Smoking and Diabetes: Sex and Gender Aspects and Their Effect on Vascular Diseases
Bibliographic record
Abstract
Smoking and diabetes mellitus (DM) have been identified as 2 major cardiovascular risk factors for many years. In the field of cardiovascular diseases, considering sex differences, or gender differences, or both has become an essential element in moving toward equitable and quality health care. We reviewed the effect of sex or gender on the link between smoking and DM. The risk of type 2 DM due to smoking has been established in both sexes at the same level. As is the case in the general population, the prevalence of smoking in those with DM is higher in men than in women, although the decrease in smoking observed in recent years is more pronounced in men than in women. Regarding chronic DM complications, smoking is an independent risk factor for all-cause mortality, as well as macrovascular and microvascular complications, in both sexes. Nevertheless, in type 2 DM, the burden of smoking appears to be greater in women than in men for coronary heart disease morbidity, with women having a 50% greater risk of fatal coronary event. Women are more dependent to nicotine, cumulate psychosocial barriers to quitting smoking, and are more likely to gain weight, which might make it more difficult for them to quit smoking. Smoking cessation advice and treatments should take into account gender differences to improve the success and long-term maintenance of abstinence in people with and without DM. This might include interventions that address emotions and stress in women or designed to reach specific populations of men.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".