MEthods and Tools for Assessing the Health Impacts of Transport: modelling study (METAHIT)

Globally and locally how people and goods move around is important for public health. Transport causes ill-health through road traffic injuries, noise, and air pollution, but is an opportunity for benefiting health through active travel. For example, in the UK motor traffic injuries cause nearly 2000 deaths a year and motor traffic related air pollution nearly 3500 premature deaths a year, while our estimates suggest the physical activity benefits of replacing car trips of less than 3 miles with cycling would prevent over 2000 premature deaths a year.

The growing interest in improving the health impacts of transport has led to the development of computer models to examine the health risks and benefits of a mode shift away from cars to active travel (walking and cycling) and public transport. Although walking and cycling do not produce air pollutants and pose low injury risk to others, pedestrians and cyclists are usually at higher risk of injury and tend to breathe in more air pollution. Most of the studies have find out that the physical activity benefits of active travel are higher than the potential risks of air pollution and injuries for those who change their mode. For society as a whole there are additional benefits as there are fewer cars on the road potentially reducing injury risks and air pollution.

Studies that have estimated the health consequences have either relied on an ad-hoc computer models developed specifically for the study, or used one of the existing tools specifically tailored for the work. We call these tools Health Impact Assessment (HIA) tools. Current state-of-the-art HIA tools, like the Integrated Transport and Health Impact Modelling Tool (ITHIM) developed by the principal investigator of this application, have been influential in quantifying the health benefits and, in some cases, harms associated with increased walking and cycling.

These tools bring together data from many different sources and rely on many assumptions. Based on our experience developing and applying these tools to different policies and scenarios we now understand more about how these assumptions can be improved and how we can make sure data from different sources are comparable. In this project a team of researchers with expertise in transport, physical activity, air pollution, road traffic injuries, noise, and computer modelling will develop the scientific methods that support the next generation of tools. We will improve the way we calculate health impacts for each of the pathways individually, and will combine them together in an integrated model to understand how they interact to produce population health effects.

We will develop and demonstrate the model for the English population. England is an ideal case study area because we have high quality data available from transport, environmental determinants, and health. The model will illustrate and test the methods developed during the project by calculating number of transport related scenarios for whole population of England and for local authorities. The scenarios will include increasing cycling, decreasing motorised traffic, increasing public transport and decreasing freight traffic. We will look at how the benefits and harms would affect different groups. The scenarios will be used both to help us improve the model and to provide policy relevant answers.

To allow others to test our methods and apply them in different settings we will make the model and the code behind it freely available online. As we develop the methods in this project we will also apply for further funding to work with policy makers to develop an online web tool that can help integrate health into transport decision making.

Urban land transport has positive (physical activity) and negative (road traffic injuries, noise and air pollutants) side effects. Studies in high income settings have found substantial population health benefits from mode shift to active travel, with physical activity dominating.

In this project we will develop the methods that will lay the basis for the next generation health impact assessment (HIA) tools. Our experience developing and applying the Integrated Transport and Health Impact Modelling Tool (ITHIM) has highlighted many of the gaps in the field, which we will work to fill in this project. Central to the project is our development of an open source stochastic integrated simulation framework within which we can use uncertainty methods such as value of information to investigate how uncertainty around input parameters and model structure impact policy relevant results. This will be used to guide future empirical studies.

We will develop and integrate new health impact pathways (noise, nitrogen dioxide (NO2) air pollution) and improve methods for existing pathways of physical activity, particulate matter air pollution, and road traffic injuries. We will develop methods to generate more realistic counterfactual scenarios, based on which trips have the highest propensity to shift mode. We will use individual-level data to better capture between-individual heterogeneity in the scenarios and evaluate wider range of outcomes. We will compare simpler and more advanced chronic disease modelling methods, and investigate the potential for applying calibration factors to the simpler, but more generalisable, method.

The framework will be implemented on a case study for England, with estimates on travel patterns, physical activity, injury risk, air pollution, noise exposures, and disease burdens estimated down to the local authority level. We will collaborate with stakeholders to disseminate findings and methods, and test them in other locations.

This project will support development of policies and approaches to improve health and well-being through improving methods for assessing the risks and benefits of transport policies and scenarios. The methods we will develop in this project will allow prediction of how changes in transport would change the exposure to air pollution, noise, injuries and physical activity, and how these changes would impact population health.

The way people and goods move around is a major public health issue. In the UK, motor traffic injuries still cause over 1700 deaths annually, with traffic-related air pollution leading to at least another 3400 premature deaths. Globally, the burden of road traffic injuries is predicted to rise from the ninth to seventh leading cause of death by 2030, while outdoor air pollution poses a huge burden, greatest in Asia. At the same time a growing burden of chronic disease associated with lack of physical activity is affecting populations in developed and developing countries. In the UK 25% of women and 20% of men are classified as inactive, with many more insufficiently active; and with total costs due to lack of physical activity estimated to be £7.4 billion a year. Utility cycling and walking provide a potentially convenient way to incorporate physical activity into everyday life.

Although transport appraisal in the UK attempts to incorporate many of these issues the reality remains severely limited. Firstly, the different health pathways are not well integrated. Secondly, walking and cycling are often considered separately from other modes. Thirdly, many factors relevant to quantifying harms and benefits are ignored e.g. the age of the people changing their behaviour. This is often because of (perceived) lack of (local) data. Therefore, health considerations are often not well integrated within transport decision making. This project speaks to an urgent need to bridge disciplinary and professional barriers.

In the short term this project will produce new results of the potential health benefits and harms of changes to transport, including the spatial and social distribution of these outcomes. We will have advanced our methodological knowledge and skills in combining multiple pathways (air pollution, noise, injuries, physical activity) in a health impact model. We will have started developing user-friendly scenario tools based on propensities to cycle (see Case for Support). We will be able to inform science and surveillance about where enhanced travel, physical activity, injuries, and air pollution data collection would most reduce uncertainty. On a larger scale, availability of the model code through an open-source portal will bring benefit in other areas.

In the medium term, through separate funding applications we will create an online tool that provides a user-friendly, interactive way for policymakers, practitioners and other interested individuals to examine the likely health consequences of transport interventions and scenarios. Our ability to realise this is evidenced by funding we have received for tool development from the Department for Transport (e.g. www.pct.bike and www.pct.bike/ict). We will also look for opportunity to integrate the methods within travel demand models. In addition we are separately applying for funding to support generalisability to Low and Middle Income countries with less robust data (through an MRC Global Challenges application).

Improving population levels of physical activity and reducing air and noise pollution, and injury risk could bring large public health benefits. By providing locally detailed estimates, new findings, and robust models we will support a more sophisticated incorporation of the likely effects of decisions into policy making, and so encourage evidence-based decisions for health-promoting policies. For details on how we aim to disseminate knowledge from these methods to potential users, see Pathways to Impact and Communications Plan.