Disparities in air pollution attributable mortality in the US population by race/ethnicity and sociodemographic factors.

There are large differences in premature mortality in the USA by race/ethnicity, education, rurality and social vulnerability index groups. Using existing concentration-response functions, published particulate matter (PM2.5) air pollution estimates, population estimates at the census tract level and county-level mortality data from the US National Vital Statistics System, we estimated the degree to which these mortality discrepancies can be attributed to differences in exposure and susceptibility to PM2.5. We show that differences in PM2.5-attributable mortality were consistently more pronounced by race/ethnicity than by education, rurality or social vulnerability index, with the Black American population having the highest proportion of deaths attributable to PM2.5 in all years from 1990 to 2016. Our model estimates that over half of the difference in age-adjusted all-cause mortality between the Black American and non-Hispanic white population was attributable to PM2.5 in the years 2000 to 2011. This difference decreased only marginally between 2000 and 2015, from 53.4% (95% confidence interval 51.2-55.9%) to 49.9% (95% confidence interval 47.8-52.2%), respectively. Our findings underscore the need for targeted air quality interventions to address environmental health disparities.

Sociodemographic and geographic variation in mortality attributable to air pollution in the United States.

There are large differences in premature mortality in the USA by racial/ethnic, education, rurality, and social vulnerability index groups. Using existing concentration-response functions, particulate matter (PM2.5) air pollution, population estimates at the tract level, and county-level mortality data, we estimated the degree to which these mortality discrepancies can be attributed to differences in exposure and susceptibility to PM2.5. We show that differences in mortality attributable to PM2.5 were consistently more pronounced between racial/ethnic groups than by education, rurality, or social vulnerability index, with the Black American population having by far the highest proportion of deaths attributable to PM2.5 in all years from 1990 to 2016. Over half of the difference in age-adjusted all-cause mortality between the Black American and non-Hispanic White population was attributable to PM2.5 in the years 2000 to 2011.

Health Effects of Wildfire Smoke Exposure.

We review current knowledge on the trends and drivers of global wildfire activity, advances in the measurement of wildfire smoke exposure, and evidence on the health effects of this exposure. We describe methodological issues in estimating the causal effects of wildfire smoke exposures on health and quantify their importance, emphasizing the role of nonlinear and lagged effects. We conduct a systematic review and meta-analysis of the health effects of wildfire smoke exposure, finding positive impacts on all-cause mortality and respiratory hospitalizations but less consistent evidence on cardiovascular morbidity. We conclude by highlighting priority areas for future research, including leveraging recently developed spatially and temporally resolved wildfire-specific ambient air pollution data to improve estimates of the health effects of wildfire smoke exposure.

Global population profile of tropical cyclone exposure from 2002 to 2019.

Tropical cyclones have far-reaching impacts on livelihoods and population health that often persist years after the event1-4. Characterizing the demographic and socioeconomic profile and the vulnerabilities of exposed populations is essential to assess health and other risks associated with future tropical cyclone events5. Estimates of exposure to tropical cyclones are often regional rather than global6 and do not consider population vulnerabilities7. Here we combine spatially resolved annual demographic estimates with tropical cyclone wind fields estimates to construct a global profile of the populations exposed to tropical cyclones between 2002 and 2019. We find that approximately 560 million people are exposed yearly and that the number of people exposed has increased across all cyclone intensities over the study period. The age distribution of those exposed has shifted away from children (less than 5 years old) and towards older people (more than 60 years old) in recent years compared with the early 2000s. Populations exposed to tropical cyclones are more socioeconomically deprived than those unexposed within the same country, and this relationship is more pronounced for people exposed to higher-intensity storms. By characterizing the patterns and vulnerabilities of exposed populations, our results can help identify mitigation strategies and assess the global burden and future risks of tropical cyclones.

Quantifying fire-specific smoke exposure and health impacts.

Rapidly changing wildfire regimes across the Western United States have driven more frequent and severe wildfires, resulting in wide-ranging societal threats from wildfires and wildfire-generated smoke. However, common measures of fire severity focus on what is burned, disregarding the societal impacts of smoke generated from each fire. We combine satellite-derived fire scars, air parcel trajectories from individual fires, and predicted smoke PM2.5 to link source fires to resulting smoke PM2.5 and health impacts experienced by populations in the contiguous United States from April 2006 to 2020. We quantify fire-specific accumulated smoke exposure based on the cumulative population exposed to smoke PM2.5 over the duration of a fire and estimate excess asthma-related emergency department (ED) visits as a result of this exposure. We find that excess asthma visits attributable to each fire are only moderately correlated with common measures of wildfire severity, including burned area, structures destroyed, and suppression cost. Additionally, while recent California fires contributed nearly half of the country's smoke-related excess asthma ED visits during our study period, the most severe individual fire was the 2007 Bugaboo fire in the Southeast. We estimate that a majority of smoke PM2.5 comes from sources outside the local jurisdictions where the smoke is experienced, with 87% coming from fires in other counties and 60% from fires in other states. Our approach could enable broad-scale assessment of whether specific fire characteristics affect smoke toxicity or impact, inform cost-effectiveness assessments for allocation of suppression resources, and help clarify the growing transboundary nature of local air quality.

The contribution of wildfire to PM2.5 trends in the USA.

Steady improvements in ambient air quality in the USA over the past several decades, in part a result of public policy1,2, have led to public health benefits1-4. However, recent trends in ambient concentrations of particulate matter with diameters less than 2.5 µm (PM2.5), a pollutant regulated under the Clean Air Act1, have stagnated or begun to reverse throughout much of the USA5. Here we use a combination of ground- and satellite-based air pollution data from 2000 to 2022 to quantify the contribution of wildfire smoke to these PM2.5 trends. We find that since at least 2016, wildfire smoke has influenced trends in average annual PM2.5 concentrations in nearly three-quarters of states in the contiguous USA, eroding about 25% of previous multi-decadal progress in reducing PM2.5 concentrations on average in those states, equivalent to 4 years of air quality progress, and more than 50% in many western states. Smoke influence on trends in the number of days with extreme PM2.5 concentrations is detectable by 2011, but the influence can be detected primarily in western and mid-western states. Wildfire-driven increases in ambient PM2.5 concentrations are unregulated under current air pollution law6 and, in the absence of further interventions, we show that the contribution of wildfire to regional and national air quality trends is likely to grow as the climate continues to warm.

Emergency department visits respond nonlinearly to wildfire smoke.

Air pollution negatively affects a range of health outcomes. Wildfire smoke is an increasingly important contributor to air pollution, yet wildfire smoke events are highly salient and could induce behavioral responses that alter health impacts. We combine geolocated data covering all emergency department (ED) visits to nonfederal hospitals in California from 2006 to 2017 with spatially resolved estimates of daily wildfire smoke PM[Formula: see text] concentrations and quantify how smoke events affect ED visits. Total ED visits respond nonlinearly to smoke concentrations. Relative to a day with no smoke, total visits increase by 1 to 1.5% in the week following low or moderate smoke days but decline by 6 to 9% following extreme smoke days. Reductions persist for at least a month. Declines at extreme levels are driven by diagnoses not thought to be acutely impacted by pollution, including accidental injuries and several nonurgent symptoms, and declines come disproportionately from less-insured populations. In contrast, health outcomes with the strongest physiological link to short-term air pollution increase dramatically in the week following an extreme smoke day: We estimate that ED visits for asthma, COPD, and cough all increase by 30 to 110%. Data from internet searches, vehicle traffic sensors, and park visits indicate behavioral changes on high smoke days consistent with declines in healthcare utilization. Because low and moderate smoke days vastly outweigh high smoke days, we estimate that smoke was responsible for an average of 3,010 (95% CI: 1,760-4,380) additional ED visits per year 2006 to 2017. Given the increasing intensity of wildfire smoke events, behavioral mediation is likely to play a growing role in determining total smoke impacts.

Infant and Neonatal Mortality During the Covid-19 Pandemic: An Interrupted Time Series Analysis From Five Low- and Middle-Income Countries.

Background: The Covid-19 pandemic led to widespread changes to health and social institutions. The effects of the pandemic on neonatal and infant health outcomes in low- and middle-income countries (LMICs) are poorly understood, and nationally representative data characterizing changes to health care and outcomes is only now emerging. Methods: We used nationally representative survey data with vital status and perinatal care information on 2,959,203 children born in India, Madagascar, Cambodia, Nepal, and the Philippines. Using interrupted time series models, we estimated the change in neonatal mortality (death in first 30 days of life) and infant mortality (death in first year of life) following the start of the Covid-19 pandemic, controlling for granular location fixed-effects and seasonality. Findings: We analyzed 2,935,052 births (146,820 deaths) before March 2020 and 24,151 births (799 deaths) after March 2020. We estimated that infant mortality increased by 9.9 deaths per 1,000 live births after March 2020 (95% CI 5.0, 15.0; p<0.01; 22% increase) and neonatal mortality increased by 6.7 deaths per 1,000 live births (95% CI 2.4, 11.1; p<0.01; 27% increase). We observe increased mortality in all study countries. We also estimated a 3.8 percentage point reduction in antenatal care use (95% CI -4.9, -2.7; p<0.01) and a 5.6 percentage point reduction in facility deliveries (95% CI -7.2, -4.0; p<0.01) during the pandemic. Interpretation: Since the start of the Covid-19 pandemic, neonatal and infant mortality are higher than expected in five LMICs. Helping LMICs resume pre-pandemic declines in neonatal and infant mortality should be a major global priority.

Global biomass fires and infant mortality.

Global outdoor biomass burning is a major contributor to air pollution, especially in low- and middle-income countries. Recent years have witnessed substantial changes in the extent of biomass burning, including large declines in Africa. However, direct evidence of the contribution of biomass burning to global health outcomes remains limited. Here, we use georeferenced data on more than 2 million births matched to satellite-derived burned area exposure to estimate the burden of biomass fires on infant mortality. We find that each additional square kilometer of burning is associated with nearly 2% higher infant mortality in nearby downwind locations. The share of infant deaths attributable to biomass fires has increased over time due to the rapid decline in other important causes of infant death. Applying our model estimates across harmonized district-level data covering 98% of global infant deaths, we find that exposure to outdoor biomass burning was associated with nearly 130,000 additional infant deaths per year globally over our 2004 to 2018 study period. Despite the observed decline in biomass burning in Africa, nearly 75% of global infant deaths due to burning still occur in Africa. While fully eliminating biomass burning is unlikely, we estimate that even achievable reductions-equivalent to the lowest observed annual burning in each location during our study period-could have avoided more than 70,000 infant deaths per year globally since 2004.

Geographically resolved social cost of anthropogenic emissions accounting for both direct and climate-mediated effects.

The magnitude and distribution of physical and societal impacts from long-lived greenhouse gases are insensitive to the emission source location; the same is not true for major coemitted short-lived pollutants such as aerosols. Here, we combine novel global climate model simulations with established response functions to show that a given aerosol emission from different regions produces divergent air quality and climate changes and associated human system impacts, both locally and globally. The marginal global damages to infant mortality, crop productivity, and economic growth from aerosol emissions and their climate effects differ by more than an order of magnitude depending on source region, with certain regions creating global external climate changes and impacts much larger than those felt locally. The complex distributions of aerosol-driven societal impacts emerge from geographically distinct and region-specific aerosol-climate interactions, estimation of which is enabled by the full Earth System Modeling Framework used here.

Daily Local-Level Estimates of Ambient Wildfire Smoke PM2.5 for the Contiguous US.

Smoke from wildfires is a growing health risk across the US. Understanding the spatial and temporal patterns of such exposure and its population health impacts requires separating smoke-driven pollutants from non-smoke pollutants and a long time series to quantify patterns and measure health impacts. We develop a parsimonious and accurate machine learning model of daily wildfire-driven PM2.5 concentrations using a combination of ground, satellite, and reanalysis data sources that are easy to update. We apply our model across the contiguous US from 2006 to 2020, generating daily estimates of smoke PM2.5 over a 10 km-by-10 km grid and use these data to characterize levels and trends in smoke PM2.5. Smoke contributions to daily PM2.5 concentrations have increased by up to 5 µg/m3 in the Western US over the last decade, reversing decades of policy-driven improvements in overall air quality, with concentrations growing fastest for higher income populations and predominantly Hispanic populations. The number of people in locations with at least 1 day of smoke PM2.5 above 100 µg/m3 per year has increased 27-fold over the last decade, including nearly 25 million people in 2020 alone. Our data set can bolster efforts to comprehensively understand the drivers and societal impacts of trends and extremes in wildfire smoke.

Exposures and behavioural responses to wildfire smoke.

Pollution from wildfires constitutes a growing source of poor air quality globally. To protect health, governments largely rely on citizens to limit their own wildfire smoke exposures, but the effectiveness of this strategy is hard to observe. Using data from private pollution sensors, cell phones, social media posts and internet search activity, we find that during large wildfire smoke events, individuals in wealthy locations increasingly search for information about air quality and health protection, stay at home more and are unhappier. Residents of lower-income neighbourhoods exhibit similar patterns in searches for air quality information but not for health protection, spend less time at home and have more muted sentiment responses. During smoke events, indoor particulate matter (PM2.5) concentrations often remain 3-4× above health-based guidelines and vary by 20× between neighbouring households. Our results suggest that policy reliance on self-protection to mitigate smoke health risks will have modest and unequal benefits.

Associations between wildfire smoke exposure during pregnancy and risk of preterm birth in California.

There is limited population-scale evidence on the burden of exposure to wildfire smoke during pregnancy and its impacts on birth outcomes. In order to investigate this relationship, data on every singleton birth in California 2006-2012 were combined with satellite-based estimates of wildfire smoke plume boundaries and high-resolution gridded estimates of surface PM2.5 concentrations and a regression model was used to estimate associations with preterm birth risk. Results suggest that each additional day of exposure to any wildfire smoke during pregnancy was associated with an 0.49 % (95 % CI: 0.41-0.59 %) increase in risk of preterm birth (<37 weeks). At sample median smoke exposure (7 days) this translated to a 3.4 % increase in risk, relative to an unexposed mother. Estimates by trimester suggest stronger associations with exposure later in pregnancy and estimates by smoke intensity indicate that observed associations were driven by higher intensity smoke-days. Exposure to low intensity smoke-days had no association with preterm birth while an additional medium (smoke PM2.5 5-10 µg/m3) or high (smoke PM2.5 > 10 µg/m3) intensity smoke-day was associated with an 0.95 % (95 % CI: 0.47-1.42 %) and 0.82 % (95 % CI: 0.41-1.24 %) increase in preterm risk, respectively. In contrast to previous findings for other pollution types, neither exposure to smoke nor the relative impact of smoke on preterm birth differed by race/ethnicity or income in our sample. However, impacts differed greatly by baseline smoke exposure, with mothers in regions with infrequent smoke exposure experiencing substantially larger impacts from an additional smoke-day than mothers in regions where smoke is more common. We estimate 6,974 (95 % CI: 5,513-8,437) excess preterm births attributable to wildfire smoke exposure 2007-2012, accounting for 3.7 % of observed preterm births during this period. Our findings have important implications for understanding the costs of growing wildfire smoke exposure, and for understanding the benefits of smoke mitigation measures.

Fine Particulate Air Pollution, Early Life Stress, and Their Interactive Effects on Adolescent Structural Brain Development: A Longitudinal Tensor-Based Morphometry Study.

Air pollution is a major environmental threat to public health; we know little, however, about its effects on adolescent brain development. Exposure to air pollution co-occurs, and may interact, with social factors that also affect brain development, such as early life stress (ELS). Here, we show that severity of ELS and fine particulate air pollution (PM2.5) are associated with volumetric changes in distinct brain regions, but also uncover regions in which ELS moderates the effects of PM2.5. We interviewed adolescents about ELS events, used satellite-derived estimates of ambient PM2.5 concentrations, and conducted longitudinal tensor-based morphometry to assess regional changes in brain volume over an approximately 2-year period (N = 115, ages 9-13 years at Time 1). For adolescents who had experienced less severe ELS, PM2.5 was associated with volumetric changes across several gray and white matter regions. Fewer effects of PM2.5 were observed for adolescents who had experienced more severe ELS, although occasionally they were in the opposite direction. This pattern of results suggests that for many brain regions, moderate to severe ELS largely constrains the effects of PM2.5 on structural development. Further theory and research is needed on the joint effects of ELS and air pollution on the brain.

The effects of armed conflict on the health of women and children.

Women and children bear substantial morbidity and mortality as a result of armed conflicts. This Series paper focuses on the direct (due to violence) and indirect health effects of armed conflict on women and children (including adolescents) worldwide. We estimate that nearly 36 million children and 16 million women were displaced in 2017, on the basis of international databases of refugees and internally displaced populations. From geospatial analyses we estimate that the number of non-displaced women and children living dangerously close to armed conflict (within 50 km) increased from 185 million women and 250 million children in 2000, to 265 million women and 368 million children in 2017. Women's and children's mortality risk from non-violent causes increases substantially in response to nearby conflict, with more intense and more chronic conflicts leading to greater mortality increases. More than 10 million deaths in children younger than 5 years can be attributed to conflict between 1995 and 2015 globally. Women of reproductive ages living near high intensity conflicts have three times higher mortality than do women in peaceful settings. Current research provides fragmentary evidence about how armed conflict indirectly affects the survival chances of women and children through malnutrition, physical injuries, infectious diseases, poor mental health, and poor sexual and reproductive health, but major systematic evidence is sparse, hampering the design and implementation of essential interventions for mitigating the harms of armed conflicts.

The changing risk and burden of wildfire in the United States.

Recent dramatic and deadly increases in global wildfire activity have increased attention on the causes of wildfires, their consequences, and how risk from wildfire might be mitigated. Here we bring together data on the changing risk and societal burden of wildfire in the United States. We estimate that nearly 50 million homes are currently in the wildland-urban interface in the United States, a number increasing by 1 million houses every 3 y. To illustrate how changes in wildfire activity might affect air pollution and related health outcomes, and how these linkages might guide future science and policy, we develop a statistical model that relates satellite-based fire and smoke data to information from pollution monitoring stations. Using the model, we estimate that wildfires have accounted for up to 25% of PM2.5 (particulate matter with diameter <2.5 µm) in recent years across the United States, and up to half in some Western regions, with spatial patterns in ambient smoke exposure that do not follow traditional socioeconomic pollution exposure gradients. We combine the model with stylized scenarios to show that fuel management interventions could have large health benefits and that future health impacts from climate-change-induced wildfire smoke could approach projected overall increases in temperature-related mortality from climate change-but that both estimates remain uncertain. We use model results to highlight important areas for future research and to draw lessons for policy.

Comparison of World Health Organization and Demographic and Health Surveys data to estimate sub-national deworming coverage in pre-school aged children.

BACKGROUND: The key metric for monitoring the progress of deworming programs in controlling soil-transmitted helminthiasis (STH) is national drug coverage reported to the World Health Organization (WHO). There is increased interest in utilizing geographically-disaggregated data to estimate sub-national deworming coverage and equity, as well as gender parity. The Demographic and Health Surveys (DHS) offer a potential source of sub-national data. This study aimed to compare deworming coverage routinely reported to WHO and estimated by DHS in pre-school aged children to inform global STH measurement and evaluation. METHODOLOGY: We compared sub-national deworming coverage in pre-school aged children reported to WHO and estimated by DHS aligned geospatially and temporally. We included data from Burundi (2016-2017), Myanmar (2015-2016), and the Philippines (2017) based on data availability. WHO provided data on the date and sub-national coverage per mass drug administration reported by Ministries of Health. DHS included maternally-reported deworming status within the past 6 months for each child surveyed. We estimated differences in sub-national deworming coverage using WHO and DHS data, and performed sensitivity analyses. PRINCIPAL FINDINGS: We compared data on pre-school aged children from 13 of 18 districts in Burundi (N = 6,835 in DHS), 11 of 15 districts in Myanmar (N = 1,462 in DHS) and 16 of 17 districts in the Philippines (N = 7,594 in DHS) following data exclusion. The national deworming coverages estimated by DHS in Burundi, Myanmar, and the Philippines were 75.5% (95% CI: 73.7%-77.7%), 47.0% (95% CI: 42.7%-51.3%), and 48.0% (95% CI: 46.0%-50.0%), respectively. The national deworming coverages reported by WHO in Burundi, Myanmar, and the Philippines were 80.1%, 93.6% and 75.7%, respectively. The mean absolute differences in district-level coverage reported to WHO and estimated by DHS in Burundi, Myanmar, and the Philippines were 9.5%, 41.5%, and 24.6%, respectively. Across countries, coverage reported to WHO was frequently higher than DHS estimates (32 of 40 districts). National deworming coverage from DHS estimates were similar by gender within countries. CONCLUSIONS AND SIGNIFICANCE: Agreement of deworming coverage reported to WHO and estimated by DHS data was heterogeneous across countries, varying from broadly compatible in Burundi to largely discrepant in Myanmar. DHS data could complement deworming data reported to WHO to improve data monitoring practices and serve as an independent sub-national source of coverage data.

Women and children living in areas of armed conflict in Africa: a geospatial analysis of mortality and orphanhood.

BACKGROUND: The population effects of armed conflict on non-combatant vulnerable populations are incompletely understood. We aimed to study the effects of conflict on mortality among women of childbearing age (15-49 years) and on orphanhood among children younger than 15 years in Africa. METHODS: We tested the extent to which mortality among women aged 15-49 years, and orphanhood among children younger than 15 years, increased in response to nearby armed conflict in Africa. Data on location, timing, and intensity of armed conflicts were obtained from the Uppsala Conflict Data Program, and data on the location, timing, and outcomes of women and children from Demographic and Health Surveys done in 35 African countries from 1990 to 2016. Mortality among women was obtained from sibling survival data. We used cluster-area fixed-effects regression models to compare survival of women during periods of nearby conflict (within 50 km) to survival of women in the same area during times without conflict. We used similar methods to examine the extent to which children living near armed conflicts are at increased risk of becoming orphans. We examined the effects of varying conflict intensity using number of direct battle deaths and duration of consecutive conflict exposure. FINDINGS: We analysed data on 1 629 352 women (19 286 387 person-years), of which 103 011 (6·3%) died (534·1 deaths per 100 000 women-years), and 2 354 041 children younger than 15 years, of which 204 276 (8·7%) had lost a parent. On average, conflict within 50 km increased women's mortality by 112 deaths per 100 000 person-years (95% CI 97-128; a 21% increase above baseline), and the probability that a child has lost at least one parent by 6·0% (95% CI 3-8). This effect was driven by high-intensity conflicts: exposure to the highest (tenth) decile conflict in terms of conflict-related deaths increased the probability of female mortality by 202% (187-218) and increased the likelihood of orphanhood by 42% compared with a conflict-free period. Among the conflict-attributed deaths, 10% were due to maternal mortality. INTERPRETATION: African women of childbearing age are at a substantially increased risk of death from nearby high-intensity armed conflicts. Children exposed to conflict are analogously at increased risk of becoming orphans. This work fills gaps in literature on the harmful effects of armed conflict on non-combatants and highlights the need for humanitarian interventions to protect vulnerable populations. FUNDING: Bill & Melinda Gates Foundation to the BRANCH Consortium.

Testing the socioeconomic and environmental determinants of better child-health outcomes in Africa: a cross-sectional study among nations.

OBJECTIVE: We sought to test hypotheses regarding the principal correlates of child-health performance among African nations based on previous evidence collected at finer spatial scales. DESIGN: Retrospective, cross-sectional study. SETTING: All countries in Africa, excluding small-island nations. PRIMARY AND SECONDARY OUTCOME MEASURES: We defined a composite child-health indicator for each country comprising the incidence of stunting, deaths from respiratory disease, deaths from diarrhoeal disease, deaths from other infectious disease and deaths from injuries for children aged under 5 years. We also compiled national-level data for Africa to test the effects of country-level water quality, air pollution, food supply, breast feeding, environmental performance, per capita wealth, healthcare investment, population density and governance quality on the child-health indicator. RESULTS: Across nations, child health was lowest when water quality, improved sanitation, air quality and environmental performance were lowest. There was also an important decline in child health as household size (a proxy for population density) increased. The remaining variables had only weak effects, but in the directions we hypothesised. CONCLUSIONS: These results emphasise the importance of continued investment in clean water and sanitation services, measures to improve air quality and efforts to restrict further environmental degradation, to promote the UN's Sustainable Development Goal 3 target to '… end preventable deaths of newborns and children under 5' and Goal 6 to '… ensure access to water and sanitation for all' by 2030.