Association between subjective social status and cardiovascular disease and cardiovascular risk factors: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: To determine the association between subjective social status (SSS), or the individual's perception of his or her position in the social hierarchy, and the odds of coronary artery disease (CAD), hypertension, diabetes, obesity and dyslipidaemia. STUDY DESIGN: Systematic review and meta-analysis. METHODS: We searched PubMed, MEDLINE, EMBASE, CINAHL, PsycINFO, SocINDEX, Web of Science and reference lists of all included studies up to October 2014, with a verification search in July 2015. Inclusion criteria were original studies in adults that reported odds, risk or hazard ratios of at least one outcome of interest (CAD, hypertension, diabetes, obesity or dyslipidaemia), comparing 'lower' versus 'higher' SSS groups, where SSS is measured on a self-anchoring ladder. ORs were pooled using a random-effects model. RESULTS: 10 studies were included in the systematic review; 9 of these were included in the meta-analysis. In analyses unadjusted for objective socioeconomic status (SES) measures such as income, education or occupation, the pooled OR comparing the bottom versus the top of the SSS ladder was 1.82 (95% CI 1.10 to 2.99) for CAD, 1.88 (95% CI 1.27 to 2.79) for hypertension, 1.90 (95% CI 1.25 to 2.87) for diabetes, 3.68 (95% CI 2.03 to 6.64) for dyslipidaemia and 1.57 (95% CI 0.95 to 2.59) for obesity. These associations were attenuated when adjusting for objective SES measures, with the only statistically significant association remaining for dyslipidaemia (OR 2.10, 95% CI 1.09 to 4.06), though all ORs remained greater than 1. CONCLUSIONS: Lower SSS is associated with significantly increased odds of CAD, hypertension, diabetes and dyslipidaemia, with a trend towards increased odds of obesity. These trends are consistently present, though the effects attenuated when adjusting for SES, suggesting that perception of one's own status on a social hierarchy has health effects above and beyond one's actual income, occupation and education.
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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 | 0.014 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.036 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".