Maternal perceptions and concerns about children’s weight status and diet quality: a study among Black immigrant families
Bibliographic record
Abstract
Abstract Objective: To identify factors influencing Black immigrant mothers’ perceptions and concerns about child weight and to compare children’s diet quality according to these perceptions and concerns. Design: Mothers’ perceptions and concerns about child weight were assessed with sex-specific figure rating scales and the Child Feeding Questionnaire, respectively. Participants’ weights and heights were measured and characterised using WHO references. Children’s dietary intakes were estimated using a 24-h dietary recall. Children’s diet quality was evaluated using the relative proportion of their energy intake provided by ultra-processed products, which were identified with the NOVA classification. χ 2 tests, multivariate logistic regressions and t tests were performed. Setting: Ottawa, Ontario, Canada. Participants: Black immigrant mothers of Sub-Saharan African and Caribbean origin ( n 186) and their 6–12-year-old children. Results: Among mothers, 32·4 % perceived their child as having overweight while 48·4 % expressed concerns about child weight. Girls and children with overweight or obesity were significantly more likely to be perceived as having overweight by their mothers than boys and normal-weight children, respectively. Mothers of children living with obesity, but not overweight, were significantly more likely to be concerned about their child’s weight than mothers of normal-weight children. Children’s diet quality did not differ according to mothers’ perceptions and concerns. Conclusions: Children’s gender and weight status were major determinants of perceptions and concerns about child weight among Black immigrant mothers. Including knowledge about mothers’ perceptions and concerns about child weight will help nutrition professionals develop interventions tailored to specific family needs within the context of their cultural backgrounds.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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".