Should Waist Circumference Cutoffs in the Context of Cardiometabolic Risk Factor Assessment be Specific to Sex, Age, and BMI?
Bibliographic record
Abstract
OBJECTIVE: A sex-specific standard waist circumference (WC) is widely used to determine cardiometabolic risk across ages even though aging impacts the link between fat distribution and cardiometabolic risk. The objective was to propose WC thresholds that better predict metabolic abnormalities according to sex, age, and body mass index (BMI) categories. METHODS: First, receiver operating characteristic analyses were performed to identify optimal age (20-49, 50-64, and 65-80 years) and BMI (normal weight, overweight, obese I, and obese II+) specific WC thresholds to correctly identify at-risk individuals, that is, presenting ≥2 cardiometabolic risk factors of metabolic syndrome (n = 23,482; NHANES 2007-2014). Second, cross-validation analyses (n = 18,686; NHANES 1999-2006) were used to validate these WC optimal thresholds. Univariate logistic regression models with WC as an independent predictor were performed to quantify odds of being at-risk for each age and BMI subgroups. RESULTS: When age and BMI categories were considered in the identification of optimal WC thresholds, sensitivity to correctly identify at-risk individuals significantly improved. CONCLUSIONS: Our results indicate that the use of WC thresholds that are specific to age and BMI subcategories significantly increases the capacity to accurately identify at-risk individuals. They would thus be highly appropriate for clinicians in the context of efficient cardiometabolic risk assessment and intervention recommendations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".