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Caffeine exposure biomonitoring: correlation and variability of urinary caffeine metabolites
Author(s) -
Pao ChingI,
Rybak Michael E.,
Pfeiffer Christine M.
Publication year - 2010
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.24.1_supplement.562.5
Subject(s) - caffeine , urine , biomarker , metabolite , biomonitoring , urinary system , chemistry , physiology , medicine , environmental chemistry , biochemistry
The use of biomarkers to estimate caffeine exposure is a potentially more reliable alternative to using dietary intake data, given the intrinsic heterogeneity of major caffeine sources such as coffee and tea. To better understand the concept of urinary biomarker estimation of caffeine exposure, we examined urinary caffeine metabolite data from two pilot studies. In the first study we looked at the correlation between caffeine biomarkers in spot urine samples from 115 random volunteers. Significant (p <0.05) correlations were observed in 103 of a possible 105 analyte combinations. Pearson r >0.8 was observed in 36 and r >0.9 in 15 cases (p <0.0001). Given its rapid metabolism, caffeine was least correlated with other metabolites. In the second study we looked at within‐individual variation and correlation between various urine caffeine biomarker measurements in 8 subjects over a 1‐week period. Significant differences in within‐individual CVs (95% CI) were observed among subjects, with the average CV across all subjects and analytes being 77% (61–93%). Creatinine normalization yielded mixed results, lowering the within‐individual CV for certain biomarkers while increasing it for others. Spot urine concentrations correlated well with 24‐hour excretion, with Pearson r values of 0.75–0.93 observed for most biomarkers. These findings will assist in the interpretation of biomarker based caffeine exposure data.