Estimates of the Global Burden of Ambient PM 2.5 , Ozone, and NO 2 on Asthma Incidence and Emergency Room Visits

Abstract

Background: Asthma is the most prevalent chronic respiratory disease worldwide, affecting 358 million people in 2015. Ambient air pollution exacerbates asthma among populations around the world and may also contribute to new-onset asthma.

Objectives: We aimed to estimate the number of asthma emergency room visits and new onset asthma cases globally attributable to fine particulate matter (${\mathrm{PM}}_{2.5}$), ozone, and nitrogen dioxide (${\text{NO}}_2$) concentrations.

Methods: We used epidemiological health impact functions combined with data describing population, baseline asthma incidence and prevalence, and pollutant concentrations. We constructed a new dataset of national and regional emergency room visit rates among people with asthma using published survey data.

Results: We estimated that 9–23 million and 5–10 million annual asthma emergency room visits globally in 2015 could be attributable to ozone and ${\mathrm{PM}}_{2.5}$, respectively, representing 8–20% and 4–9% of the annual number of global visits, respectively. The range reflects the application of central risk estimates from different epidemiological meta-analyses. Anthropogenic emissions were responsible for $\sim 37\%$ and 73% of ozone and ${\mathrm{PM}}_{2.5}$ impacts, respectively. Remaining impacts were attributable to naturally occurring ozone precursor emissions (e.g., from vegetation, lightning) and ${\mathrm{PM}}_{2.5}$ (e.g., dust, sea salt), though several of these sources are also influenced by humans. The largest impacts were estimated in China and India.

Conclusions: These findings estimate the magnitude of the global asthma burden that could be avoided by reducing ambient air pollution. We also identified key uncertainties and data limitations to be addressed to enable refined estimation. https://doi.org/10.1289/EHP3766.

Figure 1.

Pollutant concentrations used to estimate asthma impacts. (A) ${\mathrm{PM}}_{2.5}$ concentrations (annual average, in ${\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$) in 2015, described by van Donkelaar et al. (2016; $\text{max}\text{concentration}=179.8{\mathrm{\mu }\mathrm{g}/\mathrm{m}}^3$). (B) Ozone concentrations in 2015 (annual average of 8hr daily maximum, in ppb), using multi-model average from TF HTAP ensemble ($\text{max}\text{concentration}=72.9\text{ppb}$). (C) ${\text{NO}}_2$ concentrations in 2015 (annual average, in ppb), using satellite-derived dataset from method described by Lamsal et al. (2008) and adjusted by modeled ratio of daily average to $1–2\mathrm{P}.\mathrm{M}.(1300–1400\text{hours})$ concentration ($\text{max}\text{concentration}=17.5\text{ppb}$).

Figure 2.

Global asthma ERVs associated with total ozone and ${\mathrm{PM}}_{2.5}$ concentrations among all ages in 2015, using RR central estimates from three epidemiological meta-analyses. (A) Asthma ERVs (millions) attributable to ozone and ${\mathrm{PM}}_{2.5}$ from anthropogenic and all sources. Confidence intervals (CI) (95%) reflect uncertainty in RR only. (B) Portion of pollution-attributable asthma ERVs occurring in each world region (results identical for all three RR estimates).

Figure 3.

Percent of global and regional asthma ERVs for all ages in 2015 that are attributable to total ozone (top) and ${\mathrm{PM}}_{2.5}$ (bottom) concentrations, using RR central estimates from three epidemiological meta-analyses.

Figure 4.

Asthma ERVs attributable to ${\mathrm{PM}}_{2.5}$ and ozone in 2015, using Zheng et al. (2015) RR central estimates. Panels show asthma ERVs attributable to total: (A) ozone, number of cases; (B) ozone, fraction of national asthma ERVs; (C) ${\mathrm{PM}}_{2.5}$, number of cases (D) ${\mathrm{PM}}_{2.5}$, fraction of national asthma ERVs. Panels (E–H) show the same results but using anthropogenic concentrations.

Figure 5.

Asthma incidence attributable to anthropogenic ${\mathrm{PM}}_{2.5}$ and ${\text{NO}}_2$ in 2015. (A) Number of new asthma cases (millions) associated with ${\mathrm{PM}}_{2.5}$ and ${\text{NO}}_2$ for various age groups using RRs from multiple epidemiological meta-analyses. Confidence intervals (CI) (95%) reflect error in the RR estimate only. (B) Percent of pollution-attributable new asthma cases among children occurring in each region (for each pollutant, results are identical for all RR estimates applied).