Waist to height ratio as a simple tool for predicting mortality: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background : The association of central obesity with higher rates of mortality is not well studied. This study evaluates the association between waist-to-height ratio (WHtR), as a measure of central obesity, with mortality. Methods : Documents were retrieved from PubMed, Web of Science, Scopus, and Google Scholar databases until May 2022. Data were extracted from cohort studies reporting effect size (hazard ratio (HR)) regarding the association between WHtR as a continuous (per 1 SD increment) or categorical (highest/lowest) measure and all-cause and cause-specific mortality. Screening of included studies was performed independently by two authors. Moreover, the quality assessment of included studies was performed based on the Newcastle-Ottawa assessment scale. Finally, random effect meta-analysis was performed to pool the data, and the outcomes’ certainty level was assess based on the GRADE criteria Results: Of the 815 initial studies, 20 were included in the meta-analysis. Random effect meta-analysis showed that in the general population, the all-cause mortality HRs for categorical and continuous measurements of WHtR increased significantly by 23% (HR:1.23; 95%CI: 1.04-1.41) and 16% (HR:1.16; 95%CI: 1.07-1.25), respectively. Moreover, the hazard of cardiovascular (CVD) mortality increased significantly for categorical and continuous measurements of WHtR by 39% (HR:1.39; 95%CI: 1.18-1.59) and 19% (HR:1.19; 95%CI: 1.07-1.31). The quality assessment score of all included studies was high. Conclusions: Higher levels of WHtR, indicating central obesity, were associated with an increased hazard of CVD and all-cause mortality. This measure can be used in the clinical setting as a simple tool for predicting mortality.
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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 | 0.012 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.003 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".