Poor air quality is the number one environmental cause of premature death across the EU. Although great efforts have been made in the last decade to reduce air pollution levels in Belgium, a considerable part of the population is still exposed to concentrations exceeding the WHO Air Quality Guidelines. The BELAIR-POL project supports policymaking by evaluating the impact of hypothetical interventions targeting air pollution on reducing multi-morbidity and mortality in Belgium.
The overall objective of the project is to valorise existing Sciensano data sources in an integrated framework to assess the contribution of air pollution to the societal impact of non-communicable diseases, multi-morbidity and mortality in Belgium.
We use three data sources within this project:
- The Belgian Health Interview Survey data (HIS). Sciensano conducts this large-scale survey among the Belgian population every four/five years since 1997. It collects information on a wide range of health topics including physical and mental health, lifestyle, use of health care services and perception of the environment. The HIS has been part of the European Health Interview Survey (EHIS) and allows studying time trends in different health domains and in health inequalities.
- The mortality 10 years follow-up data of the HIS participants (including the cause of death) ‘FUHIS’
- Objective environmental data, based on GIS (geographical information system), describing the living environment of the HIS participants (based on residential address) in terms of air pollution, noise and green space (NAMED project)
This overall objective is achieved through the following three specific objectives:
- To collect evidence linking air quality strategies and interventions aimed at reducing air pollution in Belgium to expected reduction in air pollution concentration levels and improved public health outcomes
- To assess the potential health impact of specific air pollution reduction interventions on non-communicable diseases, multi-morbidity and cause-specific mortality among Belgian adults
- To actively support knowledge translation throughout the course of the project to support the understanding and uptake of our results.
We use advanced statistical modelling and causal inference to evaluate the impact of hypothetical intervention scenarios targeting long-term exposure to PM 2.5, PM10, NO2, and black carbon on reducing non-communicable diseases, multi-morbidity and mortality in Belgium using the HIS data from 2008 to 2018. Examples of hypothetical scenarios could involve reducing the annual average individual exposure to air pollutants by 20%, 40%, or 60%, or aiming to meet the WHO Air Quality Guidelines.
Compared with classic analytical methods, the statistical approach used in this study has the advantage to provide causal effect estimates that are more intuitive to policymakers. We display research findings in the form of percentage of disease cases or deaths that could be avoided in Belgium under specific air pollution reduction interventions. The main results allow policymakers to have a deeper insight on the potential health benefits of air pollution reduction policies in Belgium and facilitate the prioritisation of air quality strategies.