Influence of Perfluoroalkyl Substances on Occurrence of Coronavirus Disease 2019
Abstract
:1. Purpose
2. Introduction
3. Materials and Methods
3.1. Data Acquisition
3.1.1. Blood PFAS Data
3.1.2. COVID-19 Incidence Data
3.1.3. Population Count Data
3.2. Methods
- The publicly available COVID-19 incidence count data by age grouping and gender were downloaded for the location in which the participants of the given PFAS study resided. These COVID-19 incidence counts were cumulative since the start of data collection by the State or local agency in charge of acquiring and presenting the COVID-19 data on the dashboard (i.e., total counts were obtained).
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- As these data were downloaded, the age groups were delineated for the presented COVID-19 incidence count data.
- Within each of the COVID-19 incidence age groups encountered in step #1, incidence counts were estimated for each age (year) by dividing the total incidence count for that age group by the number of years represented within the group. This approach assumes that COVID-19 incidence was uniformly spread across the years within that group, and therefore, each year within an age group had the same COVID-19 incidence count estimate.
- For a given age group present in the blood PFAS concentration summary, those age groups used to present the COVID-19 incidence counts were identified which overlapped with the PFAS age group in some way. Figure 1 illustrates this through an example. In this example, the PFAS study age group spans eight years (Y5 to Y12) which are represented among four age groups used in the COVID-19 incidence data for the study location. (These four COVID-19 age groups which overlap with the PFAS age group jointly span a total of 15 years—Y1 to Y15.) Two of the four COVID-19 age groups (#2 and #3) fall within the PFAS age group in their entirety. For each of the other two COVID-19 age groups (#1 and #4), only a subset of their represented years falls within the PFAS age group.
- Across all years within the given PFAS age group, the year-specific estimated COVID-19 incidence counts calculated in step #2 were summed to obtain an estimated COVID-19 incidence count for that PFAS age group.
- Steps #3 and #4 were repeated for each age group in the blood PFAS concentration summary, yielding a COVID-19 incidence count estimate for each group.
- Measures for summary statistics related to the distribution of PFAS concentrations in blood (specifically, the 50th and 75th percentiles for both PFOS and PFOA) for the age group.
- COVID-19 incidence measure for the age group (i.e., percentage relative to the group’s population).
- New Jersey COVID-19 data: https://covid19.nj.gov/ accessed on 4 February 2022.
- North Carolina COVID-19 data: https://covid19.ncdhhs.gov/dashboard/cases-demographics accessed on 4 February 2022.
- Ohio COVID-19 data: https://coronavirus.ohio.gov/wps/portal/gov/covid-19/dashboards accessed on 4 February 2022.
- NHANES data: https://covid.cdc.gov/covid-data-tracker/#demographics accessed on 4 February 2022.
4. Results
5. Discussion
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Reference # | Study Name/Location | Target Population | Sample Collection Period | # Study Participants |
---|---|---|---|---|
[12] | GenX Exposure Study | Residents ≥6 years of age in New Hanover County, NC, USA | 2017–2018 | 344 |
[7] | Health Outcomes and Measures of the Environment (HOME) Study (pregnant women recruited) | Females of child-bearing age residing in Butler, Clermont, Hamilton, and Warren counties in Southwest Ohio | 2003–2005 | 336 |
[14] | New Jersey Biomonitoring (NJBM) Study | New Jersey residents from 20 to 74 years of age | 2016–2018 | 1030 |
[5] | NHANES | U.S. population | 2017–2018 | 1929 |
Study (Reference #) | Age Group | Age Category or Median Age (years) | COVID-19 Incidence Rate | PFOA Concentration Percentiles (ng/mL) | PFOS Concentration Percentiles (ng/mL) | |||
---|---|---|---|---|---|---|---|---|
50th | 75th | 50th | 75th | |||||
[12] | NC | 06–17 years. | Youths | 7.3% | 3.00 | 5.10 | 4.10 | 7.8 |
[12] | NC | 18+ years. | Adults | 11.1% | 4.80 | 9.40 | 7.20 | 14.5 |
[5] | Nation | 12–19 years. | Youths | 9.6% | 1.17 | 2.60 | 1.67 | 3.7 |
[5] | Nation | 20+ years. | Adults | 10.4% | 1.47 | 4.70 | 2.17 | 8.0 |
[7] | OH | 18–24 years | 21 years | 14.0% | 6.10 | 7.80 | -- | -- |
[7] | OH | 25–34 years | 29.5 years | 15.3% | 5.20 | 7.50 | -- | -- |
[7] | OH | 35–49 years. | 42 years | 13.9% | 5.70 | 9.00 | -- | -- |
[14] | NJ | 20–39 years. | 29.5 years | 13.7% | 1.89 | 2.35 | 2.67 | 3.70 |
[14] | NJ | 40–59 years. | 49.5 years | 12.2% | 2.06 | 2.48 | 2.98 | 4.19 |
[14] | NJ | 60–74 years. | 67 years | 9.9% | 2.50 | 3.29 | 4.46 | 6.12 |
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Dembek, Z.F.; Lordo, R.A. Influence of Perfluoroalkyl Substances on Occurrence of Coronavirus Disease 2019. Int. J. Environ. Res. Public Health 2022, 19, 5375. https://doi.org/10.3390/ijerph19095375
Dembek ZF, Lordo RA. Influence of Perfluoroalkyl Substances on Occurrence of Coronavirus Disease 2019. International Journal of Environmental Research and Public Health. 2022; 19(9):5375. https://doi.org/10.3390/ijerph19095375
Chicago/Turabian StyleDembek, Zygmunt F., and Robert A. Lordo. 2022. "Influence of Perfluoroalkyl Substances on Occurrence of Coronavirus Disease 2019" International Journal of Environmental Research and Public Health 19, no. 9: 5375. https://doi.org/10.3390/ijerph19095375