The dose-response relationship between socioeconomic deprivation and alcohol-attributable mortality risk—a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Individuals with low socioeconomic status (SES) experience a higher risk of mortality, in general, and alcohol-attributable mortality in particular. However, a knowledge gap exists concerning the dose-response relationships between the level of socioeconomic deprivation and the alcohol-attributable mortality risk. METHODS: We conducted a systematic literature search in August of 2020 to update a previous systematic review that included studies published up until February of 2013. Quantitative studies reporting on socioeconomic inequality in alcohol-attributable mortality among the general adult population were included. We used random-effects dose-response meta-analyses to investigate the relationship between the level of socioeconomic deprivation and the relative alcohol-attributable risk (RR), by sex and indicator of SES (education, income, and occupation). RESULTS: We identified 25 eligible studies, comprising about 241 million women and 230 million men, among whom there were about 75,200 and 308,400 alcohol-attributable deaths, respectively. A dose-response relationship between the level of socioeconomic deprivation and the RR was found for all indicators of SES. The sharpest and non-linear increase in the RR of dying from an alcohol-attributable cause of death with increasing levels of socioeconomic deprivation was observed for education, where, compared to the most educated individuals, individuals at percentiles with decreasing education had the following RR of dying: women: 25th: 2.09 [95% CI 1.70-2.59], 50th: 3.43 [2.67-4.49], 75th: 4.43 [3.62-5.50], 100th: 4.50 [3.26-6.40]; men: 25th: 2.34 [1.98-2.76], 50th: 4.22 [3.38-5.24], 75th: 5.87 [4.75-7.10], 100th: 6.28 [4.89-8.07]. CONCLUSIONS: The findings of this study show that individuals along the entire continuum of SES are exposed to increased alcohol-attributable mortality risk. Differences in the dose-response relationship can guide priorities in targeting public health initiatives.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".