Comparison of waist circumference using the World Health Organization and National Institutes of Health protocols.
Bibliographic record
Abstract
BACKGROUND: This study compares waist circumference (WC) measured using the World Health Organization (WHO) and National Institutes of Health (NIH) protocols to determine if the results differ significantly, and whether equations can be developed to allow comparison between WC taken at the two different measurement sites. DATA AND METHODS: Valid WC measurements using the WHO and NIH protocols were obtained for 6,306 respondents aged 3 to 79 from Cycle 2 of the Canadian Health Measures Survey. Linear regression was used to identify factors associated with the difference between the NIH and WHO values. Separate prediction equations by sex were generated using WC NIH as the outcome and WC_WHO and age as independent variables. Sensitivity and specificity were calculated to examine whether health risk based on the WC_WHO and on WC_NIH predicted measurements agreed with estimates based on WC_NIH actual measured values. RESULTS: For adults and children, WC_NIH significantly exceeded WC_WHO (1.0 cm for boys, 2.1 cm for girls, 0.8 cm for men and 2.2 cm for women). Predicted NIH values were statistically similar to measured values. Sensitivity (86% to 98%) and specificity (70% to 100%) values for health risk category based on the NIH predicted values were very high, meaning that respondents would be appropriately classified when compared with actual measured values. INTERPRETATION: The prediction equations proposed in this study can be applied to historical datasets to compare estimates based on WC data measured using the WHO and NIH protocols.
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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 | 0.047 | 0.144 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".