Life-course socioeconomic status and obesity: a scoping review protocol
Bibliographic record
Abstract
OBJECTIVE: We aim to explore the literature that studies the links between life-course socioeconomic status and weight status and characterize the life-course approach used. INTRODUCTION: Obesogenic environments are increasing rapidly in deprived environments, and cross-sectional studies have shown limitations in explaining the links between these environments and obesity. The life-course approach has been proposed recently to better understand the links between socioeconomic status and weight status. INCLUSION CRITERIA: Studies that identify life-course socioeconomic status and longitudinal built environment indicators and associate them with body weight indicators between January 2000 and January 2023. METHODS: Studies in French or English were searched in Medline (PubMed), Web of Science and GeoBase (Embase) according to the strategies formulated for each database. The selected studies were exported to Covidence for evaluation according to the inclusion/exclusion criteria. RESULTS: The main results retained are the association between longitudinal socioeconomic indicators and weight measures; longitudinal built environment indicators and the measures of weight.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.062 | 0.051 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.015 | 0.011 |
| Bibliometrics | 0.026 | 0.018 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.049 | 0.009 |
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".