Socioeconomic disparity in mortality and the burden of cardiovascular disease: analysis of the Prospective Urban Rural Epidemiology (PURE)-China cohort study
Bibliographic record
Abstract
BACKGROUND: Although socioeconomic inequality in cardiovascular health has long been a public health focus, the differences in cardiovascular-disease burden and mortality between people with different socioeconomic statuses has yet to be adequately addressed. We aimed to assess the effects of socioeconomic status, measured via three socioeconomic-status indicators (ie, education, occupation, and household wealth and a composite socioeconomic-status disparity index, on mortality and cardiovascular-disease burden (ie, incidence, mortality, and admission to hospital) in China. METHODS: For this analysis, we used data from the Prospective Urban Rural Epidemiology (PURE)-China cohort study, which enrolled adults aged 35-70 years from 115 urban and rural areas in 12 provinces in China between Jan 1, 2005, and Dec 31, 2009. Final follow-up was on Aug 30, 2021. Indicators of socioeconomic status were education, occupation, and household wealth; these individual indicators were also used to create an integrated socioeconomic-status index via latent class analysis. Standard questionnaires administered by trained researchers were used to obtain baseline data and were supplemeted by physical measurements. The primary outcomes were all-cause mortality, cardiovascular-disease mortality, non-cardiovascular-disease mortality, major cardiovascular disease, and cardiovascular-disease admission to hospital. Hazard ratios (HRs) and average marginal effects were used to assess the association between the primary outcomes and socioeconomic status. FINDINGS: Of 47 931 participants enrolled in the PURE-China study, 47 278 (98·6%) had complete information on sex and follow-up. After excluding 1189 (2·5%) participants with missing data on education, household wealth, and occupation at baseline, 46 089 participants were included in this analysis. Median follow-up was 11·9 years (IQR 9·5-12·6); 26 860 (58·3%) of 46 089 participants were female and 19 229 (41·7%) were male. Having no or primary education, unskilled occupation, or being in the lowest third of household wealth was associated with a higher risk of all-cause mortality, cardiovascular-disease mortality, non-cardiovascular-disease mortality, major cardiovascular disease, and cardiovascular-disease admission to hospital compared with having higher education, a professional or managerial occupation, or more household wealth. After adjustment for confounders, people categorised as having low integrated socioeconomic status based on the index had a higher risk of all-cause mortality (HR 1·65 [95% CI 1·42-1·92]), cardiovascular-disease mortality (2·19 [1·68-2·85]), non-cardiovascular disease mortality (1·43 [1·18-1·72]), major cardiovascular disease (1·43 [1·27-1·61]) and cardiovascular-disease admission to hospital (1·14 [1·01-1·28]) compared with people categorised as having high integrated socioeconomic status. INTERPRETATION: Socioeconomic-status inequalities in mortality and cardiovascular-disease outcomes exist in China. Targeted policies of equal health-care resource allocation should be promoted to equitably benefit people with fewer years of education and less household wealth. FUNDING: Funding sources are listed at the end of the Article.
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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 | 0.034 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".