Comprehensive evaluation framework for intervention on health effects of ambient temperature

Despite the existence of many interventions to mitigate or adapt to the health effects of climate change, their effectiveness remains unclear. Here, we introduce the Comprehensive Evaluation Framework for Intervention on Health Effects of Ambient Temperature to evaluate study designs and effects of intervention studies. The framework comprises three types of interventions: proactive, indirect, and direct, and four categories of indicators: classification, methods, scope, and effects. We trialed the framework by an evaluation of existing intervention studies. The evaluation revealed that each intervention has its own applicable characteristics in terms of effectiveness, feasibility, and generalizability scores. We expanded the framework's potential by offering a list of intervention recommendations in different scenarios. Future applications are then explored to establish models of the relationship between study designs and intervention effects, facilitating effective interventions to address the health effects of ambient temperature under climate change.

Air pollution changes due to COVID-19 lockdowns and attributable mortality changes in four countries

COVID-19 lockdowns reduced nitrogen dioxide (NO2) and fine particulate matter (PM2.5) emissions in many countries. We aim to quantify the changes in these pollutants and to assess the attributable changes in mortality in Jiangsu, China; California, U.S.; Central-southern Italy; and Germany during COVID-19 lockdowns in early 2020. Accounting for meteorological impacts and air pollution time trends, we use a machine learning-based meteorological normalization technique and the difference-in-differences approach to quantify the changes in NO2 and PM2.5 concentrations due to lockdowns. Using region-specific estimates of the association between air pollution and mortality derived from a causal modeling approach using data from 2015 to 2019, we assess the changes in mortality attributable to the air pollution changes caused by the lockdowns in early 2020. During the lockdowns, NO2 reductions avoided 1.41 (95% empirical confidence interval [eCI]: 0.94, 1.88), 0.44 (95% eCI: 0.17, 0.71), and 4.66 (95% eCI: 2.03, 7.44) deaths per 100,000 people in Jiangsu, China; California, U.S.; and Central-southern Italy, respectively. Mortality benefits attributable to PM2.5 reductions were also significant, albeit of a smaller magnitude. For Germany, the mortality benefits attributable to NO2 changes were not significant (0.11; 95% eCI: -0.03, 0.25), and an increase in PM2.5 concentrations was associated with an increase in mortality of 0.35 (95% eCI: 0.22, 0.48) deaths per 100,000 people during the lockdown. COVID-19 lockdowns overall improved air quality and brought attributable health benefits, especially associated with NO2 improvements, with notable heterogeneity across regions. This study underscores the importance of accounting for local characteristics when policymakers adapt successful emission control strategies from other regions.

Household Air Pollution and Child Lung Function: The Ghana Randomized Air Pollution and Health Study

Rationale: The impact of a household air pollution (HAP) stove intervention on child lung function has been poorly described. Objectives: To assess the effect of a HAP stove intervention for infants prenatally to age 1 on, and exposure-response associations with, lung function at child age 4. Methods: The Ghana Randomized Air Pollution and Health Study randomized pregnant women to liquefied petroleum gas (LPG), improved biomass, or open-fire (control) stove conditions through child age 1. We quantified HAP exposure by repeated maternal and child personal carbon monoxide (CO) exposure measurements. Children performed oscillometry, an effort-independent lung function measurement, at age 4. We examined associations between Ghana Randomized Air Pollution and Health Study stove assignment and prenatal and infant CO measurements and oscillometry using generalized linear regression models. We used reverse distributed lag models to examine time-varying associations between prenatal CO and oscillometry. Measurements and Main Results: The primary oscillometry measure was reactance at 5 Hz, X5, a measure of elastic and inertial lung properties. Secondary measures included total, large airway, and small airway resistance at 5 Hz, 20 Hz, and the difference in resistance at 5 Hz and 20 Hz (R5, R20, and R5-20, respectively); area of reactance (AX); and resonant frequency. Of the 683 children who attended the lung function visit, 567 (83%) performed acceptable oscillometry. A total of 221, 106, and 240 children were from the LPG, improved biomass, and control arms, respectively. Compared with control, the improved biomass stove condition was associated with lower reactance at 5 Hz (X5 z-score: β = -0.25; 95% confidence interval [CI] = -0.39, -0.11), higher large airway resistance (R20 z-score: β = 0.34; 95% CI = 0.23, 0.44), and higher AX (AX z-score: β = 0.16; 95% CI = 0.06, 0.26), which is suggestive of overall worse lung function. The LPG stove condition was associated with higher X5 (X5 score: β = 0.16; 95% CI = 0.01, 0.31) and lower small airway resistance (R5-20 z-score: β = -0.15; 95% CI = -0.30, 0.0), which is suggestive of better small airway function. Higher average prenatal CO exposure was associated with higher R5 and R20, and distributed lag models identified sensitive windows of exposure between CO and X5, R5, R20, and R5-20. Conclusions: These data support the importance of prenatal HAP exposure on child lung function. Clinical trial registered with www.clinicaltrials.gov (NCT01335490).

Short-Term Exposure to Fine Particulate Matter and Nitrogen Dioxide and Mortality in 4 Countries

Importance

The association between short-term exposure to air pollution and mortality has been widely documented worldwide; however, few studies have applied causal modeling approaches to account for unmeasured confounders that vary across time and space.

Objective

To estimate the association between short-term changes in fine particulate matter (PM2.5) and nitrogen dioxide (NO2) concentrations and changes in daily all-cause mortality rates using a causal modeling approach.

Design, Setting, and Participants

This cross-sectional study used air pollution and mortality data from Jiangsu, China; California; central-southern Italy; and Germany with interactive fixed-effects models to control for both measured and unmeasured spatiotemporal confounders. A total of 8 963 352 deaths in these 4 regions from January 1, 2015, to December 31, 2019, were included in the study. Data were analyzed from June 1, 2021, to October 30, 2023.

Exposure

Day-to-day changes in county- or municipality-level mean PM2.5 and NO2 concentrations.

Main Outcomes and Measures

Day-to-day changes in county- or municipality-level all-cause mortality rates.

Results

Among the 8 963 352 deaths in the 4 study regions, a 10-μg/m3 increase in daily PM2.5 concentration was associated with an increase in daily all-cause deaths per 100 000 people of 0.01 (95% CI, 0.001-0.01) in Jiangsu, 0.03 (95% CI, 0.004-0.05) in California, 0.10 (95% CI, 0.07-0.14) in central-southern Italy, and 0.04 (95% CI, 0.02- 0.05) in Germany. The corresponding increases in mortality rates for a 10-μg/m3 increase in NO2 concentration were 0.04 (95% CI, 0.03-0.05) in Jiangsu, 0.03 (95% CI, 0.01-0.04) in California, 0.10 (95% CI, 0.05-0.15) in central-southern Italy, and 0.05 (95% CI, 0.04-0.06) in Germany. Significant effect modifications by age were observed in all regions, by sex in Germany (eg, 0.05 [95% CI, 0.03-0.06] for females in the single-pollutant model of PM2.5), and by urbanicity in Jiangsu (0.07 [95% CI, 0.04-0.10] for rural counties in the 2-pollutant model of NO2).

Conclusions and Relevance

The findings of this cross-sectional study contribute to the growing body of evidence that increases in short-term exposures to PM2.5 and NO2 may be associated with increases in all-cause mortality rates. The interactive fixed-effects model, which controls for unmeasured spatial and temporal confounders, including unmeasured time-varying confounders in different spatial units, can be used to estimate associations between changes in short-term exposure to air pollution and changes in health outcomes.

Tracking Progress Toward Urban Nature Targets Using Landcover and Vegetation Indices: A Global Study for the 96 C40 Cities

Access to urban natural space, including blue and greenspace, is associated with improved health. In 2021, the C40 Cities Climate Leadership Group set 2030 Urban Nature Declaration (UND) targets: "Quality Total Cover" (30% green area within each city) and "Equitable Spatial Distribution" (70% of the population living close to natural space). We evaluate progress toward these targets in the 96 C40 cities using globally available, high-resolution data sets for landcover and normalized difference vegetation index (NDVI). We use the European Space Agency (ESA)'s WorldCover data set to define greenspace with discrete landcover categories and ESA's Sentinel-2A to calculate NDVI, adding the "open water" landcover category to characterize total natural space. We compare 2020 levels of urban green and natural space to the two UND targets and predict the city-specific NDVI level consistent with the UND targets using linear regressions. The 96-city mean NDVI was 0.538 (range: 0.148, 0.739). Most (80%) cities meet the Quality Total Cover target, and nearly half (47%) meet the Equitable Spatial Distribution target. Landcover-measured greenspace and total natural space were strong (mean R 2 = 0.826) and moderate (mean R 2 = 0.597) predictors of NDVI and our NDVI-based natural space proximity measure, respectively. The 96-city mean predicted NDVI value of meeting the UND targets was 0.478 (range: 0.352-0.565) for Quality Total Cover and 0.660 (range: 0.498-0.767) for Equitable Spatial Distribution. Our translation of the area- and access-based metrics common in urban natural space targets into the NDVI metric used in epidemiology allows for quantifying the health benefits of achieving such targets.

Evaluating the sensitivity of mortality attributable to pollution to modeling Choices: A case study for Colorado

We evaluated the sensitivity of estimated PM2.5 and NO2 health impacts to varying key input parameters and assumptions including: 1) the spatial scale at which impacts are estimated, 2) using either a single concentration-response function (CRF) or using racial/ethnic group specific CRFs from the same epidemiologic study, 3) assigning exposure to residents based on home, instead of home and work locations for the state of Colorado. We found that the spatial scale of the analysis influences the magnitude of NO2, but not PM2.5, attributable deaths. Using county-level predictions instead of 1 km2 predictions of NO2 resulted in a lower estimate of mortality attributable to NO2 by ∼ 50 % for all of Colorado for each year between 2000 and 2020. Using an all-population CRF instead of racial/ethnic group specific CRFs results in a 130 % higher estimate of annual mortality attributable for the white population and a 40 % and 80 % lower estimate of mortality attributable to PM2.5 for Black and Hispanic residents, respectively. Using racial/ethnic group specific CRFs did not result in a different estimation of NO2 attributable mortality for white residents, but led to ∼ 50 % lower estimates of mortality for Black residents, and 290 % lower estimate for Hispanic residents. Using NO2 based on home instead of home and workplace locations results in a smaller estimate of annual mortality attributable to NO2 for all of Colorado by 2 % each year and 0.3 % for PM2.5. Our results should be interpreted as an exercise to make methodological recommendations for future health impact assessments of pollution.

Ozone-related acute excess mortality projected to increase in the absence of climate and air quality controls consistent with the Paris Agreement

Short-term exposure to ground-level ozone in cities is associated with increased mortality and is expected to worsen with climate and emission changes. However, no study has yet comprehensively assessed future ozone-related acute mortality across diverse geographic areas, various climate scenarios, and using CMIP6 multi-model ensembles, limiting our knowledge on future changes in global ozone-related acute mortality and our ability to design targeted health policies. Here, we combine CMIP6 simulations and epidemiological data from 406 cities in 20 countries or regions. We find that ozone-related deaths in 406 cities will increase by 45 to 6,200 deaths/year between 2010 and 2014 and between 2050 and 2054, with attributable fractions increasing in all climate scenarios (from 0.17% to 0.22% total deaths), except the single scenario consistent with the Paris Climate Agreement (declines from 0.17% to 0.15% total deaths). These findings stress the need for more stringent air quality regulations, as current standards in many countries are inadequate.

Unpacking the factors contributing to changes in PM2.5-associated mortality in China from 2013 to 2019

From 2013 to 2019, a series of air pollution control actions significantly reduced PM2.5 pollution in China. Control actions included changes in activity levels, structural adjustment (SA) policy, energy and material saving (EMS) policy, and end-of-pipe (EOP) control in several sources, which have not been systematically studied in previous studies. Here, we integrate an emission inventory, a chemical transport model, a health impact assessment model, and a scenario analysis to quantify the contribution of each control action across a range of major emission sources to the changes in PM2.5 concentrations and associated mortality in China from 2013 to 2019. Assuming equal toxicity of PM2.5 from all the sources, we estimate that PM2.5-related mortality decreased from 2.52 (95 % confidence interval, 2.13-2.88) to 1.94 (1.62-2.24) million deaths. Anthropogenic emission reductions and declining baseline incidence rates significantly contributed to health benefits, but population aging partially offset their impact. Among the major sources, controls on power plants and industrial boilers were responsible for the highest reduction in PM2.5-related mortality (∼80 %), followed by industrial processes (∼40 %), residential combustion (∼40 %), and transportation (∼30 %). However, considering the potentially higher relative risks of power plant PM2.5, the adverse effects avoided by their control could be ∼2.4 times the current estimation. Our power plant sensitivity analyses indicate that future estimates of source-specific PM2.5 health effects should incorporate variations in individual source PM2.5 effect coefficients when available. As for the control actions, while activity levels increased for most sources, SA policy significantly reduced the emissions in residential combustion and industrial boilers, and EOP control dominated the contribution in health benefits in most sources except residential combustion. Considering the emission reduction potential by source and control actions in 2019, our results suggest that promoting clean energy in residential combustion and enforcing more stringent EOP control in the iron and steel industry should be prioritized in the future.

Quantifying Disparities in Air Pollution Exposures across the United States Using Home and Work Addresses

While human mobility plays a crucial role in determining ambient air pollution exposures and health risks, research to date has assessed risks on the basis of almost solely residential location. Here, we leveraged a database of ∼128-144 million workers in the United States and published ambient PM2.5 data between 2011 and 2018 to explore how incorporating information on both workplace and residential location changes our understanding of disparities in air pollution exposure. In general, we observed higher workplace exposures relative to home exposures, as well as increased exposures for nonwhite and less educated workers relative to the national average. Workplace exposure disparities were higher among racial and ethnic groups and job types than by income, education, age, and sex. Not considering workplace exposures can lead to systematic underestimations in disparities in exposure among these subpopulations. We also quantified the error in assigning workers home instead of a weighted home-and-work exposure. We observed that biases in associations between PM2.5 and health impacts by using home instead of home-and-work exposure were the highest among urban, younger populations.

Acute exposure to total and source-specific ambient fine particulate matter and risk of respiratory disease hospitalization in Kuwait

Many epidemiologic studies concerned with acute exposure to ambient PM2.5 have reported positive associations for respiratory disease hospitalization. However, few studies have investigated this relationship in Kuwait and extrapolating results from other regions may involve considerable uncertainty due to variations in concentration levels, particle sources and composition, and population characteristics. Local studies can provide evidence for strategies to reduce risks from episodic exposures to high levels of ambient PM2.5 and generating hypotheses for evaluating health risks from chronic exposures. Therefore, using speciated PM2.5 data from local samplers, we analyzed the impact of daily total and source-specific PM2.5 exposure on respiratory hospitalizations in Kuwait using a case-crossover design with conditional quasi-Poisson regression. Total and source-specific ambient PM2.5 were modeled using 0-5-day cumulative distributed lags. For total PM2.5, we observed a 0.16% (95% confidence interval [CI] = 0.05, 0.27%) increase in risk for respiratory hospitalization per 1 μg/m3 increase in concentration. Of the source factors assessed, dust demonstrated a statistically significant increase in risk (0.16%, 95% CI = 0.04, 0.29%), and the central estimate for regional PM2.5 was positive (0.11%) but not statistically significant (95% CI = -0.11, 0.33%). No effect was observed from traffic emissions and 'other' source factors. When hospitalizations were stratified by sex, nationality, and age, we found that female, Kuwaiti national, and adult groups had higher effect estimates. These results suggest that exposure to ambient PM2.5 is harmful in Kuwait and provide some evidence of differential toxicity and effect modification depending on the PM2.5 source and population affected.

Health-based strategies for overcoming barriers to climate change adaptation and mitigation

Climate change poses an unequivocal threat to the respiratory health of current and future generations. Human activities-largely through the release of greenhouse gases-are driving rising global temperatures. Without a concerted effort to mitigate greenhouse gas emissions or adapt to the effects of a changing climate, each increment of warming increases the risk of climate hazards (eg, heat waves, floods, and droughts) that that can adversely affect allergy and immunologic diseases. For instance, wildfires, which release large quantities of particulate matter with a diameter of less than 2.5 μm (an air pollutant), occur with greater intensity, frequency, and duration in a hotter climate. This increases the risk of associated respiratory outcomes such as allergy and asthma. Fortunately, many mitigation and adaptation strategies can be applied to limit the impacts of global warming. Adaptation strategies, ranging from promotions of behavioral changes to infrastructural improvements, have been effectively deployed to increase resilience and alleviate adverse health effects. Mitigation strategies aimed at reducing greenhouse gas emissions can not only address the problem at the source but also provide numerous direct health cobenefits. Although it is possible to limit the impacts of climate change, urgent and sustained action must be taken now. The health and scientific community can play a key role in promoting and implementing climate action to ensure a more sustainable and healthy future.

Solidarity for the Anthropocene

Social solidarity is essential to large-scale collective action, but the need for solidarity has received little attention from scholars of Earth Systems, sustainability and public health. Now, the need for solidarity requires recognition. We have entered a new planetary epoch - the Anthropocene - in which human-induced global changes are occurring at an unprecedented scale. There are multiple health crises facing humanity - widening inequity, climate change, biodiversity loss, diminishing resources, persistent poverty, armed conflict, large-scale migration, and others. These global challenges are so far-reaching, and call for such extensive, large-scale action, that solidarity is a sine qua non for tackling these challenges. However, the heightened need for solidarity has received little attention in the context of the Anthropocene and, in particular, how it can be created and nurtured has been overlooked. In this commentary, we explore the concept of solidarity from inter-species, intra-generational and inter-generational perspectives. We also propose strategies to enhance solidarity in the Anthropocene.

Identifying sensitive windows of prenatal household air pollution on birth weight and infant pneumonia risk to inform future interventions

BACKGROUND

Prenatal household air pollution impairs birth weight and increases pneumonia risk however time-varying associations have not been elucidated and may have implications for the timing of public health interventions.

METHODS

The Ghana Randomized Air Pollution and Health Study (GRAPHS) enrolled 1,414 pregnant women from Kintampo, Ghana and measured personal carbon monoxide (CO) exposure four times over pregnancy. Birth weight was measured within 72-hours of birth. Fieldworkers performed weekly pneumonia surveillance and referred sick children to study physicians. The primary pneumonia outcome was one or more physician-diagnosed severe pneumonia episode in the first year of life. We employed reverse distributed lag models to examine time-varying associations between prenatal CO exposure and birth weight and infant pneumonia risk.

RESULTS

Analyses included n = 1,196 mother-infant pairs. In models adjusting for child sex; maternal age, body mass index (BMI), ethnicity and parity at enrollment; household wealth index; number of antenatal visits; and evidence of placental malaria, prenatal CO exposures from 15 to 20 weeks gestation were inversely associated with birth weight. Sex-stratified models identified a similar sensitive window in males and a window at 10-weeks gestation in females. In models adjusting for child sex, maternal age, BMI and ethnicity, household wealth index, gestational age at delivery and average postnatal child CO exposure, CO exposure during 34-39 weeks gestation were positively associated with severe pneumonia risk, especially in females.

CONCLUSIONS

Household air pollution exposures in mid- and late- gestation are associated with lower birth weight and higher pneumonia risk, respectively. These findings support the urgent need for deployment of clean fuel stove interventions beginning in early pregnancy.

Development of a global urban greenness indicator dataset for 1,000+ cities

Global climate change has sparked efforts to adapt to increasing temperatures, especially in urban areas that experience increased day and nighttime temperatures due to the urban heat island effect. The addition of greenspace has been suggested as a possible means for urban centers to respond to increasing urban temperatures. Thus, it is important for urban planning and policymakers to have access to data on greenspace specific at a fine spatial resolution. This dataset consists of information on peak and annual average 1 × 1 km Normalized Difference Vegetation Index (NDVI) for over 1,000 global urban centers, which is an objective satellite-based measure of vegetation. Population-weighted values for both peak and annual average NDVI and include an indicator of greenness, with seven levels ranging from extremely low to extremely high are provided. Additional information regarding the climate zone (using the Köppen-Geiger climate classification) and level of development (using the Human Development Index or HDI) for each city is included. Analyses were repeated in 2010, 2015, and 2020 to provide the ability to track urban greenness over time. Data are provided in tabular format with summaries presented in both tables and graphics. These data can be used to inform policy and planning and can be used as an indicator for a variety of climate and health investigations.

Trends of source apportioned PM2.5 in Tianjin over 2013-2019: Impacts of Clean Air Actions

A long-term (2013-2019) PM_2.5 speciation dataset measured in Tianjin, the largest industrial city in northern China, was analyzed with dispersion normalized positive matrix factorization (DN-PMF). The trends of source apportioned PM_2.5 were used to assess the effectiveness of source-specific control policies and measures in support of the two China's Clean Air Actions implemented nationwide in 2013-2017 and 2018-2020, respectively. Eight sources were resolved from the DN-PMF analysis: coal combustion (CC), biomass burning (BB), vehicular emissions, dust, steelmaking and galvanizing emissions, a mixed sulfate-rich factor and secondary nitrate. After adjustment for meteorological fluctuations, a substantial improvement in PM_2.5 air quality was observed in Tianjin with decreases in PM_2.5 at an annual rate of 6.6%/y. PM_2.5 from CC decreased by 4.1%/y. The reductions in SO₂ concentration, PM_2.5 contributed by CC, and sulfate demonstrated the improved control of CC-related emissions and fuel quality. Policies aimed at eliminating winter-heating pollution have had substantial success as shown by reduced heating-related SO₂, CC, and sulfate from 2013 to 2019. The two industrial source types showed sharp drops after the 2013 mandated controls went into effect to phaseout outdated iron/steel production and enforce tighter emission standards for these industries. BB reduced significantly by 2016 and remained low due to the no open field burning policy. Vehicular emissions and road/soil dust declined over the Action's first phase followed by positive upward trends, showing that further emission controls are needed. Nitrate concentrations remained constant although NO_X emissions dropped significantly. The lack of a decrease in nitrate may result from increased ammonia emissions from enhanced vehicular NO_X controls. The port and shipping emissions were evident implying their impacts on coastal air quality. These results affirm the effectiveness of the Clean Air Actions in reducing primary anthropogenic emissions. However, further emission reductions are needed to meet global health-based air quality standards.

Using time-resolved monitor wearing data to study the effect of clean cooking interventions on personal air pollution exposures

BACKGROUND

Personal monitoring can estimate individuals' exposures to environmental pollutants; however, accuracy depends on consistent monitor wearing, which is under evaluated.

OBJECTIVE

To study the association between device wearing and personal air pollution exposure.

METHODS

Using personal device accelerometry data collected in the context of a randomized cooking intervention in Ghana with three study arms (control, improved biomass, and liquified petroleum gas (LPG) arms; N = 1414), we account for device wearing to infer parameters of PM2.5 and CO exposure.

RESULTS

Device wearing was positively associated with exposure in the control and improved biomass arms, but weakly in the LPG arm. Inferred community-level air pollution was similar across study arms (~45 μg/m3). The estimated direct contribution of individuals' cooking to PM2.5 exposure was 64 μg/m3 for the control arm, 74 μg/m3 for improved biomass, and 6 μg/m3 for LPG. Arm-specific average PM2.5 exposure at near-maximum wearing was significantly lower in the LPG arm as compared to the improved biomass and control arms. Analysis of personal CO exposure mirrored PM2.5 results.

CONCLUSIONS

Personal monitor wearing was positively associated with average air pollution exposure, emphasizing the importance of high device wearing during monitoring periods and directly assessing device wearing for each deployment.

SIGNIFICANCE

We demonstrate that personal monitor wearing data can be used to refine exposure estimates and infer unobserved parameters related to the timing and source of environmental exposures.

IMPACT STATEMENTS

In a cookstove trial among pregnant women, time-resolved personal air pollution device wearing data were used to refine exposure estimates and infer unobserved exposure parameters, including community-level air pollution, the direct contribution of cooking to personal exposure, and the effect of clean cooking interventions on personal exposure. For example, in the control arm, while average 48 h personal PM2.5 exposure was 77 μg/m3, average predicted exposure at near-maximum daytime device wearing was 108 μg/m3 and 48 μg/m3 at zero daytime device wearing. Wearing-corrected average 48 h personal PM2.5 exposures were 50% lower in the LPG arm than the control and improved biomass and inferred direct cooking contributions to personal PM2.5 from LPG were 90% lower than the other arms. Our recommendation is that studies assessing personal exposures should examine the direct association between device wearing and estimated mean personal exposure.

Association between malaria and household air pollution interventions in a predominantly rural area of Ghana

BACKGROUND

Though anecdotal evidence suggests that smoke from HAP has a repellent effect on mosquitoes, very little work has been done to assess the effect of biomass smoke on malaria infection. The study, therefore, sought to investigate the hypothesis that interventions to reduce household biomass smoke may have an unintended consequence of increasing placental malaria or increase malaria infection in the first year of life.

METHODS

This provides evidence from a randomized controlled trial among 1414 maternal-infant pairs in the Kintampo North and Kintampo South administrative areas of Ghana. Logistic regression was used to assess the association between study intervention assignment (LPG, Biolite or control) and placental malaria. Finally, an extended Cox model was used to assess the association between study interventions and all episodes of malaria parasitaemia in the first year of infant's life.

RESULTS

The prevalence of placental malaria was 24.6%. Out of this, 20.8% were acute infections, 18.7% chronic infections and 60.5% past infections. The study found no statistical significant association between the study interventions and all types of placental malaria (OR = 0.88; 95% CI 0.59-1.30). Of the 1165 infants, 44.6% experienced at least one episode of malaria parasitaemia in the first year of life. The incidence of first and/or only episode of malaria parasitaemia was however found to be similar among the study arms.

CONCLUSION

The findings suggest that cookstove interventions for pregnant women and infants, when combined with additional malaria prevention strategies, do not lead to an increased risk of malaria among pregnant women and infants.

Impact of air pollution on stunting among children in Africa

BACKGROUND

Undernutrition is a global public health crisis, causing nearly half of deaths for children under age 5 years. Little is known regarding the impact of air pollution in-utero and early childhood on health outcomes related to undernutrition. The aim of our study is to evaluate the association of prenatal and early-life exposure to PM_2.5 and child malnutrition as captured by the height-for-age z-score (HAZ), and stunting in 32 countries in Africa. We also evaluated critical windows of susceptibility during pregnancy to each environmental risk.

METHODS

We linked nationally representative anthropometric data from 58 Demographic and Health Surveys (DHS) (n = 264,207 children < 5 years of age) with the average in-utero PM_2.5 concentrations derived from satellite imagery. We then estimated associations between PM_2.5 and stunting and HAZ after controlling for child, mother and household factors, and trends in time and seasonality.

RESULTS

We observed lower HAZ and increased stunting with higher in-utero PM_2.5 exposure, with statistically significant associations observed for stunting (OR: 1.016 (95% CI: 1.002, 1.030), for a 10 μg/m³ increase). The associations observed were robust to various model specifications. Wald tests revealed that sex, wealth quintile and urban/rural were not significant effect modifiers of these associations. When evaluating associations between trimester-specific PM_2.5 levels, we observed that associations between PM_2.5 and stunting was the largest.

CONCLUSIONS

This is one of the first studies for the African continent to investigate in-utero and early-life exposure to PM_2.5 is an important marker of childhood undernutrition. Our results highlight that PM_2.5 concentrations need to be urgently mitigated to help address undernutrition in children on the continent.

Mixed methods assessment of personal heat exposure, sleep, physical activity, and heat adaptation strategies among urban residents in the Boston area, MA

The growing frequency, intensity, and duration of extreme heat events necessitates interventions to reduce heat exposures. Local opportunities for heat adaptation may be optimally identified through collection of both quantitative exposure metrics and qualitative data on perceptions of heat. In this study, we used mixed methods to characterize heat exposure among urban residents in the area of Boston, Massachusetts, US, in summer 2020. Repeated interviews of N = 24 study participants ascertained heat vulnerability and adaptation strategies. Participants also used low-cost sensors to collect temperature, location, sleep, and physical activity data. We saw significant differences across temperature metrics: median personal temperature exposures were 3.9 °C higher than median ambient weather station temperatures. Existing air conditioning (AC) units did not adequately control indoor temperatures to desired thermostat levels: even with AC use, indoor maximum temperatures increased by 0.24 °C per °C of maximum outdoor temperature. Sleep duration was not associated with indoor or outdoor temperature. On warmer days, we observed a range of changes in time-at-home, expected given our small study size. Interview results further indicated opportunities for heat adaptation interventions including AC upgrades, hydration education campaigns, and amelioration of energy costs during high heat periods. Our mixed methods design informs heat adaptation interventions tailored to the challenges faced by residents in the study area. The strength of our community-academic partnership was a large part of the success of the mixed methods approach.

Poor early childhood growth is associated with impaired lung function: Evidence from a Ghanaian pregnancy cohort

OBJECTIVES

Nearly 40% of African children under 5 are stunted. We leveraged the Ghana randomized air pollution and health study (GRAPHS) cohort to examine whether poorer growth was associated with worse childhood lung function.

STUDY DESIGN

GRAPHS measured infant weight and length at birth and 3, 6, 9,12 months, and 4 years of age. At age 4 years, n = 567 children performed impulse oscillometry. We employed multivariable linear regression to estimate associations between birth and age 4 years anthropometry and lung function. Next, we employed latent class growth analysis (LCGA) to generate growth trajectories through age 4 years. We employed linear regression to examine associations between growth trajectory assignment and lung function.

RESULTS

Birth weight and age 4 weight-for-age and height-for-age z-scores were inversely associated with airway resistance (e.g., R5 , or total airway resistance: birth weight β = -0.90 cmH2O/L/s, 95% confidence interval [CI]: -1.64, -0.16 per 1 kg increase; and R20 , or large airway resistance: age 4 height-for-age β = -0.40 cmH2O/L/s, 95% CI: -0.57, -0.22 per 1 unit z-score increase). Impaired growth trajectories identified through LCGA were associated with higher airway resistance, even after adjusting for age 4 body mass index. For example, children assigned to a persistently stunted trajectory had higher R5 (β = 2.71 cmH2O/L/s, 95% CI: 1.07, 4.34) and R20 (β = 1.43 cmH2O/L/s, 95% CI: 0.51, 2.36) as compared to normal.

CONCLUSION

Children with poorer anthropometrics through to age 4 years had higher airway resistance in early childhood. These findings have implications for lifelong lung health, including pneumonia risk in childhood and reduced maximally attainable lung function in adulthood.

Examining the Relationship between Climate Change and Vibriosis in the United States: Projected Health and Economic Impacts for the 21st Century

BACKGROUND

This paper represents, to our knowledge, the first national-level (United States) estimate of the economic impacts of vibriosis cases as exacerbated by climate change. Vibriosis is an illness contracted through food- and waterborne exposures to various Vibrio species (e.g., nonV. cholerae O1 and O139 serotypes) found in estuarine and marine environments, including within aquatic life, such as shellfish and finfish.

OBJECTIVES

The objective of this study was to project climate-induced changes in vibriosis and associated economic impacts in the United States related to changes in sea surface temperatures (SSTs).

METHODS

For our analysis to identify climate links to vibriosis incidence, we constructed three logistic regression models by Vibrio species, using vibriosis data sourced from the Cholera and Other Vibrio Illness Surveillance system and historical SSTs. We relied on previous estimates of the cost-per-case of vibriosis to estimate future total annual medical costs, lost income from productivity loss, and mortality-related indirect costs throughout the United States. We separately reported results for V. parahaemolyticus, V. vulnificus, V. alginolyticus, and "V. spp.," given the different associated health burden of each.

RESULTS

By 2090, increases in SST are estimated to result in a 51% increase in cases annually relative to the baseline era (centered on 1995) under Representative Concentration Pathway (RCP) 4.5, and a 108% increase under RCP8.5. The cost of these illnesses is projected to reach $5.2 billion annually under RCP4.5, and $7.3 billion annually under RCP8.5, relative to $2.2 billion in the baseline (2018 U.S. dollars), equivalent to 140% and 234% increases respectively.

DISCUSSION

Vibriosis incidence is likely to increase in the United States under moderate and unmitigated climate change scenarios through increases in SST, resulting in a substantial burden of morbidity and mortality, and costing billions of dollars. These costs are mostly attributable to deaths, primarily from exposure to V. vulnificus. Evidence suggests that other factors, including sea surface salinity, may contribute to further increases in vibriosis cases in some regions of the United States and should also be investigated. https://doi.org/10.1289/EHP9999a.

The effects of night-time warming on mortality burden under future climate change scenarios: a modelling study

BACKGROUND

The health impacts of climate warming are usually quantified based on daily average temperatures. However, extra health risks might result from hot nights. We project the future mortality burden due to hot nights.

METHODS

We selected the hot night excess (HNE) to represent the intensity of night-time heat, which was calculated as the excess sum of high temperature during night time. We collected historical mortality data in 28 cities from three east Asian countries, from 1981 to 2010. The associations between HNE and mortality in each city were firstly examined using a generalised additive model in combination with a distributed lag non-linear model over lag 0-10 days. We then pooled the cumulative associations using a univariate meta-regression model at the national or regional levels. Historical and future hourly temperature series were projected under two scenarios of greenhouse-gas emissions from 1980-2099, with ten general circulation models. We then projected the attributable fraction of mortality due to HNE under each scenario.

FINDINGS

Our dataset comprised 28 cities across three countries (Japan, South Korea, and China), including 9 185 598 deaths. The time-series analyses showed the HNE was significantly associated with increased mortality risks, the relative mortality risk on days with hot nights could be 50% higher than on days with non-hot nights. Compared with the rise in daily mean temperature (lower than 20%), the frequency of hot nights would increase more than 30% and the intensity of hot night would increase by 50% by 2100s. The attributable fraction of mortality due to hot nights was projected to be 3·68% (95% CI 1·20 to 6·17) under a strict emission control scenario (SSP126). Under a medium emission control scenario (SSP245), the attributable fraction of mortality was projected to increase up to 5·79% (2·07 to 9·52), which is 0·95% (-0·39 to 2·29) more than the attributable fraction of mortality due to daily mean temperature.

INTERPRETATION

Our study provides evidence for significant mortality risks and burden in association with night-time warming across Japan, South Korea, and China. Our findings suggest a growing role of night-time warming in heat-related health effects in a changing climate.

FUNDING

The National Natural Science Foundation of China, Shanghai International Science and Technology Partnership Project.

Mortality Attributable to Long-Term Exposure to Ambient Fine Particulate Matter: Insights from the Epidemiologic Evidence for Understudied Locations

Epidemiologic cohort studies have consistently demonstrated that long-term exposure to ambient fine particles (PM_2.5) is associated with mortality. Nevertheless, extrapolating results to understudied locations may involve considerable uncertainty. To explore this issue, this review discusses the evidence for (i) the associated risk of mortality, (ii) the shape of the concentration-response function, (iii) a causal interpretation, and (iv) how the source mix/composition of PM_2.5 and population characteristics may alter the effect. The accumulated evidence suggests the following: (i) In the United States, the change in all-cause mortality risk per μg/m³ is about 0.8%. (ii) The concentration-response function appears nonlinear. (iii) Causation is overwhelmingly supported. (iv) Fossil fuel combustion-related sources are likely more toxic than others, and age, race, and income may modify the effect. To illustrate the use of our findings in support of a risk assessment in an understudied setting, we consider Kuwait. However, given the complexity of this relationship and the heterogeneity in reported effects, it is unreasonable to think that, in such circumstances, point estimates can be meaningful. Consequently, quantitative probabilistic estimates, which cannot be derived objectively, become essential. Formally elicited expert judgment can provide such estimates, and this review provides the evidence to support an elicitation.

A stochastic exposure model integrating random forest and agent-based approaches: Evaluation for PM2.5 in Jiangsu, China

This research proposes an Activity Pattern embedded Air Pollution Exposure Model (AP2EM), based on survey data of when, where, and how people spend their time and indoor/outdoor ratios for microenvironments. AP2EM integrates random forest and agent-based approaches to simulate the stochastic exposure to outdoor fine particulate matter (PM_2.5) along with indoor and in-vehicle PM_2.5 of outdoor origin. The R² of the linear regression between the model's calculations and personal measurement was 0.65, which was more accurate than the commonly-used aggregated exposure (AE) model and the outdoor exposure (OE) model. The population-weighted PM_2.5 exposure estimated by the AP2EM was 36.7 μg/m³ in Jiangsu, China, during 2014-2017. The OE model overestimated exposure by 54.0%, and the AE model underestimated exposure by 6.5%. These misestimate reflect ignorance of traditional studies on effects posed from time spent indoors (~85%) and doing low respiratory rate activities (~93%), problems of biased sampling, and neglecting low probability events. The proposed AP2EM treats activity patterns of individuals as chains and uses stochastic estimates to model activity choices, providing a more comprehensive understanding of human activity and exposure characteristics. Overall, the AP2EM is applicable for other air pollutants in different regions and benefits China's air pollution control policy designs.

Benefits of Increasing Greenness on All-Cause Mortality in the Largest Metropolitan Areas of the United States Within the Past Two Decades

Across the United States, cities are creating sustainability and climate action plans (CAPs) that call to increase local vegetation. These greening initiatives have the potential to not only benefit the environment but also human health. In epidemiologic literature, greenness has a protective effect on mortality through various direct and indirect pathways. We aimed to assess how an increase in greenness could decrease mortality in the largest urban areas in the United States. We conducted a nationwide quantitative health impact assessment to estimate the predicted reduction in mortality associated with an increase in greenness across two decades (2000, 2010, and 2019). Using a recently published exposure-response function, Landsat 30 m 16-day satellite imagery from April to September, and publicly available county-level mortality data from the CDC, we calculated the age-adjusted reduction in all-cause mortality for those 65 years and older within 35 of the most populated metropolitan areas. We estimated that between 34,000 and 38,000 all-cause deaths could have been reduced in 2000, 2010, and 2019 with a local increase in green vegetation by 0.1 unit across the most populated metropolitan areas. We found that overall greenness increased across time with a 2.86% increase from 2000 to 2010 to 11.11% from 2010 to 2019. These results can be used to support CAPs by providing a quantitative assessment to the impact local greening initiatives can have on mortality. Urban planners and local governments can use these findings to calculate the co-benefits of local CAPs through a public health lens and support policy development.

Robust relationship between ambient air pollution and infant mortality in India

BACKGROUND

Ambient exposure to fine particulate matter (PM_2.5) is one of the top global health concerns. We estimate the associations between in-utero and perinatal exposure to PM_2.5 and infant, neonatal and postneonatal mortality in India. We evaluate the sensitivity of this association to two widely-used exposure assessments.

METHOD

We linked nationally representative anthropometric data from India's 2015-2016 Demographic and Health Survey (n = 259,627 children under five across 640 districts of India) with satellite-based PM_2.5 concentrations during the month of birth of each child. We then estimated the associations between PM_2.5 from each dataset and child mortality, after controlling for child, mother and household factors including trends in time and seasonality. We examined if factors: urban/rural, sex, wealth quintile and state modified the associations derived from the two datasets using Wald tests.

RESULTS

We found evidence that PM_2.5 impacts infant mortality primarily through neonatal mortality. The estimated association between neonatal mortality and PM_2.5 in trimester 3 was OR: 1.016 (95% CI: 1.003, 1.030) for every 10 μg/m³ increase in exposure. This association was robust to the exposure assessment used. Child sex was a significant effect modifier, with PM_2.5 impacting mortality in infant girls more than boys.

CONCLUSIONS

Our results revealed a robust association between ambient exposure to PM_2.5 in the latter period of pregnancy and early life with infant and neonatal mortality in India. Urgent air pollution management plans are needed to improve infant mortality in India.

Modeling future asthma attributable to fine particulate matter (PM2.5) in a changing climate: a health impact assessment

Exposure to fine particulate matter (PM_2.5) is associated with asthma development as well as asthma exacerbation in children. PM_2.5 can be directly emitted or can form in the atmosphere from pollutant precursors. PM_2.5 emitted and formed in the atmosphere is influenced by meteorology; future changes in climate may alter the concentration and distribution of PM_2.5. Our aim is to estimate the future burden of climate change and PM_2.5 on new and exacerbated cases of childhood asthma. Projected concentrations of PM_2.5 are based on the Geophysical Fluid Dynamics Laboratory Coupled Model version 3 climate model, the Representative Concentration Pathway 8.5 greenhouse gas scenario, and two air pollution emissions datasets: a 2011 emissions dataset and a 2040 emissions dataset that reflects substantial reductions in emissions of PM_2.5 as compared to the 2011 inventory. We estimate additional PM_2.5-attributable asthma as well as PM_2.5-attributable albuterol inhaler use for four future years (2030, 2050, 2075, and 2095) relative to the year 2000. Exacerbations, regardless of the trigger, are counted as attributable to PM_2.5 if the incident disease is attributable to PM_2.5. We project 38 thousand (95% CI 36, 39 thousand) additional PM_2.5-attributable incident childhood asthma cases and 29 million (95% CI 27, 31 million) additional PM_2.5-attributable albuterol inhaler uses per year in 2030, increasing to 200 thousand (95% CI 190, 210 thousand) additional incident cases and 160 million (95% CI 150, 160 million) inhaler uses per year by 2095 relative to 2000 under the 2011 emissions dataset. These additional PM_2.5-attributable incident asthma cases and albuterol inhaler use would cost billions of additional U.S. dollars per year by the late century. These outcomes could be mitigated by reducing air pollution emissions.

Corrigendum to "Prenatal household air pollutant exposure is associated with reduced size and gestational age at birth among a cohort of Ghanaian infants" [Environ. Int. 155 (2021) 106659]

[This corrects the article PMC8628363.].

Prenatal and Postnatal Household Air Pollution Exposures and Pneumonia Risk: Evidence From the Ghana Randomized Air Pollution and Health Study

BACKGROUND

Nearly 40% of the world's population is exposed daily to household air pollution. The relative impact of prenatal and postnatal household air pollution exposure on early childhood pneumonia, a leading cause of mortality, is unknown.

RESEARCH QUESTION

Are prenatal or postnatal household air pollution, or both, associated with pneumonia risk in the first year of life?

STUDY DESIGN AND METHODS

The Ghana Randomized Air Pollution and Health Study enrolled 1,414 nonsmoking, pregnant women before 24 weeks' gestation with prospective follow-up to the child's age of 1 year. We measured 72-h personal household air pollution exposures, indexed by carbon monoxide (CO), four times prenatally and three times postnatally. Weekly fieldworker surveillance identified ill-appearing children for physician pneumonia assessment. We used quasi-Poisson models to examine associations between prenatal and postnatal CO and physician-diagnosed pneumonia and severe pneumonia. Sex-specific effects were examined.

RESULTS

Of the 1,306 live births, 1,141 infants were followed up with 55,605 child-weeks of fieldworker surveillance. The estimated risk for pneumonia and severe pneumonia in the first year of life increased by 10% (relative risk [RR], 1.10; 95% CI, 1.04-1.16) and 15% (RR, 1.15; 95% CI, 1.03-1.28), respectively, per 1-part per million (ppm) increase in average prenatal CO exposure and by 6% (RR, 1.06; 95% CI, 0.99-1.13) per 1-ppm increase in average postnatal CO exposure. Sex-stratified analyses suggest that in girls, higher prenatal CO exposure was associated with pneumonia risk, while no association was seen in boys.

INTERPRETATION

Prenatal household air pollution exposure increased risk of pneumonia and severe pneumonia in the first year of life. Clean-burning interventions may be most effective when begun prenatally.

TRIAL REGISTRY

ClinicalTrials.gov; No.: NCT01335490; URL: www.clinicaltrials.gov.

Estimating Intra-Urban Inequities in PM2.5-Attributable Health Impacts: A Case Study for Washington, DC

Air pollution levels are uneven within cities, contributing to persistent health disparities between neighborhoods and population sub-groups. Highly spatially resolved information on pollution levels and disease rates is necessary to characterize inequities in air pollution exposure and related health risks. We leverage recent advances in deriving surface pollution levels from satellite remote sensing and granular data in disease rates for one city, Washington, DC, to assess intra-urban heterogeneity in fine particulate matter (PM2.5)- attributable mortality and morbidity. We estimate PM2.5-attributable cases of all-cause mortality, chronic obstructive pulmonary disease, ischemic heart disease, lung cancer, stroke, and asthma emergency department (ED) visits using epidemiologically derived health impact functions. Data inputs include satellite-derived annual mean surface PM2.5 concentrations; age-resolved population estimates; and statistical neighborhood-, zip code- and ward-scale disease counts. We find that PM2.5 concentrations and associated health burdens have decreased in DC between 2000 and 2018, from approximately 240 to 120 cause-specific deaths and from 40 to 30 asthma ED visits per year (between 2014 and 2018). However, remaining PM2.5-attributable health risks are unevenly and inequitably distributed across the District. Higher PM2.5-attributable disease burdens were found in neighborhoods with larger proportions of people of color, lower household income, and lower educational attainment. Our study adds to the growing body of literature documenting the inequity in air pollution exposure levels and pollution health risks between population sub-groups, and highlights the need for both high-resolution disease rates and concentration estimates for understanding intra-urban disparities in air pollution-related health risks.

Prenatal and Postnatal Household Air Pollution Exposure and Infant Growth Trajectories: Evidence from a Rural Ghanaian Pregnancy Cohort

BACKGROUND

The exposure-response association between prenatal and postnatal household air pollution (HAP) and infant growth trajectories is unknown.

OBJECTIVES

To evaluate associations between prenatal and postnatal HAP exposure and stove interventions on growth trajectories over the first year of life.

METHODS

The Ghana Randomized Air Pollution and Health Study enrolled n=1,414 pregnant women at ≤24wk gestation from Kintampo, Ghana, and randomized them to liquefied petroleum gas (LPG), improved biomass, or open fire (control) stoves. We quantified HAP exposure by repeated, personal prenatal and postnatal carbon monoxide (CO) and, in a subset, fine particulate matter [PM with an aerodynamic diameter of ≤2.5μm (PM2.5)] assessments. Length, weight, mid-upper arm circumference (MUAC) and head circumference (HC) were measured at birth, 3, 6, 9, and 12 months; weight-for-age, length-for-age (LAZ), and weight-for-length z (WLZ)-scores were calculated. For each anthropometric measure, we employed latent class growth analysis to generate growth trajectories over the first year of life and assigned each child to a trajectory group. We then employed ordinal logistic regression to determine associations between HAP exposures and growth trajectory assignments. Associations with stove intervention arm were also considered.

RESULTS

Of the 1,306 live births, 1,144 had valid CO data and anthropometric variables measured at least once. Prenatal HAP exposure increased risk for lower length [CO odds ratio (OR)= 1.17, 95% CI: 1.01, 1.35 per 1-ppm increase; PM2.5 OR= 1.07, 95% CI: 1.02, 1.13 per 10-μg/m3 increase], lower LAZ z-score (CO OR= 1.15, 95% CI: 1.01, 1.32 per 1-ppm increase) and stunting (CO OR= 1.25, 95% CI: 1.08, 1.45) trajectories. Postnatal HAP exposure increased risk for smaller HC (CO OR= 1.09, 95% CI: 1.04, 1.13 per 1-ppm increase), smaller MUAC and lower WLZ-score (PM2.5 OR= 1.07, 95% CI: 1.00, 1.14 and OR= 1.09, 95% CI: 1.01, 1.19 per 10-μg/m3 increase, respectively) trajectories. Infants in the LPG arm had decreased odds of having smaller HC and MUAC trajectories as compared with those in the open fire stove arm (OR= 0.58, 95% CI: 0.37, 0.92 and OR= 0.45, 95% CI: 0.22, 0.90, respectively).

DISCUSSION

Higher early life HAP exposure (during pregnancy and through the first year of life) was associated with poorer infant growth trajectories among children in rural Ghana. A cleaner-burning stove intervention may have improved some growth trajectories. https://doi.org/10.1289/EHP8109.

Prenatal household air pollutant exposure is associated with reduced size and gestational age at birth among a cohort of Ghanaian infants

BACKGROUND

Low birth weight and prematurity are important risk factors for death and disability, and may be affected by prenatal exposure to household air pollution (HAP).

METHODS

We investigate associations between maternal exposure to carbon monoxide (CO) during pregnancy and birth outcomes (birth weight, birth length, head circumference, gestational age, low birth weight, small for gestational age, and preterm birth) among 1288 live-born infants in the Ghana Randomized Air Pollution and Health Study (GRAPHS). We evaluate whether evidence of malaria during pregnancy, as determined by placental histopathology, modifies these associations.

RESULTS

We observed effects of CO on birth weight, birth length, and gestational age that were modified by placental malarial status. Among infants from pregnancies without evidence of placental malaria, each 1 ppm increase in CO was associated with reduced birth weight (-53.4 g [95% CI: -84.8, -21.9 g]), birth length (-0.3 cm [-0.6, -0.1 cm]), gestational age (-1.0 days [-1.8, -0.2 days]), and weight-for-age Z score (-0.08 standard deviations [-0.16, -0.01 standard deviations]). These associations were not observed in pregnancies with evidence of placental malaria. Each 1 ppm increase in maternal exposure to CO was associated with elevated odds of low birth weight (LBW, OR 1.14 [0.97, 1.33]) and small for gestational age (SGA, OR 1.14 [0.98, 1.32]) among all infants.

CONCLUSIONS

Even modest reductions in exposure to HAP among pregnant women could yield substantial public health benefits, underscoring a need for interventions to effectively reduce exposure. Adverse associations with HAP were discernible only among those without evidence of placental malaria, a key driver of impaired fetal growth in this malaria-endemic area.

Short-term PM2.5 and cardiovascular admissions in NY State: assessing sensitivity to exposure model choice

BACKGROUND

Air pollution health studies have been increasingly using prediction models for exposure assessment even in areas without monitoring stations. To date, most studies have assumed that a single exposure model is correct, but estimated effects may be sensitive to the choice of exposure model.

METHODS

We obtained county-level daily cardiovascular (CVD) admissions from the New York (NY) Statewide Planning and Resources Cooperative System (SPARCS) and four sets of fine particulate matter (PM_2.5) spatio-temporal predictions (2002-2012). We employed overdispersed Poisson models to investigate the relationship between daily PM_2.5 and CVD, adjusting for potential confounders, separately for each state-wide PM_2.5 dataset.

RESULTS

For all PM_2.5 datasets, we observed positive associations between PM_2.5 and CVD. Across the modeled exposure estimates, effect estimates ranged from 0.23% (95%CI: -0.06, 0.53%) to 0.88% (95%CI: 0.68, 1.08%) per 10 µg/m³ increase in daily PM_2.5. We observed the highest estimates using monitored concentrations 0.96% (95%CI: 0.62, 1.30%) for the subset of counties where these data were available.

CONCLUSIONS

Effect estimates varied by a factor of almost four across methods to model exposures, likely due to varying degrees of exposure measurement error. Nonetheless, we observed a consistently harmful association between PM_2.5 and CVD admissions, regardless of model choice.

Satellite Monitoring for Air Quality and Health

Data from satellite instruments provide estimates of gas and particle levels relevant to human health, even pollutants invisible to the human eye. However, the successful interpretation of satellite data requires an understanding of how satellites relate to other data sources, as well as factors affecting their application to health challenges. Drawing from the expertise and experience of the 2016-2020 NASA HAQAST (Health and Air Quality Applied Sciences Team), we present a review of satellite data for air quality and health applications. We include a discussion of satellite data for epidemiological studies and health impact assessments, as well as the use of satellite data to evaluate air quality trends, support air quality regulation, characterize smoke from wildfires, and quantify emission sources. The primary advantage of satellite data compared to in situ measurements, e.g., from air quality monitoring stations, is their spatial coverage. Satellite data can reveal where pollution levels are highest around the world, how levels have changed over daily to decadal periods, and where pollutants are transported from urban to global scales. To date, air quality and health applications have primarily utilized satellite observations and satellite-derived products relevant to near-surface particulate matter <2.5 μm in diameter (PM_2.5) and nitrogen dioxide (NO₂). Health and air quality communities have grown increasingly engaged in the use of satellite data, and this trend is expected to continue. From health researchers to air quality managers, and from global applications to community impacts, satellite data are transforming the way air pollution exposure is evaluated.

The effect of clean cooking interventions on mother and child personal exposure to air pollution: results from the Ghana Randomized Air Pollution and Health Study (GRAPHS)

BACKGROUND

Clean cooking interventions to reduce air pollution exposure from burning biomass for daily cooking and heating needs have the potential to reduce a large burden of disease globally.

OBJECTIVE

The objective of this study is to evaluate the air pollution exposure impacts of a fan-assisted efficient biomass-burning cookstove and a liquefied petroleum gas (LPG) stove intervention in rural Ghana.

METHODS

We randomized 1414 households in rural Ghana with pregnant mothers into a control arm (N = 526) or one of two clean cooking intervention arms: a fan-assisted efficient biomass-burning cookstove (N = 527) or an LPG stove and cylinder refills as needed (N = 361). We monitored personal maternal carbon monoxide (CO) at baseline and six times after intervention and fine particulate matter (PM_2.5) exposure twice after intervention. Children received three CO exposure monitoring sessions.

RESULTS

We obtained 5655 48-h maternal CO exposure estimates and 1903 for children, as well as 1379 maternal PM_2.5 exposure estimates. Median baseline CO exposures in the control, improved biomass, and LPG arms were 1.17, 1.17, and 1.30 ppm, respectively. Based on a differences-in-differences approach, the LPG arm showed a 47% reduction (95% confidence interval: 34-57%) in mean 48-h CO exposure compared to the control arm. Mean maternal PM_2.5 exposure in the LPG arm was 32% lower than the control arm during the post-intervention period (52 ± 29 vs. 77 ± 44 μg/m³). The biomass stove did not meaningfully reduce CO or PM_2.5 exposure.

CONCLUSIONS

We show that LPG interventions lowered air pollution exposure significantly compared to three-stone fires. However, post-intervention exposures still exceeded health-relevant targets.

SIGNIFICANCE

In a large controlled trial of cleaner cooking interventions, an LPG stove and fuel intervention reduced air pollution exposure in a vulnerable population in a low-resource setting.

The effect of clean cooking interventions on mother and child personal exposure to air pollution: results from the Ghana Randomized Air Pollution and Health Study (GRAPHS)

BACKGROUND

Clean cooking interventions to reduce air pollution exposure from burning biomass for daily cooking and heating needs have the potential to reduce a large burden of disease globally.

OBJECTIVE

The objective of this study is to evaluate the air pollution exposure impacts of a fan-assisted efficient biomass-burning cookstove and a liquefied petroleum gas (LPG) stove intervention in rural Ghana.

METHODS

We randomized 1414 households in rural Ghana with pregnant mothers into a control arm (N = 526) or one of two clean cooking intervention arms: a fan-assisted efficient biomass-burning cookstove (N = 527) or an LPG stove and cylinder refills as needed (N = 361). We monitored personal maternal carbon monoxide (CO) at baseline and six times after intervention and fine particulate matter (PM2.5) exposure twice after intervention. Children received three CO exposure monitoring sessions.

RESULTS

We obtained 5655 48-h maternal CO exposure estimates and 1903 for children, as well as 1379 maternal PM2.5 exposure estimates. Median baseline CO exposures in the control, improved biomass, and LPG arms were 1.17, 1.17, and 1.30 ppm, respectively. Based on a differences-in-differences approach, the LPG arm showed a 47% reduction (95% confidence interval: 34-57%) in mean 48-h CO exposure compared to the control arm. Mean maternal PM2.5 exposure in the LPG arm was 32% lower than the control arm during the post-intervention period (52 ± 29 vs. 77 ± 44 μg/m3). The biomass stove did not meaningfully reduce CO or PM2.5 exposure.

CONCLUSIONS

We show that LPG interventions lowered air pollution exposure significantly compared to three-stone fires. However, post-intervention exposures still exceeded health-relevant targets.

SIGNIFICANCE

In a large controlled trial of cleaner cooking interventions, an LPG stove and fuel intervention reduced air pollution exposure in a vulnerable population in a low-resource setting.

City-level vulnerability to temperature-related mortality in the USA and future projections: a geographically clustered meta-regression

BACKGROUND

Extreme heat exposure can lead to premature death. Climate change is expected to increase the frequency, intensity, and duration of extreme heat events, resulting in many additional heat-related deaths globally, as well as changing the nature of extreme cold events. At the same time, vulnerability to extreme heat has decreased over time, probably due to a combination of physiological, behavioural, infrastructural, and technological adaptations. We aimed to account for these changes in vulnerability and avoid overstated projections for temperature-related mortality. We used the historical observed decrease in vulnerability to improve future mortality estimates.

METHODS

We used historical mortality and temperature data from 208 US cities to quantify how observed changes in vulnerability from 1973 to 2013 affected projections of temperature-related mortality under various climate scenarios. We used geographically structured meta-regression to characterise the relationship between temperature and mortality for these urban populations over the specified time period. We then used the fitted relationships to project mortality under future climate conditions.

FINDINGS

Between Oct 26, 2018, and March 9, 2020, we established that differences in vulnerability to temperature were geographically structured. Vulnerability decreased over time in most areas. US mortalities projected from a 2°C increase in mean temperature decreased by more than 97% when using 2003-13 data compared with 1973-82 data. However, these benefits declined with increasing temperatures, with a 6°C increase showing only an 84% decline in projected mortality based on 2003-13 data.

INTERPRETATION

Even after accounting for adaptation, the projected effects of climate change on premature mortality constitute a substantial public health risk. Our work suggests large increases in temperature will require additional mitigation to avoid excess mortality from heat events, even in areas with high air conditioning coverage in place.

FUNDING

The US Environmental Protection Agency and Abt Associates.

On the distribution of low-cost PM2.5 sensors in the US: demographic and air quality associations

BACKGROUND

Low-cost sensors have the potential to democratize air pollution information and supplement regulatory networks. However, differentials in access to these sensors could exacerbate existing inequalities in the ability of different communities to respond to the threat of air pollution.

OBJECTIVE

Our goal was to analyze patterns of deployments of a commonly used low-cost sensor, as a function of demographics and pollutant concentrations.

METHODS

We used Wilcoxon rank sum tests to assess differences between socioeconomic characteristics and PM_2.5 concentrations of locations with low-cost sensors and those with regulatory monitors. We used Kolomogorov-Smirnov tests to examine how representative census tracts with sensors were of the United States. We analyzed predictors of the presence, and number of, sensors in a tract using regressions.

RESULTS

Census tracts with low-cost sensors were higher income more White and more educated than the US as a whole and than tracts with regulatory monitors. For all states except for California they are in locations with lower annual-average PM_2.5 concentrations than regulatory monitors. The existing presence of a regulatory monitor, the percentage of people living above the poverty line and PM_2.5 concentrations were associated with the presence of low-cost sensors in a tract.

SIGNIFICANCE

Strategies to improve access to low-cost sensors in less-privileged communities are needed to democratize air pollution data.

Role of emission controls in reducing the 2050 climate change penalty for PM2.5 in China

Previous studies demonstrated that global warming can lead to deteriorated air quality even when anthropogenic emissions were kept constant, which has been called a climate change penalty on air quality. It is expected that anthropogenic emissions will decrease significantly in the future considering the aggressive emission control actions in China. However, the dependence of climate change penalty on the choice of emission scenario is still uncertain. To fill this gap, we conducted multiple independent model simulations to investigate the response of PM_2.5 to future (2050) climate warming (RCP8.5) in China but with different emission scenarios, including the constant 2015 emissions, the 2050 CLE emissions (based on Current Legislation), and the 2050 MTFR emissions (based on Maximum Technically Feasible Reduction). For each set of emissions, we estimate climate change penalty as the difference in PM_2.5 between a pair of simulations with either 2015 or 2050 meteorology. Under 2015 emissions, we find a PM_2.5 climate change penalty of 1.43 μg m^-3 in Eastern China, leading to an additional 35,000 PM_2.5-related premature deaths [95% confidence interval (CI), 21,000-40,000] by 2050. However, the PM_2.5 climate change penalty weakens to 0.24 μg m^-3 with strict anthropogenic emission controls under the 2050 MTFR emissions, which decreases the associated PM_2.5-related deaths to 17,000. The smaller MTFR climate change penalty contributes 14% of the total PM_2.5 decrease when both emissions and meteorology are changed from 2015 to 2050, and 24% of total health benefits associated with this PM_2.5 decrease in Eastern China. This finding suggests that controlling anthropogenic emissions can effectively reduce the climate change penalty on PM_2.5 and its associated premature deaths, even though a climate change penalty still occurs even under MTFR. Strengthened controls on anthropogenic emissions are key to attaining air quality targets and protecting human health in the context of future global climate change.

Long-Term Effects of Fine Particles on Mortality: Insights from 1984

I review an important study that Professor Evans published early in his career examining the role of cross-sectional mortality studies in air pollution risk assessment. At a time when both risk assessment and particle effects on mortality were controversial, John's thoughtful analysis of the issues and data relevant to assessing long-term mortality risks from airborne particles provides a comprehensive primer that is still relevant today. The paper includes a critical literature review, a meta-analysis of published particle effect estimates, and a reanalysis of landmark cross-sectional mortality data set. EPA criteria documents and related literature had largely discounted the cross-sectional mortality findings on the basis of criticisms about exposure assessment and control for confounding. John's analysis reached a different conclusion, that is, "we are of the opinion that the cross-sectional studies reflect a causal relationship between exposure to airborne particles and premature mortality. From our point of view it is as likely that parameters have been underestimated … as that they are overestimated due to confounding." The paper acknowledged the impossibility of precisely quantifying the long-term mortality effect of particle air pollution, and that there is a need for further research utilizing alternative approaches. These conclusions foreshadow the emergence, a decade later, of the influential particulate matter (PM) mortality findings from the Harvard Six Cities and American Cancer Society cohort studies. I conclude by suggesting that well designed cross-sectional studies could play a role in identifying exposure-response associations in resource-poor settings where there is a paucity of local evidence to support air pollution regulations.

Estimating PM2.5-related premature mortality and morbidity associated with future wildfire emissions in the western US

Wildfire activity in the western United States (US) has been increasing, a trend that has been correlated with changing patterns of temperature and precipitation associated with climate change. Health effects associated with exposure to wildfire smoke and fine particulate matter (PM_2.5) include short- and long-term premature mortality, hospital admissions, emergency department visits, and other respiratory and cardiovascular incidents. We estimate PM_2.5 exposure and health impacts for the entire continental US from current and future western US wildfire activity projected for a range of future climate scenarios through the 21st century. We use a simulation approach to estimate wildfire activity, area burned, fine particulate emissions, air quality concentrations, health effects, and economic valuation of health effects, using established and novel methodologies. We find that climatic factors increase wildfire pollutant emissions by an average of 0.40% per year over the 2006-2100 period under Representative Concentration Pathway (RCP) 4.5 (lower emissions scenarios) and 0.71% per year for RCP8.5. As a consequence, spatially weighted wildfire PM_2.5 concentrations more than double for some climate model projections by the end of the 21st century. PM_2.5 exposure changes, combined with population projections, result in a wildfire PM2.5-related premature mortality excess burden in the 2090 RCP8.5 scenario that is roughly 3.5 times larger than in the baseline period. The combined effect of increased wildfire activity, population growth, and increase in the valuation of avoided risk of premature mortality over time results in a large increase in total economic impact of wildfire-related PM_2.5 mortality and morbidity in the continental US, from roughly $7 billion per year in the baseline period to roughly $36 billion per year in 2090 for RCP4.5, and $43 billion per year in RCP8.5. The climate effect alone accounts for a roughly 60% increase in wildfire PM2.5-related premature mortality in the RCP8.5 scenario, relative to baseline conditions.

The 2020 report of The Lancet Countdown on health and climate change: responding to converging crises

For the Chinese, French, German, and Spanish translations of the abstract see Supplementary Materials section.