OP51 Associations between the social environment and cardiometabolic health outcomes: systematic review (and meta-analysis)
Bibliographic record
Abstract
Background A number of studies has investigated the relationship between the social environment and lifestyle behaviours. However, to what extent the relation between the social environment (i.e., the social relationships and social context in which groups of people live and interact) and lifestyle behaviours extends to cardiometabolic disease outcomes is unknown. This systematic review and meta-analysis systematically summarizes the available evidence. Methods We systematically searched PubMed (Medline), Scopus, and Web of Science from inception to 16 February 2021. Outcomes of included studies were type 2 diabetes mellitus and cardiovascular diseases and determinants were social environmental factors such as area-level deprivation and social network size. Titles and abstracts were screened in duplicate. We assessed the quality of the studies using the Newcastle-Ottawa Scale (NOS). We meta-analysed associations when ≥3 binary associations were available per social environment dimension and when those were generated by high quality papers. For the sake of this abstract, we only present results for stroke outcomes but full results will be available at the time of the conference. The protocol was registered in PROSPERO (ID:CRD42021223035). Results From 7,671 records screened, 218 were included and 35 focused on stroke. Of these, 33 were conducted in high income countries, 60% (n=21) applied a longitudinal design, and 50% (n=17) were of poor or fair quality. Among the 35 studies, 97 relevant associations were investigated. The largest number of associations investigated was related to the dimension Economic and Social Disadvantage (71%), followed by Social Relationships and Norms (16%), Discrimination and Segregation (8%),and Social Cohesion and Social Capital (2%). Limited evidence was found for the remaining dimensions (Crime and Safety, Civic Participation and Engagement and Disorder and Incivilities) in relation to stroke. Meta-analysis of binary data from high quality studies was only possible for Economic and Social Disadvantage. More Economic and Social Disadvantage was associated with higher stroke risk/prevalence (n=5; OR=1.10; 95% CI, 1.03–1.17; I2=39.76%). Conclusion Higher levels of economic and social disadvantage seem to contribute to increased stroke risk. During the conference we will present full results of the systematic review and meta-analysis, including underexplored dimensions such as Discrimination and Segregation, Crime and Safety, Civic Participation and Engagement and Disorder and Incivilities.
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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 | 0.020 | 0.052 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.028 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".