Body Mass Index Measurement in Schools*
Bibliographic record
Abstract
BACKGROUND: School-based body mass index (BMI) measurement has attracted much attention across the nation from researchers, school officials, legislators, and the media as a potential approach to address obesity among youth. METHODS: An expert panel, convened by the Centers for Disease Control and Prevention (CDC) in 2005, reviewed and provided expertise on an earlier version of this article. The panel comprised experts in public health, education, school counseling, school medical care, and a parent organization. This article describes the purposes of BMI measurement programs, examines current practices, reviews existing research, summarizes the recommendations of experts, identifies concerns, and provides guidance including a list of safeguards and ideas for future research. RESULTS: The implementation of school-based BMI measurement for surveillance purposes, that is, to identify the percentage of students in a population who are at risk for weight-related problems, is widely accepted; however, considerable controversy exists over BMI measurement for screening purposes, that is, to assess the weight status of individual students and provide this information to parents with guidance for action. Although some promising results have been reported, more evaluation is needed to determine whether BMI screening programs are a promising practice for addressing obesity. CONCLUSIONS: Based on the available information, BMI screening meets some but not all of the criteria established by the American Academy of Pediatrics for determining whether screening for specific health conditions should be implemented in schools. Schools that initiate BMI measurement programs should evaluate the effects of the program on BMI results and on weight-related knowledge, attitudes, and behaviors of youth and their families; they also should adhere to safeguards to reduce the risk of harming students, have in place a safe and supportive environment for students of all body sizes, and implement science-based strategies to promote physical activity and healthy eating.
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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 | 0.011 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".