New Research: Improving Health Impact Assessment (HIA) of Multiple Environmental Exposures
Two new articles advance the way we estimate the health impacts of multiple, interrelated environmental exposures.
We are excited to share two closely connected papers lead by researchers (Xuan Chen, Gerard Hoek, Ulrike Gehring) from Institute for Risk Assessment Sciences (IRAS), Utrecht University, that advance how we estimate the health impacts of multiple correlated environmental exposures — moving from two air pollutants (NO2 and PM2.5) to a broader picture that includes green space and noise.
- 📄 Environmental Research (2024) Read the paper
- 📄 Environment International (2025) Read the paper
UBD Consortium members Xuan Chen and Gerard Hoek were invited to join discussions about HIA of multiple pollutants with the UK Committee on the Medical Effects of Air Pollutants (COMEAP). This engagement is closely linked to their recent work on a coefficient difference method, which was inspired by COMEAP’s previous report.
Most health impact assessments (HIAs) rely on single-exposure models, even though people are exposed to multiple correlated environmental factors — such as fine particulate matter (PM2.5), nitrogen dioxide (NO2), road traffic noise, and access to green space — at the same time.
Across these two studies, we systematically reviewed cohort studies reporting both single- and two-exposure models for associations between long-term exposure and mortality. By comparing the effect estimates from single- and two-exposure models, we derived coefficient differences for each exposure pair.
These pooled coefficient differences can be used to adjust effect estimates from meta-analyses of single-exposure models, enabling more realistic calculations of the combined health impacts of multiple environmental exposures. This approach improves HIAs for multiple correlated exposures and can be extended to other exposure–outcome pairs in future research.
This post was written by Xuan Chen from Utrecht University.
