Lewy body dementia promotion by air pollutants.

Evidence links air pollution to dementia, yet its role in Lewy body dementia (LBD) remains unclear. In this work, we showed in a cohort of 56.5 million individuals across the United States that fine particulate matter (PM) exposure raises LBD risk.

Climate-smart public health for global health resilience.

Climate change poses urgent public health risks from rising global temperatures and extreme weather events, including heatwaves, droughts, and floods, which disproportionately affect vulnerable populations. To address the current silos embedded in climate, environmental, and public health monitoring and surveillance systems, climate-smart public health (CSPH) creates an integrated platform for action across these sectors, enabling more rapid and efficient responses to climate-related public health challenges. In this Personal View, we introduce the concept of CSPH, a data-driven framework designed to monitor, assess, and adapt to climate-related health impacts.

Air pollution interventions for health.

Air pollution, a leading environmental health risk, claims millions of lives yearly, impacting health across the lifespan. Despite widespread acknowledgement of air pollution-related disease burdens, eliminating air pollution remains challenging. Many regions are reliant on fossil fuels or biomass for basic survival, and developed economies striving to reduce air pollution face persistent barriers.

Quantifying effects of solar power adoption on CO emissions reduction.

We quantify the effect of solar power adoption in reducing carbon dioxide (CO) emissions from the US electricity sector using 5 years of Energy Information Administration data, starting 1 July 2018. By tailoring a distributed lag statistical model, we estimate the immediate and time-lagged effects of increased solar generation on reducing CO emissions within a region. Our analysis highlights how solar adoption in one region affects CO emissions in neighboring regions, emphasizing the potential for collaborative efforts.

Effects of intermediate and long-term exposure to ambient air pollution and temperature on hospital admissions with second cardiovascular events among medicare beneficiaries.

Background: Air pollution has been linked to cardiovascular diseases (CVDs). In this study, we assess whether exposure to air pollutants and ambient temperature is associated with repeated admissions with adverse cardiovascular outcomes.

Methods: We used data from Medicare beneficiaries between 2000 and 2016 to look at the effects of intermediate and long-term exposure to ambient PM, NO, O, and temperature on second admissions with myocardial infarction (MI) and ischemic stroke.

Long-term impact of PM on mortality is exacerbated when wildfire events occur.

There is extensive evidence that long-term exposure to all-source PM increases mortality. However, to date, no study has evaluated whether this effect is exacerbated in the presence of wildfire events. Here, we study 60+ million older US adults and find that wildfire events increase the harmful effects of long-term all-source PM exposure on mortality, providing a new and realistic conceptualization of wildfire health risks.

Coexposure to extreme heat, wildfire burn zones, and wildfire smoke in the Western US from 2006 to 2020.

Climate change drives three heat-related hazards: extreme heat (EH), wildfire burn zones (WFBZs), and wildfire smoke (WFS). Using daily census tract-level data from 2006 to 2020, we investigated when, where, and whom these hazards coexposed in 11 Western US states. Among 18,106 tracts, at least one hazard occurred an average of 32 days (581,867 tract-days) annually.

Seasonal Average Temperature Differences and CVD Incidence: Results from the US-Based Nurses' Health Study, Nurses' Health Study II, and the Health Professional Follow-Up Study.

Background: Climate change is one of the greatest health threats facing humanity. Multiple studies have documented the impact of short-term temperature exposure on human health. However, long-term temperature exposures are far less studied.

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 pending. 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.

The impacts of air pollution on mortality and hospital readmission among Medicare beneficiaries with Alzheimer's disease and Alzheimer's disease-related dementias: a national retrospective cohort study in the USA.

Background: Alzheimer's disease and Alzheimer's disease-related dementias (AD/ADRD) are prevalent neurodegenerative disorders, posing a critical worldwide public health challenge. Ambient air pollution has been identified as a potential risk factor for AD progression based on toxicological and epidemiological studies. We aimed to evaluate the impacts of air pollution-including fine particulate matter (PM), nitrogen dioxide (NO), summer ozone (O), and oxidant-on readmission or death among Medicare enrollees previously hospitalised with an AD/ADRD diagnosis code.

Artificial intelligence for modelling infectious disease epidemics.

Infectious disease threats to individual and public health are numerous, varied and frequently unexpected. Artificial intelligence (AI) and related technologies, which are already supporting human decision making in economics, medicine and social science, have the potential to transform the scope and power of infectious disease epidemiology. Here we consider the application to infectious disease modelling of AI systems that combine machine learning, computational statistics, information retrieval and data science.

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 disease and related dementias.

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

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.