The Association between Sulfate Air Pollution and Mortality at the County Scale: An Exploration of the Impact of Scale on a Long-Term Exposure Study
Bibliographic record
Abstract
The American Cancer Society (ACS) Study and its reanalysis are built upon in order to examine the impact of scale on the observed relationship between sulfates and mortality. The limitations of the original ACS Study (Pope et al., 1995) and the reanalysis of this study (Krewski et al., 2000) are discussed; while the latter dealt with some issues in using ecological data, it did not address scale. Next, the article outlines the county-scale study, the methods used to aggregate data, and the two-stage analysis used to derive relative risk (RR). Finally, the results of working at the county scale are compared with those obtained by the reanalysis team using larger metropolitan areas. Less than half of the cohort used in the metropolitan study were used at the county scale because of the limited availability of sulfate monitors and because five-digit ZIP codes more accurately assigned individuals to geographical areas. Therefore, the county data should be considered as new and not as a reorganization of the original data set. The reanalysis and the county studies should be considered as two separate studies that took different scales as their basic organizing principle. The RR of all-cause mortality from sulfate exposure at the county scale was 1.50 (1.30, 1.73) compared with 1.25 (1.13, 1.37) at the metropolitan scale; for cardiopulmonary mortality, the RR was 1.75 (1.48, 2.08) at the county scale compared with 1.29 (1.15, 1.46) at the metropolitan scale. Because lung cancer mortality was low in some counties, the two-stage random effects model became unstable. At the county scale, the RR from sulfates was more robust to the inclusion of ecologic covariates. Other place-specific ecologic covariates were either insignificant or barely significant (with a lower 95% confidence limit near 0.99 or 1.00) when included in the two-stage regression model for all-cause mortality with sulfates. Moreover, no ecologic covariate changed the RR of all-cause mortality from sulfates by 25% or more. Both population change and unemployment rate affected the RR for cardiopulmonary mortality from sulfate exposure by 25% or more in the county-scale analysis. However, when these two variables were entered into a multiple covariate analysis, the RR from sulfates decreased but remained strongly significant. Sulfur dioxide was not an important covariate at the county scale. Thus, at the county scale, long-term exposure to sulfates appears to be more strongly associated with increased risk of all-cause and cardiopulmonary mortality than previously indicated by the ACS study and its reanalysis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".