Biomonitoring-based exposure assessment of phthalate and non-phthalate plasticizers: methodological insights from a 7-day consecutive sampling case study in Korea.

backgroundThe increasing use of plasticizers as substitutes for heavily regulated phthalates raises concerns about human exposure. However, exposure patterns and suitable biomarkers for exposure assessment remain poorly understood.

objectiveThis study aimed to evaluate temporal variability of plasticizer metabolites in consecutively collected urine samples and to estimate exposure levels using toxicokinetic (TK) modeling.

methodsTwenty metabolites of six compounds, di-isononyl phthalate (DiNP), di-isodecyl phthalate (DiDP), di-ethylhexyl adipate (DEHA), di-ethylhexyl terephthalate (DEHTP), di-isononyl cyclohexane (DINCH), and tri-octyl trimellitate (TOTM) were quantified in 218 urine samples collected from six adults over one week. Intraclass correlation coefficients (ICC) and bivariate correlations were calculated to evaluate temporal variability across biomarkers. Time-activity diaries were used to identify exposure sources, and TK modeling was applied for biomonitoring-based reverse dosimetry.

resultsMetabolites of DiNP, DEHA, and DEHTP were frequently detected (>70%). First morning voids correlated moderately with daily average concentrations for frequently detected biomarkers (Spearman's ρ = 0.34-0.62, p ≤ 0.05). ICCs ranged from 0.16 to 0.73, with carboxylated metabolites demonstrating fair-to-good temporal stability (ICC = 0.57-0.68) for DiNP, DEHA and DINCH, while the hydroxylated metabolite showed the highest reproducibility for DEHTP (ICC = 0.62). Dietary intake, particularly processed foods, appeared to be the major exposure route, as concentration peaks of DiNP and DEHTP metabolites coincided with recorded dietary events. Daily intake estimates reconstructed from TK models under intermittent ingestion scenarios were generally lower than under continuous exposure assumptions, reflecting systematic differences. For most compounds, mass-balance approaches were comparable to TK model estimates, though DEHA showed a discrepancy attributable to the metabolite-specific model structure. IMPACT: Phthalate and non-phthalate substitutes increasingly replace heavily regulated phthalates, yet methodological frameworks for biomonitoring-based exposure assessment remain limited. We combined serial urine sampling, time-activity diaries, and toxicokinetic modeling as a case study for comprehensive exposure assessment. Key findings include: (1) secondary metabolites demonstrated fair-to-good temporal stability, while first morning void samples showed moderate correlations with daily exposure; (2) time-activity diaries identified potential dietary sources; and (3) toxicokinetic modeling accounting for realistic exposure scenarios demonstrated advantages over mass-balance approaches. These findings provide practical guidelines for individual-level assessments when environmental monitoring is limited.