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

Risk assessment of a pedestrian-oriented environment

Health professionals and urban planners are increasingly calling for new approaches that involve changes in the built environment to address complex health and environmental problems. In particular, community designs to promote walking and cycling are seen as potential solutions to the obesity epidemic in the U.S. Yet, the net health effect that results from neighborhood transformations is not known today. Competing risks may be involved, particularly when considering the effects of encouraging people to be active in areas with significant air pollution and fraught with risks of traffic injuries. This dissertation proposes a conceptual framework for assessing risks and benefits that ensue from the improvement of the pedestrian environment, and investigates some of these relationships in a quantitative application. The probabilistic model developed for this work consists in simulating the movement of individuals in a case-study area that undergoes hypothetical changes in land use and street network. Resulting changes in energy expenditure due to active travel and in pollutant inhalation dose are estimated. The model uses an activity database, travel models from the transportation literature, and ozone and PM10 fields developed for this work using the Bayesian Maximum Entropy framework and a combination of monitored and modeled data. Daily individual inhalation intake is thus calculated accounting for specific activities, locations, and times of day. Uncertainty and population variability is analyzed through MonteCarlo simulation. Results show great uncertainty associated with estimating risks and benefits. For example, two travel models yield a four-fold difference in predicting the fraction of population with significant increases in PM10 inhalation dose. Conservative estimates demonstrate a significant increase in the fraction of days above a PM10 threshold across the population, and potential for some individuals to more than double their inhalation intake of both pollutants on certain days. Clear benefits in terms of physical activity, however, cannot be established by the conservative exposure model. This work is an innovative risk assessment method for analyzing health impacts of built environment policies. The dissertation concludes with suggested policies to address increased risks, and a research agenda for future work in this area

Estimating traffic contribution to particulate matter concentration in urban areas using a multilevel Bayesian meta-regression approach.

Quantifying traffic contribution to air pollution in urban settings is required to inform traffic management strategies and environmental policies that aim at improving air quality. Assessments and comparative analyses across multiple urban areas are challenged by the lack of datasets and methods available for global applications. In this study, we quantify the traffic contribution to particulate matter concentration in multiple cities worldwide by synthesising 155 previous studies reported in the World Health Organization (WHO)'s air pollution source apportionment data for PM10 and PM2.5. We employed a Bayesian multilevel meta-regression that accounts for uncertainties and captures both within- and between-study variations (in estimation methods, study protocols, etc.) through study-specific and location-specific explanatory variables. The final sample analysed in this paper covers 169 cities worldwide. Based on our analysis, traffic contribution to air pollution (particulate matter) varies from 5% to 61% in cities worldwide, with an average of 27%. We found that variability in the traffic contribution estimates reported worldwide can be explained by the region of study, publication year, PM size fraction, and population. Specifically, traffic contribution to air pollution in cities located in Europe, North America, or Oceania is on average 36% lower relative to the rest of the world. Traffic contribution is 28% lower among studies published after 2005 than those published on or before 2005. Traffic contribution is on average 24% lower among cities with less than 500,000 inhabitants and 19% higher when estimated based on PM10 relative to PM2.5. This quantitative summary overcomes challenges in the data and provides useful information for health impact modellers and decision-makers to assess impacts of traffic reduction policies.This study was supported by the project “Towards an Integrated Global Transport and Health Assessment Tool (TIGTHAT)”, funded by Medical Research Council (MRC) Global Challenges Research Fund, UK (number: RG87632-SJ). The work of the first author was partly funded by the Natural Sciences and Engineering Research Council of Canada

Evaluation of low traffic neighbourhood (LTN) impacts on NO2 and traffic

Traffic restriction measures may create safer and healthier places for community members but may also displace traffic and air pollution to surrounding streets. Effective urban planning depends on understanding the magnitude of changes resulting from policy measures, both within and surrounding intervention areas; these are largely unstudied in the case of Low traffic Neighbourhoods (LTN). We evaluated impacts of three LTNs in the London Borough of Islington, UK, on air pollution and traffic flows in and around intervention areas, based on monthly Nitrogen Dioxide (NO2) and traffic volume data provided by the local authority. We identified pre- and post-intervention monitoring periods and intervention, boundary and control sites. We then adapted the generalised difference in differences approach to evaluate the effects within LTNs and at their boundary. We found that LTNs have the potential to substantially reduce air pollution and traffic in target areas, without increasing air pollution or traffic volumes in surrounding streets. These results provide sound arguments in favour of LTNs to promote health and wellbeing in urban communities

Cycling in Warsaw, Poland - Perceived enablers and barriers according to cyclists and non-cyclists.

Cycling in urban environments provides many benefits to people. However, planning of cycling infrastructures in large cities faces numerous challenges and requires better understanding of both the factors enabling cycling as well as barriers to it, determined by particular local context. While there is a growing body of research that tackle the bike transport related questions in Western Europe and the USA, there is relatively little research on that in Central Eastern Europe (CEE), in post-communist countries. In this study we used qualitative and quantitative methods to explore urban cyclists and non-cyclists opinions about the cycling, the perceived problems and obstacles, and perception of the on-going changes in bicycle transportation system in Warsaw, Poland. Although many people see potential advantages of cycling, it is mostly perceived as a leisure time activity. Those who do utilitarian cycling are more acutely aware of the benefits, such as rapidity and flexibility of this mean of transport. The main perceived barriers are linked to lack of good cycling infrastructure in the city, the feeling of insecurity linked to the behaviour of drivers, and to maintenance during winter. In conclusion, our research highlights both the opportunities and challenges linked to the development of improved cycle transportation system, suggesting the need for a range of policies, from the infrastructure improvements and comprehensive planning of the whole transportation system, to improving the driving culture that would support feeling of security of the cyclists

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

Bayesian Maximum Entropy Integration of Ozone Observations and Model Predictions: An Application for Attainment Demonstration in North Carolina

States in the USA are required to demonstrate future compliance of criteria air pollutant standards by using both air quality monitors and model outputs. In the case of ozone, the demonstration tests aim at relying heavily on measured values, due to their perceived objectivity and enforceable quality. Weight given to numerical models is diminished by integrating them in the calculations only in a relative sense. For unmonitored locations, the EPA has suggested the use of a spatial interpolation technique to assign current values. We demonstrate that this approach may lead to erroneous assignments of non-attainment and may make it difficult for States to establish future compliance. We propose a method that combines different sources of information to map air pollution, using the Bayesian Maximum Entropy (BME) Framework. The approach gives precedence to measured values and integrates modeled data as a function of model performance. We demonstrate this approach in North Carolina, using the State’s ozone monitoring network in combination with outputs from the Multiscale Air Quality Simulation Platform (MAQSIP) modeling system. We show that the BME data integration approach, compared to a spatial interpolation of measured data, improves the accuracy and the precision of ozone estimations across the State

Understanding parents’ school travel choices: A qualitative study using the Theoretical Domains Framework

© 2017 Elsevier Ltd Traffic related air pollution is detrimental to health and creates a substantial attributable mortality burden. It is suggested that a shift from motorised transport to active forms of travel will therefore have significant health benefits. Currently 46% of school journeys for primary aged children are made by car and this figure has risen steadily. Understanding barriers to active school travel (AST) is an important first step in developing behavioural interventions to increase active travel. The purpose of this study was to explore parents’ experiences of school travel and their choices regarding travel mode with a focus on identifying barriers and facilitators to AST. Twenty parents of primary school children (4–12 years) in the West Yorkshire region took part in semi-structured interviews regarding school travel, informed by the Theoretical Domains Framework. Framework Analysis was used to identify key themes in the data and to develop a comprehensive picture of parents’ experiences of school travel at both individual and structural levels. Distance was the biggest barrier to AST. Time constraints were reported as the main barrier to parents accompanying children in AST, while concerns about safety deterred parents from allowing children to travel independently. The need to incorporate multiple jouneys, such as the work commute and/or multiple school drop-offs, placed demands on parents’ time, while difficulty getting children into local schools meant further to travel for a number of parents. Findings suggest that interventions to promote AST may be particularly effective if tailored towards working parents. However, also addressing factors such as distance to school and school travel at a policy level may produce more significant shifts in behaviour

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