Deterministic modeling of the exposure of individual participants in the National Health and Nutrition Examination Survey (NHANES) to polychlorinated biphenyls

Abstract

A population's exposure to persistent organic pollutants, e.g., polychlorinated biphenyls (PCBs), is typically assessed through national biomonitoring programs, such as the United States National Health and Nutrition Examination Survey (NHANES). To complement statistical methods, we use a deterministic modeling approach to establish mechanistic links between human contaminant concentrations and factors (e.g. age, diet, lipid mass) deemed responsible for the often considerable variability in these concentrations. Lifetime exposures to four PCB congeners in 6128 participants from NHANES 1999–2004 are simulated using the ACC-Human model supplied with individualized input parameters obtained from NHANES questionnaires (e.g., birth year, sex, body mass index, dietary composition, reproductive behavior). Modeled and measured geometric mean PCB-153 concentrations in NHANES participants of 13.3 and 22.0 ng g⁻¹ lipid, respectively, agree remarkably well, although lower model-measurement agreement for air, water, and food suggests that this is partially due to fortuitous error cancellation. The model also reproduces trends in the measured data with key factors such as age, parity and sex. On an individual level, 62% of all modeled concentrations are within a factor of three of their corresponding measured values (Spearman r_s = 0.44). However, the model attributes more of the inter-individual variability to differences in dietary lipid intake than is indicated by the measured data. While the model succeeds in predicting levels and trends on the population level, the accuracy of individual-specific predictions would need to be improved for refined exposure characterization in epidemiological studies.