Iron deficiency among low income Canadian toddlers: a cross-sectional feasibility study in a Community Health Centre and non-Community Health Centre sites
Bibliographic record
Abstract
BACKGROUND: Iron deficiency in early childhood has been associated with poor developmental outcomes. Little is known about the nutritional health of young children receiving care at Canadian Community Health Centres (CHCs). Our objectives were to describe iron deficiency among toddlers at an Ontario CHC, to compare young children attending CHCs and non-CHCs, and assess the feasibility of conducting research on children in CHC settings. METHODS: One CHC, Kingston Community Health Centres (CHC) with two clinical sites and one community programming site was added to the nine non-CHC pediatric and primary care clinics in the existing TARGet Kids! research network. A cross-sectional feasibilitystudy was conducted.and. Healthy children, ages 12-36 months were Enrolled. iron deficiency without inflammation (ferritin< 14 μg/L and CRP < 10 mg/L) and serum ferritin were assessed. Adjusted multivariable regression analyses were used to evaluate an association between CHC enrolment and iron status. RESULTS: The CHC cohort (n = 31) was older, had lower household income, lower maternal education, higher nutrition risk scores, higher cow's milk intake, shorter breastfeeding duration and higher prevalence of unhealthy weights compared with the non-CHC cohort (n = 875). There was no association between CHC status and serum ferritin (difference in median serum ferritin 4.78 μg/L, 95% confidence interval [CI] -2.5, 14.3, p = 0.22) or iron deficiency (OR 0.55, 95% CI 0.11, - 2.73, p = 0.46) using multivariable linear and logistic regression, respectively. CONCLUSION: Despite differences in sociodemographic variables, we did not detect a difference in iron status between toddlers enrolled at CHCs compared to non-CHC settings. Further research is needed to understand the health effects of poverty generally, and iron deficiency specifically among children receiving care at CHCs.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".