Abstract P263: Associations Between Dimensions of the Social Environment and Cardiometabolic Risk Factors
Bibliographic record
Abstract
Introduction: Although the social environment, including social contacts, norms and support, likely has a significant impact on cardiometabolic disease (CMD) risk, a comprehensive summary of the available evidence is lacking. Hypothesis: Exposure to unfavorable social environments is associated with greater CMD risk. Methods: We conducted a systematic review and meta-analysis on the association between social environmental characteristics and risk factors of CMD. We systematically searched PubMed, Scopus and Web of Science Core Collection from inception to 16 February 2021. Studies that used a risk factor of CMD, e.g., lipids, HbA1c or blood pressure as outcome and social environmental factors such as area-level deprivation, neighborhood racial segregation or social network size as independent variables were included. Titles and abstracts were screened in duplicate. Study quality was assessed using the Newcastle-Ottawa Scale. Data appraisal and extraction were based on the study protocol published in PROSPERO (CRD42021223035). Data were synthesized through vote counting and random effects meta-analyses, the latter if three or more associations investigated the same exposure-outcome combination. Results: A total of 168 studies reporting on 1050 associations were included in this review. Social and Economic Disadvantage was the most studied exposure (45%), followed by Social Relationships and Norms (35%), with less evidence for other social environmental dimensions. Four meta-analyses based on 24 associations suggested that an unfavorable social environment was associated with increased risk of cardiometabolic risk factors, with three of them being statistically significant. For example, individuals that experienced more economic and social disadvantage had a higher CVD risk scores (OR=1.54, 95%CI: 1.35;1.84). Meta-analyzed sex-specific associations showed inconsistent results. Of the 458 associations included in the vote counting, 323 (71%) pointed towards unfavorable social environments being associated with higher CMD risk. Conclusion: Higher economic and social disadvantage seem to contribute to unfavorable CMD risk factor profiles, while evidence for other dimensions of the social environment is limited.
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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 | 0.011 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".