XIS-PM: A daily spatiotemporal machine-learning model for PM in the contiguous United States.

Air-pollution monitoring is sparse across most of the United States, so geostatistical models are important for reconstructing concentrations of fine particulate air pollution (PM) for use in health studies. We present XGBoost-IDW Synthesis (XIS), a daily high-resolution PM machine-learning model covering the contiguous US from 2003 through 2023. XIS uses aerosol optical depth from satellites and a parsimonious set of additional predictors to make predictions at arbitrary points, capturing near-roadway gradients and allowing the estimation of address-level exposures.

Social Vulnerability and Biological Aging in New York City: An Electronic Health Records-Based Study.

Chronological age is not an accurate predictor of morbidity and mortality risk, as individuals' aging processes are diverse. Phenotypic age acceleration (PhenoAgeAccel) is a validated biological age measure incorporating chronological age and biomarkers from blood samples commonly used in clinical practice that can better reflect aging-related morbidity and mortality risk. The heterogeneity of age-related decline is not random, as environmental exposures can promote or impede healthy aging.

XIS-temperature: A daily spatiotemporal machine-learning model for air temperature in the contiguous United States.

The challenge of reconstructing air temperature for environmental applications is to accurately estimate past exposures even where monitoring is sparse. We present XGBoost-IDW Synthesis for air temperature (XIS-Temperature), a high-resolution machine-learning model for daily minimum, mean, and maximum air temperature, covering the contiguous US from 2003 through 2023. XIS uses remote sensing (land surface temperature and vegetation) along with a parsimonious set of additional predictors to make predictions at arbitrary points, allowing the estimation of address-level exposures.

A descriptive examination of rurality in the Environmental influences on Child Health Outcomes Cohort: Implications, illustrations, and future directions.

Purpose: The Environmental influences on Child Health Outcomes (ECHO) Cohort has enrolled over 60,000 children to examine how early environmental factors (broadly defined) are associated with key child health outcomes. The ECHO Cohort may be well-positioned to contribute to our understanding of rural environments and contexts, which has implications for rural health disparities research. The present study examined the outcome of child obesity to not only illustrate the suitability of ECHO Cohort data for these purposes but also determine how various definitions of rural and urban populations impact the presentation of findings and their interpretation.

Impact of metabolism-disrupting chemicals and folic acid supplementation on liver injury and steatosis in mother-child pairs.

Background & Aims: Scarce knowledge about the impact of metabolism-disrupting chemicals (MDCs) on steatotic liver disease limits opportunities for intervention. We evaluated pregnancy MDC-mixture associations with liver outcomes, and effect modification by folic acid (FA) supplementation in mother-child pairs.

Methods: We studied ∼200 mother-child pairs from the Mexican PROGRESS cohort, with 43 MDCs measured during pregnancy (estimated air pollutants, blood/urine metals or metalloids, urine high- and low-molecular-weight phthalate [HMWPs, LMWPs] and organophosphate-pesticide metabolites), and serum liver enzymes (ALT, AST) at ∼9 years post-parturition.

Estimating the effect of annual PM exposure on mortality in India: a difference-in-differences approach.

Background: In 2019, the Global Burden of Diseases, Injuries, and Risk Factors Study attributed 0·98 million deaths to ambient air pollution in India based on potentially inappropriate exposure-response functions from countries with low air pollution levels. Instead, using data from India, we investigated long-term exposure to PM and all-cause mortality with a causal inference method.

Methods: We collected national counts of annual mortality from 2009 to 2019 from the Civil Registration System at the district level to calculate annual district-level mortality rate as our main outcome and obtained annual PM concentrations from a high-resolution spatiotemporal model.

Nationwide analysis of air pollution hotspots across India: A spatiotemporal PM trend analysis (2008-2019).

Introduction: India experiences high levels of air pollution as measured by fine particulate matter <2.5 μm (PM) across the country. With limited resources, it is imperative to identify the most impacted areas.

Residential food environment and dietary antioxidant consumption among pregnant women: Modifying effects of socioeconomic factors and ethnic identity.

Background: Residential food environment influences dietary patterns, however the impact of individuals' perceived social identity on their antioxidant intake, an indicator of healthy dietary patterns, remains underexplored.

Objective: We conducted a cross-sectional analysis using data collected in a longitudinal cohort. In the study, we aimed to investigate the interactions between the food environment and two indicators of social identity, specifically a subjective ladder measure of socioeconomic status (SES) and the Multigroup Ethnic Identity Measure (MEIM) score, in relation to dietary antioxidant intake (DAI) among n = 512 Boston and NYC-resident pregnant women.

Ambient temperature exposure and rapid infant weight gain.

Background: Childhood obesity is a major public health concern, and the global rate is rising. Rapid infant weight gain is a risk factor for later overweight. Studies have linked prenatal ambient temperature exposure to fetal growth, and preliminary evidence suggests postnatal exposure may be associated with infant weight gain.

The use of time-dynamic patterns of temperature and flexible generalized models to clarify the relations between temperature and semen quality.

Background: Sperm quality has decreased over the last decades worldwide. It is affected, among others, by season and heat. This study aimed to address the association between ambient temperature and sperm quality by assessing its shape using flexible multivariate models and identifying distinct time-dynamic patterns of temperature change based on unsupervised analysis.

Beyond lung cancer: air pollution and bladder, breast and prostate cancer incidence.

Background: The carcinogenicity of air pollution and its impact on the risk of lung cancer is well known; however, there are still knowledge gaps and mixed results for other sites of cancer.

Methods: The current study aimed to evaluate the associations between ambient air pollution [fine particulate matter (PM2.5) and nitrogen oxides (NOx)] and cancer incidence.

Ambient air pollution and daily mortality in ten cities of India: a causal modelling study.

Background: The evidence for acute effects of air pollution on mortality in India is scarce, despite the extreme concentrations of air pollution observed. This is the first multi-city study in India that examines the association between short-term exposure to PM and daily mortality using causal methods that highlight the importance of locally generated air pollution.

Methods: We applied a time-series analysis to ten cities in India between 2008 and 2019.

Metabolism-Disrupting Chemical Mixtures during Pregnancy, Folic Acid Supplementation, and Liver Injury in Mother-Child Pairs.

Background And Aims: Scarce knowledge about the impact of metabolism-disrupting chemicals (MDCs) on liver injury limits opportunities for intervention. We evaluated pregnancy MDC-mixture associations with liver injury and effect modification by folic acid (FA) supplementation in mother-child pairs.

Methods: We studied ∼200 mother-child pairs from the Mexican PROGRESS cohort, with measured 43 MDCs during pregnancy (estimated air pollutants, blood/urine metals or metalloids, urine high- and low-molecular-weight phthalate [HMWPs, LMWPs] and organophosphate-pesticide [OP] metabolites), and serum liver enzymes (ALT, AST) at ∼9 years post-parturition.

A multi-resolution ensemble model of three decision-tree-based algorithms to predict daily NO concentration in France 2005-2022.

Understanding and managing the health effects of Nitrogen Dioxide (NO) requires high resolution spatiotemporal exposure maps. Here, we developed a multi-stage multi-resolution ensemble model that predicts daily NO concentration across continental France from 2005 to 2022. Innovations of this work include the computation of daily predictions at a 200 m resolution in large urban areas and the use of a spatio-temporal blocking procedure to avoid data leakage and ensure fair performance estimation.

Relative humidity, temperature, and hypertensive disorders of pregnancy: Findings from the Project Viva cohort.

Background: Preeclampsia is a multi-system hypertensive disorder of pregnancy that is a leading cause of maternal and fetal morbidity and mortality. Prior studies disagree on the cause and even the presence of seasonal patterns in its incidence. Using unsuitable time windows for seasonal exposures can bias model results, potentially explaining these inconsistencies.

Placental DNA methylation signatures of prenatal air pollution exposure and potential effects on birth outcomes: an analysis of three prospective cohorts.

Background: Pregnancy air pollution exposure (PAPE) has been linked to a wide range of adverse birth and childhood outcomes, but there is a paucity of data on its influence on the placental epigenome, which can regulate the programming of physiological functions and affect child development. This study aimed to investigate the association between prenatal air pollutant exposure concentrations and changes in placental DNA methylation patterns, and to explore the potential windows of susceptibility and sex-specific alterations.

Methods: This multi-site study used three prospective population-based mother-child cohorts: EDEN, PELAGIE, and SEPAGES, originating from four French geographical regions (Nancy, Poitiers, Brittany, and Grenoble).

Modelling Europe-wide fine resolution daily ambient temperature for 2003-2020 using machine learning.

To improve our understanding of the health impacts of high and low temperatures, epidemiological studies require spatiotemporally resolved ambient temperature (Ta) surfaces. Exposure assessment over various European cities for multi-cohort studies requires high resolution and harmonized exposures over larger spatiotemporal extents. Our aim was to develop daily mean, minimum and maximum ambient temperature surfaces with a 1 × 1 km resolution for Europe for the 2003-2020 period.

Nationwide estimation of daily ambient PM from 2008 to 2020 at 1 km in India using an ensemble approach.

High-resolution assessment of historical levels is essential for assessing the health effects of ambient air pollution in the large Indian population. The diversity of geography, weather patterns, and progressive urbanization, combined with a sparse ground monitoring network makes it challenging to accurately capture the spatiotemporal patterns of ambient fine particulate matter (PM) pollution in India. We developed a model for daily average ambient PM between 2008 and 2020 based on monitoring data, meteorology, land use, satellite observations, and emissions inventories.

Coarse Particulate Matter and Markers of Inflammation and Coagulation in the Multi-Ethnic Study of Atherosclerosis (MESA) Population: A Repeat Measures Analysis.

Background: In contrast to fine particles, less is known of the inflammatory and coagulation impacts of coarse particulate matter (, particulate matter with aerodynamic diameter ). Toxicological research suggests that these pathways might be important processes by which impacts health, but there are relatively few epidemiological studies due to a lack of a national monitoring network.

Objectives: We used new spatiotemporal exposure models to examine associations of both 1-y and 1-month average concentrations with markers of inflammation and coagulation.

Individual and joint effects of prenatal PM and maternal stress on child temperament.

Prenatal fine particulate matter (PM) and maternal psychological functioning have been associated with child cognitive outcomes, though their independent and joint impacts on earlier behavioral outcomes remains less studied. We used data from 382 mother-child pairs from a prospective birth cohort in Mexico City. Temperament was measured at 24 months using the Carey Toddler Temperament Scale (TTS).

Association between prenatal and childhood PM exposure and preadolescent anxiety and depressive symptoms.

Background: Fine particulate matter (PM) exposure has been linked to anxiety and depression in adults; however, there is limited research in the younger populations, in which symptoms often first arise.

Methods: We examined the association between early-life PM exposure and symptoms of anxiety and depression in a cohort of 8-11-year-olds in Mexico City. Anxiety and depressive symptoms were assessed using the Spanish versions of the Revised Children's Manifest Anxiety Scale and Children's Depression Inventory.

Sensitive development windows of prenatal air pollution and cognitive functioning in preschool age Mexican children.

Introduction: Neurotoxicity resulting from air pollution is of increasing concern. Considering exposure timing effects on neurodevelopmental impairments may be as important as the exposure dose. We used distributed lag regression to determine the sensitive windows of prenatal exposure to fine particulate matter (PM) on children's cognition in a birth cohort in Mexico.