Abdominal obesity and cardiovascular disease risk factors within body mass index categories.
Bibliographic record
Abstract
BACKGROUND: Several organizations recommend the use of measures of abdominal obesity in conjunction with body mass index (BMI) to assess obesity-related health risk. Recent evidence suggests that waist circumference (WC), waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR) are increasing within BMI categories. This shift may have affected the usefulness of abdominal obesity measures. DATA AND METHODS: Data are from respondents aged 18 to 79 to the 2007 to 2009 Canadian Health Measures Survey. Using logistic regression, this paper examines cardiovascular disease (CVD) risk factors in relation to WC, WHR and WHtR within BMI health-risk categories. CVD risk factors considered include components of the metabolic syndrome. RESULTS: Among men in the normal and overweight BMI categories, WHR and WHtR were positively associated with having at least two CVD risk factors. All three abdominal obesity measures were associated with increased odds of having at least two CVD risk factors among normal-weight women. Abdominal obesity was not associated with CVD risk factors for people in obese class I. INTERPRETATION: Among men and women in the normal BMI category, measures of abdominal obesity are associated with increased odds of CVD risk factors. This underscores the importance of measuring and monitoring abdominal obesity in normal-weight men and women.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.003 | 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 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".