Body composition and the apoB/apoA-I ratio in migrant Asian Indians and white Caucasians in Canada
Bibliographic record
Abstract
Migrant and native South Asians appear to be at increased risk of Type II diabetes mellitus and coronary disease. The aim of the present study was to determine the relationship between the most accurate summary index of the lipoprotein-related risk of vascular disease, the apoB (apolipoprotein B-100)/apoA-I (apolipoprotein A-I) ratio, and body composition in established migrant South Asians and white Caucasians living in Canada. Men and women living in Montreal, Canada between the ages of 20-60 years were recruited for participation in the study. Subjects were excluded if they had a history of cardiovascular disease or were taking lipid-lowering medication. Individuals identified themselves as Asian Indian or Caucasian. Anthropometric measurements were collected, including weight, height, waist circumference, hip circumference and body fat percentage. Plasma samples were analysed for total cholesterol, HDL-C (high-density lipoprotein-cholesterol), apoA-I and apoB. Indian subjects had a substantially higher WHR (waist-to-hip ratio) than Caucasian subjects [men, 0.93+/-0.01 compared with 0.86+/-0.01 respectively (P<0.001); women, 0.88+/-0.01 compared with 0.77+/-0.01 respectively (P<0.0001)]. WHR correlated strongly with body fat percentage in Caucasians (men, r=0.63, P=0.0002; women, r=0.74, P<0.0001). By contrast, there was no correlation in Indians (men, r=0.22, P value not significant; women, r=0.23, P value not significant). In addition, Indian men and women had a higher apoB/A-I ratio than Caucasians [men, 0.85+/-0.04 compared with 0.66+/-0.04 respectively (P=0.001); women, 0.73+/-0.04 compared with 0.56+/-0.03 respectively (P=0.0003)]. Of interest, there were also significant correlations between the apoB/apoA-I ratio and WHR in all of the groups, except the Indian women, which were stronger than the correlation of the apoB/apoA-I ratio with BMI. On the other hand, there was no significant relationship between the apoB/apoA-I ratio and the body fat percentage in any of the groups. In conclusion, the present study confirms that, as body fat percentage increases, the distribution of body fat differs between migrant Indians and Caucasians living in Canada. It also relates differences in body fat distribution to differences in the apoB/apoA-I ratio, providing at least part of the answer as to why South Asians may be at increased risk of vascular disease.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".