The Relationship Between Paternal Preconception Obesity and Health Behaviors and Childhood Obesity: Protocol for a Systematic Review
Bibliographic record
Abstract
BACKGROUND: Childhood obesity is a global public health concern and is a priority for researchers and policy makers. To overcome the epidemic of obesity, influencing factors throughout the life span need to be addressed, including those in the preconception period. A better understanding of the association between paternal preconception factors and childhood obesity is important for public health interventions. OBJECTIVE: This systematic review will examine the relationship between paternal preconception obesity and health behaviors and their offspring's overweight or obesity. METHODS: Peer-reviewed quantitative studies and grey literature that report associations between paternal preconception obesity and health behaviors-such as smoking, exercise, and eating habits-and childhood overweight and obesity will be identified through a computerized literature search in 7 databases. The quality of each study will be assessed using the Quality Assessment Tool for Quantitative Studies. Characteristics of the included studies will be reported, and relevant findings from each paternal preconception exposure will be narratively synthesized. This review will follow the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) 2020 guidelines. RESULTS: This systematic review is anticipated to begin in December 2021 and be completed by the end of August 2022. CONCLUSIONS: This systematic review will contribute to a better understanding of the relationship between preconception paternal exposures and their offspring's overweight or obesity. Findings will help support health professionals working with prospective parents to educate fathers on the benefits of improving their weight and health behaviors during the preconception period. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/31254.
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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 | 0.071 | 0.099 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.017 | 0.019 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.081 | 0.010 |
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".