This study proposes to estimate carboxyhaemoglobin (COHb) levels in the blood of men and women of various ages exposed to common concentrations of carbon monoxide (CO) using a model with only one free parameter while integrating alveoli-blood and blood-tissue CO exchanges. The model retained is essentially that of Coburn et al. (1965) with two important additions: an alveoli compartment for the dynamics of CO exchanges between alveoli and blood, and a compartment for the significant amounts of CO bound to heme proteins in extravascular spaces. The model was validated by comparing its simulations with various published data sets for the COHb time profiles of volunteers exposed to known CO concentrations. Once the model was validated, it was used to simulate various situations of interest for their impact on public health. This approach yields reliable estimations of the time profiles of COHb levels resulting from different levels of CO exposure over various periods of time and under various conditions (resting, exercise, working, and smoking). The non-linear kinetics of CO, observed experimentally, were correctly reproduced by simulations with the model. Simulations were also carried out iteratively to determine the exposure times and CO concentrations in ambient air needed to reach the maximum levels of COHb recommended by Health Canada, the U.S. Environmental Protection Agency (EPA), and the World Health Organisation (WHO) for each age group of the general population. The lowest CO concentrations leading to maximum COHb levels of 1.5, 2, and 2.5% were determined.

OBJECTIVE:This study was undertaken to estimate the absorbed doses of carbaryl and the associated health risks in a group of horticultural greenhouse workers in the Province of Quebec, Canada, using a toxicokinetic modeling approach.METHODS:A mathematical model was developed to relate the absorbed dose of carbaryl, the evolution of its body burden and that of its metabolites and the urinary excretion rate of biomarkers. The free parameters of this model were determined using published time course data in volunteers exposed to carbaryl under controlled conditions. The model was used to determine cumulative urinary amounts of 1-naphthol that would be excreted by a typical worker exposed to a pre-established no-observed-adverse-effect level (NOAEL) dose; this biomarker amount was then taken as a biological reference value below which the risks of health effects were considered negligible. As a measure of the applicability of this approach to practical situations, the model was used to estimate the dose of carbaryl absorbed by each greenhouse worker, starting from his/her cumulative urinary excretion time courses of 1-naphthol over a 24-h period following the onset of a work exposure. Their cumulative 1-naphthol levels were then compared to the biological reference value obtained from the model and the NOAEL dose.RESULTS:Following the onset of a work exposure to carbaryl, a clear increase in the urinary excretion rate of 1-naphthol was observed in most workers. The reconstructed absorbed doses were found to vary between 3.3 and 143 nmol/kg of body weight (bw) depending on the working conditions. Simulations of the observed cumulative urinary excretion time course of each worker also showed that exposure appeared to occur mainly (a) through inhalation for the applicators and individuals without direct contact with treated plants and (b) through the dermal route for individuals manipulating treated plants. Although the workers under study clearly appeared to have been exposed to carbaryl in the greenhouses, 24-h cumulative 1-naphthol levels ranged from 4.8 to 65.1% of the proposed biological reference value of 32 nmol/kg bw in 24-h urine collections following the onset of a work exposure.CONCLUSION:This suggests that the workers under study probably did not incur a serious health risk under the normal exposure conditions prevailing during the study period.

Risk AnalysisVolume 27, Issue 1 p. 9-10 Estimating Past Dioxin Exposure: Response to Steenland and Bartell Lesa L. Aylward, Lesa L. AylwardSearch for more papers by this authorHong Cheng, Corresponding Author Hong Cheng *Address correspondence to Hong Cheng, Department of Epidemiology, UAB School of Public Health, 527C RPHB, 1665 University Boulevard, Birmingham, AL 35294-0022, USA; tel: (205) 975-8679; heheng@ms.soph.uab.edu.Search for more papers by this authorColleen Beall, Colleen BeallSearch for more papers by this authorThomas B. Starr, Thomas B. StarrSearch for more papers by this authorRobert Brunet, Robert BrunetSearch for more papers by this authorGaétan Carrier, Gaétan CarrierSearch for more papers by this authorElizabeth Delzell, Elizabeth DelzellSearch for more papers by this author Lesa L. Aylward, Lesa L. AylwardSearch for more papers by this authorHong Cheng, Corresponding Author Hong Cheng *Address correspondence to Hong Cheng, Department of Epidemiology, UAB School of Public Health, 527C RPHB, 1665 University Boulevard, Birmingham, AL 35294-0022, USA; tel: (205) 975-8679; heheng@ms.soph.uab.edu.Search for more papers by this authorColleen Beall, Colleen BeallSearch for more papers by this authorThomas B. Starr, Thomas B. StarrSearch for more papers by this authorRobert Brunet, Robert BrunetSearch for more papers by this authorGaétan Carrier, Gaétan CarrierSearch for more papers by this authorElizabeth Delzell, Elizabeth DelzellSearch for more papers by this author First published: 13 March 2007 https://doi.org/10.1111/j.1539-6924.2006.00877.xRead the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume27, Issue1February 2007Pages 9-10 RelatedInformation

Exposure to selected organophosphorus insecticides (OPs), malathion, diazinon and acephate, was evaluated in a group of horticultural greenhouse workers. This was achieved through measurements of the cumulative urinary excretion time courses of specific and non-specific biomarkers over a 24 h period following the onset of work exposure. For malathion, the absorbed daily doses were estimated from the 24 h cumulative urinary amounts of the specific mono- and di-carboxylic acid metabolites (the sum of MCA and DCA) through the use of a kinetic model. The observed 24 h urinary levels were also compared with a biological reference value (BRV) of 57 nmol kg(-1) of body weight established in a previous work on the basis of a human no-observed-effect level exposure dose. Excretion values were found to be 2.5% or less of the BRV, suggesting a negligible health risk. Both median and 95th percentile concentrations of DCA (n = 57 samples) were, however, slightly higher than the baseline values determined by the Centers for Disease Control and Prevention (CDC) in the US civilian population (MCA was not analyzed by the CDC). The cumulative urinary excretion time course of the methyl phosphoric (MP) derivatives, which are metabolites of malathion but also of several other OPs, was also determined. Though relatively low, the MP levels were from 3 to 31 times higher than would be expected on the basis of the malathion specific MCA and DCA excretions, indicating that MP excretions stem from sources other than malathion exposure. Accordingly, only the time courses of MCA and DCA excretion rate (nmol h(-1)) were compatible with the time of work exposure. Urinary biomarkers of exposure to diazinon and acephate were also measured. Urinary concentrations were essentially below or equal to the analytical limit of detection of 1 microg l(-1) for 2-isopropyl-4-methyl-6-hydroxypyrimidine (n = 54) and of 0.8 microg l(-1) for acephate and methamidophos (n = 59): values within the baseline range of the US civilian population, like the observed phosphoric metabolite concentrations. The workers under study thus appeared to be only slightly more exposed to malathion than the general population. However, their overall exposure to OPs, as measured by non-specific phosphoric metabolites, was similar to that of the general population, whose exposure occurs mainly through the ingestion of contaminated food. These results question the relevance of measuring non-specific phosphoric metabolites when attempting to assess low-dose occupational exposure to a specific OP.

We examined the relation between cancer mortality and time‐dependent cumulative exposure to 2,3,7,8‐tetrachlorodibenzo‐p‐dioxin (TCDD) estimated from a concentration‐ and age‐dependent kinetic model of elimination, and we estimated incremental cancer risks at age 75. Data from the National Institute for Occupational Safety and Health study of 3,538 workers with occupational exposure to TCDD were analyzed using standardized mortality ratios and Cox regression procedures. Analyses adjusted for potential confounding by age, year of birth, and race and considered exposure lag periods of 0, 10, or 15 years. Other potential confounders including smoking and other occupational exposures were evaluated indirectly. To explore the influence of extreme values of cumulative TCDD ppt‐years, we restricted the analysis to observations with exposure below the 95th percentile or used logarithmic (ln) transformed exposure values. We applied penalized smoothing splines to examine variation in the exposure‐response relation across the exposure range. TCDD was not statistically significantly associated with cancer mortality using the full data set, regardless of the lag period. When we restricted the analysis to observations with exposure below the 95th percentile, TCDD was associated positively with cancer mortality, particularly when a 15‐year lag was applied (untransformed exposure data: regression coefficient , standard error (s.e.) = 1.4 × 10−6, p < 0.05; ln‐transformed exposure data: , s.e. = 2.9 × 10−2, p < 0.05). The estimated incremental lifetime risk of mortality at age 75 from all cancers was about 6 to more than 10 times lower than previous estimates derived from this cohort using exposure models that did not consider the age and concentration dependence of TCDD elimination.

A multi-compartment kinetic model was developed to describe the kinetics of parathion and its metabolites, p-nitrophenol (p-NP) and alkyl phosphates (AP), in order to assess worker exposure and health risks. Model compartments represent body burdens and excreta of parathion and its metabolites, to minimize the number of compartments and free parameters, regrouping was carried out on the basis of the time scales of the kinetic processes involved. Burden variations in time were described mathematically by differential equations that ensure conservation of mass on a mole basis. Model parameter values were determined from statistical fits to published in vivo kinetic data in humans. Except for the dermal absorption fraction and absorption rate, which are known to be subject to wide intra- and inter-individual variability, a single set of parameter values for the internal body kinetics enabled the model to simulate accurately, the available kinetic data. For dermal exposure to parathion, with a typical absorption rate of 0.085 h(-1). model simulations show that it takes 20 h to recover half of the total amounts of p-NP eventually excreted in urine and 30 h for the AP. The model can be used to estimate the dose of parathion absorbed under different exposure routes and temporal scenarios, based on measurements of amounts of metabolites accumulated in urine over given time periods. Using the above dose-excreta links and the human no-observed-effect level for parathion reported in the literature for the inhibition of cholinesterase activities, biological reference values are proposed in the form of specific amounts of urinary metabolites excreted over chosen time periods.

In the province of Quebec (Canada), the phytocide Garlon 4, whose active ingredient is triclopyr, is often used to prevent trees from reaching electrical conductors. The object of this paper is to assess the potential health risks in workers coming into contact with Garlon 4. Ten workers collected their urine during the 22 h following the beginning of a work shift. Measured urinary amounts of triclopyr varied between 1 and 13 mg. The absorbed daily doses were estimated from the amounts of triclopyr in urine through the use of a kinetic model that links the rates of triclopyr elimination to absorbed doses. These estimated doses were compared with the no-observed-effect level (NOEL) observed in rats: 5 mg per kg of body weight. The upper-bound estimations of the worker's daily absorbed doses were found to be 13.3% or less of the rat NOEL.

Significant amounts of methylmercury (MeHg) can bioaccumulate in fish and sea mammals. To monitor MeHg exposure in individuals, organic and inorganic mercury are often measured in blood samples or in hair strands, the latter being by far the best integrator of past exposure. With knowledge of the MeHg kinetics in humans, the levels of both biomarkers can be related to MeHg body burden and intakes. In the present study, we use the toxicokinetic model of Carrier et al. (2001) describing the distribution and excretion of MeHg in humans, to reconstruct the history of MeHg intakes of indigenous women of the Inuvik region in Canada starting from total mercury concentrations in hair segments. From these reconstructed MeHg intakes, the corresponding simulated mercury blood concentrations are found to be good predictors of the concentrations actually measured in blood samples. An important conclusion of this study is that, for almost all subjects, the reconstructed history of their MeHg intakes provides much lower intake values than intakes estimated from questionnaires on food consumption and estimated MeHg levels in these foods; the mean value of the reconstructed MeHg intakes is 0.03 μ g/kg/day compared with the mean value of 0.20 μ g/kg/day obtained from questionnaires. The model was also used to back-calculate the MeHg intakes from concentrations in hair strands collected from aboriginals of the Amazon region in Brazil, a population significantly more exposed than the population of the Inuvik region.

Recent studies demonstrating a concentration dependence of elimination of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) suggest that previous estimates of exposure for occupationally exposed cohorts may have underestimated actual exposure, resulting in a potential overestimate of the carcinogenic potency of TCDD in humans based on the mortality data for these cohorts. Using a database on U.S. chemical manufacturing workers potentially exposed to TCDD compiled by the National Institute for Occupational Safety and Health (NIOSH), we evaluated the impact of using a concentration- and age-dependent elimination model (CADM) (Aylward et al., 2005) on estimates of serum lipid area under the curve (AUC) for the NIOSH cohort. These data were used previously by Steenland et al. (2001) in combination with a first-order elimination model with an 8.7-year half-life to estimate cumulative serum lipid concentration (equivalent to AUC) for these workers for use in cancer dose-response assessment. Serum lipid TCDD measurements taken in 1988 for a subset of the cohort were combined with the NIOSH job exposure matrix and work histories to estimate dose rates per unit of exposure score. We evaluated the effect of choices in regression model (regression on untransformed vs. ln-transformed data and inclusion of a nonzero regression intercept) as well as the impact of choices of elimination models and parameters on estimated AUCs for the cohort. Central estimates for dose rate parameters derived from the serum-sampled subcohort were applied with the elimination models to time-specific exposure scores for the entire cohort to generate AUC estimates for all cohort members. Use of the CADM resulted in improved model fits to the serum sampling data compared to the first-order models. Dose rates varied by a factor of 50 among different combinations of elimination model, parameter sets, and regression models. Use of a CADM results in increases of up to five-fold in AUC estimates for the more highly exposed members of the cohort compared to estimates obtained using the first-order model with 8.7-year half-life. This degree of variation in the AUC estimates for this cohort would affect substantially the cancer potency estimates derived from the mortality data from this cohort. Such variability and uncertainty in the reconstructed serum lipid AUC estimates for this cohort, depending on elimination model, parameter set, and regression model, have not been described previously and are critical components in evaluating the dose-response data from the occupationally exposed populations.

Urinary biomarkers of chlorpyrifos (CPF) exposure are often measured in field studies, although biological reference values (BRVs) are not yet available to assess health risks. This study aimed at proposing BRVs for CPF metabolites in workers' urine based on a toxicokinetic approach. As a first step, a toxicokinetic model was developed, using published human kinetic data, to link the absorbed dose of CPF under a variety of exposure routes and temporal scenarios to the urinary excretion of its major metabolites, 3,5,6-trichloro-2-pyridinol (3,5,6-TCP) and alkyl phosphates (AP). The model was then used to propose BRVs for CPF metabolites in urine below which workers should not experience adverse health effects. This was achieved by linking (1) a literature-reported, repeated CPF no-observed-effect level (NOEL) daily exposure dose for the inhibition of red-blood-cell acetylcholinesterase activity to a corresponding absorbed daily dose, and (2) this absorbed daily dose to the urinary excretion of CPF metabolites. Model simulations under a variety of exposure scenarios showed that the safest BRVs are obtained from a dermal exposure scenario with the slowest absorption rate compatible with available literature data rather than from respiratory or oral exposure scenarios. Also, model simulations showed that, for a given total absorbed dose, absorption over 8 hours results in smaller 3,5,6-TCP and AP urinary excretion rates than those obtained from the same dose absorbed over shorter durations. From these considerations, BRVs were derived by simulating an 8-hour dermal CPF exposure such that the total absorbed daily dose corresponds to the absorbed NOEL. The reference values are proposed in the form of total amounts of 3,5,6-TCP and AP metabolites excreted in urine over chosen time periods (24 and 48 hours).

Serial measurements of serum lipid 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) concentrations in 36 adults from Seveso, Italy, and three patients from Vienna, Austria, with initial serum lipid TCDD concentrations ranging from 130 to 144,000 ppt, were modeled using a modified version of a previously published toxicokinetic model for the distribution and elimination of dioxins. The original model structure accounted for a concentration-dependent increase in overall elimination rate for TCDD due to nonlinear distribution of TCDD to the liver (secondary to induction of the binding protein CYP1A2), from which elimination takes place via a first-order process. The original model structure was modified to include elimination due to lipid partitioning of TCDD from circulation into the large intestine, based on published human data. We optimized the fit of the modified model to the data by varying the hepatic elimination rate parameter for each of the 39 people. The model fits indicate that there is significant interindividual variability of TCDD elimination efficiency in humans and also demonstrate faster elimination in men compared to women, and in younger vs. older persons. The data and model results indicate that, for males, the mean apparent half-life for TCDD (as reflected in changes in predicted serum lipid TCDD level) ranges from less than 3 years at serum lipid levels above 10,000 ppt to over 10 years at serum lipid levels below 50 ppt. Application of the model to serum sampling data from the cohort of US herbicide-manufacturing workers assembled by the National Institute of Occupational Safety and Health (NIOSH) indicates that previous estimates of peak serum lipid TCDD concentrations in dioxin-exposed manufacturing workers, based on first-order back-extrapolations with half-lives of 7-9 years, may have underestimated the maximum concentrations in these workers and other occupational cohorts by several-fold to an order of magnitude or more. Such dose estimates, based on a single sampling point decades after last exposure, are highly variable and dependent on a variety of assumptions and factors that cannot be fully determined, including interindividual variations in elimination efficiency. Dose estimates for these cohorts should be re-evaluated in light of the demonstration of concentration-dependent elimination kinetics for TCDD, and the large degree of uncertainty in back-calculated dose estimates should be explicitly incorporated in quantitative estimates of TCDD's carcinogenic potency based on such data.

Malaria vaccine candidates have already been tested and new trials are being carried out. We present a brief description of specific issues of validity that are relevant when assessing vaccine efficacy in the field and illustrate how the application of these principles might improve our interpretation of the data being gathered in actual malaria vaccine field trials. Our discussion assumes that vaccine evaluation shares the same general principles of validity with epidemiologic causal inference, i.e., the process of drawing inferences from epidemiologic data aiming at the identification of causes of diseases. Judicious exercise of these principles indicates that, for meaningful interpretation, measures of vaccine efficacy require definitions based upon arguments conditional on the amount of exposure to infection, and specification of the initial and final states in which one believes the effect of interest takes place.

A toxicokinetic model is proposed to predict the time evolution of malathion and its metabolites, mono- and dicarboxylic acids (MCA, DCA) and phosphoric derivatives (dimethyl dithiophosphate [DMDTP], dimethyl thiophosphate [DMTP], and dimethyl phosphate [DMP]) in the human body and excreta, under a variety of exposure routes and scenarios. The biological determinants of the kinetics were established from published data on the in vivo time profiles of malathion and its metabolites in the blood and urine of human volunteers exposed by intravenous, oral, or dermal routes. In the model, body and excreta compartments were used to represent the time varying amounts of each of the following: malathion, MCA, DCA, DMDTP, DMTP, and DMP. The dynamic of intercompartment exchanges was described mathematically by a differential equation system that ensured conservation of mass at all times. The model parameters were determined by statistically adjusting the explicit solution of the differential equations to the experimental human data. Simulations provide a close approximation to kinetic data available in the published literature. When simulating a dermal exposure to malathion, the main route of entry for workers, the model predicts that it takes an average of 11.8 h to recover half of the absorbed dose of malathion eventually excreted in urine as metabolites, compared to 3.2 h following an intravenous injection and 4.0 h after oral administration. This shows that following a dermal exposure, the absorption rate governs the urinary excretion rate of malathion metabolites because the dermal absorption rate is much slower than biotransformation and renal clearance processes. The model served to establish biological reference values for malathion metabolites in urine since it allows links to be made between the absorbed dose of malathion and the time course of cumulative amounts of metabolites excreted in urine. From the no-observed-effect level (NOEL) of 0.61 micromol/kg/day derived from the data of Moeller and Rider (1962), the model predicts corresponding biological reference values for MCA, DCA, and phosphoric derivatives of 44, 13, and 62 nmol/kg, respectively, in 24-h urine samples. The latter were used to assess the health risk of workers exposed to malathion in botanical greenhouses, starting from urinary measurements of MCA and DCA metabolites.

Particle boards and other wood boards are usually made with formaldehyde-based resins. Woodworkers are thus exposed to formaldehyde in vapor form as well as from airborne dust once it enters their respiratory tract. These workers remain exposed to formaldehyde released from the dust still present in their upper respiratory tract, even after their work shift. In assessing the risk associated with formaldehyde exposure, one needs to consider the relative importance of these two sources of exposure. This study proposes two kinetic models to estimate and compare the exposures. For various exposure scenarios, one model predicts the amount of formaldehyde absorbed from the ambient vapor form and the other predicts the amount absorbed by the respiratory tract upon its release from wood product dust. Model parameters are determined using data from published studies. Based on a daily work shift of 8 hr, with a dust concentration in air of 5 mg/m(3) and a formaldehyde concentration bound to dust of 9 microg/mg, model simulations predict that the amount of absorbed formaldehyde released from wood dust is approximately 1/100 of the amount absorbed from the ambient vapor form at a concentration level of 0.38 mg/m(3) (0.3 ppm). Since the formaldehyde concentration in wood dust used above is much higher than usually observed while the dust and vapor form formaldehyde concentrations are of the order of acceptable upper values, these results indicate that the formaldehyde exposure from wood dust is comparatively negligible.

Many compartment based epidemiological models are written as differential equation systems for various status subpopulation sizes with per person-time transfer rates between compartments. However, field data obtained by sampling at chosen times is usually provided in terms of status proportions from the total observable population (e.g., relative prevalence). Relationships between per person-time transfer rates (incidence, mortality, intervention rates) and proportions are not obvious when heterogeneity is at work because the various subpopulation sizes undergo different attrition rates and are not evolving in synchrony with the corresponding proportions. Rules are proposed to write sets of differential equations for compartment models, directly in terms of the proportions of the total observable at any time. To facilitate the writing of relationships between per person-time transfer rates and proportions, the systems are cast in network equivalent forms satisfying rules analogous to those of electrical networks (Kirchhoff's law for currents). The method is also extended to variability in the rates within a status subpopulation, considering. either a fixed set of compartmental subdivisions or an inner continuum of differences in rates.

A method for estimating the dependence of intrinsic intervention benefits on time elapsed since the intervention took place is proposed. The method is aimed at intervention programs against diseases where one or all of the following components of hazard intensity may undergo important and unknown variations: 1) the intervention benefits to a subject are a function of the time elapsed since the intervention took place, or since inception for a continuing treatment, 2) the subjects vulnerability is an unknown function of their age, 3) the exogenous or environmental baseline intensity, to which all are assumed subjected, fluctuates arbitrarily with calendar time. During the time span of a study, these variables interact in a complex way, possibly masking the real contribution of the intervention. However, with very general assumptions about how hazard components interact, the cumulative hazards of subpopulations treated at different times in the past are shown to be described mathematically by a convolution of the time elapsed dependent intervention benefit function with the age and calendar time dependent baseline intensity. Starting from the cumulative hazards of untreated and treated subpopulations that had the intervention at different times in the past, a method of deconvolution through regularization is proposed to reconstruct the time elapsed dependence of the intervention benefit function. The regularization technique used is of the ‘penalized least square smoothing’ type, it is applied to the solution of Volterra integral equations of the first kind under noisy inputs. Simulations, to test for the reconstruction of different modes of time elapsed variation of the intervention benefits, are carried out on realistically noisy ‘data sets’ taken to be available at a limited number of time points. The stability of the estimated reconstructions, to measurement errors, is examined through repeated simulations with random noise added to inputs. The method is applied to a Brazilian data set where BCG vaccination resulted in a small reduction in the cumulated risk of leprosy infection.