A systematic review of social connections as determinants of obesity: Longitudinal evidence limited to marital transitions
Bibliographic record
Abstract
BACKGROUND: Social relationships impact health and may affect proximal determinants such as obesity. Our review examined empirical evidence of the impact of changes in social relationships on risk of obesity in aging adults, with attention to gender. METHODS: We systematically searched Medline, EMBASE, Scopus, CINAHL, and ProQuest Dissertations and reference lists of relevant reviews and papers published up to November 2022. Longitudinal studies examining changes in marital status, living arrangement, social participation, and social networks and anthropometric changes or incident obesity were deemed eligible. Relevant data were extracted and synthesized narratively. RESULTS: We identified 41,910 eligible titles, resulting in 252 full texts and 7 included studies. All studies were conducted in the United States and assessed marital transitions only; 3 studies included both women and men. Overall, compared with people who remain non-married, entering marriage leads to a significant increase in body mass index (BMI) for both genders. Conversely, transitioning out of marriage through widowhood or divorce leads to a decrease in weight (kg/lbs), waist circumference, and BMI for both genders. All seven studies were deemed to be of medium quality. CONCLUSIONS: Our review revealed a paucity of prospective evidence on social connections as determinants of obesity among aging adults. There is limited evidence that marital transitions are associated with changes in anthropometric measurements in aging individuals, but no evidence on the effects of changes in living arrangements, social participation, and social networks on anthropometric measurements. More research attention to the social determinants of obesity is warranted.
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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 | 0.012 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.013 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".