Association Between Obesity and Cigarette Smoking: A Community-Based Study
Bibliographic record
Abstract
Background: Cigarettes smoking and obesity are major public health problems and leading causes of preventable morbidity and mortality worldwide. The aim of this study was to investigate the relationship between cigarettes smoking and body weight status among Northern Saudi subjects. Methods: Data were collected during cross-sectional survey which included 5,000 Saudi selected from 30 primary health care centers (PHCs) in Hail Region. Results: The overall prevalence of obesity in Hail was 36.9%. The prevalence of cigarettes smoking was 10.2%. In those who are current smokers, obesity was present in 24.9%, normal weight in 30.9% and overweight in 7.4%. In those who are ex-smokers, obesity was present in 45.0%, normal weight in 20.3% and overweight in 31.3%. In those who never smoked, obesity was present in 27.6%, normal weight in 32.8% and overweight in 37.3%. Conclusion: Obesity was most prevalent among ex-smokers and least prevalent among current smokers. It is clear that from the analyses, the group of current smokers were less likely to be obese in comparison with never smokers and ex-smokers were more likely to be obese than both current smokers and never smokers. J Endocrinol Metab. 2016;6(5):149-153 doi: http://dx.doi.org/10.14740/jem378e
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".