Dairy Product Intake and Its Association with Body Weight and Cardiovascular Disease Risk Factors in a Population in Dietary Transition
Bibliographic record
Abstract
OBJECTIVE: Higher dairy product intake has shown beneficial effects on body weight, blood pressure, type 2 diabetes, and cardiovascular disease (CVD) risk factors in Caucasian populations. This study evaluated dairy product intake and its association with body weight and CVD risk profile among a population undergoing a dietary transition in Canada, the Nunavik Inuit. METHODS: Data were collected from August 27 to October 1, 2004, in the 14 villages of Nunavik on a Canadian research icebreaker (Canadian Coast Guard ship Amundsen). Dairy product intake and calcium intake were evaluated in 543 Inuit using a food frequency questionnaire. Physiological (lipid profile, fasting glucose, and insulin) and anthropometrical measurements were also obtained. RESULTS: The range of median dairy product intake extended from 120 g/d in the lowest tertile to 290 g/d in the highest tertile. The median of calcium intake was 524 mg/d. Participants in the highest tertile of dairy product consumption had higher body weight, fat-free mass, waist circumference, waist-to-hip ratio, and fasting glucose concentrations than participants in the lowest tertile (all p < 0.01). After adjustments for potential cofactors, no significant association was observed. A higher prevalence of Inuit participants with metabolic syndrome was observed in the higher tertile compared with the first tertile (10.3% vs 1.6%; p < 0.001). CONCLUSIONS: Higher dairy product intake in Nunavik Inuit is not related to protective effects on body weight and CVD. The consumption of dairy products in Nunavik Inuit is probably not sufficient to withdraw beneficial effects on body weight or CVD risk factors, as observed in North American populations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".