There are large differences in premature mortality in the USA by racial/ethnic, education, rurality, and social vulnerability index groups. Using existing concentration-response functions, particulate matter (PM2.5) air pollution, population estimates at the tract level, and county-level mortality data, we estimated the degree to which these mortality discrepancies can be attributed to differences in exposure and susceptibility to PM2.5. We show that differences in mortality attributable to PM2.5 were consistently more pronounced between racial/ethnic groups than by education, rurality, or social vulnerability index, with the Black American population having by far the highest proportion of deaths attributable to PM2.5 in all years from 1990 to 2016. Over half of the difference in age-adjusted all-cause mortality between the Black American and non-Hispanic White population was attributable to PM2.5 in the years 2000 to 2011.

The authors have declared no competing interest.

PG is a Chan Zuckerberg Biohub investigator. DF is supported by the Gerhard C. Starck Foundation. MVK is supported by National Institutes of Health (NIH) grant R00DA051534. EB is supported by NIH grants R01AI127250 and R01HD104835. SHN is supported by the Robert Woods Johnson Foundation. TB is supported by NIH grant R01CA228147 and by the California Environmental Protection Agency's Office of Environmental Health Hazard Assessment (#21-E0018).

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The use of the data in the study are approved and regulated by the National Center for Health Statistics Data Use Agreement (DUA) for Vital Statistics Data Files. It was internally reviewed and approved by the Stanford Managing Senior Contract & Grant Officer.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes

Data and code are publicly accessible on GitHub (https://github.com/FridljDa/pm25_inequality) and Zenodo (doi:10.5281/zenodo.10038691). Population estimates from the ACS and NCHS are publicly available and shared on the repositories above. Death certificate data was obtained from the National Center for Health Statistics, which mandates that all cells with fewer than 10 deaths and at the subnational level must be suppressed. Data derived from death certificates are, thus, only shared at the national level.

doi:10.5281/zenodo.10038691

https://github.com/FridljDa/pm25_inequality