Maternal perceptions of underweight and overweight for 6–8 years olds from a Canadian cohort: reporting weights, concerns and conversations with healthcare providers
Bibliographic record
Abstract
OBJECTIVES: The majority of mothers do not correctly identify their child's weight status. The reasons for the misperception are not well understood. This study's objective was to describe maternal perceptions of their child's body mass index (BMI) and maternal report of weight concerns raised by a health professional. DESIGN: Prospective, community-based cohort. PARTICIPANTS: Data were collected in 2010 from 450 mothers previously included in a longitudinal birth cohort. Mothers of children aged 6-8 years reported their child's anthropometric measures and were surveyed concerning their opinion about their child's weight. They were also asked if a healthcare provider raised any concerns regarding their child's body weight. Child BMI was categorised according to the WHO Growth Charts adapted for Canada. Descriptive statistics and bivariate analyses were used to evaluate mothers' ability to correctly identify their children's body habitus. RESULTS: 74% of children had a healthy BMI, 10% were underweight, 9% were overweight and 7% were obese. 80%, 89% and 62% of mothers with underweight, overweight and obese children, respectively, believed that their child was at the right weight. The proportion of mothers who recalled a health professional raising concerns about their child being underweight, overweight, and obese was low (12.5%). CONCLUSIONS: The majority of mothers with children at unhealthy weights misclassified and normalised their child's weight status, and they did not recall a health professional raising concerns regarding their child's weight. The highest rates of child body weight misclassification occurred in overweight children. This suggests that there are missed opportunities for healthcare professionals to improve knowledge exchange and early interventions to assist parents to recognise and support healthy weights for their 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".