Abstract

Long-term exposure to environmental chemicals can detrimentally impact human health, and understanding the relationship between age distribution and levels of external and internal exposure is crucial. Nonetheless, existing methods for assessing population-wide exposure across age groups are limited. To bridge this research gap, we introduced a modeling approach designed to assess both chronic external and internal exposure to chemicals at the population level. The external and internal exposure assessments were quantified in terms of the average daily dose (ADD) and steady-state blood concentration of the environmental chemical, respectively, which were categorized by age and gender groups. The modeling process was presented within a spreadsheet framework, affording users the capability to execute population-wide exposure analyses across a spectrum of chemicals. Our simulation outcomes underscored a salient trend: younger age groups, particularly infants and children, exhibited markedly higher ADD values and blood concentrations of environmental chemicals compared to their older counterparts. This observation is due to the elevated basal metabolic rate per unit of body weight characteristic of younger individuals, coupled with their diminished biotransformation kinetics of xenobiotics within their livers. These factors collectively contribute to increased intake rates of environmental chemicals per unit of body weight through air and food consumption, along with heightened bioaccumulation of these chemicals within their bodies (e.g., blood). Furthermore, we augmented the precision of the external and internal exposure assessment by incorporating the age distribution across the population. The simulation outcomes unveiled that, to estimate the central tendency of the population's exposure levels, employing the baseline value group (age group 21–30) or the surrogate age of 25 serves as a simple yet dependable approach. However, for comprehensive population protection, our recommendation aligns with conducting exposure assessments for the younger age groups (age group 0–11). Future studies should integrate individual-level exposure assessment, analyze vulnerable population groups, and refine population structures within our developed model.

Full Text
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