Canadian global village reality: Anthropometric surrogate cutoffs and metabolic abnormalities among Canadians of East Asian, South Asian, and European descent
Bibliographic record
Abstract
OBJECTIVE: To test the appropriateness of body mass index (BMI) and waist circumference (WC) cutoff points derived in largely white populations (ie, those of European descent) for detecting obesity-related metabolic abnormalities among East Asian and South Asian Canadians. DESIGN: Cross-sectional survey. SETTING: Primary care and community settings in Ontario. PARTICIPANTS: Canadians of East Asian (n = 130), South Asian (n = 113), and European (n = 111) descent. MAIN OUTCOME MEASURES: Variables for metabolic syndromes, including BMI, WC, body fat percentage, blood pressure, lipid profile, and fasting blood glucose and insulin levels, were measured. Receiver operating characteristics curve analysis was used to generate BMI and WC cutoff points based on various criteria for metabolic syndromes. RESULTS: Adjusting for sex and age, East Asian Canadians had a significantly lower mean BMI (23.2 kg/m 2) and mean WC (79.6 cm) than did those of South Asian (26.1 kg/m 2 and 90.3 cm) and European (26.5 kg/m 2 and 89.3 cm) descent (P < .05). The BMI cutoffs for an increased risk of metabolic abnormalities ranged from 23.1 to 24.4 kg/m 2 in East Asian Canadians; 26.6 to 26.8 kg/m 2 in South Asian Canadians; and 26.3 to 28.2 kg/m 2 in European Canadians. Waist circumference cutoffs for increased risk of metabolic abnormalities were relatively low in East Asian men (83.3 to 85.2 cm) and women (74.1 to 76.7 cm), compared with South Asian men (98.8 cm) and women (90.1 to 93.5 cm), as well as European men (91.6 to 95.2 cm) and women (82.8 to 88.3 cm). CONCLUSION: The BMI and WC cutoffs used for defining risk of metabolic abnormalities should be lowered for East Asian Canadians but not for South Asian Canadians. The World Health Organization ethnic-specific BMI and WC cutoffs should be used with caution, particularly with Asian migrants who have resided in Canada for a long period of time.
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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 | 0.002 | 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 | 0.001 |
| 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".