Trends in mortality from coronary heart and cerebrovascular diseases in the Americas: 1970–2000
Bibliographic record
Abstract
OBJECTIVE: To describe trends in mortality from coronary heart disease (CHD) and cerebrovascular accidents (CVAs) over the period 1970 to 2000 in the Americas. METHODS: Age standardised mortality rates were derived from the World Health Organization database and grouped according to the International classification of diseases, ninth revision. Joinpoint analysis was used to identify changes in trends. RESULTS: In the USA and Canada, CHD mortality rates declined by about 60% in both sexes. In Latin America, falls in CHD mortality were observed for Argentina, Brazil, Chile, Cuba, and Puerto Rico. In 2000, mortality rates among men were highest in Venezuela (137.3/100,000) and lowest (apart from Ecuador) in Argentina (63.5/100,000). For women, the rates were highest in Cuba (79.4/100,000) and lowest in Argentina (26.5/100,000). For CVA mortality, a decline by about 60% was observed in the USA and Canada for both sexes. The falls were smaller (about -25% to -40% among men and -20% to -50% among women) in Puerto Rico, Argentina, Chile, and Costa Rica and only minor in Ecuador, Mexico, and Venezuela. Around 2000, CVA mortality in Latin America was highest in Brazil (85.5/100,000 among men and 61.7/100,000 among women) and lowest in Puerto Rico (29.3/100,000 among men and 24.1/100,000 among women). CONCLUSIONS: Recent falls in CHD and CVA were less favourable in Latin America than in the USA and Canada. This may reflect unfavourable changes in nutrition (including obesity), physical activity, and smoking in most Latin American countries, together with less effective control of hypertension and management of the diseases.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".