Teenage Obese Pregnancy: The "Double Burden" of Age and Excessive Weight on the Mother-Offspring Pair’s Health
Bibliographic record
Abstract
Obesity and pregnancy are a combination that may create unique interconnected challenges for the health of the next generation. Although pregnant obese adolescents are of concern worldwide, yet it is an issue that is currently unattended to. Here, we provide an overview of the implications for the mother-offspring pair’s health associated to teenage-pregnancy, with a focus on obesity and ‘what works’ to prevent the obesity-risk during pregnancy. Interrelated health-issues are highlighted, which include: increased negative consequences related to childbearing at young age; associations of maternal pre-gravid excessive-weight with maternal and fetal complications; and limited evidence addressing obese pregnancy in adolescents. Targeting adolescents appears the most effective approach to reduce the obesity-risk trajectory of the prospective parents early-in-life, thus breaking the intergenerational cycle of non-communicable diseases. Specifically-focused educational programs with clear and motivational messages about nutrition, physical activity and sexual health, are perceived as key-components of preventive campaigns with digital web-based technology and specialized health-services being the most promising platforms to deliver knowledge. Successful education has a double advantage: to establish healthy behaviors among adolescents at an early-stage of life, thereby preventing both obesity and early pregnancy. Lastly, realistic solutions require also political understanding and commitment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".