Using Parametric g-Computation for Time-to-Event Data and Distributed Lag Models to Identify Critical Exposure Windows for Preterm Birth: An Illustrative Example Using PM2.5 in a Retrospective Birth Cohort Based in Eastern Massachusetts (2011-2016).

BACKGROUND: Parametric g-computation is an attractive analytic framework to study the health effects of air pollution. Yet, the ability to explore biologically relevant exposure windows within this framework is underdeveloped. OBJECTIVES: We outline a novel framework for how to incorporate complex lag-responses using distributed lag models (DLMs) into parametric g-computation analyses for survival data. We call this approach "g-survival-DLM" and illustrate its use examining the association between PM2.5 during pregnancy and the risk of preterm birth (PTB). METHODS: We applied the g-survival-DLM approach to estimate the hypothetical static intervention of reducing average PM2.5 in each gestational week by 20% on the risk of PTB among 9,403 deliveries from Beth Israel Deaconess Medical Center, Boston, Massachusetts, 2011-2016. Daily PM2.5 was taken from a 1-km grid model and assigned to address at birth. Models were adjusted for sociodemographics, time trends, nitrogen dioxide, and temperature. To facilitate implementation, we provide a detailed description of the procedure and accompanying R syntax. RESULTS: There were 762 (8.1%) PTBs in this cohort. The gestational week-specific median PM2.5 concentration was relatively stable across pregnancy at ∼7µg/m3. We found that our hypothetical intervention strategy changed the cumulative risk of PTB at week 36 (i.e., the end of the preterm period) by -0.009 (95% confidence interval: -0.034, 0.007) in comparison with the scenario had we not intervened, which translates to about 86 fewer PTBs in this cohort. We also observed that the critical exposure window appeared to be weeks 5-20. DISCUSSION: We demonstrate that our g-survival-DLM approach produces easier-to-interpret, policy-relevant estimates (due to the g-computation); prevents immortal time bias (due to treating PTB as a time-to-event outcome); and allows for the exploration of critical exposure windows (due to the DLMs). In our illustrative example, we found that reducing fine particulate matter [particulate matter (PM) with aerodynamic diameter ≤2.5µm (PM2.5)] during gestational weeks 5-20 could potentially lower the risk of PTB. https://doi.org/10.1289/EHP13891.

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 PM2·5 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. We assessed city-wide daily PM2·5 concentrations using a novel hybrid nationwide spatiotemporal model and estimated city-specific effects of PM2·5 using a generalised additive Poisson regression model. City-specific results were then meta-analysed. We applied an instrumental variable causal approach (including planetary boundary layer height, wind speed, and atmospheric pressure) to evaluate the causal effect of locally generated air pollution on mortality. We obtained an integrated exposure-response curve through a multivariate meta-regression of the city-specific exposure-response curve and calculated the fraction of deaths attributable to air pollution concentrations exceeding the current WHO 24 h ambient PM2·5 guideline of 15 µg/m3. To explore the shape of the exposure-response curve at lower exposures, we further limited the analyses to days with concentrations lower than the current Indian standard (60 µg/m3). FINDINGS: We observed that a 10 µg/m3 increase in 2-day moving average of PM2·5 was associated with 1·4% (95% CI 0·7-2·2) higher daily mortality. In our causal instrumental variable analyses representing the effect of locally generated air pollution, we observed a stronger association with daily mortality (3·6% [2·1-5·0]) than our overall estimate. Our integrated exposure-response curve suggested steeper slopes at lower levels of exposure and an attenuation of the slope at high exposure levels. We observed two times higher risk of death per 10 µg/m3 increase when restricting our analyses to observations below the Indian air quality standard (2·7% [1·7-3·6]). Using the integrated exposure-response curve, we observed that 7·2% (4·2%-10·1%) of all daily deaths were attributed to PM2·5 concentrations higher than the WHO guidelines. INTERPRETATION: Short-term PM2·5 exposure was associated with a high risk of death in India, even at concentrations well below the current Indian PM2·5 standard. These associations were stronger for locally generated air pollutants quantified through causal modelling methods than conventional time-series analysis, further supporting a plausible causal link. FUNDING: Swedish Research Council for Sustainable Development.

All-cause, cardiovascular, and respiratory mortality and wildfire-related ozone: a multicountry two-stage time series analysis.

BACKGROUND: Wildfire activity is an important source of tropospheric ozone (O3) pollution. However, no study to date has systematically examined the associations of wildfire-related O3 exposure with mortality globally. METHODS: We did a multicountry two-stage time series analysis. From the Multi-City Multi-Country (MCC) Collaborative Research Network, data on daily all-cause, cardiovascular, and respiratory deaths were obtained from 749 locations in 43 countries or areas, representing overlapping periods from Jan 1, 2000, to Dec 31, 2016. We estimated the daily concentration of wildfire-related O3 in study locations using a chemical transport model, and then calibrated and downscaled O3 estimates to a resolution of 0·25°â€ˆ× 0·25° (approximately 28 km2 at the equator). Using a random-effects meta-analysis, we examined the associations of short-term wildfire-related O3 exposure (lag period of 0-2 days) with daily mortality, first at the location level and then pooled at the country, regional, and global levels. Annual excess mortality fraction in each location attributable to wildfire-related O3 was calculated with pooled effect estimates and used to obtain excess mortality fractions at country, regional, and global levels. FINDINGS: Between 2000 and 2016, the highest maximum daily wildfire-related O3 concentrations (≥30 µg/m3) were observed in locations in South America, central America, and southeastern Asia, and the country of South Africa. Across all locations, an increase of 1 µg/m3 in the mean daily concentration of wildfire-related O3 during lag 0-2 days was associated with increases of 0·55% (95% CI 0·29 to 0·80) in daily all-cause mortality, 0·44% (-0·10 to 0·99) in daily cardiovascular mortality, and 0·82% (0·18 to 1·47) in daily respiratory mortality. The associations of daily mortality rates with wildfire-related O3 exposure showed substantial geographical heterogeneity at the country and regional levels. Across all locations, estimated annual excess mortality fractions of 0·58% (95% CI 0·31 to 0·85; 31 606 deaths [95% CI 17 038 to 46 027]) for all-cause mortality, 0·41% (-0·10 to 0·91; 5249 [-1244 to 11 620]) for cardiovascular mortality, and 0·86% (0·18 to 1·51; 4657 [999 to 8206]) for respiratory mortality were attributable to short-term exposure to wildfire-related O3. INTERPRETATION: In this study, we observed an increase in all-cause and respiratory mortality associated with short-term wildfire-related O3 exposure. Effective risk and smoke management strategies should be implemented to protect the public from the impacts of wildfires. FUNDING: Australian Research Council and the Australian National Health and Medical Research Council.

Two Decades of Air Pollution Health Risk Assessment: Insights From the Use of WHO's AirQ and AirQ+ Tools.

Objectives: We evaluated studies that used the World Health Organization's (WHO) AirQ and AirQ+ tools for air pollution (AP) health risk assessment (HRA) and provided best practice suggestions for future assessments. Methods: We performed a comprehensive review of studies using WHO's AirQ and AirQ+ tools, searching several databases for relevant articles, reports, and theses from inception to Dec 31, 2022. Results: We identified 286 studies that met our criteria. The studies were conducted in 69 countries, with most (57%) in Iran, followed by Italy and India (∼8% each). We found that many studies inadequately report air pollution exposure data, its quality, and validity. The decisions concerning the analysed population size, health outcomes of interest, baseline incidence, concentration-response functions, relative risk values, and counterfactual values are often not justified, sufficiently. Many studies lack an uncertainty assessment. Conclusion: Our review found a number of common shortcomings in the published assessments. We suggest better practices and urge future studies to focus on the quality of input data, its reporting, and associated uncertainties.

Prenatal Exposure to Ambient Air Pollution and Cerebral Palsy.

Importance: Air pollution is associated with structural brain changes, disruption of neurogenesis, and neurodevelopmental disorders. The association between prenatal exposure to ambient air pollution and risk of cerebral palsy (CP), which is the most common motor disability in childhood, has not been thoroughly investigated. Objective: To evaluate the associations between prenatal residential exposure to ambient air pollution and risk of CP among children born at term gestation in a population cohort in Ontario, Canada. Design, Setting, and Participants: Population-based cohort study in Ontario, Canada using linked, province-wide health administrative databases. Participants were singleton full term births (≥37 gestational weeks) born in Ontario hospitals between April 1, 2002, and March 31, 2017. Data were analyzed from January to December 2022. Exposures: Weekly average concentrations of ambient fine particulate matter with a diameter 2.5 µm (PM2.5) or smaller, nitrogen dioxide (NO2), and ozone (O3) during pregnancy assigned by maternal residence reported at delivery from satellite-based estimates and ground-level monitoring data. Main outcome and measures: CP cases were ascertained by a single inpatient hospitalization diagnosis or at least 2 outpatient diagnoses for children from birth to age 18 years. Results: The present study included 1 587 935 mother-child pairs who reached term gestation, among whom 3170 (0.2%) children were diagnosed with CP. The study population had a mean (SD) maternal age of 30.1 (5.6) years and 811 745 infants (51.1%) were male. A per IQR increase (2.7 µg/m3) in prenatal ambient PM2.5 concentration was associated with a cumulative hazard ratio (CHR) of 1.12 (95% CI, 1.03-1.21) for CP. The CHR in male infants (1.14; 95% CI, 1.02-1.26) was higher compared with the CHR in female infants (1.08; 95% CI, 0.96-1.22). No specific window of susceptibility was found for prenatal PM2.5 exposure and CP in the study population. No associations or windows of susceptibility were found for prenatal NO2 or O3 exposure and CP risk. Conclusions and relevance: In this large cohort study of singleton full term births in Canada, prenatal ambient PM2.5 exposure was associated with an increased risk of CP in offspring. Further studies are needed to explore this association and its potential biological pathways, which could advance the identification of environmental risk factors of CP in early life.

Associations between Historical Redlining and the Risk of Pregnancy Complications and Adverse Birth Outcomes in Massachusetts, 1995-2015.

Objective: To assess the impact of historical redlining on the risk of pregnancy complications and adverse birth outcomes in Massachusetts (MA) from 1995 to 2015. Methods: In total, 288,787 pregnant people from the MA Birth Registry had information on parental characteristics, pregnancy factors, and redlining data at parental residences at the time of delivery. Historic redlining data were based on MA Home Owners' Loan Corporation (HOLC) security maps, with grades assigned (A "best," B "still desirable," C "definitely declining," and D "hazardous"). We used covariate-adjusted binomial regression models to examine associations between HOLC grade and each chronic condition and pregnancy/birth outcome. Results: Living in HOLC grades B through D compared with A was associated with an increased risk of entering pregnancy with chronic conditions and adverse pregnancy/birth outcomes. The strongest associations were seen with pregestational diabetes (adjusted risk ratio [RR] Grade D: 1.7, 95% confidence interval [CI]: 1.3, 2.4) and chronic hypertension (adjusted RR Grade D: 1.5, 95% CI: 1.1, 1.9). Conclusions: Historical redlining policies from the 1930s were associated with adverse pregnancy outcomes and chronic conditions; associations were strongest for chronic conditions in pregnancy.

Global and Regional Cardiovascular Mortality Attributable to Nonoptimal Temperatures Over Time.

BACKGROUND: The association between nonoptimal temperatures and cardiovascular mortality risk is recognized. However, a comprehensive global assessment of this burden is lacking. OBJECTIVES: The goal of this study was to assess global cardiovascular mortality burden attributable to nonoptimal temperatures and investigate spatiotemporal trends. METHODS: Using daily cardiovascular deaths and temperature data from 32 countries, a 3-stage analytical approach was applied. First, location-specific temperature-mortality associations were estimated, considering nonlinearity and delayed effects. Second, a multivariate meta-regression model was developed between location-specific effect estimates and 5 meta-predictors. Third, cardiovascular deaths associated with nonoptimal, cold, and hot temperatures for each global grid (55 km × 55 km resolution) were estimated, and temporal trends from 2000 to 2019 were explored. RESULTS: Globally, 1,801,513 (95% empirical CI: 1,526,632-2,202,831) annual cardiovascular deaths were associated with nonoptimal temperatures, constituting 8.86% (95% empirical CI: 7.51%-12.32%) of total cardiovascular mortality corresponding to 26 deaths per 100,000 population. Cold-related deaths accounted for 8.20% (95% empirical CI: 6.74%-11.57%), whereas heat-related deaths accounted for 0.66% (95% empirical CI: 0.49%-0.98%). The mortality burden varied significantly across regions, with the highest excess mortality rates observed in Central Asia and Eastern Europe. From 2000 to 2019, cold-related excess death ratios decreased, while heat-related ratios increased, resulting in an overall decline in temperature-related deaths. Southeastern Asia, Sub-Saharan Africa, and Oceania observed the greatest reduction, while Southern Asia experienced an increase. The Americas and several regions in Asia and Europe displayed fluctuating temporal patterns. CONCLUSIONS: Nonoptimal temperatures substantially contribute to cardiovascular mortality, with heterogeneous spatiotemporal patterns. Effective mitigation and adaptation strategies are crucial, especially given the increasing heat-related cardiovascular deaths amid climate change.

Air pollution from biomass burning disrupts early adolescent cortical microarchitecture development.

Exposure to outdoor particulate matter (PM2.5) represents a ubiquitous threat to human health, and particularly the neurotoxic effects of PM2.5 from multiple sources may disrupt neurodevelopment. Studies addressing neurodevelopmental implications of PM exposure have been limited by small, geographically limited samples and largely focus either on macroscale cortical morphology or postmortem histological staining and total PM mass. Here, we leverage residentially assigned exposure to six, data-driven sources of PM2.5 and neuroimaging data from the longitudinal Adolescent Brain Cognitive Development Study (ABCD Study®), collected from 21 different recruitment sites across the United States. To contribute an interpretable and actionable assessment of the role of air pollution in the developing brain, we identified alterations in cortical microstructure development associated with exposure to specific sources of PM2.5 using multivariate, partial least squares analyses. Specifically, average annual exposure (i.e., at ages 8-10 years) to PM2.5 from biomass burning was related to differences in neurite development across the cortex between 9 and 13 years of age.

Extreme Temperatures and Stroke Mortality: Evidence From a Multi-Country Analysis.

BACKGROUND: Extreme temperatures contribute significantly to global mortality. While previous studies on temperature and stroke-specific outcomes presented conflicting results, these studies were predominantly limited to single-city or single-country analyses. Their findings are difficult to synthesize due to variations in methodologies and exposure definitions. METHODS: Within the Multi-Country Multi-City Network, we built a new mortality database for ischemic and hemorrhagic stroke. Applying a unified analysis protocol, we conducted a multinational case-crossover study on the relationship between extreme temperatures and stroke. In the first stage, we fitted a conditional quasi-Poisson regression for daily mortality counts with distributed lag nonlinear models for temperature exposure separately for each city. In the second stage, the cumulative risk from each city was pooled using mixed-effect meta-analyses, accounting for clustering of cities with similar features. We compared temperature-stroke associations across country-level gross domestic product per capita. We computed excess deaths in each city that are attributable to the 2.5% hottest and coldest of days based on each city's temperature distribution. RESULTS: We collected data for a total of 3 443 969 ischemic strokes and 2 454 267 hemorrhagic stroke deaths from 522 cities in 25 countries. For every 1000 ischemic stroke deaths, we found that extreme cold and hot days contributed 9.1 (95% empirical CI, 8.6-9.4) and 2.2 (95% empirical CI, 1.9-2.4) excess deaths, respectively. For every 1000 hemorrhagic stroke deaths, extreme cold and hot days contributed 11.2 (95% empirical CI, 10.9-11.4) and 0.7 (95% empirical CI, 0.5-0.8) excess deaths, respectively. We found that countries with low gross domestic product per capita were at higher risk of heat-related hemorrhagic stroke mortality than countries with high gross domestic product per capita (P=0.02). CONCLUSIONS: Both extreme cold and hot temperatures are associated with an increased risk of dying from ischemic and hemorrhagic strokes. As climate change continues to exacerbate these extreme temperatures, interventional strategies are needed to mitigate impacts on stroke mortality, particularly in low-income countries.

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. OBJECTIVES: We aimed to investigate humidity and temperature as possible causes for seasonal trends in preeclampsia in Project Viva, a prebirth cohort in Boston, Massachusetts, considering only exposure windows that precede disease onset. METHODS: Using the Parameter-elevation Relationships on Independent Slopes Model (PRISM) Climate Dataset, we estimated daily residential temperature and relative humidity (RH) exposures during pregnancy. Our primary multinomial regression adjusted for person-level covariates and season. Secondary analyses included distributed lag models (DLMs) and adjusted for ambient air pollutants including fine particulates (PM2.5). We used Generalized Additive Mixed Models (GAMMs) for systolic blood pressure (SBP) trajectories across hypertensive disorder statuses to confirm exposure timing. RESULTS: While preeclampsia is typically diagnosed late in pregnancy, GAMM-fitted SBP trajectories for preeclamptic and non-preeclamptic women began to diverge at around 20 weeks' gestation, confirming the need to only consider early exposures. In the primary analysis with 1776 women, RH in the early second trimester, weeks 14-20, was associated with significantly higher odds of preeclampsia (OR per IQR increase: 1.81, 95% CI: 1.10, 2.97). The DLM corroborated this window, finding a positive association from weeks 12-20. There were no other significant associations between RH or temperature and preeclampsia or gestational hypertension in any other time period. DISCUSSION: The association between preeclampsia and RH in the early second trimester was robust to model choice, suggesting that RH may contribute to seasonal trends in preeclampsia incidence. Differences between these results and those of prior studies could be attributable to exposure timing differences.

Air pollution from biomass burning disrupts early adolescent cortical microarchitecture development.

Exposure to outdoor particulate matter (PM 2.5 ) represents a ubiquitous threat to human health, and particularly the neurotoxic effects of PM 2.5 from multiple sources may disrupt neurodevelopment. Studies addressing neurodevelopmental implications of PM exposure have been limited by small, geographically limited samples and largely focus either on macroscale cortical morphology or postmortem histological staining and total PM mass. Here, we leverage residentially assigned exposure to six, data-driven sources of PM 2.5 and neuroimaging data from the longitudinal Adolescent Brain Cognitive Development Study (ABCD Study®), collected from 21 different recruitment sites across the United States. To contribute an interpretable and actionable assessment of the role of air pollution in the developing brain, we identified alterations in cortical microstructure development associated with exposure to specific sources of PM 2.5 using multivariate, partial least squares analyses. Specifically, average annual exposure (i.e., at ages 8-10 years) to PM 2.5 from biomass burning was related to differences in neurite development across the cortex between 9 and 13 years of age.

SARS-CoV-2, periodontal pathogens, and host factors: The trinity of oral post-acute sequelae of COVID-19.

COVID-19 as a pan-epidemic is waning but there it is imperative to understand virus interaction with oral tissues and oral inflammatory diseases. We review periodontal disease (PD), a common inflammatory oral disease, as a driver of COVID-19 and oral post-acute-sequelae conditions (PASC). Oral PASC identifies with PD, loss of teeth, dysgeusia, xerostomia, sialolitis-sialolith, and mucositis. We contend that PD-associated oral microbial dysbiosis involving higher burden of periodontopathic bacteria provide an optimal microenvironment for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. These pathogens interact with oral epithelial cells activate molecular or biochemical pathways that promote viral adherence, entry, and persistence in the oral cavity. A repertoire of diverse molecules identifies this relationship including lipids, carbohydrates and enzymes. The S protein of SARS-CoV-2 binds to the ACE2 receptor and is activated by protease activity of host furin or TRMPSS2 that cleave S protein subunits to promote viral entry. However, PD pathogens provide additional enzymatic assistance mimicking furin and augment SARS-CoV-2 adherence by inducing viral entry receptors ACE2/TRMPSS, which are poorly expressed on oral epithelial cells. We discuss the mechanisms involving periodontopathogens and host factors that facilitate SARS-CoV-2 infection and immune resistance resulting in incomplete clearance and risk for 'long-haul' oral health issues characterising PASC. Finally, we suggest potential diagnostic markers and treatment avenues to mitigate oral PASC.

Global, regional, and national burden of heatwave-related mortality from 1990 to 2019: A three-stage modelling study.

BACKGROUND: The regional disparity of heatwave-related mortality over a long period has not been sufficiently assessed across the globe, impeding the localisation of adaptation planning and risk management towards climate change. We quantified the global mortality burden associated with heatwaves at a spatial resolution of 0.5°×0.5° and the temporal change from 1990 to 2019. METHODS AND FINDINGS: We collected data on daily deaths and temperature from 750 locations of 43 countries or regions, and 5 meta-predictors in 0.5°×0.5° resolution across the world. Heatwaves were defined as location-specific daily mean temperature ≥95th percentiles of year-round temperature range with duration ≥2 days. We first estimated the location-specific heatwave-mortality association. Secondly, a multivariate meta-regression was fitted between location-specific associations and 5 meta-predictors, which was in the third stage used with grid cell-specific meta-predictors to predict grid cell-specific association. Heatwave-related excess deaths were calculated for each grid and aggregated. During 1990 to 2019, 0.94% (95% CI: 0.68-1.19) of deaths [i.e., 153,078 cases (95% eCI: 109,950-194,227)] per warm season were estimated to be from heatwaves, accounting for 236 (95% eCI: 170-300) deaths per 10 million residents. The ratio between heatwave-related excess deaths and all premature deaths per warm season remained relatively unchanged over the 30 years, while the number of heatwave-related excess deaths per 10 million residents per warm season declined by 7.2% per decade in comparison to the 30-year average. Locations with the highest heatwave-related death ratio and rate were in Southern and Eastern Europe or areas had polar and alpine climates, and/or their residents had high incomes. The temporal change of heatwave-related mortality burden showed geographic disparities, such that locations with tropical climate or low incomes were observed with the greatest decline. The main limitation of this study was the lack of data from certain regions, e.g., Arabian Peninsula and South Asia. CONCLUSIONS: Heatwaves were associated with substantial mortality burden that varied spatiotemporally over the globe in the past 30 years. The findings indicate the potential benefit of governmental actions to enhance health sector adaptation and resilience, accounting for inequalities across communities.

Ambient fine particulate matter and daily mortality: a comparative analysis of observed and estimated exposure in 347 cities.

BACKGROUND: Model-estimated air pollution exposure products have been widely used in epidemiological studies to assess the health risks of particulate matter with diameters of ≤2.5 µm (PM2.5). However, few studies have assessed the disparities in health effects between model-estimated and station-observed PM2.5 exposures. METHODS: We collected daily all-cause, respiratory and cardiovascular mortality data in 347 cities across 15 countries and regions worldwide based on the Multi-City Multi-Country collaborative research network. The station-observed PM2.5 data were obtained from official monitoring stations. The model-estimated global PM2.5 product was developed using a machine-learning approach. The associations between daily exposure to PM2.5 and mortality were evaluated using a two-stage analytical approach. RESULTS: We included 15.8 million all-cause, 1.5 million respiratory and 4.5 million cardiovascular deaths from 2000 to 2018. Short-term exposure to PM2.5 was associated with a relative risk increase (RRI) of mortality from both station-observed and model-estimated exposures. Every 10-µg/m3 increase in the 2-day moving average PM2.5 was associated with overall RRIs of 0.67% (95% CI: 0.49 to 0.85), 0.68% (95% CI: -0.03 to 1.39) and 0.45% (95% CI: 0.08 to 0.82) for all-cause, respiratory, and cardiovascular mortality based on station-observed PM2.5 and RRIs of 0.87% (95% CI: 0.68 to 1.06), 0.81% (95% CI: 0.08 to 1.55) and 0.71% (95% CI: 0.32 to 1.09) based on model-estimated exposure, respectively. CONCLUSIONS: Mortality risks associated with daily PM2.5 exposure were consistent for both station-observed and model-estimated exposures, suggesting the reliability and potential applicability of the global PM2.5 product in epidemiological studies.

The association of short-term increases in ambient PM2.5 and temperature exposures with stillbirth: racial/ethnic disparities among Medicaid recipients.

Racial/ethnic disparities in the association between short-term (e.g. days, weeks) ambient fine particulate matter (PM2.5) and temperature exposures and stillbirth in the US have been understudied. A time-stratified, case-crossover design using a distributed lag non-linear model (0 to 6-day lag) estimated stillbirth odds due to short-term increases in average daily PM2.5 and temperature exposures among 118,632 Medicaid recipients from 2000-2014. Disparities by maternal race/ethnicity (Black, White, Hispanic, Asian, American Indian) and zip-code level socioeconomic status (SES) were assessed. In the temperature-adjusted model, a 10 µg/m3 increase in PM2.5 concentration was marginally associated with increased stillbirth odds at lag 1 (0.68% 95%CI:[-0.04,1.40]) and lag 2 (0.52% 95%CI:[-0.03,1.06]), but not lag 0-6 (2.80% 95%CI:[-0.81,6.45]). An association between daily PM2.5 concentrations and stillbirth odds was found among Black individuals at the cumulative lag (0-6 days: 9.26% 95%CI:[3.12,15.77]), but not among other races/ethnicities. A stronger association between PM2.5 concentrations and stillbirth odds existed among Black individuals living in zip codes with the lowest median household income (lag0-6:14.13% 95%CI:[4.64,25.79]). Short-term temperature increases were not associated with stillbirth risk among any race/ethnicity. Black Medicaid enrollees, and especially those living in lower SES areas, may be more vulnerable to stillbirth due to short-term increases in PM2.5 exposure.

Comparison for the effects of different components of temperature variability on mortality: A multi-country time-series study.

BACKGROUND: Temperature variability (TV) is associated with increased mortality risk. However, it is still unknown whether intra-day or inter-day TV has different effects. OBJECTIVES: We aimed to assess the association of intra-day TV and inter-day TV with all-cause, cardiovascular, and respiratory mortality. METHODS: We collected data on total, cardiovascular, and respiratory mortality and meteorology from 758 locations in 47 countries or regions from 1972 to 2020. We defined inter-day TV as the standard deviation (SD) of daily mean temperatures across the lag interval, and intra-day TV as the average SD of minimum and maximum temperatures on each day. In the first stage, inter-day and intra-day TVs were modelled simultaneously in the quasi-Poisson time-series model for each location. In the second stage, a multi-level analysis was used to pool the location-specific estimates. RESULTS: Overall, the mortality risk due to each interquartile range [IQR] increase was higher for intra-day TV than for inter-day TV. The risk increased by 0.59% (95% confidence interval [CI]: 0.53, 0.65) for all-cause mortality, 0.64% (95% CI: 0.56, 0.73) for cardiovascular mortality, and 0.65% (95% CI: 0.49, 0.80) for respiratory mortality per IQR increase in intra-day TV0-7 (0.9 °C). An IQR increase in inter-day TV0-7 (1.6 °C) was associated with 0.22% (95% CI: 0.18, 0.26) increase in all-cause mortality, 0.44% (95% CI: 0.37, 0.50) increase in cardiovascular mortality, and 0.31% (95% CI: 0.21, 0.41) increase in respiratory mortality. The proportion of all-cause deaths attributable to intra-day TV0-7 and inter-day TV0-7 was 1.45% and 0.35%, respectively. The mortality risks varied by lag interval, climate area, season, and climate type. CONCLUSIONS: Our results indicated that intra-day TV may explain the main part of the mortality risk related to TV and suggested that comprehensive evaluations should be proposed in more countries to help protect human health.

Grouped mixtures of air pollutants and seasonal temperature anomalies and cardiovascular hospitalizations among U.S. Residents.

BACKGROUND: Air pollution is a recognized risk factor for cardiovascular disease (CVD). Temperature is also linked to CVD, with a primary focus on acute effects. Despite the close relationship between air pollution and temperature, their health effects are often examined separately, potentially overlooking their synergistic effects. Moreover, fewer studies have performed mixture analysis for multiple co-exposures, essential for adjusting confounding effects among them and assessing both cumulative and individual effects. METHODS: We obtained hospitalization records for residents of 14 U.S. states, spanning 2000-2016, from the Health Cost and Utilization Project State Inpatient Databases. We used a grouped weighted quantile sum regression, a novel approach for mixture analysis, to simultaneously evaluate cumulative and individual associations of annual exposures to four grouped mixtures: air pollutants (elemental carbon, ammonium, nitrate, organic carbon, sulfate, nitrogen dioxide, ozone), differences between summer and winter temperature means and their long-term averages during the entire study period (i.e., summer and winter temperature mean anomalies), differences between summer and winter temperature standard deviations (SD) and their long-term averages during the entire study period (i.e., summer and winter temperature SD anomalies), and interaction terms between air pollutants and summer and winter temperature mean anomalies. The outcomes are hospitalization rates for four prevalent CVD subtypes: ischemic heart disease, cerebrovascular disease, heart failure, and arrhythmia. RESULTS: Chronic exposure to air pollutant mixtures was associated with increased hospitalization rates for all CVD subtypes, with heart failure being the most susceptible subtype. Sulfate, nitrate, nitrogen dioxide, and organic carbon posed the highest risks. Mixtures of the interaction terms between air pollutants and temperature mean anomalies were associated with increased hospitalization rates for all CVD subtypes. CONCLUSIONS: Our findings identified critical pollutants for targeted emission controls and suggested that abnormal temperature changes chronically affected cardiovascular health by interacting with air pollution, not directly.

Longitudinal associations between ambient PM2.5 exposure and lipid levels in two Indian cities.

Background: Exposure to ambient PM2.5 is known to affect lipid metabolism through systemic inflammation and oxidative stress. Evidence from developing countries, such as India with high levels of ambient PM2.5 and distinct lipid profiles, is sparse. Methods: Longitudinal nonlinear mixed-effects analysis was conducted on >10,000 participants of Centre for cArdiometabolic Risk Reduction in South Asia (CARRS) cohort in Chennai and Delhi, India. We examined associations between 1-month and 1-year average ambient PM2.5 exposure derived from the spatiotemporal model and lipid levels (total cholesterol [TC], triglycerides [TRIG], high-density lipoprotein cholesterol [HDL-C], and low-density lipoprotein cholesterol [LDL-C]) measured longitudinally, adjusting for residential and neighborhood-level confounders. Results: The mean annual exposure in Chennai and Delhi was 40 and 102 µg/m3 respectively. Elevated ambient PM2.5 levels were associated with an increase in LDL-C and TC at levels up to 100 µg/m3 in both cities and beyond 125 µg/m3 in Delhi. TRIG levels in Chennai increased until 40 µg/m3 for both short- and long-term exposures, then stabilized or declined, while in Delhi, there was a consistent rise with increasing annual exposures. HDL-C showed an increase in both cities against monthly average exposure. HDL-C decreased slightly in Chennai with an increase in long-term exposure, whereas it decreased beyond 130 µg/m3 in Delhi. Conclusion: These findings demonstrate diverse associations between a wide range of ambient PM2.5 and lipid levels in an understudied South Asian population. Further research is needed to establish causality and develop targeted interventions to mitigate the impact of air pollution on lipid metabolism and cardiovascular health.

Associations between long-term exposure to air pollution and kidney function utilizing electronic healthcare records: a cross-sectional study.

BACKGROUND: Chronic kidney disease (CKD) affects more than 38 million people in the United States, predominantly those over 65 years of age. While CKD etiology is complex, recent research suggests associations with environmental exposures. METHODS: Our primary objective is to examine creatinine-based estimated glomerular filtration rate (eGFRcr) and diagnosis of CKD and potential associations with fine particulate matter (PM2.5), ozone (O3), and nitrogen dioxide (NO2) using a random sample of North Carolina electronic healthcare records (EHRs) from 2004 to 2016. We estimated eGFRcr using the serum creatinine-based 2021 CKD-EPI equation. PM2.5 and NO2 data come from a hybrid model using 1 km2 grids and O3 data from 12 km2 CMAQ grids. Exposure concentrations were 1-year averages. We used linear mixed models to estimate eGFRcr per IQR increase of pollutants. We used multiple logistic regression to estimate associations between pollutants and first appearance of CKD. We adjusted for patient sex, race, age, comorbidities, temporality, and 2010 census block group variables. RESULTS: We found 44,872 serum creatinine measurements among 7,722 patients. An IQR increase in PM2.5 was associated with a 1.63 mL/min/1.73m2 (95% CI: -1.96, -1.31) reduction in eGFRcr, with O3 and NO2 showing positive associations. There were 1,015 patients identified with CKD through e-phenotyping and ICD codes. None of the environmental exposures were positively associated with a first-time measure of eGFRcr < 60 mL/min/1.73m2. NO2 was inversely associated with a first-time diagnosis of CKD with aOR of 0.77 (95% CI: 0.66, 0.90). CONCLUSIONS: One-year average PM2.5 was associated with reduced eGFRcr, while O3 and NO2 were inversely associated. Neither PM2.5 or O3 were associated with a first-time identification of CKD, NO2 was inversely associated. We recommend future research examining the relationship between air pollution and impaired renal function.