Cannabis, Tobacco Use, and COVID-19 Outcomes.

Importance: It is unclear whether cannabis use is associated with adverse health outcomes in patients with COVID-19 when accounting for known risk factors, including tobacco use. Objective: To examine whether cannabis and tobacco use are associated with adverse health outcomes from COVID-19 in the context of other known risk factors. Design, Setting, and Participants: This retrospective cohort study used electronic health record data from February 1, 2020, to January 31, 2022. This study included patients who were identified as having COVID-19 during at least 1 medical visit at a large academic medical center in the Midwest US. Exposures: Current cannabis use and tobacco smoking, as documented in the medical encounter. Main Outcomes and Measures: Health outcomes of hospitalization, intensive care unit (ICU) admission, and all-cause mortality following COVID-19 infection. The association between substance use (cannabis and tobacco) and these COVID-19 outcomes was assessed using multivariable modeling. Results: A total of 72 501 patients with COVID-19 were included (mean [SD] age, 48.9 [19.3] years; 43 315 [59.7%] female; 9710 [13.4%] had current smoking; 17 654 [24.4%] had former smoking; and 7060 [9.7%] had current use of cannabis). Current tobacco smoking was significantly associated with increased risk of hospitalization (odds ratio [OR], 1.72; 95% CI, 1.62-1.82; P < .001), ICU admission (OR, 1.22; 95% CI, 1.10-1.34; P < .001), and all-cause mortality (OR, 1.37, 95% CI, 1.20-1.57; P < .001) after adjusting for other factors. Cannabis use was significantly associated with increased risk of hospitalization (OR, 1.80; 95% CI, 1.68-1.93; P < .001) and ICU admission (OR, 1.27; 95% CI, 1.14-1.41; P < .001) but not with all-cause mortality (OR, 0.97; 95% CI, 0.82-1.14, P = .69) after adjusting for tobacco smoking, vaccination, comorbidity, diagnosis date, and demographic factors. Conclusions and Relevance: The findings of this cohort study suggest that cannabis use may be an independent risk factor for COVID-19-related complications, even after considering cigarette smoking, vaccination status, comorbidities, and other risk factors.

Machine-Learning Predictions of High Arsenic and High Manganese at Drinking Water Depths of the Glacial Aquifer System, Northern Continental United States.

Globally, over 200 million people are chronically exposed to arsenic (As) and/or manganese (Mn) from drinking water. We used machine-learning (ML) boosted regression tree (BRT) models to predict high As (>10 µg/L) and Mn (>300 µg/L) in groundwater from the glacial aquifer system (GLAC), which spans 25 states in the northern United States and provides drinking water to 30 million people. Our BRT models' predictor variables (PVs) included recently developed three-dimensional estimates of a suite of groundwater age metrics, redox condition, and pH. We also demonstrated a successful approach to significantly improve ML prediction sensitivity for imbalanced data sets (small percentage of high values). We present predictions of the probability of high As and high Mn concentrations in groundwater, and uncertainty, at two nonuniform depth surfaces that represent moving median depths of GLAC domestic and public supply wells within the three-dimensional model domain. Predicted high likelihood of anoxic condition (high iron or low dissolved oxygen), predicted pH, relative well depth, several modeled groundwater age metrics, and hydrologic position were all PVs retained in both models; however, PV importance and influence differed between the models. High-As and high-Mn groundwater was predicted with high likelihood over large portions of the central part of the GLAC.

Machine Learning Predictions of pH in the Glacial Aquifer System, Northern USA.

A boosted regression tree model was developed to predict pH conditions in three dimensions throughout the glacial aquifer system of the contiguous United States using pH measurements in samples from 18,386 wells and predictor variables that represent aspects of the hydrogeologic setting. Model results indicate that the carbonate content of soils and aquifer materials strongly controls pH and, when coupled with long flowpaths, results in the most alkaline conditions. Conversely, in areas where glacial sediments are thin and carbonate-poor, pH conditions remain acidic. At depths typical of drinking-water supplies, predicted pH >7.5-which is associated with arsenic mobilization-occurs more frequently than predicted pH <6-which is associated with water corrosivity and the mobilization of other trace elements. A novel aspect of this model was the inclusion of numerically based estimates of groundwater flow characteristics (age and flowpath length) as predictor variables. The sensitivity of pH predictions to these variables was consistent with hydrologic understanding of groundwater flow systems and the geochemical evolution of groundwater quality. The model was not developed to provide precise estimates of pH at any given location. Rather, it can be used to more generally identify areas where contaminants may be mobilized into groundwater and where corrosivity issues may be of concern to prioritize areas for future groundwater monitoring.

Elevated Manganese Concentrations in United States Groundwater, Role of Land Surface-Soil-Aquifer Connections.

Chemical data from 43 334 wells were used to examine the role of land surface-soil-aquifer connections in producing elevated manganese concentrations (>300 µg/L) in United States (U.S.) groundwater. Elevated concentrations of manganese and dissolved organic carbon (DOC) in groundwater are associated with shallow, anoxic water tables and soils enriched in organic carbon, suggesting soil-derived DOC supports manganese reduction and mobilization in shallow groundwater. Manganese and DOC concentrations are higher near rivers than farther from rivers, suggesting river-derived DOC also supports manganese mobilization. Anthropogenic nitrogen may also affect manganese concentrations in groundwater. In parts of the northeastern U.S. containing poorly buffered soils, ∼40% of the samples with elevated manganese concentrations have pH values < 6 and elevated concentrations of nitrate relative to samples with pH ≥ 6, suggesting acidic recharge produced by the oxidation of ammonium in fertilizer helps mobilize manganese. An estimated 2.6 million people potentially consume groundwater with elevated manganese concentrations, the highest densities of which occur near rivers and in areas with organic carbon rich soil. Results from this study indicate land surface-soil-aquifer connections play an important role in producing elevated manganese concentrations in groundwater used for human consumption.