Iron Depletion Is Associated With Daytime Bottle-feeding in the Second and Third Years of Life
Bibliographic record
Abstract
OBJECTIVE: To measure the association between daytime bottle-feeding and iron depletion in young children. DESIGN: Cross-sectional design with concurrent measurement of exposure and outcome. The exposure was the current container (bottle or cup) used for daytime milk consumption. Child, maternal, and dietary variables were collected. SETTING: Community-based pediatric practice serving a diverse population in an urban Canadian city. PARTICIPANTS: One hundred fifty healthy children, aged 12 to 38 months, attending a well-child care visit. MAIN OUTCOME MEASURE: Iron depletion (serum ferritin level, <10 microg/L]). RESULTS: Of the 150 children, 82 (55%) were bottle-fed and 68 (45%) were cup fed. Iron depletion occurred in 29 (37%) of 78 bottle-fed and in 12 (18%) of 67 cup-fed children. The crude relative risk for iron depletion was 1.81 (95% confidence interval, 1.09-3.01). In the final logistic regression model, a significant association between bottle use and iron depletion was identified, beginning after the age of 16 months. At 18 months, the relative risk, adjusted for several child, maternal, and dietary variables, for the association between bottle use and iron depletion was 1.31 (95% confidence interval,1.24-1.47); at 24 months, the adjusted relative risk was 2.50 (95% confidence interval, 2.46-2.53). Milk consumption of more than 16 oz/d occurred in 55 (67%) of the 82 bottle-fed and in 22 (32%) of the 68 cup-fed children (P<.001). CONCLUSIONS: In the second and third years of life, there is an almost 2-fold association between iron depletion and daytime bottle-feeding compared with cup feeding. The child's age may be a modifier, and milk volume consumed may be a mediator, of this association. Duration of bottle use is a potentially modifiable practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".