PM_2.5-Attributable Mortality Burden Variability in the Continental U.S

Area of Science:

• Environmental epidemiology
• Public health
• Air quality science

Background:

• Epidemiologic studies link fine particulate matter (PM2.5) exposure to premature mortality.
• Current health impact assessments often use a single log-linear hazard ratio (HR) to estimate mortality burdens.

Purpose of the Study:

• To estimate the total PM2.5-attributable premature mortality burden using diverse exposure models and HRs.
• To evaluate the sensitivity of mortality estimates to different methodologies and stratification factors.
• To provide transparency on the impact of input choices on mortality estimates.

Main Methods:

• Utilized multiple exposure models with varied methods for estimating PM2.5 concentrations.
• Applied a range of epidemiologic hazard ratios relating long-term PM2.5 exposure to mortality.
• Stratified mortality burden estimates by race/ethnicity and PM2.5 exposure levels.

Main Results:

• Mortality burden estimates showed greater variability due to different HRs (~3-fold) than exposure models (<10%).
• Future mortality burden estimates stratified by race/ethnicity exceeded unstratified population estimates.
• Stratifying HRs by exposure concentration thresholds yielded substantially higher mortality estimates.

Conclusions:

• The choice of hazard ratio significantly influences PM2.5-attributable mortality estimates.
• Stratification by race/ethnicity and exposure level reveals higher mortality burdens.
• Transparency in methodology is crucial for accurate health impact assessments of air quality improvements.