Cow’s milk fat and child adiposity: a prospective cohort study
Bibliographic record
Abstract
BACKGROUND: International guidelines recommend children aged 9 months to 2 years consume whole (3.25%) fat cow's milk, and children older than age 2 years consume reduced (0.1-2%) fat cow's milk to prevent obesity. The objective of this study was to evaluate the longitudinal relationship between cow's milk fat (0.1-3.25%) intake and body mass index z-score (zBMI) in childhood. We hypothesized that higher cow's milk fat intake was associated with lower zBMI. METHODS: A prospective cohort study of children aged 9 months to 8 years was conducted through the TARGet Kids! primary care research network. The exposure was cow's milk fat consumption (skim (0.1%), 1%, 2%, whole (3.25%)), measured by parental report. The outcome was zBMI. Height and weight were measured by trained research assistants and zBMI was determined according to WHO growth standards. A linear mixed effects model and logistic generalized estimating equations were used to determine the longitudinal association between cow's milk fat intake and child zBMI. RESULTS: Among children aged 9 months to 8 years (N = 7467; 4699 of whom had repeated measures), each 1% increase in cow's milk fat consumed was associated with a 0.05 lower zBMI score (95% CI -0.07 to -0.03, p < 0.0001) after adjustment for covariates including volume of milk consumed. Compared to children who consumed reduced fat (0.1-2%) milk, there was evidence that children who consumed whole milk had 16% lower odds of overweight (OR = 0.84, 95% CI 0.77 to 0.91, p < 0.0001) and 18% lower odds of obesity (OR = 0.82, 95% CI 0.68 to 1.00, p = 0.047). CONCLUSIONS: Guidelines for reduced fat instead of whole cow's milk during childhood may not be effective in preventing overweight or obesity.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".