Association between Obesity and Cardiometabolic Health Risk in Asian-Canadian Sub-Groups
Bibliographic record
Abstract
OBJECTIVES: To quantify and compare the association between the World Health Organizations' Asian-specific trigger points for public health action ['increased risk': body mass index (BMI) ≥23 kg/m2, and; 'high risk': BMI ≥27.5 kg/m2] with self-reported cardiovascular-related conditions in Asian-Canadian sub-groups. METHODS: Six cycles of the Canadian Community Health Survey (2001-2009) were pooled to examine BMI and health in Asian sub-groups (South Asians, Chinese, Filipino, Southeast Asians, Arabs, West Asians, Japanese and Korean; N = 18 794 participants, ages 18-64 y). Multivariable logistic regression, adjusting for demographic, lifestyle characteristics and acculturation measures, was used to estimate the odds of cardiovascular-related health (high blood pressure, heart disease, diabetes, 'at least one cardiometabolic condition') outcomes across all eight Asian sub-groups. RESULTS: Compared to South Asians (OR = 1.00), Filipinos had higher odds of having 'at least one cardiometabolic condition' (OR = 1.29, 95% CI: 1.04-1.62), whereas Chinese (0.63, 0.474-0.9) and Arab-Canadians had lower odds (0.38, 0.28-0.51). In ethnic-specific analyses (with 'acceptable' risk weight as the referent), 'increased' and 'high' risk weight categories were the most highly associated with 'at least one cardiometabolic condition' in Chinese ('increased': 3.6, 2.34-5.63; 'high': 8.9, 3.6-22.01). Compared to normal weight South Asians, being in the 'high' risk weight category in all but the Southeast Asian, Arab, and Japanese ethnic groups was associated with approximately 3-times the likelihood of having 'at least one cardiometabolic condition'. CONCLUSION: Differences in the association between obesity and cardiometabolic health risks were seen among Asian sub-groups in Canada. The use of WHO's lowered Asian-specific BMI cut-offs identified obesity-related risks in South Asian, Filipino and Chinese sub-groups that would have been masked by traditional BMI categories. These findings have implications for public health messaging, especially for ethnic groups at higher odds of obesity-related health risks.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".