Modifying factors and temporal trends of adverse health effects of short-term exposure to PM2.5 in Canada (2001–2018)
Bibliographic record
Abstract
Considerable evidence has been accumulated on serious acute health outcomes associated with short-term exposure to ambient fine particulate matter (PM 2.5 ). Modifying factors of those associations, however, have been less explored and need further analyses. In this national study, we investigated whether short-term effects of PM 2.5 are modified according to region, cause of mortality/hospitalization, season, age, and sex. PM 2.5 -related adverse health effects were estimated by an ecological time-series study, covering about 80 % of the Canadian population for 18 years (2001–2018). We estimated city-specific associations using daily averages of PM 2.5 and temperature, and daily counts of hospitalizations and mortality (non-accidental all-cause, circulatory, and respiratory). National and regional associations were then estimated with a 2-stage model. We considered potential modifying factors of PM 2.5 -related adverse health effects, and examined linear trends in the annual associations. Nationally, PM 2.5 exposure was associated with both hospitalizations and mortality, and there was evidence of differences by the modifying factors. Of the various causes, circulatory mortality and respiratory hospitalization were more attributable to PM 2.5 exposure. We found regional differences for both all-cause hospitalization and all-cause mortality, and seasonal differences for respiratory hospitalization (warm season) and circulatory hospitalization (cold season). Circulatory mortality risk was significant for seniors and females. All-cause hospitalizations appeared to gradually decrease over time, but annual all-cause mortality remained constant at 0.6 % of the population. Adverse health effects of PM 2.5 exposures may depend on not only PM 2.5 concentration, but also other factors (region, cause, season, age, sex). National estimates for the baseline (age ≥ 1 year, both sexes) risk cannot be interpreted without consideration of the differences by modifying factors. Study findings can be used by seniors, women, and those who have pre-existing health conditions to make informed decisions regarding their health risks from daily exposure to ambient PM 2.5 . • Ambient PM 2.5 -related public health risks were estimated in Canada for 2001–2018. • PM 2.5 exposure was associated with cause-specific hospitalizations and mortality. • PM 2.5 -related health risks were modified by region, cause, season, age, and sex. • Seniors (>65) and females appeared vulnerable to short-term exposure to PM 2.5 . • Temporal trends in the annual PM 2.5 -related health risks varied by some factors.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".