Life-course socioeconomic status and obesity: scoping review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIF: The life-course approach is believed to enhance our understanding of the intricate links between life-course socioeconomic status and obesity. In this scoping review, we delve into the literature that examines the links between life-course socioeconomic status and obesity and aim to characterize the life-course approach that was used. METHODS: Our search strategy was based on the PRISMA checklist and was performed using three databases: Medline (PubMed), GeoBase (Embase), and Web of Science. We focused on studies that identify life-course socioeconomic and built environment indicators and associate them with body weight status indicators. RESULTS: Using stringent inclusion criteria, we identified 52 relevant studies. Our analysis identified three main methodological strategies for studying the influence of life-course socioeconomic status on obesity. The main methodological approaches identified that characterize life-course approach are: 1) sensitive periods, 2) social mobility, or 3) risk accumulation. We found that low socioeconomic status in childhood, adulthood, or late adulthood; a disadvantaged socioeconomic trajectory; and cumulative exposure to socioeconomic disadvantages throughout the life-course increased the risk of obesity. Notably, the association between life-course socioeconomic status and obesity was significantly stronger for women in 56% of the studies. CONCLUSION: The social inequalities in obesity observed today are the outcome of socioeconomic inequalities accumulated over the life course. 56% of studies show that the influence of life-course socioeconomic status on socioeconomic inequalities in obesity is even stronger in women. Policymakers should prioritize specific interventions aimed at reducing socioeconomic disparities in obesity, particularly among women.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it