Limits...
A multi-individual pharmacokinetic model framework for interpreting time trends of persistent chemicals in human populations: application to a postban situation.

Ritter R, Scheringer M, MacLeod M, Schenker U, Hungerbühler K - Environ. Health Perspect. (2009)

Bottom Line: For this case, the framework quantitatively describes the relationships among the half-life for reduction of body burdens of POPs derived from CSTD, the half-life describing decline in daily intake, and the half-life of elimination from the human body.The full utility of these data has not been exploited so far.An efficient and informative monitoring strategy for banned POPs in humans would coordinate sampling of consistent sets of CSTD from young adults with total diet studies.

View Article: PubMed Central - PubMed

Affiliation: Safety and Environmental Technology Group, ETH Zurich, Zurich, Switzerland.

ABSTRACT

Background: Human milk and blood are monitored to detect time trends of persistent organic pollutants (POPs) in humans. It is current practice to use log-linear regression to fit time series of averaged cross-sectional biomonitoring data, here referred to as cross-sectional trend data (CSTD).

Objective: The goals of our study are to clarify the interpretation of half-lives derived from fitting exponential functions to declining CSTD and to provide a method of estimating human elimination half-lives from CSTD collected in a postban situation.

Methods: We developed a multi-individual pharmacokinetic model framework and present analytical solutions for a postban period. For this case, the framework quantitatively describes the relationships among the half-life for reduction of body burdens of POPs derived from CSTD, the half-life describing decline in daily intake, and the half-life of elimination from the human body.

Results: The half-life derived from exponential fitting of CSTD collected under postban conditions describes the exposure trend and is independent of human elimination kinetics. We use a case study of DDT (dichlorodiphenyltrichloroethane) to show that CSTD can be combined with exposure data obtained from total diet studies to estimate elimination kinetics of POPs for humans under background exposure conditions.

Conclusions: CSTD provide quantitative information about trends in human exposure and can be combined with exposure studies to estimate elimination kinetics. The full utility of these data has not been exploited so far. An efficient and informative monitoring strategy for banned POPs in humans would coordinate sampling of consistent sets of CSTD from young adults with total diet studies.

Show MeSH

Related in: MedlinePlus

Influence of human elimination half-life, t1/2elim, and characteristic age, tcage, on modeled CSTD and CSD. We assume an initial daily intake, I0, of 20,000 ng/person/day for two chemicals: chemical 1, with t1/2elim = 8 years, and chemical 2, with t1/2elim = 3 years; the half-life of decline in exposure, t1/2dec, is the same for both chemicals and is assumed to be 12 years. (A) For the slowly eliminated chemical 1, concentrations in humans are higher than for the more rapidly eliminated chemical 2. In addition, the trend lines for two characteristic ages, 20 years and 40 years, are separated for chemical 1 but are almost identical for chemical 2. However, all four CSTD lines are parallel and reflect, according to Equation 7, the half-life in decline of intake, t1/2dec, of 12 years. “Preadult” indicates < 20 years of age. (B) Modeled CSD, calculated for the year 2002, as a function of age. Only the slowly eliminated chemical 1 shows a significant increase of concentration with age.
© Copyright Policy - public-domain
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC2721873&req=5

f2-ehp-117-1280: Influence of human elimination half-life, t1/2elim, and characteristic age, tcage, on modeled CSTD and CSD. We assume an initial daily intake, I0, of 20,000 ng/person/day for two chemicals: chemical 1, with t1/2elim = 8 years, and chemical 2, with t1/2elim = 3 years; the half-life of decline in exposure, t1/2dec, is the same for both chemicals and is assumed to be 12 years. (A) For the slowly eliminated chemical 1, concentrations in humans are higher than for the more rapidly eliminated chemical 2. In addition, the trend lines for two characteristic ages, 20 years and 40 years, are separated for chemical 1 but are almost identical for chemical 2. However, all four CSTD lines are parallel and reflect, according to Equation 7, the half-life in decline of intake, t1/2dec, of 12 years. “Preadult” indicates < 20 years of age. (B) Modeled CSD, calculated for the year 2002, as a function of age. Only the slowly eliminated chemical 1 shows a significant increase of concentration with age.

Mentions: Figure 2A illustrates the influence of changes in kelim and tcage on modeled CSTD. A change in kelim causes a parallel shift of the logarithmic CSTD function. As can be deduced from Equation 7, other parameters such as I0, bw, Ea, and flipid will also change the value for KCSTD and thus cause a parallel shift of the CSTD function. However, as stated above, the slope of the CSTD function is solely determined by the rate constant of the intake trend, kdec. Figure 2A also shows that chemicals with slower elimination show larger differences in concentrations measured in individuals of different ages that may be included in CSD. Hence, the slower the elimination kinetics of a chemical, the more important it is to include only empirical CSD with consistent age structure in the time trend analysis.


A multi-individual pharmacokinetic model framework for interpreting time trends of persistent chemicals in human populations: application to a postban situation.

Ritter R, Scheringer M, MacLeod M, Schenker U, Hungerbühler K - Environ. Health Perspect. (2009)

Influence of human elimination half-life, t1/2elim, and characteristic age, tcage, on modeled CSTD and CSD. We assume an initial daily intake, I0, of 20,000 ng/person/day for two chemicals: chemical 1, with t1/2elim = 8 years, and chemical 2, with t1/2elim = 3 years; the half-life of decline in exposure, t1/2dec, is the same for both chemicals and is assumed to be 12 years. (A) For the slowly eliminated chemical 1, concentrations in humans are higher than for the more rapidly eliminated chemical 2. In addition, the trend lines for two characteristic ages, 20 years and 40 years, are separated for chemical 1 but are almost identical for chemical 2. However, all four CSTD lines are parallel and reflect, according to Equation 7, the half-life in decline of intake, t1/2dec, of 12 years. “Preadult” indicates < 20 years of age. (B) Modeled CSD, calculated for the year 2002, as a function of age. Only the slowly eliminated chemical 1 shows a significant increase of concentration with age.
© Copyright Policy - public-domain
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2721873&req=5

f2-ehp-117-1280: Influence of human elimination half-life, t1/2elim, and characteristic age, tcage, on modeled CSTD and CSD. We assume an initial daily intake, I0, of 20,000 ng/person/day for two chemicals: chemical 1, with t1/2elim = 8 years, and chemical 2, with t1/2elim = 3 years; the half-life of decline in exposure, t1/2dec, is the same for both chemicals and is assumed to be 12 years. (A) For the slowly eliminated chemical 1, concentrations in humans are higher than for the more rapidly eliminated chemical 2. In addition, the trend lines for two characteristic ages, 20 years and 40 years, are separated for chemical 1 but are almost identical for chemical 2. However, all four CSTD lines are parallel and reflect, according to Equation 7, the half-life in decline of intake, t1/2dec, of 12 years. “Preadult” indicates < 20 years of age. (B) Modeled CSD, calculated for the year 2002, as a function of age. Only the slowly eliminated chemical 1 shows a significant increase of concentration with age.
Mentions: Figure 2A illustrates the influence of changes in kelim and tcage on modeled CSTD. A change in kelim causes a parallel shift of the logarithmic CSTD function. As can be deduced from Equation 7, other parameters such as I0, bw, Ea, and flipid will also change the value for KCSTD and thus cause a parallel shift of the CSTD function. However, as stated above, the slope of the CSTD function is solely determined by the rate constant of the intake trend, kdec. Figure 2A also shows that chemicals with slower elimination show larger differences in concentrations measured in individuals of different ages that may be included in CSD. Hence, the slower the elimination kinetics of a chemical, the more important it is to include only empirical CSD with consistent age structure in the time trend analysis.

Bottom Line: For this case, the framework quantitatively describes the relationships among the half-life for reduction of body burdens of POPs derived from CSTD, the half-life describing decline in daily intake, and the half-life of elimination from the human body.The full utility of these data has not been exploited so far.An efficient and informative monitoring strategy for banned POPs in humans would coordinate sampling of consistent sets of CSTD from young adults with total diet studies.

View Article: PubMed Central - PubMed

Affiliation: Safety and Environmental Technology Group, ETH Zurich, Zurich, Switzerland.

ABSTRACT

Background: Human milk and blood are monitored to detect time trends of persistent organic pollutants (POPs) in humans. It is current practice to use log-linear regression to fit time series of averaged cross-sectional biomonitoring data, here referred to as cross-sectional trend data (CSTD).

Objective: The goals of our study are to clarify the interpretation of half-lives derived from fitting exponential functions to declining CSTD and to provide a method of estimating human elimination half-lives from CSTD collected in a postban situation.

Methods: We developed a multi-individual pharmacokinetic model framework and present analytical solutions for a postban period. For this case, the framework quantitatively describes the relationships among the half-life for reduction of body burdens of POPs derived from CSTD, the half-life describing decline in daily intake, and the half-life of elimination from the human body.

Results: The half-life derived from exponential fitting of CSTD collected under postban conditions describes the exposure trend and is independent of human elimination kinetics. We use a case study of DDT (dichlorodiphenyltrichloroethane) to show that CSTD can be combined with exposure data obtained from total diet studies to estimate elimination kinetics of POPs for humans under background exposure conditions.

Conclusions: CSTD provide quantitative information about trends in human exposure and can be combined with exposure studies to estimate elimination kinetics. The full utility of these data has not been exploited so far. An efficient and informative monitoring strategy for banned POPs in humans would coordinate sampling of consistent sets of CSTD from young adults with total diet studies.

Show MeSH
Related in: MedlinePlus