Invited Perspective: The NO2 and Mortality Dilemma Solved? Almost There!

Choices of morbidity outcomes and concentration-response functions for health risk assessment of long-term exposure to air pollution

Background

Air pollution health risk assessment (HRA) has been typically conducted for all causes and cause-specific mortality based on concentration-response functions (CRFs) from meta-analyses that synthesize the evidence on air pollution health effects. There is a need for a similar systematic approach for HRA for morbidity outcomes, which have often been omitted from HRA of air pollution, thus underestimating the full air pollution burden. We aimed to compile from the existing systematic reviews and meta-analyses CRFs for the incidence of several diseases that could be applied in HRA. To achieve this goal, we have developed a comprehensive strategy for the appraisal of the systematic reviews and meta-analyses that examine the relationship between long-term exposure to particulate matter with an aerodynamic diameter smaller than 2.5 µm (PM2.5), nitrogen dioxide (NO2), or ozone (O3) and incidence of various diseases.

Methods

To establish the basis for our evaluation, we considered the causality determinations provided by the US Environmental Protection Agency Integrated Science Assessment for PM2.5, NO2, and O3. We developed a list of pollutant/outcome pairs based on these assessments and the evidence of a causal relationship between air pollutants and specific health outcomes. We conducted a comprehensive literature search using two databases and identified 75 relevant systematic reviews and meta-analyses for PM2.5 and NO2. We found no relevant reviews for long-term exposure to ozone. We evaluated the reliability of these studies using an adaptation of the AMSTAR 2 tool, which assesses various characteristics of the reviews, such as literature search, data extraction, statistical analysis, and bias evaluation. The tool's adaptation focused on issues relevant to studies on the health effects of air pollution. Based on our assessment, we selected reviews that could be credible sources of CRF for HRA. We also assessed the confidence in the findings of the selected systematic reviews and meta-analyses as the sources of CRF for HRA. We developed specific criteria for the evaluation, considering factors such as the number of included studies, their geographical distribution, heterogeneity of study results, the statistical significance and precision of the pooled risk estimate in the meta-analysis, and consistency with more recent studies. Based on our assessment, we classified the outcomes into three lists: list A (a reliable quantification of health effects is possible in an HRA), list B+ (HRA is possible, but there is greater uncertainty around the reliability of the CRF compared to those included on list A), and list B- (HRA is not recommended because of the substantial uncertainty of the CRF).

Results

In our final evaluation, list A includes six CRFs for PM2.5 (asthma in children, chronic obstructive pulmonary disease, ischemic heart disease events, stroke, hypertension, and lung cancer) and three outcomes for NO2 (asthma in children and in adults, and acute lower respiratory infections in children). Three additional outcomes (diabetes, dementia, and autism spectrum disorders) for PM2.5 were included in list B+. Recommended CRFs are related to the incidence (onset) of the diseases. The International Classification of Diseases, 10th revision codes, age ranges, and suggested concentration ranges are also specified to ensure consistency and applicability in an HRA. No specific suggestions were given for ozone because of the lack of relevant systematic reviews.

Conclusion

The suggestions formulated in this study, including CRFs selected from the available systematic reviews, can assist in conducting reliable HRAs and contribute to evidence-based decision-making in public health and environmental policy. Future research should continue to update and refine these suggestions as new evidence becomes available and methodologies evolve.

Long-term exposure to air pollution and incidence of gastric and the upper aerodigestive tract cancers in a pooled European cohort: The ELAPSE project

Air pollution has been shown to significantly impact human health including cancer. Gastric and upper aerodigestive tract (UADT) cancers are common and increased risk has been associated with smoking and occupational exposures. However, the association with air pollution remains unclear. We pooled European subcohorts (N = 287,576 participants for gastric and N = 297,406 for UADT analyses) and investigated the association between residential exposure to fine particles (PM2.5), nitrogen dioxide (NO2), black carbon (BC) and ozone in the warm season (O3w) with gastric and UADT cancer. We applied Cox proportional hazards models adjusting for potential confounders at the individual and area-level. During 5,305,133 and 5,434,843 person-years, 872 gastric and 1139 UADT incident cancer cases were observed, respectively. For gastric cancer, we found no association with PM2.5, NO2 and BC while for UADT the hazard ratios (95% confidence interval) were 1.15 (95% CI: 1.00-1.33) per 5 μg/m3 increase in PM2.5, 1.19 (1.08-1.30) per 10 μg/m3 increase in NO2, 1.14 (1.04-1.26) per 0.5 × 10-5 m-1 increase in BC and 0.81 (0.72-0.92) per 10 μg/m3 increase in O3w. We found no association between long-term ambient air pollution exposure and incidence of gastric cancer, while for long-term exposure to PM2.5, NO2 and BC increased incidence of UADT cancer was observed.

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.

Air pollution benefits from reduced on-road activity due to COVID-19 in the United States

On-road transportation is one of the largest contributors to air pollution in the United States. The COVID-19 pandemic provided the unintended experiment of reduced on-road emissions' impacts on air pollution due to lockdowns across the United States. Studies have quantified on-road transportation's impact on fine particulate matter (PM2.5)-attributable and ozone (O3)-attributable adverse health outcomes in the United States, and other studies have quantified air pollution-attributable health outcome reductions due to COVID-19-related lockdowns. We aim to quantify the PM2.5-attributable, O3-attributable, and nitrogen dioxide (NO2)-attributable adverse health outcomes from traffic emissions as well as the air pollution benefits due to reduced on-road activity during the pandemic in 2020. We estimate 79,400 (95% CI 46,100-121,000) premature mortalities each year due to on-road-attributable PM2.5, O3, and NO2. We further break down the impacts by pollutant and vehicle types (passenger [PAS] vs. freight [FRT] vehicles). We estimate PAS vehicles to be responsible for 63% of total impacts and FRT vehicles 37%. Nitrogen oxide (NOX) emissions from these vehicles are responsible for 78% of total impacts as it is a precursor for PM2.5 and O3. Utilizing annual vehicle miles traveled reductions in 2020, we estimate that 9,300 (5,500-14,000) deaths from air pollution were avoided in 2020 due to the state-specific reductions in on-road activity across the continental United States. By quantifying the air pollution public health benefits from lockdown-related reductions in on-road emissions, the results from this study stress the need for continued emission mitigation policies, like the U.S. Environmental Protection Agency's (EPA) recently proposed NOX standards for heavy-duty vehicles, to mitigate on-road transportation's public health impact.

Ambient nitrogen dioxide in 47 187 neighbourhoods across 326 cities in eight Latin American countries: population exposures and associations with urban features

BACKGROUND

Health research on ambient nitrogen dioxide (NO2) is sparse in Latin America, despite the high prevalence of NO2-associated respiratory diseases in the region. This study describes within-city distributions of ambient NO2 concentrations at high spatial resolution and urban characteristics associated with neighbourhood ambient NO2 in 326 Latin American cities.

METHODS

We aggregated estimates of annual surface NO2 at 1 km2 spatial resolution for 2019, population counts, and urban characteristics compiled by the SALURBAL project to the neighbourhood level (ie, census tracts). We described the percentage of the urban population living with ambient NO2 concentrations exceeding WHO air quality guidelines. We used multilevel models to describe associations of neighbourhood ambient NO2 concentrations with population and urban characteristics at the neighbourhood and city levels.

FINDINGS

We examined 47 187 neighbourhoods in 326 cities from eight Latin American countries. Of the roughly 236 million urban residents observed, 85% lived in neighbourhoods with ambient annual NO2 above WHO guidelines. In adjusted models, higher neighbourhood-level educational attainment, closer proximity to the city centre, and lower neighbourhood-level greenness were associated with higher ambient NO2. At the city level, higher vehicle congestion, population size, and population density were associated with higher ambient NO2.

INTERPRETATION

Almost nine out of every ten residents of Latin American cities live with ambient NO2 concentrations above WHO guidelines. Increasing neighbourhood greenness and reducing reliance on fossil fuel-powered vehicles warrant further attention as potential actionable urban environmental interventions to reduce population exposure to ambient NO2.

FUNDING

Wellcome Trust, National Institutes of Health, Cotswold Foundation.

A hyperlocal hybrid data fusion near-road PM2.5 and NO2 annual risk and environmental justice assessment across the United States

Exposure to traffic-related air pollutants (TRAPs) has been associated with numerous adverse health effects. TRAP concentrations are highest meters away from major roads, and disproportionately affect minority (i.e., non-white) populations often considered the most vulnerable to TRAP exposure. To demonstrate an improved assessment of on-road emissions and to quantify exposure inequity in this population, we develop and apply a hybrid data fusion approach that utilizes the combined strength of air quality observations and regional/local scale models to estimate air pollution exposures at census block resolution for the entire U.S. We use the regional photochemical grid model CMAQ (Community Multiscale Air Quality) to predict the spatiotemporal impacts at local/regional scales, and the local scale dispersion model, R-LINE (Research LINE source) to estimate concentrations that capture the sharp TRAP gradients from roads. We further apply the Regionalized Air quality Model Performance (RAMP) Hybrid data fusion technique to consider the model's nonhomogeneous, nonlinear performance to not only improve exposure estimates, but also achieve significant model performance improvement. With a R2 of 0.51 for PM2.5 and 0.81 for NO2, the RAMP hybrid method improved R2 by ~0.2 for both pollutants (an increase of up to ~70% for PM2.5 and ~31% NO2). Using the RAMP Hybrid method, we estimate 264,516 [95% confidence interval [CI], 223,506-307,577] premature deaths attributable to PM2.5 from all sources, a ~1% overall decrease in CMAQ-estimated premature mortality compared to RAMP Hybrid, despite increases and decreases in some locations. For NO2, RAMP Hybrid estimates 138,550 [69,275-207,826] premature deaths, a ~19% increase (22,576 [11,288 - 33,864]) compared to CMAQ. Finally, using our RAMP hybrid method to estimate exposure inequity across the U.S., we estimate that Minorities within 100 m from major roads are exposed to up to 15% more PM2.5 and up to 35% more NO2 than their White counterparts.

Long-Term Exposure to Traffic-Related Air Pollution and Diabetes: A Systematic Review and Meta-Analysis

Objectives: We report results of a systematic review on the health effects of long-term traffic-related air pollution (TRAP) and diabetes in the adult population. Methods: An expert Panel appointed by the Health Effects Institute conducted this systematic review. We searched the PubMed and LUDOK databases for epidemiological studies from 1980 to July 2019. TRAP was defined based on a comprehensive protocol. Random-effects meta-analyses were performed. Confidence assessments were based on a modified Office for Health Assessment and Translation (OHAT) approach, complemented with a broader narrative synthesis. We extended our interpretation to include evidence published up to May 2022. Results: We considered 21 studies on diabetes. All meta-analytic estimates indicated higher diabetes risks with higher exposure. Exposure to NO₂ was associated with higher diabetes prevalence (RR 1.09; 95% CI: 1.02; 1.17 per 10 μg/m³), but less pronounced for diabetes incidence (RR 1.04; 95% CI: 0.96; 1.13 per 10 μg/m³). The overall confidence in the evidence was rated moderate, strengthened by the addition of 5 recently published studies. Conclusion: There was moderate evidence for an association of long-term TRAP exposure with diabetes.

Impact of Ambient Ultrafine Particles on Cause-Specific Mortality in Three German Cities

Rationale: Exposure to ambient air pollution has been associated with adverse effects on morbidity and mortality. However, the evidence for ultrafine particles (UFPs; 10-100 nm) based on epidemiological studies remains scarce and inconsistent. Objectives: We examined associations between short-term exposures to UFPs and total particle number concentrations (PNCs; 10-800 nm) and cause-specific mortality in three German cities: Dresden, Leipzig, and Augsburg. Methods: We obtained daily counts of natural, cardiovascular, and respiratory mortality between 2010 and 2017. UFPs and PNCs were measured at six sites, and measurements of fine particulate matter (PM2.5; ⩽2.5 μm in aerodynamic diameter) and nitrogen dioxide were collected from routine monitoring. We applied station-specific confounder-adjusted Poisson regression models. We investigated air pollutant effects at aggregated lags (0-1, 2-4, 5-7, and 0-7 d after UFP exposure) and used a novel multilevel meta-analytical method to pool the results. Additionally, we assessed interdependencies between pollutants using two-pollutant models. Measurements and Main Results: For respiratory mortality, we found a delayed increase in relative risk of 4.46% (95% confidence interval, 1.52 to 7.48%) per 3,223-particles/cm3 increment 5-7 days after UFP exposure. Effects for PNCs showed smaller but comparable estimates consistent with the observation that the smallest UFP fractions showed the largest effects. No clear associations were found for cardiovascular or natural mortality. UFP effects were independent of PM2.5 in two-pollutant models. Conclusions: We found delayed effects for respiratory mortality within 1 week after exposure to UFPs and PNCs but no associations for natural or cardiovascular mortality. This finding adds to the evidence on the independent health effects of UFPs.

Ambient nitrogen dioxide in 47,187 neighborhoods across 326 cities in eight Latin American countries: population exposures and associations with urban features

Background

Health research on ambient nitrogen dioxide (NO2) is sparse in Latin America, despite the high prevalence of NO2-associated respiratory diseases in the region. This study describes within-city distributions of ambient NO2 concentrations at high spatial resolution and urban characteristics associated with neighborhood ambient NO2 in 326 Latin American cities.

Methods

We aggregated estimates of annual surface NO2 at 1 km2 spatial resolution for 2019, population counts, and urban characteristics compiled by the SALURBAL project to the neighborhood level (i.e., census tracts). We described the percent of the urban population living with ambient NO2 levels exceeding WHO Air Quality Guidelines. We used multilevel models to describe associations of neighborhood ambient NO2 concentrations with population and urban characteristics at the neighborhood and city levels.

Findings

We examined 47,187 neighborhoods in 326 cities from eight Latin American countries. Of the ≈236 million urban residents observed, 85% lived in neighborhoods with ambient annual NO2 above WHO guidelines. In adjusted models, higher neighborhood-level educational attainment, closer proximity to the city center, and lower neighborhood-level greenness were associated with higher ambient NO2. At the city level, higher vehicle congestion, population size, and population density were associated with higher ambient NO2.

Interpretation

Almost nine out of every 10 residents of Latin American cities live with ambient NO2 concentrations above WHO guidelines. Increasing neighborhood greenness and reducing reliance on fossil fuel-powered vehicles warrant further attention as potential actionable urban environmental interventions to reduce population exposure to ambient NO2.

Funding

Wellcome Trust, National Institutes of Health, Cotswold Foundation.

Air pollution and surrounding greenness in relation to ischemic stroke: A population-based cohort study

BACKGROUND

Evidence for the association between environmental exposures and ischemic stroke (IS) is limited and inconsistent. We aimed to assess the relationship between exposure to air pollutants, residential surrounding greenness, and incident IS, and to identify population subgroups particularly sensitive to these exposures.

METHODS

We used data from administrative health registries of the public healthcare system in Catalonia, Spain to construct a cohort of individuals aged 18 years and older without a previous stroke diagnosis at 1st January 2016 (n = 3 521 274). We collected data on sociodemographic characteristics and cerebrovascular risk factors, and derived exposure at the participant's residence to ambient levels of fine particulate matter (PM_2.5), black carbon (BC), nitrogen dioxide (NO₂), and Normalized Difference Vegetation Index (NDVI) in a 300 m buffer as an indicator of greenness. The primary outcome was IS diagnosis at any point during the follow-up. We used Cox proportional hazards models to estimate associations between environmental exposures and incident IS and stratified analyses to investigate effect modification.

RESULTS

Between 1st January 2016 and 31st December 2017, 10 865 individuals were admitted to public hospitals with an IS diagnosis. Median exposure levels were: 17 µg/m³ PM_2.5, 35 µg/m³ NO₂, 2.28 µg/m³ BC and 0.27 NDVI. Individuals with higher residential exposure to air pollution were at greater risk of IS: HR 1·04 (95% CI:0·99-1·10) per 5 µg/m³ of PM_2.5; HR 1.05 (95% CI:1·00-1·10) per 1 µg/m³ of BC; HR 1·04 (95% CI:1·03-1·06) per 10 µg/m³ of NO₂. Conversely, individuals with higher residential surrounding green space, had lower risk of IS (HR 0·84; CI 95%:0·7-1.0). There was no evidence of effect modification by individual characteristics.

CONCLUSIONS

Higher incidence of IS was observed in relation to long-term exposures to air pollution, particularly NO₂, in a region that meets European health-based air quality standards. Residential surrounding greenness was associated with lower incidence of IS.