Years of potential life lost in residents affected by floods in Hunan, China
Bibliographic record
Abstract
The potential life loss caused by floods has not been studied before. We carried out a retrospective cohort study in flood areas in Hunan, China in 1999. The standard mortality rate (SMR) and years of potential life lost (YPLL) were used to quantify the burden of flood on health. The SMRs of injury/poisoning and malignant neoplasm were higher in the river flood (151.36 x 10(-5), 127.30 x 10(-5)) and drainage problems (143.74 x 10(-5), 105.87 x 10(-5)) groups than those in the no-flood group (113.40 x 10(-5), 74.81 x 10(-5)). The standard rates of YPLL (SYPLL per thousand) in the river flood (89.56 per thousand) and drainage problems (71.30 per thousand) groups were significantly higher than those in the no-flood group (65.74 per thousand, P<0.05). The SYPLL was significantly higher in males than in females. The percentages of attributable risk (PARs) of SMRs and PARs of SYPLLs resulting from flood were 12.26 and 26.60% in the river flood group and 10.56 and 7.80% in the drainage problems group. We conclude that floods increase the affected residents' SYPLL, and that the river flood had stronger effects than the drainage problems floods.
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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 | 0.000 | 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) | 0.000 | 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".