Michael E. Ginevan

Use of environmental tobacco smoke constituents as markers for exposure.

The 16-City Study analyzed for gas-phase environmental tobacco smoke (ETS) constituents (nicotine, 3-ethenyl pyridine [3-EP], and myosmine) and for particulate-phase constituents (respirable particulate matter [RSP], ultraviolet-absorbing particulate matter [UVPM], fluorescing particulate matter [FPM], scopoletin, and solanesol). In this second of three articles, we discuss the merits of each constituent as a marker for ETS and report pair-wise comparisons of the markers. Neither nicotine nor UVPM were good predictors for RSP. However, nicotine and UVPM were good qualitative predictors of each other. Nicotine was correlated with other gas-phase constituents. Comparisons between UVPM and other particulate-phase constituents were performed. Its relation with FPM was excellent, with UVPM approximately 1 1/2 times FPM. The correlation between UVPM and solanesol was good, but the relationship between the two was not linear. The relation between UVPM and scopoletin was not good, largely because of noise in the scopoletin measures around its limit of detection. We considered the relation between nicotine and saliva cotinine, a metabolite of nicotine. The two were highly correlated on the group level. That is, for each cell (smoking home and work, smoking home but nonsmoking work, and so forth), there was high correlation between average cotinine and 24-hour time-weighted average (TWA) nicotine concentrations. However, on the individual level, the correlations, although significant, were not biologically meaningful. A consideration of cotinine and nicotine or 3-EP on a subset of the study whose only exposure to ETS was exclusively at work or exclusively at home showed that home exposure was a more important source of ETS than work exposure.

Implications of estimates of residential organophosphate exposure from dialkylphosphates (DAPs) and their relevance to risk

Recent epidemiological studies have claimed to associate a variety of toxicological effects of organophosphorus insecticides (OPs) and residential OP exposure based on the dialkyl phosphates (DAPs; metabolic and environmental breakdown products of OPs) levels in the urine of pregnant females. A key premise in those epidemiology studies was that the level of urinary DAPs was directly related to the level of parent OP exposure. Specific chemical biomarkers and DAPs representing absorbed dose of OPs are invaluable to reconstruct human exposures in prospective occupational studies and even in non-occupational studies when exposure to a specific OP can be described. However, measurement of those detoxification products in urine without specific knowledge of insecticide exposure is insufficient to establish OP insecticide exposure. DAPs have high oral bioavailability and are ubiquitously present in produce at concentrations several-fold greater than parent OPs. Studies relying on DAPs as an indicator of OP exposure that lack credible information on proximate OP exposure are simply measuring DAP exposure and misattributing OP exposure.

The Air Force Health Study: An Epidemiologic Retrospective

In 1979, the U.S. Air Force announced that an epidemiologic study would be undertaken to determine whether the Air Force personnel involved in Operation Ranch Hand-the program responsible for herbicide spraying in Vietnam-had experienced adverse health effects as a result of that service. In January 1982 the Air Force Health Study (AFHS) protocol was approved and the 20 year matched cohort study consisting of independent mortality, morbidity and reproductive health components was initiated. This controversial study has been criticized regarding the studys potential scientific limitations as well as some of the administrative aspects of its conduct. Now, almost 30 years since the implementation of the AFHS and nearly a decade since the final follow up examinations, an appraisal of the study indicates that the results of the AFHS do not provide evidence of disease in the Ranch Hand veterans caused by their elevated levels of exposure to Agent Orange.

Statistical tools for environmental quality measurement

Preface Sample Support and Related Scale Issues in Sampling and Sampling Design Basic Tools and Concepts-Description of Data Hypothesis Testing Correlation and Regression Tools for Dealing with Censored Data The Promise of the Bootstrap Tools for the Analysis of Spatial Data Tools for the Analysis of Temporal Data

Human exposure assessment. I: Understanding the uncertainties.

Exposure estimates produced using predictive exposure assessment methods are associated with a number of uncertainties that relate to the inherent variability of the values for a given input parameter (e.g., body weight, ingestion rate, inhalation rate) and to unknowns concerning the representativeness of the assumptions and methods used. Despite recent or ongoing consensus-building efforts that have made significant strides forward in promoting consistency in methodologies and parameter default values, the potential variability in the output exposure estimates has not been adequately addressed from a quantitative aspect. This is exemplified by remaining tendencies within federal and state agencies to use worst-case approaches for exposure assessment. In this study, range-sensitivity and Monte Carlo analyses were performed on several different exposure scenarios in order to illustrate the impact of the variability in input parameters on the total variability of the exposure output. The results of this study indicate that the variability associated with the example scenarios range up to more than four orders of magnitude when just some of the parameters are allowed to vary. Comparison of exposure estimates obtained using Monte Carlo simulations (in which selected parameters were allowed to vary over their observed ranges) to exposure estimates obtained using standard parameter default assumptions demonstrate that a default value approach can produce an exposure estimate that exceeds the 95th percentile exposure in an exposed population.

Assessing exposure to allied ground troops in the Vietnam War: A comparison of AgDRIFT and Exposure Opportunity Index models

The AgDRIFT aerial dispersion model is well validated and closely related to the AGDISP model developed by the USDA Forest Service to determine on- and off-target deposition and penetration of aerially applied pesticide through foliage of trees. The Exposure Opportunity Index (EOI) model was developed to estimate relative exposure of ground troops in Vietnam to aerially applied herbicides. We compared the output of the two models to determine whether their predictions were in substantial agreement, but found a total lack of concordance. While the AgDRIFT model estimated that ground-level deposition through foliage was reduced more than 20 orders of magnitude at less than 1 km from the flight line, the EOI model predicted deposition declines less than one order of magnitude 4 km from the flight line. Interestingly the EOI model predicts a four-fold variability in EOI on the flight line, where exposure should be essentially invariant because the spray apparatus is designed to apply herbicide at a constant rate. We believe that the EOI model cannot be used to provide individual exposure estimates for the purpose of conducting epidemiologic studies. Moreover, evaluation of the position data for both herbicide spray swaths and troop locations, together with the actual patterns of spray deposition predicted by the AgDRIFT model, suggests that precise individual-level exposure assessments for ground troops in Vietnam are impossible. However, we suggest that well-validated tools like AgDRIFT can be used to estimate exposure to groups of individuals.

Distribution of exposure concentrations and doses for constituents of environmental tobacco smoke

The ultimate goal of the research reported in this series of three articles is to derive distributions of doses of selected environmental tobacco smoke (ETS)-related chemicals for nonsmoking workers. This analysis uses data from the 16-City Study collected with personal monitors over the course of one workday in workplaces where smoking occurred. In this article, we describe distributions of ETS chemical concentrations and the characteristics of those distributions (e.g., whether the distribution was log normal for a given constituent) for the workplace exposure. Next, we present population parameters relevant for estimating dose distributions and the methods used for estimating those dose distributions. Finally, we derive distributions of doses of selected ETS-related constituents obtained in the workplace for people in smoking work environments. Estimating dose distributions provided information beyond the usual point estimate of dose and showed that the preponderance of individuals exposed to ETS in the workplace were exposed at the low end of the dose distribution curve. The results of this analysis include estimations of hourly maxima and time-weighted average (TWA) doses of nicotine from workplace exposures to ETS (extrapolated from 1 day to 1 week) and doses derived from modeled lung burdens of ultraviolet-absorbing particulate matter (UVPM) and solanesol resulting from workplace exposures to ETS (extrapolated from 1 day to 1 year).

Human exposure assessment. II. Quantifying and reducing the uncertainties

Alternative methods of human exposure assessment that reduce and/or allow quantification of the uncertainties associated with exposure estimates are surveyed and illustrated. These alternative approaches include (1) use of more appropriate exposure parameter default values rather than values that result in extreme exposure estimates; (2) incorporation of time-activity data to better define appropriate exposure duration values; (3) the use of reasonable exposure scenarios rather than the traditional Maximally Exposed Individual (MEI) approach; (4) the use of stochastic approaches such as Monte Carlo-based and information analysis-based methods; (5) use of bivariate analysis to identify the extent to which interdependencies between different exposure parameters affect the distribution of exposure estimates; (6) use of less-than-lifetime exposure and risk assessment; and (7) incorporation of physiological considerations relevant to absorbed dose estimation, including route-specific impacts, use of improved absorption factors, and application of pharmacokinetic models. Other ways to improve the exposure assessment process, including assuring statistical equivalency in comparing different exposure estimates and incorporation of sensitive subpopulation considerations are also discussed, as are key research needs.

Assessing exposure to allied ground troops in the Vietnam War: a quantitative evaluation of the Stellman Exposure Opportunity Index model.

The Exposure Opportunity Index (EOI) is a proximity-based model developed to estimate relative exposure of ground troops in Vietnam to aerially applied herbicides. We conducted a detailed quantitative evaluation of the EOI model by using actual herbicide spray missions isolated in time and space. EOI scores were calculated for each of 36 hypothetical receptor location points associated with each spray mission for 30 herbicide missions for two time periods - day of herbicide application and day 2-3 post-application. Our analysis found an enormous range of EOI predictions with 500-1000-fold differences across missions directly under the flight path. This quantitative examination of the EOI suggests that extensive testing of the models code is warranted. Researchers undertaking development of a proximity-based exposure model for epidemiologic studies of either Vietnam veterans or the Vietnamese population should conduct a thorough and realistic analysis of how precise and accurate the model results are likely to be and then assess whether the model results provide a useful basis for their planned epidemiologic studies.

Logarithmic dose transformation in epidemiologic dose-response analysis: use with caution.

Dose-response models based on the logarithm of dose or exposure are utilized in the analysis of both toxicological and epidemiologic data. While the applications are similar, fundamental differences in the studies conducted by each discipline affects the interpretation of the use of the logarithmic dose transformation. Using numerical illustrations and examples from the literature, this paper explores the implications of using logarithmic dose transformation in epidemiologic studies and provides some caveats for consideration in interpreting epidemiologic studies based upon logarithmic dose transformation.