Prevalence of toddler, child and adolescent overweight and obesity derived from primary care electronic medical records: an observational study
Bibliographic record
Abstract
BACKGROUND: Population monitoring and surveillance of objectively measured child weight data in Canada is limited to national surveys with poor regional applicability, and no healthy weight data are available for children less than 2 years of age. We aimed to determine the prevalence of childhood overweight and obesity using objective measures derived from primary care electronic medical records. METHODS: Observational data included all height and weight records for children less than 20 years of age, between 2004 and 2013, from 3 Ontario primary care research networks. We calculated body mass index (BMI)-for-age and weight-for-length using the World Health Organization Growth Standards and Reference to assign growth status indicator categories by age group. Descriptive data and prevalence estimates were generated for 2013. We also compared weight-for-length for children less than 2 years of age with a corresponding billing code for known well-child visits. RESULTS: Our study included 8261 children with a corresponding growth status indicator, a sample close to 4 times larger than the national survey sample. In 2013, 28.4% of children aged 5-19 years, and 6% of children aged 0-5 years, were categorized as overweight or obese. Between 2008 and 2013, the total number of 18-month well baby visit billing codes was 1152; 6.9% of this group were categorized as overweight or obese; 19.2% were categorized as having risk of overweight. INTERPRETATION: Primary care electronic medical records show good potential for ongoing population monitoring of overweight and obesity, particularly for very young children for whom early intervention is likely to show the greatest positive health impact.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".