A Comparison of Self-Reported Analgesic Use and Detection of Urinary Ibuprofen and Acetaminophen Metabolites by Means of Metabonomics: The INTERMAP Study

Abstract

Information on dietary supplements, medications, and other xenobiotics in epidemiologic surveys is usually obtained from questionnaires and is subject to recall and reporting biases. The authors used metabolite data obtained from hydrogen-1 (or proton) nuclear magnetic resonance ((1)H NMR) analysis of human urine specimens from the International Study of Macro-/Micro-Nutrients and Blood Pressure (INTERMAP Study) to validate self-reported analgesic use. Metabolic profiling of two 24-hour urine specimens per individual was carried out for 4,630 participants aged 40-59 years from 17 population samples in Japan, China, the United Kingdom, and the United States (data collection, 1996-1999). (1)H NMR-detected acetaminophen and ibuprofen use was low (∼4%) among East Asian population samples and higher (>16%) in Western population samples. In a comparison of self-reported acetaminophen and ibuprofen use with (1)H NMR-detected acetaminophen and ibuprofen metabolites among 496 participants from Chicago, Illinois, and Belfast, Northern Ireland, the overall rate of concordance was 81%-84%; the rate of underreporting was 15%-17%; and the rate of underdetection was approximately 1%. Comparison of self-reported unspecified analgesic use with (1)H NMR-detected acetaminophen and ibuprofen metabolites among 2,660 Western INTERMAP participants revealed similar levels of concordance and underreporting. Screening for urinary metabolites of acetaminophen and ibuprofen improved the accuracy of exposure information. This approach has the potential to reduce recall bias and other biases in epidemiologic studies for a range of substances, including pharmaceuticals, dietary supplements, and foods.

Oxidative Stress and Inflammation Induced by Environmental and Psychological Stressors: A Biomarker Perspective

“…Self-administration is the main cause for personal exposure (exposure in the wider environment is negligible), and large-scale, cross-sectional metabolic phenotyping studies of humans have shown a high prevalence of significant (e.g. therapeutic dose) exposure (91,92). Characterising population-level use of therapeutics (e.g.…”

Associations between Statin use and changes in pain, function and structural progression: a longitudinal study of persons with knee osteoarthritis

“…During these visits, staff reviewed medications and recorded the medication name, self-reported duration and frequency of use (as needed or regular). Because of potential problems associated with recall and bias,11 12 we used the yearly in-person visit data to guide coding for statin use. Data related to dosage were not reported in OAI.…”

Metabolic phenotyping for discovery of urinary biomarkers of diet, xenobiotics and blood pressure in the INTERMAP Study: an overview

“…Within the INTERMAP, we have been successful in identification of a number of metabolites including metabolites derived from dietary and drug intake. 84–87 …”

“…87 We applied PCA on 1 H NMR spectra of US participants and identified 413 urine samples containing acetaminophen and its metabolites (acetaminophen users) and then applied OPLS-DA analysis on a subset of 70 urine samples from acetaminophen users and 70 urine samples from acetaminophen non-users. 86 The OPLS-DA loading coefficient plot showed that differentiation between acetaminophen users vs. non-users primarily resulted from the presence of acetaminophen and its metabolites acetaminophen glucuronide, acetaminophen sulfate, and the acetylcysteine conjugate of acetaminophen.…”

“…87 Urinary spectra of UK (Belfast, N=216) and US (Chicago, N=280) participants were inspected for the presence or absence of metabolites in spectral regions containing acetaminophen and ibuprofen. 87 These spectra were used to construct prediction models (sensitivity > 98%) based on self-reported analgesic use; overall rates of concordance between questionnaire data and urinary spectra were high for both populations: 83.8% (95% confidence interval, CI: 78.9, 88.7) in Belfast and 81.1% (95% CI: 76.5, 85.7) in Chicago. Overall rates of under-detection of acetaminophen and ibuprofen were low (about 1%) and were comparable for both Belfast and Chicago.…”