Comparaison de trois systèmes de classification du poids de l'enfant d'âge préscolaire d'une région québécoise
Bibliographic record
Abstract
INTRODUCTION: Overweight in children is a serious public health problem. The use of different weight classification systems in research and clinical practice results in variable the estimate of prevalences of overweight, which complicates follow-up of this health problem in the population. The study compared three child body weight classification systems by estimating the prevalence of overweight established by each system. METHOD: In 2010, a study was conducted in 259 five-year-old children at the time of routine childhood vaccination. The children's height and weight were measured. The prevalence of overweight was determined and compared to the International Obesity Task Force (IOTF), the Centers for Disease Control and Prevention (CDC) and the World Health Organization (WHO) criteria. RESULTS: According to the IOTF, 16.6% of children of the study were overweight (obesity 3.1%). According to the CDC, 24.3% of children were overweight (obesity 9.1%) and according to WHO, the prevalence was 26.3% (obesity 6.2%). According to the IOTF criteria, obesity affected more girls than boys (2.7% vs. 0.4%), whereas similar proportions were observed with the other two systems. CONCLUSION: This study demonstrates that the prevalence of overweight in children varies considerably depending on the classification system used. These results support the need to consider the system used in clinical practice and in research when monitoring the course of the prevalence of this health problem.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".