The Role of Socioeconomic Position in the Association Between Mental Disorders and Mortality
Bibliographic record
Abstract
Importance: Studies are lacking summarizing how the association between mental disorders and mortality varies by socioeconomic position (SEP), particularly considering different aspects of SEP, specific types of mental disorders, and causes of death. Objective: To investigate the role of SEP in the association between mental disorders and mortality and the association between SEP and mortality among people with mental disorders. Data Sources: MEDLINE, Embase, PsycINFO, and Web of Science were searched from January 1, 1980, through April 3, 2023, and a snowball search of reference and citation lists was conducted. Study Selection: Inclusion criteria were observational studies estimating the associations between different types of mental disorders and mortality, stratified by SEP and between SEP and mortality in people with mental disorders. Data Extraction and Synthesis: Pairs of reviewers independently extracted data using a predefined data extraction form and assessed the risk of bias using the adapted Newcastle-Ottawa scale. Graphical analyses of the dose-response associations and random-effects meta-analyses were performed. Heterogeneity was explored through meta-regressions and sensitivity analyses. Main Outcomes and Measures: All-cause and cause-specific mortality. Results: Of 28 274 articles screened, 71 including more than 4 million people with mental disorders met the inclusion criteria (most of which were conducted in high-income countries). The relative associations between mental disorders and mortality were similar across SEP levels. Among people with mental disorders, belonging to the highest rather than the lowest SEP group was associated with lower all-cause mortality (pooled relative risk [RR], 0.79; 95% CI, 0.73-0.86) and mortality from natural causes (RR, 0.73; 95% CI, 0.62-0.85) and higher mortality from external causes (RR, 1.18; 95% CI, 0.99-1.41). Heterogeneity was high (I2 = 83% to 99%). Results from subgroup, sensitivity, and meta-regression analyses were consistent with those from the main analyses. Evidence on absolute scales, specific diagnoses, and specific causes of death was scarce. Conclusion and Relevance: This study did not find a sufficient body of evidence that SEP moderated the relative association between mental disorders and mortality, but the underlying mortality rates may differ by SEP group, despite having scarcely been reported. This information gap, together with our findings related to SEP and a possible differential risk between natural and external causes of death in individuals with specific types of mental disorders, warrants further research.
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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 | 0.012 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".