro, Rome, Vienna, Zurich) to complete a series of questionnaires on travel behavior, physical activity levels, and BMI. To assess the association between transport mode and BMI as well as change in BMI we performed crude and adjusted linear mixed-effects modeling for cross-sectional (n = 7380) and longitudinal (n = 2316) data, respectively. RESULTS: Cross-sectionally, BMI was 0.027 kg/m2 (95%CI 0.015 to 0.040) higher per additional day of car use per month. Inversely, BMI was -0.010 kg/m2 (95%CI -0.020 to -0.0002) lower per additional day of cycling per month. Changes in BMI were smaller in the longitudinal within-person assessment, however still statistically significant. BMI decreased in occasional (less than once per week) and non-cyclists who increased cycling (-0.303 kg/m2, 95%CI -0.530 to -0.077), while frequent (at least once per week) cyclists who stopped cycling increased their BMI (0.417 kg/m2, 95%CI 0.033 to 0.802). CONCLUSIONS: Our analyses showed that people lower their BMI when starting or increasing cycling, demonstrating the health benefits of active mobility.
BACKGROUND: In the fight against rising overweight and obesity levels, and unhealthy urban environments, the renaissance of active mobility (cycling and walking as a transport mode) is encouraging. Transport mode has been shown to be associated to body mass index (BMI), yet there is limited longitudinal evidence demonstrating causality. We aimed to associate transport mode and BMI cross-sectionally, but also prospectively in the first ever European-wide longitudinal study on transport and health. METHODS: Data were from the PASTA project that recruited adults in seven European cities (Antwerp, Barcelona, London, Oerebro, Rome, Vienna, Zurich) to complete a series of questionnaires on travel behavior, physical activity levels, and BMI. To assess the association between transport mode and BMI as well as change in BMI we performed crude and adjusted linear mixed-effects modeling for cross-sectional (n = 7380) and longitudinal (n = 2316) data, respectively. RESULTS: Cross-sectionally, BMI was 0.027 kg/m2 (95%CI 0.015 to 0.040) higher per additional day of car use per month. Inversely, BMI was -0.010 kg/m2 (95%CI -0.020 to -0.0002) lower per additional day of cycling per month. Changes in BMI were smaller in the longitudinal within-person assessment, however still statistically significant. BMI decreased in occasional (less than once per week) and non-cyclists who increased cycling (-0.303 kg/m2, 95%CI -0.530 to -0.077), while frequent (at least once per week) cyclists who stopped cycling increased their BMI (0.417 kg/m2, 95%CI 0.033 to 0.802). CONCLUSIONS: Our analyses showed that people lower their BMI when starting or increasing cycling, demonstrating the health benefits of active mobility.
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