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Long-term air pollution and COVID-19 mortality rates in California: Findings from the Spring/Summer and Winter surges of COVID-19.
Garcia, Erika; Marian, Brittney; Chen, Zhanghua; Li, Kenan; Lurmann, Fred; Gilliland, Frank; Eckel, Sandrah P.
  • Garcia E; Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA. Electronic address: garc991@usc.edu.
  • Marian B; Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA.
  • Chen Z; Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA.
  • Li K; Spatial Sciences Institute, University of Southern California, Los Angeles, CA, USA.
  • Lurmann F; Sonoma Technology, Inc, Petaluma, CA, USA.
  • Gilliland F; Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA.
  • Eckel SP; Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA.
Environ Pollut ; 292(Pt B): 118396, 2022 Jan 01.
Article in English | MEDLINE | ID: covidwho-1482582
ABSTRACT
A growing number of studies report associations between air pollution and COVID-19 mortality. Most were ecological studies at the county or regional level which disregard important local variability and relied on data from only the first few months of the pandemic. Using COVID-19 deaths identified from death certificates in California, we evaluated whether long-term ambient air pollution was related to weekly COVID-19 mortality at the census tract-level during the first ∼12 months of the pandemic. Weekly COVID-19 mortality for each census tract was calculated based on geocoded death certificate data. Annual average concentrations of ambient particulate matter <2.5 µm (PM2.5) and <10 µm (PM10), nitrogen dioxide (NO2), and ozone (O3) over 2014-2019 were assessed for all census tracts using inverse distance-squared weighting based on data from the ambient air quality monitoring system. Negative binomial mixed models related weekly census tract COVID-19 mortality counts to a natural cubic spline for calendar week. We included adjustments for potential confounders (census tract demographic and socioeconomic factors), random effects for census tract and county, and an offset for census tract population. Data were analyzed as two study periods Spring/Summer (March 16-October 18, 2020) and Winter (October 19, 2020-March 7, 2021). Mean (standard deviation) concentrations were 10.3 (2.1) µg/m3 for PM2.5, 25.5 (7.1) µg/m3 for PM10, 11.3 (4.0) ppb for NO2, and 42.8 (6.9) ppb for O3. For Spring/Summer, adjusted rate ratios per standard deviation increase were 1.13 (95% confidence interval 1.09, 1.17) for PM2.5, 1.16 (1.11, 1.21) for PM10, 1.06 (1.02, 1.10) for NO2, and 1.09 (1.04, 1.14) for O3. Associations were replicated in Winter, although they were attenuated for PM2.5 and PM10. Study findings support a relation between long-term ambient air pollution exposure and COVID-19 mortality. Communities with historically high pollution levels might be at higher risk of COVID-19 mortality.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Air Pollutants / Air Pollution / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Topics: Long Covid Limits: Humans Country/Region as subject: North America Language: English Journal: Environ Pollut Journal subject: Environmental Health Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Air Pollutants / Air Pollution / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Topics: Long Covid Limits: Humans Country/Region as subject: North America Language: English Journal: Environ Pollut Journal subject: Environmental Health Year: 2022 Document Type: Article