Gender, stressful life events and interactions with sleep: a systematic review of determinants of adiposity in young people
Bibliographic record
Abstract
OBJECTIVES: Overweight and obesity among young people are high and rising. Social stressors and sleep are independently associated with obesity, but are rarely studied together or examined for gender-specific effects. The literature regarding adolescent populations is especially lacking. This review assesses whether experiencing stressful life events results in greater adiposity in young women and young men compared with those who do not experience stressful life events, and whether the relationship is modified by sleep problems. DESIGN: We systematically searched six bibliometric databases (Web of Science, Embase Ovid, PsycINFO, CINHAL, PubMed, ProQuest Dissertations) supplemented by hand searches. Longitudinal prospective studies or reviews were eligible for inclusion when they examined gender-specific changes in adiposity in young adults (age 13-18 years) as a function of stressful life event alone or in combination with sleep problems. RESULTS: We found one study eligible for inclusion reporting mixed impact of stressful life events on body mass index (BMI) between genders. The study assessed specific life events and showed significantly lower BMI at follow-up among young men who experienced a residence change, but significantly higher BMI among young women who experienced setting up a family and who reported internal locus of control. CONCLUSIONS: Despite ample research on social stressors or sleep problems and weight, we still know little about the role of stressful life events, or combined effects with sleep, on obesity risk in adolescents from a gender perspective. Existing evidence suggests specific life events affect weight differently between the genders. Robust, high-quality longitudinal studies to decipher this dual burden on obesity during adolescence should be prioritised, as firm conclusions remain elusive.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".