Social environment and cardiometabolic health outcomes: systematic review and meta-analysis
Bibliographic record
Abstract
Abstract A number of studies investigated the relationship between the social environment (SE) (i.e., the social relationships and social context in which groups of people live and interact) and lifestyle behaviours. However, to what extent this relation extends to cardiometabolic disease (CMD) outcomes is unknown. This systematic review and meta-analysis summarizes the available evidence. We systematically searched PubMed (Medline), Scopus, and Web of Science from inception to 16 February 2021. Outcomes of were type 2 diabetes mellitus and cardiovascular diseases and determinants were SE factors. We assessed the quality of the studies with Newcastle-Ottawa Scale (NOS). We meta-analysed exposure-outcome combinations when ≥3 associations from high quality papers were available. Results are expressed as OR, 95%CI. From 7,671 records screened, 208 were included. Of these, 92% were conducted in high income countries, 58% were cross-sectional studies, and 20% were of poor quality. Among the 208 studies, 746 relevant associations were investigated. The largest number of associations investigated was on the dimension Economic and Social Disadvantage (ESD; 59%), followed by Social Relationships and Norms (21%) and Discrimination and Segregation (9%). Less evidence was found for the remaining dimensions. Meta-analysis of 14 exposure-outcome combinations indicated that worse SE was associated with increased odds of CMD outcomes. Despite this tendency, only the association between ESD and heart failure was statistically significant (1.58, 1.11-2.27; n = 4; I2=92%). Generally, heterogeneity was high. In conclusion, higher levels of ESD seem to contribute to increased risk of heart failure. The existing literature is highly heterogeneous and varies notably in terminology. Moreover, the dimensions Social Cohesion and Social Capital, Crime and Safety, Civic Participation and Engagement and Disorder and Incivilities are underexplored in relation to CMD. (PROSPERO-ID: CRD42021223035). Key messages • Worse SE was associated with increased odds of CMD outcomes, with higher levels of Economic and Social Disadvantage being statistically significantly associated with increased risk of heart failure. • The existing literature is highly heterogeneous and varies notably in study design and terminology.
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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 | 0.015 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.031 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".