ArticleMetabolism open2025
Using metabolic syndrome severity in the "real world": Associations with diabetes and cardiovascular disease in all of us vs. NHANES.
Article in Metabolism open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Metabolic syndrome severity is related to perceived discrimination and stress in the all of us cohort.Comprehensive psychoneuroendocrinology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: While the severity of the metabolic syndrome (MetS) is associated with type 2 diabetes and cardiovascular disease (CVD) in research cohorts, it is unclear if this association remains when using clinically-collected data, which is more subject to error and bias. Methods: We used a previously-validated MetS-severity z-score (MetS-Z) to compare the degree of cardiometabolic derangement between clinically-collected data from the electronic health-record (EHR) in the All-of-Us cohort (N = 101,676) with research-collected data from NHANES 2017-2020 (n = 3470). We assessed (separately) the odds of current diabetes and CVD in each cohort based on MetS z-score, adjusted for sex, race/ethnicity, education and income. Results: Mean MetS-Z-scores in All of Us (vs. NHANES) were higher overall (0.41 vs. 0.15), including being slightly higher among those without diabetes (0.03 vs. -0.09) and similar among those with diagnosed diabetes (1.42 vs. 1.50). In All of Us (vs. NHANES) MetS-Z was higher among those without CVD (0.36 vs. 0.10) but similar among those with CVD (0.72 vs. 0.66). Adjusted odds of diagnosed diabetes and CVD based on MetS-Z remained significant when using clinically-collected data in All of Us (diabetes: 3.41 [95 % confidence interval 3.34, 3.49]; CVD: 1.20 [1.18, 1.21]), though not as high as in NHANES (diabetes: 5.83 [4.52, 7.51]; CVD: 1.43 [1.27, 1.61]). Conclusion: While EHR data is limited by selection bias and data accuracy concerns (e.g. lack of fasting laboratory testing), we found overall similar relationships between MetS-severity, diabetes and CVD in EHR-based and research-based cohorts, supporting utility of these data in risk algorithms.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.