Association between fruit juice consumption and self‐reported body mass index among adult Canadians
Bibliographic record
Abstract
BACKGROUND: The prevalence of obesity and being overweight is rising among adult Canadians and diet is recognised as one of the main causes of obesity. The consumption of fruit and vegetables is shown to be protective against obesity and being overweight but little is known about the association of fruit juice consumption and obesity and being overweight. The present study aimed to investigate the association between fruit juice consumption and self-reported body mass index (BMI) among adult Canadians. METHODS: This analysis is based on the Canadian Community Health Survey, Cycle 3.1. A regression method was used to assess the association of fruit juice consumption with self-reported BMI in 18-64-year-old Canadians who had been adjusted for sex, age, total household income, education, self-rated health, and daily energy expenditure. Because the analysis is based on a cross-sectional dataset, it does not imply a cause and effect relationship. RESULTS: Almost 38.6% of adult Canadians reported a fruit juice intake of 0.5-1.4 times per day and 18.2% consumed fruit juice more than 1.5 times per day. Participants with normal weight were likely to consume more fruit juice than obese individuals. Regression analysis showed a negative association between fruit juice consumption and BMI after adjusting for age, sex, education, marital status, income, total fruit and vegetable intake, daily energy expenditure, and self-rated health. On average, for each daily serving of fruit juice, a -0.22 unit (95% confidence interval = -0.33 to -0.11) decrease in BMI was observed. CONCLUSIONS: The results obtained showed a moderate negative association between fruit juice intake and BMI, which may suggest that a moderate daily consumption of fruit juice is associated with normal weight status.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".