Sociodemographic Factors Are Associated with the Abundance of PFAS Sources and Detection in U.S. Community Water Systems.

Drinking water contaminated by per- and polyfluoroalkyl substances (PFAS) is a widespread public health concern, and exposure-response relationships are known to vary across sociodemographic groups. However, research on disparities in drinking water PFAS exposures and the siting of PFAS sources in marginalized communities is limited. Here, we use monitoring data from 7873 U.S. community water systems (CWS) in 18 states to show that PFAS detection is positively associated with the number of PFAS sources and proportions of people of color who are served by these water systems. Each additional industrial facility, military fire training area, and airport in a CWS watershed was associated with a 10-108% increase in perfluorooctanoic acid and a 20-34% increase in perfluorooctane sulfonic acid in drinking water. Waste sector sources were also significantly associated with drinking water PFAS concentrations. CWS watersheds with PFAS sources served higher proportions of Hispanic/Latino and non-Hispanic Black residents compared to those without PFAS sources. CWS serving higher proportions of Hispanic/Latino and non-Hispanic Black residents had significantly increased odds of detecting several PFAS. This likely reflects disparities in the siting of PFAS contamination sources. Results of this work suggest that addressing environmental justice concerns should be a component of risk mitigation planning for areas affected by drinking water PFAS contamination.

County-level associations between drinking water PFAS contamination and COVID-19 mortality in the United States.

BACKGROUND: Epidemiologic and animal studies both support relationships between exposures to per- and polyfluoroalkyl substances (PFAS) and harmful effects on the immune system. Accordingly, PFAS have been identified as potential environmental risk factors for adverse COVID-19 outcomes. OBJECTIVE: Here, we examine associations between PFAS contamination of U.S. community water systems (CWS) and county-level COVID-19 mortality records. Our analyses leverage two datasets: one at the subnational scale (5371 CWS serving 621 counties) and one at the national scale (4798 CWS serving 1677 counties). The subnational monitoring dataset was obtained from statewide drinking monitoring of PFAS (2016-2020) and the national monitoring dataset was obtained from a survey of unregulated contaminants (2013-2015). METHODS: We conducted parallel analyses using multilevel quasi-Poisson regressions to estimate cumulative incidence ratios for the association between county-level measures of PFAS drinking water contamination and COVID-19 mortality prior to vaccination onset (Jan-Dec 2020). In the primary analyses, these regressions were adjusted for several county-level sociodemographic factors, days after the first reported case in the county, and total hospital beds. RESULTS: In the subnational analysis, detection of at least one PFAS over 5 ng/L was associated with 12% higher [95% CI: 4%, 19%] COVID-19 mortality. In the national analysis, detection of at least one PFAS above the reporting limits (20-90 ng/L) was associated with 13% higher [95% CI: 8%, 19%] COVID-19 mortality. IMPACT STATEMENT: Our findings provide evidence for an association between area-level drinking water PFAS contamination and higher COVID-19 mortality in the United States. These findings reinforce the importance of ongoing state and federal monitoring efforts supporting the U.S. Environmental Protection Agency's 2024 drinking water regulations for PFAS. More broadly, this example suggests that drinking water quality could play a role in infectious disease severity. Future research would benefit from study designs that combine area-level exposure measures with individual-level outcome data.

Associations between solar and geomagnetic activity and cognitive function in the Normative Aging study.

BACKGROUND: Studies show that changes in solar and geomagnetic activity (SGA) influence melatonin secretion and the autonomic nervous system. We evaluated associations between solar and geomagnetic activity and cognitive function in the Normative Aging Study from 1992 to 2013. METHODS: We used logistic and linear generalized estimating equations and regressions to evaluate the associations between moving averages of sunspot number (SSN) and Kp index (a measure of geomagnetic activity) and a binary measure for Mini-Mental State Examination (MMSE) scores (≤25 or > 25) and six other cognitive tests as continuous measures, combined into one global composite score and considered separately. RESULTS: A one-IQR increase in same-day SSN and Kp index were associated with 17% (95% CI: 3%, 34%) and 19% (95% CI: 4%, 36%) increases in the odds of low MMSE score. We observed small increases in the global cognitive score with increasing SSN, although we observed decreases specifically in relation to the backwards digit span test. CONCLUSIONS: Periods of high SGA were associated with cognitive function. SGA may not equally impact all aspects of cognitive function, as evidenced by differences in associations observed for the MMSE, global cognitive score, and individual cognitive tests. Given that much of the pathology of cognitive decline in the elderly remains unexplained, studies specifically targeting decline and with longer follow-up periods are warranted.

Programmatic conversion of crystal structures into 3D printable files using Jmol.

BACKGROUND: Three-dimensional (3D) printed crystal structures are useful for chemistry teaching and research. Current manual methods of converting crystal structures into 3D printable files are time-consuming and tedious. To overcome this limitation, we developed a programmatic method that allows for facile conversion of thousands of crystal structures directly into 3D printable files. RESULTS: A collection of over 30,000 crystal structures in crystallographic information file (CIF) format from the Crystallography Open Database (COD) were programmatically converted into 3D printable files (VRML format) using Jmol scripting. The resulting data file conversion of the 30,000 CIFs proceeded as expected, however some inconsistencies and unintended results were observed with co-crystallized structures, racemic mixtures, and structures with large counterions that led to 3D printable files not containing the desired chemical structure. Potential solutions to these challenges are considered and discussed. Further, a searchable Jmol 3D Print website was created that allows users to both discover the 3D file dataset created in this work and create custom 3D printable files for any structure in the COD. CONCLUSIONS: Over 30,000 crystal structures were programmatically converted into 3D printable files, allowing users to have quick access to a sizable collection of 3D printable crystal structures. Further, any crystal structure (>350,000) in the COD can now be conveniently converted into 3D printable file formats using the Jmol 3D Print website created in this work. The 3D Print website also allows users to convert their own CIFs into 3D printable files. 3D file data, scripts, and the Jmol 3D Print website are provided openly to the community in an effort to promote discovery and use of 3D printable crystal structures. The 3D file dataset and Jmol 3D Print website will find wide use with researchers and educators seeking to 3D print chemical structures, while the scripts will be useful for programmatically converting large database collections of crystal structures into 3D printable files.