Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis.
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ABSTRACT:
SUBMITTER: Wu X
PROVIDER: S-EPMC7673673 | biostudies-literature | 2020 Nov
REPOSITORIES: biostudies-literature
Publications
Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis.
Wu X X Nethery R C RC Sabath M B MB Braun D D Dominici F F
Science advances 20201104 45
Assessing whether long-term exposure to air pollution increases the severity of COVID-19 health outcomes, including death, is an important public health objective. Limitations in COVID-19 data availability and quality remain obstacles to conducting conclusive studies on this topic. At present, publicly available COVID-19 outcome data for representative populations are available only as area-level counts. Therefore, studies of long-term exposure to air pollution and COVID-19 outcomes using these ...[more]
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Project description:The novel human coronavirus disease 2019 (COVID-19) pandemic has claimed more than 240,000 lives worldwide, causing tremendous public health, social, and economic damages. While the risk factors of COVID-19 are still under investigation, environmental factors, such as urban air pollution, may play an important role in increasing population susceptibility to COVID-19 pathogenesis. We conducted a cross-sectional nationwide study using zero-inflated negative binomial models to estimate the association between long-term (2010-2016) county-level exposures to NO2, PM2.5 and O3 and county-level COVID-19 case-fatality and mortality rates in the US. We used both single and multipollutant models and controlled for spatial trends and a comprehensive set of potential confounders, including state-level test positive rate, county-level healthcare capacity, phase-of-epidemic, population mobility, sociodemographic, socioeconomic status, behavior risk factors, and meteorological factors. 1,027,799 COVID-19 cases and 58,489 deaths were reported in 3,122 US counties from January 22, 2020 to April 29, 2020, with an overall observed case-fatality rate of 5.8%. Spatial variations were observed for both COVID-19 death outcomes and long-term ambient air pollutant levels. County-level average NO2 concentrations were positively associated with both COVID-19 case-fatality rate and mortality rate in single-, bi-, and tri-pollutant models (p-values<0.05). Per inter-quartile range (IQR) increase in NO2 (4.6 ppb), COVID-19 case-fatality rate and mortality rate were associated with an increase of 7.1% (95% CI 1.2% to 13.4%) and 11.2% (95% CI 3.4% to 19.5%), respectively. We did not observe significant associations between long-term exposures to PM2.5 or O3 and COVID-19 death outcomes (p-values>0.05), although per IQR increase in PM2.5 (3.4 ug/m3) was marginally associated with 10.8% (95% CI: -1.1% to 24.1%) increase in COVID-19 mortality rate. Long-term exposure to NO2, which largely arises from urban combustion sources such as traffic, may enhance susceptibility to severe COVID-19 outcomes, independent of long-term PM2.5 and O3 exposure. The results support targeted public health actions to protect residents from COVID-19 in heavily polluted regions with historically high NO2 levels. Moreover, continuation of current efforts to lower traffic emissions and ambient air pollution levels may be an important component of reducing population-level risk of COVID-19 deaths.
| S-EPMC7273261 | biostudies-literature
Project description:BackgroundThe novel human coronavirus disease 2019 (COVID-19) pandemic has claimed more than 600,000 lives worldwide, causing tremendous public health, social, and economic damages. Although the risk factors of COVID-19 are still under investigation, environmental factors, such as urban air pollution, may play an important role in increasing population susceptibility to COVID-19 pathogenesis.MethodsWe conducted a cross-sectional nationwide study using zero-inflated negative binomial models to estimate the association between long-term (2010-2016) county-level exposures to NO2, PM2.5, and O3 and county-level COVID-19 case-fatality and mortality rates in the United States. We used both single- and multi-pollutant models and controlled for spatial trends and a comprehensive set of potential confounders, including state-level test positive rate, county-level health care capacity, phase of epidemic, population mobility, population density, sociodemographics, socioeconomic status, race and ethnicity, behavioral risk factors, and meteorology.ResultsFrom January 22, 2020, to July 17, 2020, 3,659,828 COVID-19 cases and 138,552 deaths were reported in 3,076 US counties, with an overall observed case-fatality rate of 3.8%. County-level average NO2 concentrations were positively associated with both COVID-19 case-fatality rate and mortality rate in single-, bi-, and tri-pollutant models. When adjusted for co-pollutants, per interquartile-range (IQR) increase in NO2 (4.6 ppb), COVID-19 case-fatality rate and mortality rate were associated with an increase of 11.3% (95% CI 4.9%-18.2%) and 16.2% (95% CI 8.7%-24.0%), respectively. We did not observe significant associations between COVID-19 case-fatality rate and long-term exposure to PM2.5 or O3, although per IQR increase in PM2.5 (2.6 μg/m3) was marginally associated, with a 14.9% (95% CI 0.0%-31.9%) increase in COVID-19 mortality rate when adjusted for co-pollutants.DiscussionLong-term exposure to NO2, which largely arises from urban combustion sources such as traffic, may enhance susceptibility to severe COVID-19 outcomes, independent of long-term PM2.5 and O3 exposure. The results support targeted public health actions to protect residents from COVID-19 in heavily polluted regions with historically high NO2 levels. Continuation of current efforts to lower traffic emissions and ambient air pollution may be an important component of reducing population-level risk of COVID-19 case fatality and mortality.
| S-EPMC7505160 | biostudies-literature
Project description:ImportancePrior studies on the association between fine particulate matter with diameters 2.5 μm or smaller (PM2.5) and probability of death have not applied multilevel analysis disaggregating data for US census tract, states, and counties, nor tested its interaction by socioeconomic status (SES). Such an approach could provide a more refined identification and targeting of populations exposed to increased risk from PM2.5.ObjectiveTo assess the association between PM2.5 and age-specific mortality risk (ASMR) using disaggregated data at the census tract level and evaluate such association according to census tract SES.Design, setting, and participantsThis nationwide cross-sectional study used a linkage of 3 different data sets. ASMR for the period of 2010 to 2015 was obtained from the National Center for Health Statistic, SES data covering a period from 2006 to 2016 came from the American Community Survey, and mean PM2.5 exposure levels from 2010 to 2015 were derived from well-validated atmospheric chemistry and machine learning models. Data were analyzed in April 2021.ExposuresThe main exploratory variable was mean census tract-level long-term exposure to PM2.5 from 2010 to 2015.Main outcomes and measuresThe primary outcome was census tract-level ASMR. Multilevel models were used to quantify the geographic variation in ASMR at levels of census tract, county, and state. Additional analysis explored the interaction of SES in the association of ASMR with PM2.5 exposure.ResultsData from 67 148 census tracts nested in 3087 counties and 50 states were analyzed. The association between exposure to PM2.5 and ASMR varied substantially across census tracts. The magnitude of such association also varied across age groups, being higher among adults and older adults. Census tracts accounted for most of the total geographic variation in mortality risk (range, 77.0%-94.2%). ASMR was higher in deciles with greater PM2.5 concentration. For example, ASMR for age 75 to 84 years was 54.6 per 1000 population higher in the decile with the second-highest PM2.5 concentration than in the decile with the lowest PM2.5 concentration. The ASMR, PM2.5 concentrations, and magnitude of the association between both were higher in the census tracts with the lowest SES.Conclusions and relevanceThis cross-sectional study found that census tracts with lower SES presented higher PM2.5 concentrations. ASMR and air pollution varied substantially across census tracts. There was an association between air pollution and ASMR across all age groups in the United States. These findings suggest that equitable public policies aimed at improving air quality are needed and important to increase life expectancy.
| S-EPMC9131742 | biostudies-literature
Project description:Exposure to air pollution can exacerbate the severe COVID-19 conditions, subsequently causing an increase in the death rate. In this study, we investigated the association between long-term exposure to air pollution and risks of COVID-19 hospitalization and mortality in Arak, Iran. Air pollution data was obtained from air quality monitoring stations located in Arak, including particulate matter (PM), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3) and carbon monoxide (CO). Daily numbers of Covid-19 cases including hospital admissions (hospitalization) and deaths (mortality) were obtained from a national data registry recorded by Arak University of Medical Sciences. A Poisson regression model with natural spline functions was applied to set the effects of air pollution on COVID-19 hospitalization and mortality. The percent change of COVID-19 hospitalization per 10 μg/m3 increase in PM2.5 and PM10 were 8.5% (95% CI 7.6 to 11.5) and 4.8% (95% CI 3 to 6.5), respectively. An increase of 10 μg/m3 in PM2.5 resulting in 5.6% (95% CI: 3.1-8.3%) increase in COVID-19 mortality. The percent change of hospitalization (7.7%, 95% CI 2.2 to 13.3) and mortality (4.5%, 95% CI 0.3 to 9.5) were positively significant per one ppb increment in SO2, while NO2, O3 and CO were inversely associated with hospitalization and mortality. Our findings strongly suggesting that a small increase in long-term exposure to PM2.5, PM10 and SO2 elevating risks of hospitalization and mortality related to COVID-19.
| S-EPMC9154086 | biostudies-literature
Project description:ImportanceAmbient fine particulate matter (PM2.5) air pollution is associated with increased risk of several causes of death. However, epidemiologic evidence suggests that current knowledge does not comprehensively capture all causes of death associated with PM2.5 exposure.ObjectiveTo systematically identify causes of death associated with PM2.5 pollution and estimate the burden of death for each cause in the United States.Design, setting, and participantsIn a cohort study of US veterans followed up between 2006 and 2016, ensemble modeling was used to identify and characterize morphology of the association between PM2.5 and causes of death. Burden of death associated with PM2.5 exposure in the contiguous United States and for each state was then estimated by application of estimated risk functions to county-level PM2.5 estimates from the US Environmental Protection Agency and cause-specific death rate data from the Centers for Disease Control and Prevention.Main outcomes and measuresNonlinear exposure-response functions of the association between PM2.5 and causes of death and burden of death associated with PM2.5.ExposuresAnnual mean PM2.5 levels.ResultsA cohort of 4 522 160 US veterans (4 243 462 [93.8%] male; median [interquartile range] age, 64.1 [55.7-75.5] years; 3 702 942 [82.0%] white, 667 550 [14.8%] black, and 145 593 [3.2%] other race) was followed up for a median (interquartile range) of 10.0 (6.8-10.2) years. In the contiguous United States, PM2.5 exposure was associated with excess burden of death due to cardiovascular disease (56 070.1 deaths [95% uncertainty interval {UI}, 51 940.2-60 318.3 deaths]), cerebrovascular disease (40 466.1 deaths [95% UI, 21 770.1-46 487.9 deaths]), chronic kidney disease (7175.2 deaths [95% UI, 5910.2-8371.9 deaths]), chronic obstructive pulmonary disease (645.7 deaths [95% UI, 300.2-2490.9 deaths]), dementia (19 851.5 deaths [95% UI, 14 420.6-31 621.4 deaths]), type 2 diabetes (501.3 deaths [95% UI, 447.5-561.1 deaths]), hypertension (30 696.9 deaths [95% UI, 27 518.1-33 881.9 deaths]), lung cancer (17 545.3 deaths [95% UI, 15 055.3-20 464.5 deaths]), and pneumonia (8854.9 deaths [95% UI, 7696.2-10 710.6 deaths]). Burden exhibited substantial geographic variation. Estimated burden of death due to nonaccidental causes was 197 905.1 deaths (95% UI, 183 463.3-213 644.9 deaths); mean age-standardized death rates (per 100 000) due to nonaccidental causes were higher among black individuals (55.2 [95% UI, 50.5-60.6]) than nonblack individuals (51.0 [95% UI, 46.4-56.1]) and higher among those living in counties with high (65.3 [95% UI, 56.2-75.4]) vs low (46.1 [95% UI, 42.3-50.4]) socioeconomic deprivation; 99.0% of the burden of death due to nonaccidental causes was associated with PM2.5 levels below standards set by the US Environmental Protection Agency.Conclusions and relevanceIn this study, 9 causes of death were associated with PM2.5 exposure. The burden of death associated with PM2.5 was disproportionally borne by black individuals and socioeconomically disadvantaged communities. Effort toward cleaner air might reduce the burden of PM2.5-associated deaths.
| S-EPMC6902821 | biostudies-literature
Project description:Nitrogen dioxide (NO2) pollution is associated with adverse health effects, but its spatial variability between ground monitors is poorly characterized. NO2 column observations from the Tropospheric Monitoring Instrument (TROPOMI) have unprecedented spatial resolution and high accuracy over the globe. Land-use regression (LUR) models predict surface-level NO2 with relevance for epidemiological and environmental justice studies. We use TROPOMI NO2 columns in a land use regression (LUR) model to improve surface NO2 concentration estimates over the United States. The TROPOMI LUR predictions have improved correlation with ground monitors (Adj. R 2 = 0.72) and bias (Mean Bias, MB = 14.2%) compared with an existing LUR using less granular NO2 data from a legacy satellite instrument (Adj. R 2 = 0.54 and MB = 49%; for North America). Removing TROPOMI NO2 from the LUR decreased R 2 by 29.1%, 8.1 times the impact of removing road system information. These findings reveal that novel Earth observing satellites can enhance surface NO2 surveillance by capturing pollution variation between monitors without relying heavily on other data sources.
| S-EPMC11833862 | biostudies-literature
Project description:Imposing stricter regulations for PM2.5 has the potential to mitigate damaging health and climate change effects. Recent evidence establishing a link between exposure to air pollution and COVID-19 outcomes is one of many arguments for the need to reduce the National Ambient Air Quality Standards (NAAQS) for PM2.5. However, many studies reporting a relationship between COVID-19 outcomes and PM2.5 have been criticized because they are based on ecological regression analyses, where area-level counts of COVID-19 outcomes are regressed on area-level exposure to air pollution and other covariates. It is well known that regression models solely based on area-level data are subject to ecological bias, i.e., they may provide a biased estimate of the association at the individual-level, due to within-area variability of the data. In this paper, we augment county-level COVID-19 mortality data with a nationally representative sample of individual-level covariate information from the American Community Survey along with high-resolution estimates of PM2.5 concentrations obtained from a validated model and aggregated to the census tract for the contiguous United States. We apply a Bayesian hierarchical modeling approach to combine county-, census tract-, and individual-level data to ultimately draw inference about individual-level associations between long-term exposure to PM2.5 and mortality for COVID-19. By analyzing data prior to the Emergency Use Authorization for the COVID-19 vaccines we found that an increase of 1 μg/m3 in long-term PM2.5 exposure, averaged over the 17-year period 2000-2016, is associated with a 3.3% (95% credible interval, 2.8 to 3.8%) increase in an individual's odds of COVID-19 mortality. Code to reproduce our study is publicly available at https://github.com/NSAPH/PM_COVID_ecoinference. The results confirm previous evidence of an association between long-term exposure to PM2.5 and COVID-19 mortality and strengthen the case for tighter regulations on harmful air pollution and greenhouse gas emissions.
| S-EPMC10395946 | biostudies-literature
Project description:China is the world's largest emitter of anthropogenic air pollutants, and measurable amounts of Chinese pollution are transported via the atmosphere to other countries, including the United States. However, a large fraction of Chinese emissions is due to manufacture of goods for foreign consumption. Here, we analyze the impacts of trade-related Chinese air pollutant emissions on the global atmospheric environment, linking an economic-emission analysis and atmospheric chemical transport modeling. We find that in 2006, 36% of anthropogenic sulfur dioxide, 27% of nitrogen oxides, 22% of carbon monoxide, and 17% of black carbon emitted in China were associated with production of goods for export. For each of these pollutants, about 21% of export-related Chinese emissions were attributed to China-to-US export. Atmospheric modeling shows that transport of the export-related Chinese pollution contributed 3-10% of annual mean surface sulfate concentrations and 0.5-1.5% of ozone over the western United States in 2006. This Chinese pollution also resulted in one extra day or more of noncompliance with the US ozone standard in 2006 over the Los Angeles area and many regions in the eastern United States. On a daily basis, the export-related Chinese pollution contributed, at a maximum, 12-24% of sulfate concentrations over the western United States. As the United States outsourced manufacturing to China, sulfate pollution in 2006 increased in the western United States but decreased in the eastern United States, reflecting the competing effect between enhanced transport of Chinese pollution and reduced US emissions. Our findings are relevant to international efforts to reduce transboundary air pollution.
| S-EPMC3918792 | biostudies-literature
Project description:ObjectiveThe present study aimed to determine the association between chronic exposure to fine particulate matter (PM2.5), sociodemographic aspects, and health conditions with COVID-19 mortality in Colombia.MethodsWe performed an ecological study using data at the municipality level. We used COVID-19 data obtained from government public reports up to and including July 17th, 2020. We defined PM2.5 long-term exposure as the 2014-2018 average of the estimated concentrations at municipalities obtained from the Copernicus Atmospheric Monitoring Service Reanalysis (CAMSRA) model. We fitted a logit-negative binomial hurdle model for the mortality rate adjusting for sociodemographic and health conditions.ResultsEstimated mortality rate ratios (MRR) for long-term average PM2.5 were not statistically significant in either of the two components of the hurdle model (i.e., the likelihood of reporting at least one death or the count of fatal cases). We found that having 10% or more of the population over 65 years of age (MRR = 3.91 95%CI 2.24-6.81), the poverty index (MRR = 1.03 95%CI 1.01-1.05), and the prevalence of hypertension over 6% (MRR = 1.32 95%CI1.03-1.68) are the main factors associated with death rate at the municipality level. Having higher hospital beds capacity is inversely correlated to mortality.ConclusionsThere was no evidence of an association between long-term exposure to PM2.5 and COVID-19 mortality rate at the municipality level in Colombia. Demographics, health system capacity, and social conditions did have evidence of an ecological effect on COVID-19 mortality. The use of model-based estimations of long-term PM2.5 exposure includes an undetermined level of uncertainty in the results, and therefore they should be interpreted as preliminary evidence.
| S-EPMC7688425 | biostudies-literature
Project description:BackgroundAmbient nitrogen dioxide (NO2) and fine particulate matter with aerodynamic diameter ≤2.5μm (PM2.5) threaten public health in the US, and systemic racism has led to modern-day disparities in the distribution and associated health impacts of these pollutants.ObjectivesMany studies on environmental injustices related to ambient air pollution focus only on disparities in pollutant concentrations or provide only an assessment of pollution or health disparities at a snapshot in time. In this study, we compare injustices in NO2- and PM2.5-attributable health burdens, considering NO2-attributable health impacts across the entire US; document changing disparities in these health burdens over time (2010-2019); and evaluate how more stringent air quality standards would reduce disparities in health impacts associated with these pollutants.MethodsThrough a health impact assessment, we quantified census tract-level variations in health outcomes attributable to NO2 and PM2.5 using health impact functions that combine demographic data from the US Census Bureau; two spatially resolved pollutant datasets, which fuse satellite data with physical and statistical models; and epidemiologically derived relative risk estimates and incidence rates from the Global Burden of Disease study.ResultsDespite overall decreases in the public health damages associated with NO2 and PM2.5, racial and ethnic relative disparities in NO2-attributable pediatric asthma and PM2.5-attributable premature mortality have widened in the US during the last decade. Racial relative disparities in PM2.5-attributable premature mortality and NO2-attributable pediatric asthma have increased by 16% and 19%, respectively, between 2010 and 2019. Similarly, ethnic relative disparities in PM2.5-attributable premature mortality have increased by 40% and NO2-attributable pediatric asthma by 10%.DiscussionEnacting and attaining more stringent air quality standards for both pollutants could preferentially benefit the most marginalized and minoritized communities by greatly reducing racial and ethnic relative disparities in pollution-attributable health burdens in the US. Our methods provide a semi-observational approach to track changes in disparities in air pollution and associated health burdens across the US. https://doi.org/10.1289/EHP11900.
| S-EPMC10916678 | biostudies-literature