Association of body mass index, waist-to-hip ratio and waist circumference with cardiovascular risk factors: Isfahan Healthy Heart Program
Bibliographic record
Abstract
BACKGROUND: Investigating association of obesity indexes with other risk factors of cardiovascular diseases can help finding the best index in clinic for each sex. In this study, relationship of obesity based on body mass index (BMI), waist circumference, and waist-to-hip ratio with cardiovascular disease risk factors was investigated. METHODS: Participants of the first phase of Isfahan Healthy Heart Program (IHHP)in 2000-2001, including 12800 healthy people aged over 19 years from Isfahan, Najafabad and Arak (Iran), were studied. Anthropometric indexes and cardiovascular risk factors were collected using conventional definitions and standard questionnaires. Kappa coefficient of agreement between calculated risk factors with definition of obesity based on anthropometric indexes was calculated using SPSS software. RESULTS: Waist circumference showed the highest correlation with cardiovascular risk factors in men and women. Obesity based on BMI and waist-to-hip ratio in both sexes showed the same correlation with cardiovascular risk factors. In the correlation study matched for age, it was shown that the highest correlation was seen between waist circumference and two other indexes. Correlation coefficient over 60% showed the strongest agreement between obesity indexes and metabolic syndrome. CONCLUSION: In Iranian population, waist circumference as a simple measure with a higher agreement with cardiovascular risk factors can be used in clinical settings and epidemiological studies. Keywords: Obesity Indexes, Obesity, Cardiovascular Risk Factors, Isfahan.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".