MORTALITY IN THE COKE/STEEL-MAKING TOWN OF SYDNEY, NOVA SCOTIA, 1951–1994.
Bibliographic record
Abstract
MORTALITY IN THE COKE/STEEL-MAKING TOWN OF SYDNEY, NOVA SCOTIA, 1951–1994. MICHEL CAMUS, BAND PIERRE, ZIELINSKI JAN, JIANG HUIXIA, SEMENCIW ROBERT. Health Canada. EMail: [email protected] Until 1988, the air of Sydney (Nova-Scotia, Canada) was heavily polluted by metals and gases emitted by a coke oven and a steel foundry. A creek pouring into Sydney’s harbour was used as a waste site. Now dubbed “the Sydney Tar Ponds”, it is heavily contaminated with PAHs, polychlorinated biphenyls (PCBs), solvents, and various heavy metals. In the early 1980s, high levels of contaminants in the sea fauna lead to a fishing ban. Populations may have been contaminated through respiratory, digestive and cutaneous routes. Previous reports have shown excess cancer mortality in the area, but were limited by short observation periods, biased comparisons, and residential misclassification. OBJECTIVES: To assess the health impact of past and present pollution in Sydney, a comprehensive health impact assessment plan was developed by citizens groups and governmental partners. In the exploratory “Phase I” of the plan, an ecologic mortality study covering 44 years of data (1951–94) was conducted to screen which of 120 causes of death suggested Sydney-specific risks relative to the surrounding and socio-economically comparable Cape Breton County. METHODS: Local mortality rates were corrected after assessing residential misclassification errors from a review of all death certificate data, using GIS tools. SMRs were computed using Canadian rates, and a Poisson chi-square statistic was used to test whether SMRs were significantly higher (P<=.05) in Sydney relative to Cape Breton County excluding Sydney. RESULTS: There was no excess mortality among the population 0 to 14 years of age. Among adults, some SMRs were significantly higher in Sydney than in CBC: “all cancers” (SMR ratio=1.05), cancers of the salivary glands(2.4), esophagus(1.3) and colon(1.3), multiple myeloma(1.8), ill-defined and secondary cancers(1.3), diabetes in males(1.6), multiple sclerosis(1.8), asthma(1.4), liver diseases(1.3). Many more SMRs were significantly elevated relative to Canada but not relative to surrounding CBC. CONCLUSION: These excess risks suggested Sydney-specific health problems but could not be attributed to specific pollution factors. Because this mortality study was less biased, more sensitive and more specific than previous ones, the observed excess risks had a greater impact on health decisions and research. They justified and were used to design well-focused case-control studies for the health impact assessment’s “Phase II”. Phase II is under way and will test specific occupational, environmental and life style hypotheses with a better control of potential confounders.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".