116 Association between family income, risk for food insecurity and iron deficiency in healthy young Canadian children
Bibliographic record
Abstract
Abstract Background Iron deficiency peaks in prevalence (12% or higher) in early childhood and has been associated with poor developmental outcomes. Previous research examining associations between income and food insecurity (FI) with iron deficiency has been inconsistent and most did not measure iron status directly using serum ferritin or control for potential confounding variables. Objectives To examine the independent effects of family income and family risk for FI on iron status in healthy young children attending primary care. Design/Methods Healthy children ages 12–29 months were included in a cross-sectional analysis. Family income and risk for FI were collected from parents through self-reported questionnaires. Children with an affirmative response to the 1-item FI screen on the NutriSTEP (a validated screening tool of nutritional risk) or to at least one of the 2 items on the 2-item FI screen based on the 18-item Household Food Security Survey were categorized as a family at risk for FI. Iron status was assessed by serum ferritin. Children with C-reactive protein (CRP) >5 mg/L were excluded. Multivariable logistic regression analyses were used to examine the associations between both family income and family risk for FI with iron deficiency (serum ferritin <12µg/L) and IDA (serum ferritin <12 µg/L and hemoglobin <110 g/L), adjusting for age, sex, birthweight, zBMI, CRP, breastfeeding duration, bottle use, cow’s milk intake, formula feeding in the first year. Results Of 1245 children included, 131 (10.5%) of children were from households with a family income of <$40,000, 77 (6.2%) children were from families at risk for FI, 15% had iron deficiency, and 5% had IDA. The odds of children with a family income of <$40,000 having iron deficiency was 3 times (95% CI: 1.75, 5.26; P<0.0001) and having IDA was 4 times (95% CI: 1.71, 9.25; P=0.001) that for children in the highest family income group. Fully adjusted logistic regression showed weak evidence of a decreased odds of iron deficiency among children in families at risk for FI (OR 0.44, 95% CI: 0.19, 1.04; P=0.06) than all other children, and no association with IDA (OR 0.18, 95% CI: 0.02, 1.38; P=0.10). Conclusion A low family income of <$40,000 was associated with an increased risk for iron deficiency and IDA in young children. Risk for FI was not a risk factor for iron deficiency or IDA. Targeting income security may be more effective than targeting access to food to reduce health inequities in iron deficiency.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".