Health effects of multi-pollutant profiles

• In Boston (1999–2009), there was a significant association of PM2.5 on total mortality.
• The effect of PM2.5 on total mortality differed for days with distinct mixture types.
• Days with a strong contribution of primary traffic emissions show a higher association.
• The days were categorized by mixture type using a novel cluster method.
• Identifying harmful mixtures allows for future investigations of their mechanisms.

BackgroundThe association between exposure to particle mass and mortality is well established; however, there are still uncertainties as to whether certain chemical components are more harmful than others. Moreover, understanding the health effects associated with exposure to pollutant mixtures may lead to new regulatory strategies.ObjectivesRecently we have introduced a new approach that uses cluster analysis to identify distinct air pollutant mixtures by classifying days into groups based on their pollutant concentration profiles. In Boston during the years 1999–2009, we examined whether the effect of PM2.5 on total mortality differed by distinct pollution mixtures.MethodsWe applied a time series analysis to examine the association of PM2.5 with daily deaths. Subsequently, we included an interaction term between PM2.5 and the pollution mixture clusters.ResultsWe found a 1.1% increase (95% CI: 0.0, 2.2) and 2.3% increase (95% CI: 0.9–3.7) in total mortality for a 10 μg/m3 increase in the same day and the two-day average of PM2.5 respectively. The association is larger in a cluster characterized by high concentrations of the elements related to primary traffic pollution and oil combustion emissions with a 3.7% increase (95% CI: 0.4, 7.1) in total mortality, per 10 μg/m3 increase in the same day average of PM2.5.ConclusionsOur study shows a higher association of PM2.5 on total mortality during days with a strong contribution of traffic emissions, and fuel oil combustion. Our proposed method to create multi-pollutant profiles is robust, and provides a promising tool to identify multi-pollutant mixtures which can be linked to the health effects.