Caregiver feeding practices for infants and toddlers and their eating behaviors in Singapore
Bibliographic record
Abstract
Introduction Research on early childhood caregiver feeding practices and eating behaviors is limited, especially within Asian populations. This study examined these practices across key feeding domains of variety, autonomy, and mealtime setting and timing, stratified by three age groups: 0 to <7 months, 7 to <13 months, and 13 to <36 months. Methods A cross-sectional survey of 1,307 caregivers from a multi-ethnic population in Singapore captured demographic data, feeding practices, child eating behaviors, and caregivers’ knowledge, attitudes, and practices. One-way analysis of variance (ANOVA), independent T-tests and the chi-square test were used to assess feeding practices and eating behaviors across age groups. Results Regarding dietary variety, 14.8 and 6.1% of infants aged 7 to <13 months were offered three or fewer food groups frequently and daily, respectively. Additionally, 11.9% of infants were receiving processed foods often. At this age, only 1.0% of infants were consuming sugar-sweetened beverages (SSBs) often, while 2.0% consumed them daily. Among older children (aged 13 to <36 months), 8.1% were offered a limited variety of three food groups, while 4.5% were offered fewer than three. In contrast, a significantly higher proportion frequently consumed processed foods (24.0%) and sugar-sweetened beverages (25.2%; p < 0.05). In terms of autonomy, only 75.4% of infants (7– < 13 months) and 89.5% of older children (13– < 36 months) were able to self-feed. Caregivers of older children (13– < 36 months) were less likely to recognize hunger and satiety cues compared to those of infants (0–< 13 months; p < 0.05). Older children (13– < 36 months) also more frequently required special mealtime settings (36.6%), viewed screens during meals (29.9%), and were less likely to be offered post-midnight meals nightly (22.6% compared to infants; 70.3%; 0–< 13 months; p < 0.05). Conclusion These findings underscore the need for culturally tailored educational interventions to improve suboptimal feeding practices in children under three in Singapore’s multiethnic population.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".