Trends in the leading causes of injury mortality, Australia, Canada and the United States, 2000–2014
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to highlight the differences in injury rates between populations through a descriptive epidemiological study of population-level trends in injury mortality for the high-income countries of Australia, Canada and the United States. METHODS: Mortality data were available for the US from 2000 to 2014, and for Canada and Australia from 2000 to 2012. Injury causes were defined using the International Classification of Diseases, Tenth Revision external cause codes, and were grouped into major causes. Rates were direct-method age-adjusted using the US 2000 projected population as the standard age distribution. RESULTS: US motor vehicle injury mortality rates declined from 2000 to 2014 but remained markedly higher than those of Australia or Canada. In all three countries, fall injury mortality rates increased from 2000 to 2014. US homicide mortality rates declined, but remained higher than those of Australia and Canada. While the US had the lowest suicide rate in 2000, it increased by 24% during 2000-2014, and by 2012 was about 14% higher than that in Australia and Canada. The poisoning mortality rate in the US increased dramatically from 2000 to 2014. CONCLUSION: Results show marked differences and striking similarities in injury mortality between the countries and within countries over time. The observed trends differed by injury cause category. The substantial differences in injury rates between similarly resourced populations raises important questions about the role of societal-level factors as underlying causes of the differential distribution of injury in our communities.
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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 | 0.008 | 0.001 |
| 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".