Loneliness, Social Isolation, and Social Support and the Development of Type II Diabetes: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND & OBJECTIVES: Type 2 diabetes mellitus (T2DM) is a growing global health concern. Emerging evidence suggests psychosocial factors such as loneliness, social isolation, and low social support may contribute to its development, but findings remain inconsistent. This systematic review and meta-analysis synthesizes existing literature to determine whether these social factors are associated with incident T2DM risk. METHODS: A systematic search was conducted in PubMed, PsycINFO, Scopus, and Web of Science. Eligible studies assessed loneliness, social isolation, or social support and reported incident T2DM as the outcome. Three reviewers independently screened studies, extracted data, and assessed quality using the OHAT Risk of Bias tool. Meta-analyses used a random-effects model with adjusted hazard and odds ratios. Heterogeneity was assessed using the I² statistic, and publication bias was assessed using funnel plots and Egger’s test. RESULTS: Eighteen studies were included. Individuals experiencing loneliness (RR = 1.27; 95% CI: 1.21—1.34) or low workplace social support (RR = 1.18; 95% CI: 1.06—1.32) had a significantly higher risk of developing T2DM compared to those reporting no loneliness or high workplace support. Positive but non-significant associations were observed for social isolation (RR = 1.21; 95% CI: 0.98—1.49), low structural support (RR = 1.10; 95% CI: 0.98—1.23), and low functional support (RR = 1.03; 95% CI: 0.99—1.08). CONCLUSIONS: These findings emphasize the importance of social connections in metabolic health, suggesting that interventions aimed at reducing loneliness and strengthening social and workplace support may play a role in diabetes prevention efforts.
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How this classification was reachedexpand
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 | 0.003 | 0.000 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".