doi:10.1155/2012/934895 Research Article Targeting Policy for Obesity Prevention: Identifying the Critical Age for Weight Gain in Women
Bibliographic record
Abstract
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The obesity epidemic requires the development of prevention policy targeting individuals most likely to benefit. We used selfreported prepregnancy body weight of all women giving birth in Nova Scotia between 1988 and 2006 to define obesity and evaluated socioeconomic, demographic, and temporal trends in obesity using linear regression. There were 172,373 deliveries in this cohort of 110,743 women. Maternal body weight increased significantly by 0.5 kg per year from 1988, and lower income and rural residence were both associated significantly with increasing obesity. We estimated an additional 82,000 overweight or obese women in Nova Scotia in 2010, compared to the number that would be expected from obesity rates of just two decades ago. The critical age for weight gain was identified as being between 20 and 24 years. This age group is an important transition age between adolescence and adulthood when individuals first begin to accept responsibility for food planning, purchasing, and preparation. Policy and public health interventions must target those most at risk, namely, younger women and the socially deprived, whilst
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.704 | 0.552 |
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".