Age- and sex- specific all-cause mortality risk greatest in metabolic syndrome combinations with elevated blood pressure from 7 U.S. cohorts
Bibliographic record
Abstract
BACKGROUND: The association between metabolic syndrome (MetS) and all-cause mortality is well established but it is unclear if there are differences in mortality risk among the 32 possible MetS combinations. Hence, the purpose of this study is to evaluate the associations between different MetS combinations and its individual components with all-cause mortality, and to examine differences in the association by age and sex. METHODS: A merged sample of 82,717 adults from 7 U.S. cohorts was used. RESULTS: In our sample, MetS was present in 32% of men, 34% of women, 28% of younger adults (18-65 years) and 62% of older adults (>65 years) with 14,989 deaths over 14.6 ± 7.4 years of follow-up. Risk of all-cause mortality was higher in younger individuals with a greater number of MetS factors present, but in older adults having all 5 MetS factors was the only combination significantly associated with mortality. Regardless of age or sex, elevated blood pressure was the MetS factor most consistently present in MetS combinations that were significantly and most strongly associated with mortality. In fact, elevated blood pressure in the absence of other risk factors was significantly associated with mortality in men (HR, 95% CI = 1.56, 1.33-1.84), women (HR = 1.62, 1.44-1.81) and younger adults (HR = 1.61, 1.45-1.79). Conversely, waist circumference, glucose and triglycerides in isolation were not associated with mortality (p>0.05). CONCLUSION: In a large U.S. population, different combinations of MetS components vary substantially in their associations with all-cause mortality. Men, women and younger individuals with MetS combinations including elevated blood pressure had stronger associations with greater mortality risk, with minimal associations between MetS and mortality risk in older adults. Thus, we suggest that future algorithms may wish to consider differential weighting of these common metabolic risk factors, particularly in younger populations.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".