Environmental Pollution Effects on Mortality in an Industrial and a Non-industrial Municipality, in Voiotia Prefecture, Greece
Bibliographic record
Abstract
In the Oinofita region, there was strong evidence of air pollution and hexavalent chromium (Cr(VI))-contaminated drinking water due to the increased number of industries, in contrast to the closely-located region of Arachova, which served as a control. To examine the health effects of environmental pollution, we performed an ecological study to compare the all-cause and cause-specific mortality. We considered the registered citizens of both study areas during an 11-year period (1999-2009) and we used the direct method of standardization to calculate the age, gender and period standardized rates (ASRs) and the standardized rate ratios (SRRs), using the greater Prefecture of Voiotia as the standard population. Statistically significantly higher rates of all-cause mortality (SRR = 1.22, 95% confidence intervals (CI) 1.1-1.4), cardiovascular (SRR = 1.36, 95% CI 1.1-1.7) and cerebrovascular diseases (SRR = 2.93, 95% CI 1.8-4.8) were identified for Oinofita compared to Arachova. Furthermore, suggestive results were found for cardiopulmonary diseases among males (SRR = 1.52, 95% CI 1.0-2.4) and leukaemias (SRR = 4.65, 95% CI 0.9-25.3). Elevated SRRs, not statistically significant though, were also observed for respiratory diseases, all cancers and specific cancer sites (lip, oral cavity and pharynx, liver, stomach, pancreas, lung, prostate, colon and kidney and other genitourinary organs among females). Increased mortality rates in the Oinofita region support the hypothesis of adverse health effects association with air pollution and Cr(VI)-contaminated drinking water. Further studies are needed to determine if this association is causal and to establish preventive guidelines and public health recommendations.
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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 | 0.003 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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 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".