ArticleFrontiers in nutrition2023
Associations of urinary caffeine and caffeine metabolites with metabolic syndrome in US adults.
Article in Frontiers in nutrition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
- Principal Components Analysis of Spot Urine Caffeine and Caffeine Metabolites Identifies Promising Exposure Biomarkers of Caffeine and Theobromine Intake in a Cross-Sectional Survey of the United States Population (National Health and Nutrition Examination Survey 2009-2014).Current developments in nutrition · 2025Article
- Associations of urinary caffeine metabolites with sex hormones: comparison of three statistical models.Frontiers in nutrition · 2024Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aims: The relationship between caffeine and metabolic syndrome (MetS) has only been evaluated from the perspective of caffeine consumption. The association between urinary caffeine and MetS is still unclear. This study examined the associations between urinary caffeine and its metabolites and MetS and its components among adults. Methods: Data from the United States (US) National Health and Nutrition Examination Survey (NHANES) 2011-2014 was analyzed. NHANES is a stratified, multi-stage survey of all non-institutionalized persons in the US. A total of 2,394 subjects aged ≥ 18 years without missing data were selected in this study. Urinary caffeine and caffeine metabolite levels were quantified using high-performance liquid chromatography-electrospray ionization-tandem quadrupole mass spectrometry (HPLC-ESI-MS/MS) with stable isotope-labeled internal standards. We performed principal components analysis (PCA) to investigate the underlying correlation structure of 15 features of urinary caffeine and its metabolites and then used these principal components (PCs) as independent variables to conduct logistic regression analysis with or without restricted cubic spline (RCS) terms to explore the associations between caffeine metabolites and MetS. Results: Two main PCs that were derived from the PCA explained 90.67% of the total variance of caffeine and its metabolites. The first PC (PC1, strongly correlated with 1-MU, 1,3-DMU, 1,7-DMU, 1,3,7-TMU, 1-MX, 1,3-DMX, 1,7-DMX, 1,3,7-TMX, and AAMU) was positively correlated with risk of MetS (OR = 1.27, Conclusion: Urinary caffeine metabolites were positively associated with the risk of MetS and its components through different linear or non-linear patterns.
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