Exposure Assessment In Epidemiology Research Articles

Exposure assessment in epidemiology: does gender matter?

The pathway from potential hazards in the work environment to the measurement or estimation of personal exposure for epidemiologic studies comprises many steps, each of which can be influenced by factors that may or may not differ by gender. This article explores this pathway to address the question, "Should the potential for gender differences be taken into account in the activity of exposure assessment for epidemiologic studies?" Evidence from previously published studies and data from the investigators' own research were examined to explore whether or not several theoretical sources of gender 'bias' in exposure assessment have been found in actual studies. Sources of bias examined included: differences in job tasks despite same job titles; differences in delivered exposure due to differences in protective equipment, body size, or other relationships to exposure sources; and differences in estimated exposure arising from study methods or design. Evidence was found for gender differences (and thus potential bias) from all these sources, at least in some studies. We conclude that the answer to the question posed, "Does gender matter, in exposure assessment for epidemiology?" is a qualified 'yes,' but that the magnitude and direction of the potential bias cannot be predicted, a priori. Am. J. Ind. Med. 44:576-583, 2003.

USING GIS FOR EXPOSURE ASSESSMENT

Exposure misclassification has long been characterized as the Achilles heel of environmental epidemiological studies. A plausible explanation for inadequate exposure assessment in environmental epidemiology is the lack of cross-disciplinary training and communication between health, earth, and engineering scientists. As health scientists, epidemiologists have a keen understanding of the biological factors that need to be studied to determine if a population is at risk to disease because of exposure to particular contaminants in their environment. However, they generally are not trained in the sciences necessary to determine the level at which that contaminant was present in the environment of their study population. Conversely, earth scientists and environmental engineers are trained in methods for quantifying source, fate and transport of contaminants in an environment, but have little knowledge of how to apply this information in a human health study. By this presentation, I hope to demonstrate how geographic information system (GIS) and related computer-based technologies can serve as a means for improving exposure assessment for environmental epidemiological studies, and in that context, serve as a learning and communications bridge between health, earth, and engineering sciences. The term ‘environment’ implies a spatial context. Thus, the study of interactions between humans and their environment requires spatial information. We have identified at least 15 elements in the exposure assessment process for an environmental epidemiological study. In this presentation I will review the key elements of this process. Particular emphasis will be given to those steps in which GIS has the potential or has been demonstrated to enhance the state of the science of exposure assessment. For example, one step in exposure assessment is source identification for the chemical compound of interest. A typical method for conducting exposure assessment in epidemiology is to interview study participants in order to obtain information that can relate or infer exposure to such sources. However, in many studies, sources of these compounds cannot be ascertained through questionnaires. Regions exist in the USA where the general population resides in intensive agriculture landscapes, but are not engaged in agricultural production. It is highly unlikely that such individuals would know what chemicals are used on crops near their homes. I will present and discuss a GIS-based method for identifying crops and linking crop-type to pesticide use for use in epidemiological studies concerning non-occupational exposure to agricultural pesticides that holds promise for exposure classification. The use of GIS in exposure assessment requires attention to fundamental elements of geospatial science, including resolution and scale. I will present a comparative analysis of two GIS-based exposure metrics using different resolution and operational scale data. The two methods resulted in significantly different exposure classification and resultant risk estimates when compared in the context of an epidemiology study concerning non-occupational exposure to agricultural pesticides.

Exposure levels and determinants of softwood dust exposures in BC lumber mills, 1981-1997.

Measurements of personal exposure to wood dust (n = 1237) collected by the Workers' Compensation Board of British Columbia, Canada, over the period 1981-1997 were used to construct an empirical model to identify broad determinants of softwood dust exposure. Potential determinants of exposure examined included species of tree processed; company; geographic location of lumber mill; department; job title; calendar year; and production factors such as board feet of lumber produced per year. A determinants of exposure model was built using multiple linear regression. Nested within this compliance database was a subset of samples collected for a research study. These enabled the authors to explore whether differences in exposure measurements can in part be explained by sampling strategy (research versus compliance). Potential differences were examined by examining differences in means for each job title, stratified by sampling strategy; and by offering "sampling strategy" as a categorical predictor variable to the empirical model. Multiple linear regressions revealed the most important determinants of increased wood dust exposure to be mill location away from the coast, earlier calendar year, and indoor jobs. The empirical model had an R2 of 0.39 and a predictive range from 0.02 to 25.45 mg/m3. Research and compliance sampling strategies showed no difference in mean exposure and distribution in the empirical model (p < 0.05), suggesting that regulatory exposure databases may be of utility for exposure assessment in epidemiology. This research indicates that compliance-sampling strategies do not result in an overestimation of mean exposure levels within jobs, but they do focus on a biased sample of jobs-those most highly exposed.

Adipose Tissue as a Medium for Epidemiologic Exposure Assessment

Adipose Tissue as a Medium for Epidemiologic Exposure Assessment

Adipose tissue as a medium for epidemiologic exposure assessment.

In the United States, adipose tissue is rarely used as a medium for assessment of prior exposures in epidemiologic studies. Adipose tissue aspirations are in general less invasive and carry less risk than phlebotomy. Tissue samples can be analyzed for a wide number of epidemiologically important exposures. Beyond reflecting long-term energy balance, this tissue offers a relatively stable depot of triglyceride and fat-soluble substances, such as fat-soluble vitamins, and pesticides. As a tissue it represents the greatest reservoir of carotenoids in the body. Halogenated hydrocarbons may be measured in concentrations of hundreds-fold greater than those in blood of the same individuals. The composition of adipose tissue also reflects the long-term dietary intakes of a number of essential fatty acids. The turnover times of all of these substances in adipose tissue remain under-researched. Sampling and storage of adipose tissue, homogeneity of sampling sites, turnover times, and the effects of diet, age, gender, race, hormones, and disease on adipose tissue composition are discussed in this review of current knowledge about adipose tissue stability. Experience in the use of adipose tissue sampling in epidemiologic studies in various countries has shown that it is simple to conduct, requires little training, carries little risk, and does not result in excessive participant refusal.

Adipose Tissue as a Medium for Epidemiologic Exposure Assessment

Adipose Tissue as a Medium for Epidemiologic Exposure Assessment

Workshop Summary: Occupational Exposure Assessment: Investigating Why Exposure Measurements Vary

In recent years occupational exposure assessment has received increasing attention in the scientific literature. This attention has mainly been focused on exposure assessment in epidemiology. Recently, two important and widely recognized working group meetings have set the stage for retrospective exposure assessment in epidemiology. In Europe a so-called concerted action was completely devoted to retrospective exposure assessment in epidemiology. Almost all these activities focus on retrospective exposure assessment. As a consequence, so-called qualitative or semi-quantitative exposure estimation strategies receive most attention. Exposure monitoring and quantitative exposure estimation in epidemiology received little attention, while strategies are as underdeveloped as for other exposure assessment strategies. Therefore a workshop was organized at the First International Scientific Conference of the International Occupational Hygiene Association (Brussels, December 10, 1992) to establish the {open_quotes}state of the art{close_quotes} in research of quantitative occupational exposure assessment. Because underlying phenomenons that cause exposure variability are similar for epidemiological exposure assessment, compliance testing, and other strategies applied in occupational hygiene, discussion was not limited to epidemiology. 3 refs.

Exposure Assessment for Epidemiology and Hazard Control. Edited by S. M. Rappaport and Thomas J. Smith. Lewis Publishers, Inc., Chelsea, Michigan, 1991, 302 pages, $49.95 (within the U.S.); $59.95 (outside the U.S.)

Exposure Assessment for Epidemiology and Hazard Control. Edited by S. M. Rappaport and Thomas J. Smith. Lewis Publishers, Inc., Chelsea, Michigan, 1991, 302 pages, $49.95 (within the U.S.); $59.95 (outside the U.S.)

Exposure Assessment for Epidemiology: Characteristics of Exposure

Abstract Estimation of past exposures to potential health hazards is one of the most difficult problems for industrial hygiene research. Although it is very difficult, it is not impossible. There are two conceptual models that can guide the hygienist in this task: the source-receptor model and the task-TWA (time-weighted average) model of full-shift exposures. The source-receptor model is a formalization of the professional decision criteria used by hygienists in their initial assessments of a workplace to identify where hazards might exist and where to sample. Thus, by performing a detailed assessment of the nature of past operations, raw materials, and job activities, it is frequently possible to identify where exposures might have occurred and what agents might have been involved. The task-TWA model is useful for developing historical estimates of full-shift exposures by integrating information on changes in job activities with limited monitoring data. It is particularly useful for extrapolating TWA ex...

Exposure assessment for occupational epidemiology.

Exposure evaluation for epidemiology has special requirements, which can be derived from the pharmacological processes that determine the exposure-effect relationship. Since environmental concentrations of toxic agents typically are highly variable over time, the tissue concentrations they produce will vary over time, and consequently the level of effects will also vary over time. A general, six-step approach is proposed for developing an exposure assessment for an epidemiologic study. This approach uses pharmacologic models to guide the choice of exposure measurement parameters and to guide the epidemiologic data analysis. The approach is illustrated for evaluations of reversible airway effects of ozone and irreversible pulmonary effects of a mixed silica dust. Effect indices are introduced as a means of quantifying the temporal interrelationships of the exposure profiles and the pharmacologic models. These indices have advantages over both dose indices and simple dose-outcome models.