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

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

Severity of injuries in different modes of transport, expressed with disability-adjusted life years (DALYs).

BACKGROUND: Health impact assessment (HIA) studies are increasingly predicting the health effects of mode shifts in traffic. The challenge for such studies is to combine the health effects, caused by injuries, with the disease driven health effects, and to express the change in the health with a common health indicator. Disability-adjusted life year (DALY) combines years lived disabled or injured (YLD) and years of life lost (YLL) providing practical indicator to combine injuries with diseases. In this study, we estimate the average YLDs for one person injured in a transport crash to allow easy to use methods to predict health effects of transport injuries. METHODS: We calculated YLDs and YLLs for transport fatalities and injuries based on the data from the Swedish Traffic Accident Data Acquisition (STRADA). In STRADA, all the fatalities and most of the injuries in Sweden for 2007-2011 were recorded. The type of injury was recorded with the Abbreviated Injury Scale (AIS) codes. In this study these AIS codes were aggregated to injury types, and YLDs were calculated for each victim by multiplying the type of injury with the disability weight and the average duration of that injury. YLLs were calculated by multiplying the age of the victim with life expectancy of that age and gender. YLDs and YLLs were estimated separately for different gender, mode of transport and location of the crash. RESULTS: The average YLDs for injured person was 14.7 for lifelong injuries and 0.012 for temporal injuries. The average YLDs per injured person for lifelong injuries for pedestrians, cyclists and car occupants were 9.4, 12.8 and 18.4, YLDs, respectively. Lifelong injuries sustained in rural areas were on average 31% more serious than injuries in urban areas. CONCLUSIONS: The results show that shifting modes of transport will not only change the likelihood of injuries but also the severity of injuries sustained, if injured. The results of this study can be used to predict DALY changes in HIA studies that take into account mode shifts between different transport modes, and in other studies predicting the health effects of traffic injuries.We would like to thank Jan Ifver from the Swedish Transport agency for providing us the STRADA data and Tomasz Szreniawski from the Systems Research Institute, Poland, for helping with the data organizing. The work is part of the European-wide project Transportation Air pollution and Physical ActivitieS: an integrated health risk assessment progamme of climate change and urban policies (TAPAS)(http://www.tapas-program.org/), which has partners in Barcelona, Basel, Copenhagen, Paris, Prague and Warsaw. TAPAS is a four year project (partly) funded by the Coca-Cola Foundation, AGAUR, and CREAL. The funders have no role in the planning of study design; in the collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the article for publication. All authors are independent from the funders. The work was undertaken under the auspices of the Centre for Diet and Activity Research (CEDAR), a UKCRC Public Health Research Centre of Excellence which is funded by the British Heart Foundation, Cancer Research UK, Economic and Social Research Council, Medical Research Council, the National Institute for Health Research, and the Wellcome Trust. MT’s work has also been funded by the Ministry of Science and Higher Education through the Iuventus Plus project number IP2011 055871.This is the final published version, which is also available from BMC Public Health at http://www.biomedcentral.com/1471-2458/14/765

Can air pollution negate the health benefits of cycling and walking?

Active travel (cycling, walking) is beneficial for the health due to increased physical activity (PA). However, active travel may increase the intake of air pollution, leading to negative health consequences. We examined the risk-benefit balance between active travel related PA and exposure to air pollution across a range of air pollution and PA scenarios. The health effects of active travel and air pollution were estimated through changes in all-cause mortality for different levels of active travel and air pollution. Air pollution exposure was estimated through changes in background concentrations of fine particulate matter (PM2.5), ranging from 5 to 200μg/m3. For active travel exposure, we estimated cycling and walking from 0 up to 16h per day, respectively. These refer to long-term average levels of active travel and PM2.5 exposure. For the global average urban background PM2.5 concentration (22μg/m3) benefits of PA by far outweigh risks from air pollution even under the most extreme levels of active travel. In areas with PM2.5 concentrations of 100μg/m3, harms would exceed benefits after 1h 30min of cycling per day or more than 10h of walking per day. If the counterfactual was driving, rather than staying at home, the benefits of PA would exceed harms from air pollution up to 3h 30min of cycling per day. The results were sensitive to dose-response function (DRF) assumptions for PM2.5 and PA. PA benefits of active travel outweighed the harm caused by air pollution in all but the most extreme air pollution concentrations.MT and JW: The work was undertaken by the Centre for Diet and Activity Research (CEDAR), a UKCRC Public Health Research Centre of Excellence. Funding from the British Heart Foundation, Cancer Research UK, Economic and Social Research Council, Medical Research Council, the National Institute for Health Research, and the Wellcome Trust, under the auspices of the UK Clinical Research Collaboration, is gratefully acknowledged. AJN, DRR, MJN, SK and TG: The work was supported by the project Physical Activity through Sustainable Transportation Approaches (PASTA) funded by the European Union's Seventh Framework Program under EC‐GA No. 602624-2 (FP7-HEALTH-2013-INNOVATION-1). The sponsors had no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the article for publication. JW is supported by MRC Population Health Scientist fellowship. THS is supported by the Brazilian Science without Borders Scheme (Process number: 200358/2014-6) and the Sao Paulo Research Foundation (Process number: 2012/08565-4).This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.ypmed.2016.02.00

Cycling behaviour in 17 countries across 6 continents : levels of cycling, who cycles, for what purpose, and how far?

International comparisons of cycling behaviour have typically been limited to high-income countries and often limited to the prevalence of cycling, with lack of discussions on demographic and trip characteristics. We used a combination of city, regional, and national travel surveys from 17 countries across the six continents, ranging from years 2009 through 2019. We present a descriptive analysis of cycling behaviour including level of cycling, trip purpose and distance, and user demographics, at the city-level for 35 major cities (>1 million population) and in urbanised areas nationwide for 11 countries. The Netherlands, Japan and Germany are among the highest cycling countries and their cities among the highest cycling cities. In cities and countries with high cycling levels, cycling rates tend to be more equal between work and non-work trips, whereas in geographies with low cycling levels, cycling to work is higher than cycling for other trips. In terms of cycling distance, patterns in high- and low-cycling geographies are more similar. We found a strong positive association between the level of cycling and women’s representation among cyclists. In almost all geographies with cycling mode share greater than 7% women made as many cycle trips as men, and sometimes even greater. The share of cycling trips by women is much lower in geographies with cycling mode shares less than 7%. Among the geographies with higher levels of cycling, children (60 years) remain underrepresented in all geographies but have relatively better representation where levels of cycling are high. In low-cycling settings, females are underrepresented across all the age groups, and more so when older than 16 years. With increasing level of cycling, representation of females improves across all the age groups, and most significantly among children and older adults. Clustering the cities and countries into homogeneous cycling typologies reveals that high cycling levels always coincide with high representation of females and good representations of all age groups. In low-cycling settings, it is the reverse. We recommend that evaluations of cycling policies include usage by gender and age groups as benchmarks in addition to overall use. To achieve representation across different age and gender groups, making neighbourhoods cycling friendly and developing safer routes to school, should be equally high on the agenda as cycling corridors that often cater to commuting traffic

Air Pollution Exposure during Pregnancy and Childhood Autistic Traits in Four European Population-Based Cohort Studies: The ESCAPE Project

Background: Prenatal exposure to air pollutants has been suggested as a possible etiologic factor for the occurrence of autism spectrum disorder. Objectives: We aimed to assess whether prenatal air pollution exposure is associated with childhood autistic traits in the general population. Methods: Ours was a collaborative study of four European population-based birth/child cohorts—CATSS (Sweden), Generation R (the Netherlands), GASPII (Italy), and INMA (Spain). Nitrogen oxides (NO2, NOx) and particulate matter (PM) with diameters of ≤ 2.5 μm (PM2.5), ≤ 10 μm (PM10), and between 2.5 and 10 μm (PMcoarse), and PM2.5 absorbance were estimated for birth addresses by land-use regression models based on monitoring campaigns performed between 2008 and 2011. Levels were extrapolated back in time to exact pregnancy periods. We quantitatively assessed autistic traits when the child was between 4 and 10 years of age. Children were classified with autistic traits within the borderline/clinical range and within the clinical range using validated cut-offs. Adjusted cohort-specific effect estimates were combined using random-effects meta-analysis. Results: A total of 8,079 children were included. Prenatal air pollution exposure was not associated with autistic traits within the borderline/clinical range (odds ratio = 0.94; 95% CI: 0.81, 1.10 per each 10-μg/m3 increase in NO2 pregnancy levels). Similar results were observed in the different cohorts, for the other pollutants, and in assessments of children with autistic traits within the clinical range or children with autistic traits as a quantitative score. Conclusions: Prenatal exposure to NO2 and PM was not associated with autistic traits in children from 4 to 10 years of age in four European population-based birth/child cohort studies.Funding was provided as follows: ESCAPE Project— European Community’s Seventh Framework Program (FP7/2007-2011-GA#211250). CATSS, Sweden— Swedish Research Council for Health, Working Life and Welfare (FORTE), Swedish Research Council (VR) Formas, in partner hip with FORTE and VINNOVA (cross-disciplinary research program concerning children’s and young people’s mental health); VR through the Swedish Initiative for Research on Microdata in the Social And Medical Sciences (SIMSAM) framework grant 340-2013-5867; HKH Kronprinsessan Lovisas förening för barnasjukvård; and the Strategic Research Program in Epidemiology at Karolinska Institutet. Generation R, the Netherlands—The Generation R Study is conducted by the Erasmus University Medical Center in close collaboration with the School of Law and Faculty of Social Sciences of the Erasmus University Rotterdam; the Municipal Health Service Rotterdam area, Rotterdam; the Rotterdam Homecare foundation, Rotterdam; and the Stichting Trombosedienst & Artsenlaboratorium Rijnmond (STAR-MDC), Rotterdam. The general design of the Generation R Study is made possible by financial support from the Erasmus University Medical Center, Rotterdam; the Erasmus University Rotterdam; the Netherlands Organization for Health Research and Development (ZonMw); the Netherlands Organization for Scientific Research (NWO); and the Ministry of Health, Welfare and Sport. The Netherlands Organisation for Applied Scientific Research (TNO) received funding from the Netherlands Ministry of Infrastructure and the Environment to support exposure assessment. GASPII, Italy—grant from the Italian Ministry of Health (ex art.12, 2001). INMA, Spain— grants from Instituto de Salud Carlos III (Red INMA G03/176 and CB06/02/0041 FIS-FEDER 03/1615, 04/1509, 04/1112, 04/1931, 05/1079, 05/1052, 06/1213, 07/0314, 09/02647, 11/01007, 11/02591, CP11/00178, FIS-PI041436, FIS-PI081151, FIS-PI06/0867, FIS-PS09/00090), PI13/1944, PI13_02032, PI14/0891, PI14/1687, MS13/00054, UE (FP7-ENV-2011 cod 282957, and HEALTH.2010.2.4.5-1); Generalitat de Catalunya-CIRIT 1999SGR 00241; La Fundació La Marató de TV3 (090430); Conselleria de Sanitat Generalitat Valenciana; Department of Health of the Basque Government (2005111093 and 2009111069); and Provincial Government of Gipuzkoa (DFG06/004 and DFG08/001). V.W.V.J. received an additional grant from the Netherlands Organization for Health Research and Development (ZonMw 90700303, 916.10159). A.G.’s work was supported by a research grant from the European Community’s 7th Framework Programme (FP7/2008–2013-GA#212652). A full roster of the INMA project investigators can be found online (http://www. proyectoinma.org/presentacion-inma/listado-investigadores/ en_listado-investigadores.html)

Development of West-European PM2.5 and NO2 land use regression models incorporating satellite-derived and chemical transport modelling data

Satellite-derived (SAT) and chemical transport model (CTM) estimates of PM2.5 and NO2 are increasingly used in combination with Land Use Regression (LUR) models. We aimed to compare the contribution of SAT and CTM data to the performance of LUR PM2.5 and NO2 models for Europe. Four sets of models, all including local traffic and land use variables, were compared (LUR without SAT or CTM, with SAT only, with CTM only, and with both SAT and CTM). LUR models were developed using two monitoring data sets: PM2.5 and NO2 ground level measurements from the European Study of Cohorts for Air Pollution Effects (ESCAPE) and from the European AIRBASE network. LUR PM2.5 models including SAT and SAT+CTM explained ~60% of spatial variation in measured PM2.5 concentrations, substantially more than the LUR model without SAT and CTM (adjR(2): 0.33-0.38). For NO2 CTM improved prediction modestly (adjR(2): 0.58) compared to models without SAT and CTM (adjR(2): 0.47-0.51). Both monitoring networks are capable of producing models explaining the spatial variance over a large study area. SAT and CTM estimates of PM2.5 and NO2 significantly improved the performance of high spatial resolution LUR models at the European scale for use in large epidemiological studies

WHO Air Quality Guidelines 2021-aiming for healthier air for all: a joint statement by medical, public health, scientific societies and patient representative organisations

[Extract] After years of intensive research and deliberations with experts across the globe, the World Health Organization (WHO) updated its 2005 Global Air Quality Guidelines (AQG) in September 2021 [1, 2]. The new air quality guidelines (WHO AQG) are ambitious and reflect the large impact that air pollution has on global health. They recommend aiming for annual mean concentrations of PM2.5 not exceeding 5 µg/m3 and NO2 not exceeding 10 µg/m3, and the peak season mean 8-hr ozone concentration not exceeding 60 µg/m3 [1]. For reference, the corresponding 2005 WHO guideline values for PM2.5 and NO2 were, respectively, 10 µg/m3 and 40 µg/m3 with no recommendation issued for long-term ozone concentrations [3]. While the guidelines are not legally binding, we hope they will influence air quality policy across the globe for many years to come

Health impact assessment of increasing public transport and cycling use in Barcelona: A morbidity and burden of disease approach

Objective: Quantify the health impacts on morbidity of reduced car trips and increased public transport and cycling trips. Methods: A health impact assessment study of morbidity outcomes related to replacing car trips in Barcelona metropolitan (3,231,458 inhabitants). Through 8 different transport scenarios, the number of cases of disease or injuries related to physical activity, particulate matter air pollution < 2.5 μm (PM2.5) and traffic incidents in travelers was estimated. We also estimate PM2.5 exposure and cases of disease in the general population. Results: A 40% reduction in long-duration car trips substituted by public transport and cycling trips resulted in annual reductions of 127 cases of diabetes, 44 of cardiovascular diseases, 30 of dementia, 16 minor injuries, 0.14 major injuries, 11 of breast cancer and 3 of colon-cancer, amounting to a total reduction of 302 Disability Adjusted Life Years per year in travelers. The reduction in PM2.5 exposure in the general population resulted in annual reductions of 7 cases of low birth weight, 6 of preterm birth, 1 of cardiovascular disease and 1 of lower respiratory tract infection. Conclusions: Transport policies to reduce car trips could produce important health benefits in terms of reduced morbidity, particularly for those who take up active transportation