Smoking, smoking cessation and heart disease risk: A 16-year follow-up study.
Bibliographic record
Abstract
BACKGROUND: Smoking is a major risk factor for heart disease. Over the past decade, the prevalence of smoking and the number of cigarettes smoked per day have decreased in Canada. Using a contemporary cohort of Canadian men and women, this study measured associations between smoking, smoking cessation and heart disease. METHODS: The study is based on nine cycles of data (1994/1995 through 2010/2011) from the National Population Health Survey, which collected information on smoking status every two years. The study sample consists of 4,712 men and 5,715 women aged 25 or older and free from heart disease in 1994/1995. Heart disease was determined by self-report of diagnosis, medication for, or death from heart disease. Relative risks of incident heart disease were compared among current daily smokers, former daily smokers, and those who never smoked daily. RESULTS: Compared with those who had never smoked daily, current daily smokers had a 60% higher risk of incident heart disease during the follow-up period. The risks were lower among current daily smokers who consumed fewer cigarettes. Although smoking cessation was associated with a lower risk of heart disease, 20 or more years of continuous cessation were required for the risk to approach that of people who never smoked daily. INTERPRETATION: Smoking cessation and cutting down the number of cigarettes smoked per day reduce the risk of heart disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".