Comparing trends in mid-life ‘deaths of despair’ in the USA, Canada and UK, 2001–2019: is the USA an anomaly?
Bibliographic record
Abstract
OBJECTIVES: In recent years, 'deaths of despair' due to drugs, alcohol and suicide have contributed to rising mid-life mortality in the USA. We examine whether despair-related deaths and mid-life mortality trends are also changing in peer countries, the UK and Canada. DESIGN: Descriptive analysis of population mortality rates. SETTING: The USA, UK (and constituent nations England and Wales, Northern Ireland and Scotland) and Canada, 2001-2019. PARTICIPANTS: Full population aged 35-64 years. OUTCOME MEASURES: We compared all-cause and 'despair'-related mortality trends at mid-life across countries using publicly available mortality data, stratified by three age groups (35-44, 45-54 and 55-64 years) and by sex. We examined trends in all-cause mortality and mortality by causes categorised as (1) suicides, (2) alcohol-specific deaths and (3) drug-related deaths. We employ several descriptive approaches to visually inspect age, period and cohort trends in these causes of death. RESULTS: The USA and Scotland both saw large relative increases and high absolute levels of drug-related deaths. The rest of the UK and Canada saw relative increases but much lower absolute levels in comparison. Alcohol-specific deaths showed less consistent trends that did not track other 'despair' causes, with older groups in Scotland seeing steep declines over time. Suicide deaths trended slowly upward in most countries. CONCLUSIONS: In the UK, Scotland has suffered increases in drug-related mortality comparable with the USA, while Canada and other UK constituent nations did not see dramatic increases. Alcohol-specific and suicide mortalities generally follow different patterns to drug-related deaths across countries and over time, questioning the utility of a cohesive 'deaths of despair' narrative.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".