Within- and Between-individual Temporal Variability in Spot Urine Caffeine and Caffeine Metabolite Concentrations in 50 North Carolina Adults over a Six-week Period (P06-019-19). (13th June 2019)

• Record Type: Journal Article
• Authors: Rybak, Michael; Pao, Ching-I; Sternberg, Maya
• Is Part Of: Current developments in nutrition. Volume 3(2019)Supplement 1
• Publication Date: 2019-06-13
• Subjects: Nutrition -- Periodicals; Nutritional Physiological Phenomena; Nutrition; Periodicals; Periodicals; Fulltext; Internet Resources; Periodicals; 612.3
• DOI: 10.1093/cdn/nzz031.P06-019-19
• Languages: English
• ISSNs: 2475-2991

Abstract

Abstract: Objectives: The majority of studies examining caffeine as risk factor in human health rely upon dietary intake data to assess exposure. Intake variability associated with major dietary sources (e.g., coffee) as well as capturing intake from emerging sources (e.g., energy drinks) presents challenges. Measures of caffeine and caffeine metabolite excretion in the urine are associated with caffeine intake and may be suitable as caffeine intake biomarkers. Little is known regarding the temporal variability of these measures in spot urine samples, and better understanding of this behavior would help in determining the number of samples needed to accurately represent biomarker concentration over a given time period. Methods: We measured spot urine caffeine and caffeine metabolites in 2292 surplus samples from the US EPA's Pilot Study to Estimate Human Exposures to Pyrethroids using an Exposure Reconstruction Approach (Ex-R) Study, and calculated results by concentration, normalized by specific gravity (SG) and creatinine excretion (CR), and excretion rate. Samples were collected from 50 participants (age 19–59 y) residing near Chapel Hill, NC, over a 6-week period, consisting of bedtime, first-morning voids, and 24-h collections. We calculated intra-class correlations (ICCs) and other descriptive statistics, and used ICCs to determine whether a single spot urine sample may be sufficient to estimate the analyte concentration for the indicated timeframe (ICC ≥ 0.8). Results: Concentration ICCs were highest for caffeine (0.79–0.89) and its metabolites theophylline (0.85–0.92) and paraxanthine (0.75–0.85) when measured over a given 24-h period; SG normalization increased ICCs for theophylline (0.89–0.96) and paraxanthine (0.79–0.92) but not for caffeine (0.80–0.87), with CR normalization and excretion rate yielding mixed results. The highest ICCs determined across the entire 6-week period were for CR normalized concentrations of 1-methyluric acid from bedtime (0.77) or 24-h (0.76) samples. Conclusions: Based on ICCs obtained from Ex-R study samples, it may be possible to estimate urine caffeine, theophylline, and paraxanthine concentrations over a 24-h period by use of a single spot urine sample, with more samples needed for longer timeframes. Funding Sources: US EPA and CDC congressional appropriations.