Intake of supplementary food during pregnancy and lactation and its association with child nutrition in Timor Leste
Bibliographic record
Abstract
ABSTRACT: There is little evidence on maternal consumption of supplementary food on nutritional status of children. The objectives of this study were to measure the prevalence and determinants of supplementary food intake during pregnancy and lactation, and their association with nutritional status of under-five children in Timor Leste. METHODS: Cross-sectional data from Timor Leste Demographic and Health Survey on 5,993 mother (15-49 years) child dyads (<5 years) were included in the analysis. Self-reported intake of supplementary food intake was the explanatory variable. Child's nutritional status was assessed by stunting, wasting, and underweight and categorized according to WHO recommendations. RESULTS: The prevalence of taking supplementary food during pregnancy and lactation was, respectively, 29.1% (95% CI [27.2-31.0]) 31.0% (95% CI [29.1-33.0]), and that of taking iron supplement during pregnancy was close to three-fifths (63.1%, 95% CI [60.9-65.3]). The odds of taking supplementary food during pregnancy and lactation were lower among those in the younger age groups and higher among urban residents. Compared with mothers who had supplementary food during pregnancy and lactation, those did not have had respectively 1.36 (OR = 1.360, 95% CI [1.191-2.072]) and 1.15 times (OR = 1.152, 95% CI [1.019-1.754]) higher odds of having stunted, and 1.30 (OR = 1.307, 95% CI [1.108-1.853]) and 1.43 (OR = 1.426, 95% CI [1.140-1.863]) times higher odds of having underweight children. Those who had none of the supplements had respectively 1.67 (OR = 1.674, 95% CI [1.118-2.087]) and 1.63 (OR = 1.631, 95% CI [1.130-2.144]) times higher odds of having stunted and underweight children. CONCLUSION: A great majority of the mothers in Timor Leste are not taking supplementary food during pregnancy and lactation. We found a positive relationship between supplementary food intake during pregnancy and lactation with stunting and wasting among under-five children.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".