Female lung cancer mortality and long-term exposure to particulate matter in Italy
Bibliographic record
Abstract
Background: Outdoor air pollution and particulate matter (PM) have recently been classified in Group 1 by IARC. In Italy there is no epidemiological study on the association between female lung cancer and PM as measured by the official monitoring stations. Methods: We estimated the dose–response relationship between female lung cancer mortality and available long-term outdoor PM10 and/or PM2.5 concentrations for all the Italian province capital city municipalities (respectively, 64 and 32 municipalities). Multiple regression analysis of standardized mortality rates (SMRates) for the period 2000–11, as a function of PM concentrations, considering percentage of smokers and deprivation index as additional explanatory variables, was performed for PM10 only. Results: The number of province capital cities with available PM2.5 data was not sufficient to detect a significant increment of SMRates as a function of concentrations. An SMRate increase of 0.325 for 1 μg m−3 increment of PM10 concentration was calculated. Moreover, the attributable risk of the overall SMRates for the two subgroups of municipalities under/equal and above 20 μg m−3 value was evaluated. Attributable deaths were computed by both the unitary SMRate increase and the attributable risk. A rough estimate of the impact of PM10 exposure at level above the WHO guideline value of 20 μg m−3 in these 64 municipalities is between 2920 and 3449 lung cancer deaths out of 22 162 (13–16%). Conclusion: Maintaining the PM10 concentrations below such WHO recommendation, an overall saving of nearly 300 lung cancer deaths per year in a population of 8 146 520 women living in the municipalities at study has been evaluated.
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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 | 0.008 | 0.000 |
| 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) | 0.002 | 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".