TABLE 2
FIGURE 1
Odds Ratio ( OR ) and Confidence Interval (CI) From Model 1 for Each 1-Unit Increase in Pollutant Concentration
Reactions That Allow for the Nitrogen Oxide (NO)–Nitrogen Dioxide (NO 2 ) Ratio
Pollutant
OR
95% CI
NO + O 3 → NO 2 + O 2 NO 2 + O 2 → NO + O 3
Average AQI
1.1634
[0.5932, 2.2734]
Average SO 2 concentration (ppb) Average NO 2 concentration (ppb) Average PM 2.5 concentration (μg/m 3 ) Average PM 10 concentration (μg/m 3 )
7.9047 x 10 4
[7.0445 x 10 -4 , 8.8698 x 10 12 ]
0.6427
[0.0752, 5.4971] [1.1195, 18.5664] [0.6989, 1.1411]
Note. O 2 = oxygen; O 3 = ozone. Source: Hagenbjörk et al., 2017.
4.5990*
0.7602
*Statistically significant. Note. AQI = Air Quality Index; NO 2 = nitrogen dioxide; PM = particulate matter; SO 2 = sulfur dioxide.
has been shown to increase when the concen- tration of O 3 is low (Figure 1; Hagenbjörk et al., 2017). This increase is likely because O 3 oxidizes NO to produce NO 2 (Kimbrough et al., 2017). At low levels of O 3 , NO will accumu- late, thereby increasing the NO to NO 2 ratio. Furthermore, inhaled NO in the clini- cal setting has been shown to be protective against SARS-Cov-2, as it can inhibit viral replication of coronaviruses (Rajendran et al., 2022). Currently, NO is used as a vaso- dilator in the treatment of acute respiratory distress syndrome, which is a common result of severe COVID-19 (Alqahtani et al., 2022). It is important to note that these levels of NO would be at much lower concentrations than levels used in clinical settings. Further research is needed to study this hypothesis. Limitations There are four main limitations in our study. First, the exposure data were sampled at the county level. The 90-day average exposures were calculated from this information for each COVID-19 case reported to the Indiana Department of Health with a positive test result during the study period. The use of population-level exposure data for individual patients leaves a broad range of potential vari- ability. Some of the factors that could con- tribute to intra-county variation include the presence of factories, nearby roads, and crop dust. To help account for these factors, we restricted our analysis to MSAs, where there is more likely to be more than one report- ing site per county. When several values for a single day were present in the raw data, these values were averaged before calculat- ing the 90-day average exposure. Our study, however, did not account for travel out of an individual’s county of residence.
TABLE 3
Odds Ratio ( OR ) and Confidence Interval (CI) From Model 2 for Each 1-Unit Increase in Pollutant Concentration
Pollutant
OR
95% CI
Average AQI
0.9578
[0.0426, 2.1549]
Average SO 2 concentration (ppb) Average NO 2 concentration (ppb) Average PM 2.5 concentration (μg/m 3 ) Average PM 10 concentration (μg/m 3 )
1.2016 x 10 4
[1.1302 x 10 -6 , 1.2775 x 10 14 ]
0.1609*
[0.0550, 0.4705] [0.5724, 22.5358] [1.1545, 6.4250]
3.5916
2.7235*
*Statistically significant. Note. AQI = Air Quality Index; NO 2 = nitrogen dioxide; PM = particulate matter; SO 2 = sulfur dioxide.
gested several mechanisms that could explain these associations (Karan et al., 2020; Weaver et al., 2022). Additionally, it has been shown that the average 90-day PM 10 concentration is associated with an increased risk of mortal- ity in individuals with chronic lung disease. One possible explanation for this relation- ship is that short-term particulate matter pol- lution has been shown to upregulate ACE-2 and TMPRSS-2, which are key proteins that enable the cellular entry of SARS-CoV-2 (Weaver et al., 2022). The upregulation of these proteins would provide the SARS- CoV-2 virus with more binding sites, which could enable an increased initial viral load. Other researchers have suggested that particulate matter could potentially serve as a carrier, allowing the SARS-CoV-2 virus to travel on its surface (Meo et al., 2021). This function could potentially compound other eects of air pollution, including increased
alveolar permeability, to produce severe dis- ease (Marian et al., 2022). In Italy, particulate matter samples were found to contain SARS- CoV-2 viral particles (Meo et al., 2021). This hypothesis is further supported by the find- ings of numerous studies that demonstrate a positive relationship between particulate matter concentrations and daily COVID-19 case counts (Copat et al., 2020). In our study, Model 2 demonstrated a protec- tive OR for NO 2 . Our hypothesis is that nitrogen oxide (NO), rather than NO 2 , might be driving this protective association. Previous research has identified NO 2 as a risk factor for severe COVID-19 outcomes (Copat et al., 2020; Meo et al., 2021). At low levels of NO 2 and O 3 —as seen in Indiana during the study period—it is hypothesized that the model might instead reflect the protective factor of NO, which exists in a ratio with NO 2 in the atmosphere (Hagen- björk et al., 2017). The ratio of NO and NO 2
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September 2024 • Journal of Environmental Health
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