Global, regional and national estimates of the burden of childhood asthma attributable to NO2 exposure for 204 countries and territories from 1990 to 2023: a Global Burden of Disease study 2023
Bibliographic record
Abstract
<h2>Summary</h2><h3>Background</h3> Asthma, a chronic lung condition characterised by inflammation and airway constriction, has been associated with nitrogen dioxide (NO<sub>2</sub>) exposure, an association that particularly impacts children. Our study rigorously assessed this relationship and estimated the global burden of childhood asthma attributable to NO<sub>2</sub> exposure in 204 countries and territories from 1990 to 2023. <h3>Methods</h3> We systematically reviewed epidemiological studies evaluating NO<sub>2</sub>'s long-term impact on childhood asthma. Using burden of proof meta-regression methods that account for bias by adjusting for study-design covariates and quantify remaining unexplained between-study heterogeneity to incorporate into uncertainty, we estimated the relative risk of childhood asthma occurring as a function of NO<sub>2</sub> exposure. From this, we computed global and country-specific population attributable fractions (PAFs) – i.e., the proportional change in asthma risk that would occur if NO<sub>2</sub> exposure were reduced to a theoretical minimum exposure level range of 4.6–6.2 ppb. We applied PAFs to data from the 2023 Global Burden of Disease Study (GBD) to derive the asthma burden attributable to NO<sub>2</sub> exposure in children and youths under 20 years old. Burden of proof methods allowed us to further compute risk–outcome metrics quantifying the magnitude of the NO<sub>2</sub>–asthma association and its strength of supporting evidence. <h3>Findings</h3> We identified a total of 27 cohort studies, spanning 12 countries, primarily in Europe and high-income North America, with some studies from Asia (China and Japan). A meta-regression log-linear risk curve of these studies produced a summary RR of 1.05 (95% UI 0.99–1.12) per 5 ppb NO<sub>2</sub> and Egger's regression indicated significant publication bias. We estimated a global PAF of 4.67% (95% uncertainty interval [UI]: −3.75 to 20.6; all UIs reported in this study are inclusive of between-study heterogeneity except where noted), yielding 233,000 (−250,000–956,000) years lived with disability (YLDs) attributable to NO<sub>2</sub> globally in 2023. GBD 2023 ranked NO<sub>2</sub> seventh among environmental risk factors contributing to YLDs in children for all causes and third for childhood asthma YLDs. Attributable burden estimates and trends varied significantly by GBD super-region. While NO<sub>2</sub>-attributable childhood asthma burden has declined substantially since 1990 in the high-income and central Europe, eastern Europe, and central Asia super-regions, NO<sub>2</sub> remains a prominent environmental risk factor in these two super-regions, ranked third in both super-regions for paediatric asthma YLDs in 2023, contributing 57,100 (−63 600 to 242,000) and 6570 (−7050 to 30,200) YLDs, respectively. In South Asia, NO<sub>2</sub> ranks second as risk factor for pediatric asthma contributing to 20,100 (−17 600, 105,000) YLDs in 2023. <h3>Interpretation</h3> NO<sub>2</sub> pollution remains a top environmental risk for paediatric health, necessitating policy interventions targeting NO<sub>2</sub> pollution, especially in high-income locations and urban areas. <h3>Funding</h3> The research described in this article was conducted in part under contract with the Health Effects Institute (HEI), an organization jointly funded by the United States Environmental Protection Agency (EPA) and certain motor vehicle and engine manufacturers, grant number 4977/20-11. The contents of this article do not necessarily reflect the views of HEI or its sponsors, nor do they necessarily reflect the views and policies of the EPA or motor vehicle and engine manufacturers. Additional funding for this study was received by the Gates foundation, grant no. OPP1152504 for MB, KB, and SW. SA, DG, AM and GHK were supported by NASA grant no. 80NSSC21K0511 and SA and GHK NIH grant no. P20ES036775.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".