Understanding Differences in the Body Burden–Age Relationships of Bioaccumulating Contaminants Based on Population Cross Sections versus Individuals

Abstract

Background: Body burdens of persistent bioaccumulative contaminants estimated from the cross-sectional biomonitoring of human populations are often plotted against age. Such relationships have previously been assumed to reflect the role of age in bioaccumulation.Objectives: We used a mechanistic modeling approach to reproduce concentration-versus-age relationships and investigate factors that influence them.Method: CoZMoMAN is an environmental fate and human food chain bioaccumulation model that estimates time trends in human body burdens in response to time-variant environmental emissions. Trends of polychlorinated biphenyl (PCB) congener 153 concentrations versus age for population cross sections were estimated using simulated longitudinal data for individual women born at different times. The model was also used to probe the influence of partitioning and degradation properties, length of emissions, and model assumptions regarding lipid content and liver metabolism on concentration–age trends of bioaccumulative and persistent contaminants.Results: Body burden–age relationships for population cross sections and individuals over time are not equivalent. The time lapse between the peak in emissions and sample collection for biomonitoring is the most influential factor controlling the shape of concentration–age trends for chemicals with human metabolic half-lives longer than 1 year. Differences in observed concentration–age trends for PCBs and polybrominated diphenyl ethers are consistent with differences in emission time trends and human metabolic half-lives.Conclusions: Bioaccumulation does not monotonically increase with age. Our model suggests that the main predictors of cross-sectional body burden trends with age are the amount of time elapsed after peak emissions and the human metabolic and environmental degradation rates.

Can polychlorinated biphenyl (PCB) signatures and enantiomer fractions be used for source identification and to age date occupational exposure?

“…Although the PCB concentration is well correlated with the number of years an individual has worked at the company it should not be used in isolation as proof that occupational exposure has occurred. Higher PCB concentrations have been reported in older individuals as a result of accumulation of the more persistent congeners and exposure to higher historical background concentrations (Megson et al, 2013a;Quinn and Wania, 2012). There are also several physiological characteristics, such as body fat, serum albumin and age, that can Table 1 PCB concentrations and enantiomer fractions recorded in workers.…”

Changes in persistent organic pollutant levels from adolescence to young adulthood

“…Elimination rates and their half-lives are often adjusted for the body burden – age relationship (cf. (Quinn and Wania 2012), but our EFA has shown that distinct dietary routines are also underlying factors that should be part of the regression model specification.…”

Menstrual cycle perturbation by organohalogens and elements in the Cree of James Bay, Canada

“…Confounders showing significant correlation (p<0.05) with menstrual cycle function endpoints were included with contaminant variables in regression analyses against endocrine endpoints. Age is a primary correlate of bio-accumulated POHs (Quinn and Wania, 2012), so using age as one of the confounders removes the age effect from the exposure variables incorporating these organic contaminants. Body mass index (BMI) was not included as a potential confounder because it was not significantly correlated with the selected reproductive endpoints.…”