Educational inequalities in adult mortality: a systematic review and meta-analysis of the Asia Pacific region
Bibliographic record
Abstract
OBJECTIVES: In this study, we aim to analyse the relationship between educational attainment and all-cause mortality of adults in the high-income Asia Pacific region. DESIGN: This study is a comprehensive systematic review and meta-analysis with no language restrictions on searches. Included articles were assessed for study quality and risk of bias using the Joanna Briggs Institute critical appraisal checklists. A random-effects meta-analysis was conducted to evaluate the overall effect of individual level educational attainment on all-cause mortality. SETTING: The high-income Asia Pacific Region consisting of Japan, South Korea, Singapore and Brunei Darussalam. PARTICIPANTS: Articles reporting adult all-cause mortality by individual-level education were obtained through searches conducted from 25 November 2019 to 6 December 2019 of the following databases: PubMed, Web of Science, Scopus, EMBASE, Global Health (CAB), EconLit and Sociology Source Ultimate. PRIMARY AND SECONDARY OUTCOME MEASURES: Adult all-cause mortality was the primary outcome of interest. RESULTS: Literature searches resulted in 15 345 sources screened for inclusion. A total of 30 articles meeting inclusion criteria with data from the region were included for this review. Individual-level data from 7 studies covering 222 241 individuals were included in the meta-analyses. Results from the meta-analyses showed an overall risk ratio of 2.40 (95% CI 1.74 to 3.31) for primary education and an estimate of 1.29 (95% CI 1.08 to 1.54) for secondary education compared with tertiary education. CONCLUSION: The results indicate that lower educational attainment is associated with an increase in the risk of all-cause mortality for adults in the high-income Asia Pacific region. This study offers empirical support for the development of policies to reduce health disparities across the educational gradient and universal access to all levels of education. PROSPERO REGISTRATION NUMBER: CRD42020183923.
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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 | 0.018 | 0.045 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.030 |
| Bibliometrics | 0.008 | 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) | 0.003 | 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".