Improving consistency in estimating future health burdens from environmental risk factors: case study for ambient air pollution

Developing more precise estimation methods for future health burden metrics is crucial to understanding how the health of future populations will evolve. The authors of this paper developed and applied a demographic model for calculating future health burdens from PM_2.5 exposure rather than using exogenous projections of future population and mortality rates. By using this alternative methodology, they found that a demographic model estimated a 48% larger health burden in 2050 when PM_2.5 is kept constant compared to the traditional model. They also showed that larger changes in non-PM_2.5 mortality rates and relatively higher projected PM_2.5 exposure produced the largest differences between PM_2.5 attributable mortality estimated using the demographic model compared with the traditional exogenous model. Conversely, the authors found that where the World Health Organization’s air quality guidelines are followed, these health burdens fall away dramatically, revealing a scenario where ~71 million lives could be saved by 2050.

Using this dynamic demographic modelling to assess the health benefits of different policies and measures will improve the evaluation of health consequences of policy decisions. This will enable researchers to provide a more consistent assessment of how interventions have impacted and will impact mortality and population changes. It also helps to quantify health advantages brought about by strategies that reduce multiple health risks simultaneously, such as integrated air pollution and climate change mitigation activities.