The rise and fall of tobacco smoking and associated rise and fall of coronary atherosclerosis the lethal role of tobacco
Bibliographic record
Abstract
In this review two new hypotheses are explored, one, that the decline in coronary heart disease is mainly due to a dramatic decline in the prevalence of underlying atherosclerosis and two, that tobacco smoking has been a much greater influence on atherosclerosis than previously estimated. The major outcome of coronary atherosclerosis is myocardial infarction. Between 1900 and 1960 the prevalence of coronary atherosclerosis dramatically rose in young male soldiers. Between 1960 and 2010 the prevalence of coronary atherosclerosis in young US soldiers equally dramatically fell. Understanding the reasons for this rise and fall offers important insights into the causes of atherosclerosis. In 1960 over 50% of US military personnel were tobacco smokers but by 1988 the rate had reduced to 30%. The increased prevalence of coronary atherosclerosis in young soldiers between 1900 and 1960 was mainly due to increased tobacco smoking. An additional influence was an increase in food and sugar consumption. The fall in atherosclerosis between 1960 and 2010 was probably due to a reduction in tobacco smoking and to a lesser extent, control of hypertension and lowering of high serum total cholesterol. In Western populations up to two thirds of the fall in deaths due to myocardial infarction has been shown to be due to declines in the incidence of heart attacks. Based on the data included in this review it is arguable that the main reason for the fall in the incidence of heart attacks is the fall in the prevalence of underlying coronary atherosclerosis. The adverse influences of tobacco have been well documented. However the enormity of these adverse influences has not been recognised. Over 50% of men continue to smoke tobacco in China, Indonesia, Russia and middle eastern countries. Based on the experience of Western countries over half of these men will die of smoking related conditions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".