The Environmental Burden of the United States' Bitcoin Mining Boom.

Bitcoin mines-massive computing clusters generating cryptocurrency tokens-consume vast amounts of electricity. The amount of fine particle (PM) air pollution created because of their electricity consumption, and its effect on environmental health, is unknown. In this study, we located the 34 largest mines in the United States in 2022, identified the electricity-generating plants that responded to them, and pinpointed communities most harmed by Bitcoin mine-attributable air pollution.

Fish Consumption and DHA Supplementation during Pregnancy: Study of Gestational and Neonatal Outcomes.

Several studies have explored the association between fish consumption during pregnancy and favorable neonatal outcomes, although some yield conflicting results. The American College of Obstetricians and Gynecologists recommends two to three servings of low-mercury fish per week for pregnant or breastfeeding women. However, fish can be a source of pollutants, like methylmercury, impacting neurological development.

Childhood PM exposure and upward mobility in the United States.

Although it is well documented that exposure to fine particulate matter (PM) increases the risk of several adverse health outcomes, less is known about its relationship with economic opportunity. Previous studies have relied on regression modeling, which implied strict assumptions regarding confounding adjustments and did not explore geographical heterogeneity. We obtained data for 63,165 US census tracts (86% of all census tracts in the United States) on absolute upward mobility (AUM) defined as the mean income rank in adulthood of children born to families in the 25th percentile of the national income distribution.

Policy-induced air pollution health disparities: Statistical and data science considerations.

Air pollution causes premature death and disease and disproportionately harms non-white and lower-income groups in the United States. Government policies are responsible for the racial disparity in air pollution exposure and related health outcomes. Investigating complex relationships between policies, air pollution, and health requires (i) harmonized data connecting policies, environmental exposures, socioeconomic characteristics, and health at the individual and area level; (ii) interpretable estimands accounting for the complex interplay between policies and disparities in exposures and health outcomes; and (iii) data science approaches that can elucidate direct and indirect policy effects on disparities to identify effective interventions.

Differential recall bias in estimating treatment effects in observational studies.

Observational studies are frequently used to estimate the effect of an exposure or treatment on an outcome. To obtain an unbiased estimate of the treatment effect, it is crucial to measure the exposure accurately. A common type of exposure misclassification is recall bias, which occurs in retrospective cohort studies when study subjects may inaccurately recall their past exposure.

Comparing traditional and causal inference methodologies for evaluating impacts of long-term air pollution exposure on hospitalization with Alzheimer's disease and related dementias.

Alzheimer's disease and related dementias (ADRD) present a growing public health burden in the United States. One actionable risk factor for ADRD is air pollution: multiple studies have found associations between air pollution and exacerbation of ADRD. Our study builds on previous studies by applying modern statistical causal inference methodologies-generalized propensity score (GPS) weighting and matching-on a large, longitudinal dataset.

Long-term exposure to air pollution, greenness and temperature and survival after a nonfatal myocardial infarction.

Background: Little is known about the impact of environmental exposures on mortality risk after a myocardial infarction (MI).

Objective: The goal of this study was to evaluate associations of long-term temperature, air pollution and greenness exposures with mortality among survivors of an MI.

Methods: We used data from the US-based Nurses' Health Study to construct an open cohort of survivors of a nonfatal MI 1990-2017.

Excess Fatal Overdoses in the United States During the COVID-19 Pandemic by Geography and Substance Type: March 2020-August 2021.

To assess heterogeneity in pandemic-period excess fatal overdoses in the United States, by location (state, county) and substance type. We used seasonal autoregressive integrated moving average (SARIMA) models to estimate counterfactual death counts in the scenario that no pandemic had occurred. Such estimates were subtracted from actual death counts to assess the magnitude of pandemic-period excess mortality between March 2020 and August 2021.

Confounder-dependent Bayesian mixture model: Characterizing heterogeneity of causal effects in air pollution epidemiology.

Several epidemiological studies have provided evidence that long-term exposure to fine particulate matter (pm2.5) increases mortality rate. Furthermore, some population characteristics (e.

Identifying dietary consumption patterns from survey data: a Bayesian nonparametric latent class model.

Dietary assessments provide the snapshots of population-based dietary habits. Questions remain about how generalisable those snapshots are in national survey data, where certain subgroups are sampled disproportionately. We propose a Bayesian overfitted latent class model to derive dietary patterns, accounting for survey design and sampling variability.

Matching on Generalized Propensity Scores with Continuous Exposures.

In the context of a binary treatment, matching is a well-established approach in causal inference. However, in the context of a continuous treatment or exposure, matching is still underdeveloped. We propose an innovative matching approach to estimate an average causal exposure-response function under the setting of continuous exposures that relies on the generalized propensity score (GPS).

Associations of fine particulate matter with incident cardiovascular disease; comparing models using ZIP code-level and individual-level fine particulate matter and confounders.

Background: PM has been positively associated with cardiovascular disease (CVD) incidence. Most evidence has come from cohorts and administrative databases. Cohorts typically have extensive information on potential confounders and residential-level exposures.

All cause and cause specific mortality associated with transition to daylight saving time in US: nationwide, time series, observational study.

Objectives: To estimate the association between the transition to daylight saving time and the risks of all cause and cause specific mortality in the US.

Design: Nationwide time series observational study based on weekly data.

Setting: US state level mortality data from the National Center for Health Statistics, with death counts from 50 US states and the District of Columbia, from the start of 2015 to the end of 2019.

Exposure-response associations between chronic exposure to fine particulate matter and risks of hospital admission for major cardiovascular diseases: population based cohort study.

Objective: To estimate exposure-response associations between chronic exposure to fine particulate matter (PM) and risks of the first hospital admission for major cardiovascular disease (CVD) subtypes.

Design: Population based cohort study.

Setting: Contiguous US.

Short term exposure to low level ambient fine particulate matter and natural cause, cardiovascular, and respiratory morbidity among US adults with health insurance: case time series study.

Objective: To estimate the excess relative and absolute risks of hospital admissions and emergency department visits for natural causes, cardiovascular disease, and respiratory disease associated with daily exposure to fine particulate matter (PM) at concentrations below the new World Health Organization air quality guideline limit among adults with health insurance in the contiguous US.

Design: Case time series study.

Setting: US national administrative healthcare claims database.

Long-term exposure to ambient PM2.5, particulate constituents and hospital admissions from non-respiratory infection.

The association between PM2.5 and non-respiratory infections is unclear. Using data from Medicare beneficiaries and high-resolution datasets of PM2.

Long-Term Exposure to Low-Level and Mortality: Investigation of Heterogeneity by Harmonizing Analyses in Large Cohort Studies in Canada, United States, and Europe.

Background: Studies across the globe generally reported increased mortality risks associated with particulate matter with aerodynamic diameter () exposure with large heterogeneity in the magnitude of reported associations and the shape of concentration-response functions (CRFs). We aimed to evaluate the impact of key study design factors (including confounders, applied exposure model, population age, and outcome definition) on effect estimates by harmonizing analyses on three previously published large studies in Canada [Mortality-Air Pollution Associations in Low Exposure Environments (MAPLE), 1991-2016], the United States (Medicare, 2000-2016), and Europe [Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE), 2000-2016] as much as possible.

Methods: We harmonized the study populations to individuals years of age, applied the same satellite-derived exposure estimates, and selected the same sets of potential confounders and the same outcome.

Mortality risk from United States coal electricity generation.

Policy-makers seeking to limit the impact of coal electricity-generating units (EGUs, also known as power plants) on air quality and climate justify regulations by quantifying the health burden attributable to exposure from these sources. We defined "coal PM" as fine particulate matter associated with coal EGU sulfur dioxide emissions and estimated annual exposure to coal PM from 480 EGUs in the US. We estimated the number of deaths attributable to coal PM from 1999 to 2020 using individual-level Medicare death records representing 650 million person-years.

The association between temperature and alcohol- and substance-related disorder hospital visits in New York State.

Background: Limited evidence exists on how temperature increases are associated with hospital visits from alcohol- and substance-related disorders, despite plausible behavioral and physiological pathways.

Methods: In the present study, we implemented a case-crossover design, which controls for seasonal patterns, long-term trends, and non- or slowly-varying confounders, with distributed lag non-linear temperature terms (0-6 days) to estimate associations between daily ZIP Code-level temperature and alcohol- and substance-related disorder hospital visit rates in New York State during 1995-2014. We also examined four substance-related disorder sub-causes (cannabis, cocaine, opioid, sedatives).

Long-term exposure to summer specific humidity and cardiovascular disease hospitalizations in the US Medicare population.

Introduction: Most climate-health studies focus on temperature; however, less is known about health effects of exposure to atmospheric moisture. Humid air limits sweat evaporation from the body and can in turn exert strain on the cardiovascular system. We evaluated associations of long-term exposure to summer specific humidity with cardiovascular disease (CVD), coronary heart disease (CHD) and cerebrovascular disease (CBV) hospitalization.

Short-term excess mortality following tropical cyclones in the United States.

Knowledge of excess deaths after tropical cyclones is critical to understanding their impacts, directly relevant to policies on preparedness and mitigation. We applied an ensemble of 16 Bayesian models to 40.7 million U.

Does choice of outdoor heat metric affect heat-related epidemiologic analyses in the US Medicare population?

Unlabelled: Outdoor air temperature is associated with increased morbidity and mortality. Other thermal indices theoretically confer greater physiological relevance by incorporating additional meteorological variables. However, the optimal metric for predicting excess deaths or hospitalizations owing to extreme heat among US Medicare beneficiaries remains unknown.

Combining aggregate and individual-level data to estimate individual-level associations between air pollution and COVID-19 mortality in the United States.

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.

Seasonal Temperature Variability and Mortality in the Medicare Population.

Background: Seasonal temperature variability remains understudied and may be modified by climate change. Most temperature-mortality studies examine short-term exposures using time-series data. These studies are limited by regional adaptation, short-term mortality displacement, and an inability to observe longer-term relationships in temperature and mortality.