Exposure–Response Associations of Ambient Heavy Metal and Persistent Organic Pollutant with All-Cause and Cause-Specific Mortality: A Prospective Cohort Study
Bibliographic record
Abstract
The exposure-response associations of ambient heavy metals and persistent organic pollutants (POPs) with mortality in the general population remain unclear. This cohort study aimed to explore the long-term effect of exposure to four air pollutants, including lead (Pb), cadmium (Cd), mercury (Hg), and benzo(a)pyrene [B(a)P] on all-cause and cause-specific mortality. This study involved 497,056 participants from the UK Biobank cohort. We used the Cox proportional hazards model to calculate associations. Effects of joint exposure to heavy metals were estimated using quantile g-computation. Shape of the exposure-response association was examined by fitting penalty splines, in both the total population and subpopulations stratified by age, sex, smoking status, and genetic factors. Modifying effects of age, sex, smoking status, and genetic factors were also examined. Over a median follow-up of 13.7 years, we identified 39,530 (8.0%) deaths. Exposure to mixtures of Pb, Cd, and Hg was associated with 1.040-1.154 times increased risk of all-cause cancer, cardiovascular disease (CVD), stroke, and respiratory disease mortality. Of the specific causes of mortality, Pb and Cd were most strongly associated with respiratory diseases, including chronic obstructive pulmonary disease, followed by ischemic heart disease, CVD, and cancer. Hg and B(a)P seemed to exhibit lower toxicity compared with Pb and Cd. Exposure-response curves demonstrated monotonically increased risk for most mortality outcomes, though Hg was found to be nonlinearly associated with all-cause and stroke mortality. Age, smoking status, and genetic factors were found to modify the susceptibility to heavy metals. Our findings suggested that long-term exposure to heavy metals and B(a)P was monotonically associated with elevated risk of multiple mortality outcomes, indicating there may be no safe threshold for these chemicals. Substantial benefits to public health could be achieved through stringent environmental regulations and clean air initiatives.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".