The health risks and benefits of cycling in urban environments compared with car use: health impact assessment study

From Testiwiki
Revision as of 15:44, 26 April 2012 by EssiV (talk | contribs) (Introduction)
Jump to: navigation, search


This page (including the files available for download at the bottom of this page) contains a draft version of a manuscript, whose final version is published and is available in the [1]. If referring to this text in scientific or other official papers, please refer to the published final version as: David Rojas-Rueda, Audrey de Nazelle, Marko Tainio, Mark J Nieuwenhuijsen: The health risks and benefits of cycling in urban environments compared with car use: health impact assessment study. BMJ 2011;343:d4521 {doi|10.1136/bmj.d4521}.

Title

Editing The health risks and benefits of cycling in urban environments compared with car use: health impact assessment study

Authors and contact information

David Rojas-Rueda predoctoral researcher, correspondence author
(Rojas-Rueda drojas@creal.cat)
(Center for Research in Environmental Epidemiology, Barcelona, Spain)
(Municipal Institute of Medical Research (IMIM-Hospital del Mar) Barcelona, Spain)
(CIBER Epidemiology and Public Health (CIBERESP) Madrid, Spain)
Audrey de Nazelle researcher
(Center for Research in Environmental Epidemiology, Barcelona, Spain)
(Municipal Institute of Medical Research (IMIM-Hospital del Mar) Barcelona, Spain)
(CIBER Epidemiology and Public Health (CIBERESP) Madrid, Spain)
Marko Tainio researcher
(Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland
(Department of Environmental Health, National Institute for Health and Welfare, Kuopio, Finland)
Mark J Nieuwenhuijsen research professor
(Center for Research in Environmental Epidemiology, Barcelona, Spain)
(Municipal Institute of Medical Research (IMIM-Hospital del Mar) Barcelona, Spain)
(CIBER Epidemiology and Public Health (CIBERESP) Madrid, Spain)

Abstract

Objective To estimate the risks and benefits to health of travel by bicycle, using a bicycle sharing scheme, compared with travel by car in an urban environment.

Design Health impact assessment study.

Setting Public bicycle sharing initiative, Bicing, in Barcelona, Spain. Participants 181 982 Bicing subscribers.

Main outcomes measures The primary outcome measure was all cause mortality for the three domains of physical activity, air pollution (exposure to particulate matter <2.5 μm), and road traffic incidents. The secondary outcome was change in levels of carbon dioxide emissions.

Results Compared with car users the estimated annual change in mortality of the Barcelona residents using Bicing (n=181 982) was 0.03 deaths from road traffic incidents and 0.13 deaths from air pollution. As a result of physical activity, 12.46 deaths were avoided (benefit:risk ratio 77). The annual number of deaths avoided was 12.28. As a result of journeys by Bicing, annual carbon dioxide emissions were reduced by an estimated 9 062 344 kg.

Conclusions Public bicycle sharing initiatives such as Bicing in Barcelona have greater benefits than risks to health and reduce carbon dioxide emissions.

Introduction

Bicycle sharing schemes have become increasingly popular in countries throughout Europe, Asia, and America to encourage cycling as an alternative means of transport in urban areas. Large low cost rental systems (between 1000 and 50 000 bicycles) aimed at encouraging cycling for short urban trips and multimodality (cycling along with another mode of transit) for longer trips have been implemented by cities such as Lyon (2005), Stockholm (2006), Barcelona (2007), Seville (2007), Paris (2007), Toulouse (2007), Hangzhou (2008), Milan (2008), Brussels (2009), Montreal (2009), Mexico City (2010), London (2010), and Guangzhou (2010). In the United States, such large scale initiatives are being considered for Los Angeles and New York. The general impetus for these policies is more often the reduction of traffic congestion than the promotion of health.

Motivated by the growing challenges of global obesity and climate change, international organisations have been calling for multisectoral and multidisciplinary approaches to increase physical activity and reduce reliance on cars.2-5 In 2005 the European Union formulated an important area of action “addressing the obesogenic environment to stimulate physical activity” (Commission of the European Communities 2005). The Transport Health and Environment, Pan-European Program (THE PEP) provides guidance to policymakers and local professionals on how to encourage cycling and walking along with an instrument, the health economic assessment tool, to estimate the health benefits and cost effectiveness of cycling.6 Similarly, in the United States the Centers for Disease Control and Prevention has developed guidelines for the prevention of obesity.3 Integrating the promotion of walking and cycling into daily life (for example, as part of commuting) is a promising way to increase physical activity across a population. Cycling does, however, have some potential risks such as increased road traffic incidents and exposure to air pollution.

We estimated the effect on health of Bicing, the public bicycle sharing initiative in Barcelona, Spain (see web extra appendix). As direct outcomes on health are hard to measure, we estimated the effects by studying all cause mortality using a newly developed health impact model to integrate recently developed tools, existing data from scientific studies, and local data. We focused on the three domains of exposure to air pollution, physical activity, and road traffic incidents. We also estimated the reduction in carbon dioxide emissions.

Methods

Bicing, the public bicycle sharing initiative in Barcelona, Spain, was introduced in March 2007 to improve the use of different types of transport, promote sustainable transport, create a new individual public transport system, promote the bicycle as a common means of transport, improve air quality, and reduce noise pollution. By August 2009, 182 062 people had subscribed to Bicing (11% of the population in Barcelona municipality), with 68% of trips being used for commuting to work or school and 37% combined with another mode of travel. The mean distance travelled by Bicing on a working day was 3.29 km (mean duration 14.1 minutes) and at weekends was 4.15 km (17.8 minutes).7 Framework We used a health impact assessment framework to estimate the potential effects on health of cycling compared with travel by car (see web extra appendix figure 1). Exposure-response functions were derived from existing studies and calibrated for current exposure and health conditions in Barcelona. We chose to model the effects of all cause mortality due to physical activity, road traffic incidents, and exposure to air pollution based on discussions held among experts during a workshop in Barcelona in 2009 that suggested these domains would have the greatest impact and best available data.8 Recent publications provided further guidance.6 9 10 We focused on residents of Barcelona who started cycling regularly using Bicing after its implementation. Therefore we assessed the additional benefits from physical activity and additional risks due to incremental inhalation of air pollution and increased exposure of new cyclists to road traffic incidents compared with previous exposures as car users. We did not consider the benefits of decreased car use to the general population of Barcelona because of Bicing. We also estimated savings in carbon dioxide emissions. Table 1 summarises the main input data used in the model. The web extra appendix provides a detailed description of assumptions and calculation steps used to derive the model inputs from available data outlined in this section. Cycling and car use We obtained statistics on travel by car, cycling, and Bicing use in Barcelona from a combination of data provided by the Bicing management company, Barcelona de Serveis Municipals (B:SM) and from travel surveys carried out by the city and by the metropolitan area transportation departments.11 12 Based on these sources of data, we estimated the mean number of trips daily and duration of trip by travel mode in the city. We calculated that 28 251 Bicing members used the scheme regularly. We assumed that 90% of these users (n=25 426) were new cyclists who had shifted travel mode from cars and that their current Bicing trips replaced the same trips previously made by a car—the same number of trips and same distance for each trip. We also carried out sensitivity analyses using different scenarios to assess the impact of shifting from other modes of transport, with 10% changing from cars, 60% from public transport, and 30% from walking, based on figures in a UN report (see web extra table 9).1 Air pollution For the domain of air pollution we considered exposure to particulate matter less than 2.5 μm, which has shown strong associations with all cause mortality.13-15 We assessed the levels of exposure and inhaled dose in car users compared with Bicing users (see web extra appendix figure 4). Concentrations for each mode were obtained from a study carried out in Barcelona.16 We assumed that the relative concentrations between modes were representative of annual average relative concentrations. We estimated yearly inhaled doses of these contaminants, accounting for mode specific inhalation rates, exposures, and duration of trip, as in a previous study.17 To simplify, we assumed non-travel times to be spent resting and sleeping while exposed to background annual concentrations of particulate matter less than 2.5 μm. To estimate the relative risk of mortality associated with incremental intake of pollutant for cyclists compared with car users, similar to another study,9 we applied the ratio between the estimated inhaled dose for cyclists and for car users to exposure-response functions reported in the literature. We used the update by previous researchers,18 of the most commonly used relative risk functions in risk assessment of exposure to particulate matter less than 2.5 μm.19 As a sensitivity analysis, we also carried out this calculation for mortality risks associated with increments of black smoke inhalation (a mix of particles and carbon fume resulting from the incomplete combustion of fossil fuels) and tested the hypothesis that traffic related air pollution may be more toxic than the ambient concentrations found in the cities from which the relative risk functions were derived.13 14 Traffic mortality For road traffic incidents we used data from the Barcelona public health agency.20 We derived mortality from incidents per billion kilometres travelled by bicycle and by car from estimates of total yearly distance travelled by bicycle and car linked to traffic mortality data by mode in the past nine years. We then calculated relative risks of all cause mortality in a road traffic crash for cyclists compared with car drivers, assuming the same distance travelled for each mode, as in a previous study.9 (See web extra figure 5.) Physical activity To quantify the benefits of physical activity, we followed the approach presented in the health economic assessment tool for cycling project.6 This instrument uses relative risks of all cause mortality for commuters who use bicycles compared with other modes of transport derived from a study in Copenhagen of the largest health cohort that specifically considered health effects of commuting by bicycle.21 As in the health economic assessment tool for cycling, we adjusted the relative risk function for daily average distances cycled in Barcelona compared with Copenhagen (see web extra figure 6). Mortality rates Using the relevant relative risk functions from our three domains derived for our study conditions in Barcelona, we calculated the change in mortality (increment or decrement) associated with travel by cycling using the Bicing initiative. To obtain the population attributable number of deaths as in other classic risk assessment frameworks, we applied the relative risk to the number of deaths in our population of interest.22 23 To quantify the number of deaths expected in the Bicing population assumed to have started cycling when the initiative was implemented (90% of users in our scenario), we used all cause mortality rates