Cities affect our health in many ways at once, from air pollution and heat to noise, green space and physical activity. In this Lab Snapshot, Mark Nieuwenhuijsen explains how his programme studies these combined exposures and translates them into evidence that can support healthier urban planning, climate action and nature-based solutions.
We quantify the health impacts of urban and transport planning practices, including climate action, through exposures such as air pollution, noise, temperature, green space and physical activity, in order to inform policy making and help make cities more sustainable, liveable and healthier.
What is the big question behind your work on cities and health?
Cities are complex systems, so we need a holistic systems approach. These exposures happen at the same time and may interact with each other, which means that studying them one by one can miss part of the picture.
Urban and transport planning practices, climate action and nature-based solutions all affect health, either negatively or positively. We need to quantify these effects and impacts so that we can make recommendations to the urban and transport planning community and support measures that promote health. Healthy cities are essential for people to prosper and for the economy to thrive.
In simple terms, we estimate the possible change in exposure under a counterfactual scenario, for example after a new policy, and combine this with robust exposure-response evidence from the literature. This allows us to estimate which fraction of disease or mortality in a population is related to those exposures, or could be prevented, and express the health benefits as cases of disease, deaths, years of life lost or DALYs (Disability-Adjusted Life Year) prevented.
The work is highly interdisciplinary and requires urban and transport planning, environmental science, statistics, epidemiology, health research and the ability to work with large datasets and new data science approaches. One example is UBDPolicy, where we are working with a dataset of more than 800 European cities to quantify mortality and disease burden related to urban and transport planning practices.
Perhaps the main issue is not misunderstanding but lack of awareness of how much current urban and transport planning practices affect health. In a city like Barcelona, around 20% of mortality may be premature and linked to these factors, and many of those deaths could be avoided if practices were improved.
I would be especially interested in connecting with people working in data science, including the use of big data and artificial intelligence.
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