Short-Term Association between Sulfur Dioxide and Mortality: A Multicountry Analysis in 399 Cities
Bibliographic record
Abstract
Background: Epidemiological evidence on the health risks of sulfur dioxide (SO2) is more limited compared with other pollutants, and doubts remain on several aspects, such as the form of the exposure–response relationship, the potential role of copollutants, as well as the actual risk at low concentrations and possible temporal variation in risks. Objectives: Our aim was to assess the short-term association between exposure to SO2 and daily mortality in a large multilocation data set, using advanced study designs and statistical techniques. Methods: The analysis included 43,729,018 deaths that occurred in 399 cities within 23 countries between 1980 and 2018. A two-stage design was applied to assess the association between the daily concentration of SO2 and mortality counts, including first-stage time-series regressions and second-stage multilevel random-effect meta-analyses. Secondary analyses assessed the exposure–response shape and the lag structure using spline terms and distributed lag models, respectively, and temporal variations in risk using a longitudinal meta-regression. Bi-pollutant models were applied to examine confounding effects of particulate matter with an aerodynamic diameter of ≤10μm (PM10) and 2.5μm (PM2.5), ozone, nitrogen dioxide, and carbon monoxide. Associations were reported as relative risks (RRs) and fractions of excess deaths. Results: The average daily concentration of SO2 across the 399 cities was 11.7 μg/m3, with 4.7% of days above the World Health Organization (WHO) guideline limit (40 μg/m3, 24-h average), although the exceedances occurred predominantly in specific locations. Exposure levels decreased considerably during the study period, from an average concentration of 19.0 μg/m3 in 1980–1989 to 6.3 μg/m3 in 2010–2018. For all locations combined, a 10-μg/m3 increase in daily SO2 was associated with an RR of mortality of 1.0045 [95% confidence interval (CI): 1.0019, 1.0070], with the risk being stable over time but with substantial between-country heterogeneity. Short-term exposure to SO2 was associated with an excess mortality fraction of 0.50% [95% empirical CI (eCI): 0.42%, 0.57%] in the 399 cities, although decreasing from 0.74% (0.61%, 0.85%) in 1980–1989 to 0.37% (0.27%, 0.47%) in 2010–2018. There was some evidence of nonlinearity, with a steep exposure–response relationship at low concentrations and the risk attenuating at higher levels. The relevant lag window was 0–3 d. Significant positive associations remained after controlling for other pollutants. Discussion: The analysis revealed independent mortality risks associated with short-term exposure to SO2, with no evidence of a threshold. Levels below the current WHO guidelines for 24-h averages were still associated with substantial excess mortality, indicating the potential benefits of stricter air quality standards. https://doi.org/10.1289/EHP11112
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".