US exceptionalism? International trends in midlife mortality
Bibliographic record
Abstract
BACKGROUND: Rising midlife mortality in the USA has raised concerns, particularly the increase in 'deaths of despair' (due to drugs, alcohol and suicide). Life expectancy is also stalling in other countries such as the UK, but how trends in midlife mortality are evolving outside the USA is less understood. We provide a synthesis of cause-specific mortality trends in midlife (25-64 years of age) for the USA and the UK as well as other high-income and Central and Eastern European (CEE) countries. METHODS: We document trends in midlife mortality in the USA, UK and a group of 13 high-income countries in Western Europe, Australia, Canada and Japan, as well as seven CEE countries from 1990 to 2019. We use annual mortality data from the World Health Organization Mortality Database to analyse sex- and age-specific (25-44, 45-54 and 55-64 years) age-standardized death rates across 15 major cause-of-death categories. RESULTS: US midlife mortality rates have worsened since 1990 for several causes of death including drug-related, alcohol-related, suicide, metabolic diseases, nervous system diseases, respiratory diseases and infectious/parasitic diseases. Deaths due to homicide, transport accidents and cardiovascular diseases have declined since 1990 but saw recent increases or stalling of improvements. Midlife mortality also increased in the UK for people aged 45-54 year and in Canada, Poland and Sweden among for those aged 25-44 years. CONCLUSIONS: The USA is increasingly falling behind not only high-income, but also CEE countries, some of which were heavily impacted by the post-socialist mortality crisis of the 1990s. Although levels of midlife mortality in the UK are substantially lower than those in the USA overall, there are signs that UK midlife mortality is worsening relative to that in Western Europe.
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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 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".