Monday, 28 February 2011 21:01

Exposure Assessment

Rate this item
(1 Vote)

The assessment of exposures is a critical step in identifying workplace hazards through epidemiological investigation. The exposure assessment process may be subdivided into a series of activities. These include:

  1. compiling an inventory of potentially toxic agents and mixtures present in the targeted work environment
  2. determining how exposures occur and how likely they are to vary among employees
  3. selecting appropriate measures or indices for quantifying exposures
  4. collecting data that will enable study participants to be assigned qualitative or quantitative exposure values for each measure. Whenever possible, these activities should be carried out under the guidance of a qualified industrial hygienist.


Occupational health studies are often criticized because of inadequacies in the assessment of exposures. Inadequacies may lead to differential or non-differential misclassification of exposure and subsequent bias or loss of precision in the exposure-effect analyses. Efforts to improve the situation are evidenced by several recent international conferences and texts devoted to this topic (ACGIH 1991; Armstrong et al. 1992; Proceedings of the Conference on Retrospective Assessment of Occupational Exposures in Epidemiology 1995). Clearly, technical developments are providing new opportunities for advancing exposure assessment. These developments include improvements in analytical instrumentation, a better understanding of pharmacokinetic processes, and the discovery of new biomarkers of exposure. Because occupational health studies often depend on historic exposure information for which no specific monitoring would have been undertaken, the need for retrospective exposure assessment adds an additional dimension of complexity to these studies. However, improved standards for assessment and for ensuring the reliability of such assessments continue to be developed (Siemiatycki et al. 1986). Prospective exposure assessments, of course, can be more readily validated.

The term exposure refers to the concentration of an agent at the boundary between individual and environment. Exposure is normally presumed when an agent is known to be present in a work environment and there is a reasonable expectation of employee contact with that agent. Exposures may be expressed as an 8-hour time-weighted-average (TWA) concentration, which is a measure of exposure intensity that has been averaged over an 8-hour work shift. Peak concentrations are intensities averaged over shorter time periods such as 15 minutes. Cumulative exposure is a measure of the product of average intensity and duration (e.g., a mean 8-hour TWA concentration multiplied by years worked at that mean concentration). Depending on the nature of the study and the health outcomes of interest, evaluation of peak, average intensity, cumulative or lagged exposures may be desirable.

By way of contrast, dose refers to the deposition or absorption of an agent per unit time. Dose or daily intake of an agent may be estimated by combining environmental measurement data with standard assumptions regarding, among other factors, breathing rates and dermal penetration. Alternatively, intake may be estimated based on biomonitoring data. Dose ideally would be measured at the target organ of interest.

Important exposure assessment factors include:

  1. identification of the relevant agents
  2. determination of their presence and concentrations in appropriate environmental media (e.g., air, contact surfaces)
  3. assessment of the likely routes of entry (inhalation, skin absorption, ingestion), the time course of exposure (daily variation), and cumulative duration of exposure expressed in weeks, months or years
  4. evaluation of the effectiveness of engineering and personal controls (e.g., use of protective clothing and respiratory protection may mediate exposures) and, finally
  5. host and other considerations that may modulate target organ concentrations.


These include the physical level of work activity and the prior health status of individuals. Special care should be taken in assessing exposure to agents that are persistent or tend to bioaccumulate (e.g., certain metals, radionuclides or stable organic compounds). With these materials, internal body burdens may increase insidiously even when environmental concentrations appear to be low.

While the situation can be quite complex, often it is not. Certainly, many valuable contributions to identifying occupational hazards have come from studies using common-sense approaches to exposure assessment. Sources of information that can be helpful in identifying and categorizing exposures include:

  1. employee interviews
  2. employer personnel and production records (these include work records, job descriptions, facility and process histories, and chemical inventories)
  3. expert judgement
  4. industrial hygiene records (area, personal, and compliance monitoring, and surface wipe samples, together with health hazard or comprehensive survey reports)
  5. interviews with long-term or retired employees and
  6. biomonitoring data.


There are several advantages to categorizing individual exposures in as much detail as possible. Clearly, the informativeness of a study will be enhanced to the extent that the relevant exposures have been adequately described. Secondly, the credibility of the findings may be increased because the potential for confounding can be addressed more satisfactorily. For example, referents and exposed individuals will differ as to exposure status, but may also differ relative to other measured and unmeasured explanatory factors for the disease of interest. However, if an exposure gradient can be established within the study population, it is less likely that the same degree of confounding will persist within exposure subgroups, thus strengthening the overall study findings.

Job Exposure Matrices

One of the more practical and frequently used approaches to exposure assessment has been to estimate exposures indirectly on the basis of job titles. The use of job exposure matrices can be effective when complete work histories are available and there is a reasonable constancy in both the tasks and exposures associated with the jobs under study. On the broadest scale, standard industry and job title groupings have been devised from routinely collected census data or occupational data provided on death certificates. Unfortunately, the information maintained in these large record systems is often limited to the “current” or “usual” occupation. Furthermore, because the standard groupings do not take into account the conditions present in specific workplaces, they must usually be regarded as crude exposure surrogates.

For community- and registry-based case-control studies, a more detailed exposure assessment has been achieved by utilizing expert opinion to translate job history data obtained through personal interview into semi-quantitative evaluations of likely exposures to specific agents (Siemiatycki et al. 1986). Experts, such as chemists and industrial hygienists, are chosen to assist in the exposure evaluation because of their knowledge and familiarity with various industrial processes. By combining the detailed questionnaire data with knowledge of industrial processes, this approach has been helpful in characterizing exposure differences across work facilities.

The job-exposure matrix approach has also been employed successfully in industry- and company-specific studies (Gamble and Spirtas 1976). Individual job histories (a chronological listing of past department and job assignments for each employee) are often retained in company personnel files and, when available, provide a complete job history for the employees while they are working at that facility. These data may be expanded upon through personal interviews of the study participants. The next step is to inventory all job titles and department or work area designations used during the study period. These may easily range into the hundreds or even thousands within large, multi-process facilities or across companies within an industry, when production, maintenance, research, engineering, plant support services and administrative jobs are all considered over time (often several decades), allowing for changes in industrial processes. Data consolidation can be facilitated by creating a computer file of all work history records and then using edit routines to standardize job title terminology. Those jobs involving relatively homogeneous exposures can be combined to simplify the process of linking exposures to individual jobs. However, the grouping of jobs and work locations should be supported wherever possible by measurement data collected according to a sound sampling strategy.

Even with computerized work histories, retrospective linkage of exposure data to individuals can be a difficult task. Certainly, workplace conditions will be altered as technologies change, product demand shifts, and new regulations are put in place. There may also be changes in product formulations and seasonal production patterns in many industries. Permanent records may be kept regarding some changes. However, it is less likely that records will be retained regarding seasonal and other marginal process and production changes. Employees also may be trained to perform multiple jobs and then be rotated among jobs as production demands change. All of these circumstances add complexity to the exposure profiles of employees. Nevertheless, there are also work settings that have remained relatively unchanged for many years. In the final analysis, each work setting must be evaluated in its own right.

Ultimately, it will be necessary to summarize the worklife exposure history of each person in a study. Considerable influence on the final exposure-effect measures of risk has been demonstrated (Suarez-Almazor et al. 1992), and hence great care has to be exercised in selecting the most appropriate summary measure of exposure.

Industrial Hygiene—Environmental Measurement

Monitoring of work exposures is a fundamental ongoing activity in protecting employee health. Thus, industrial hygiene records may already exist at the time an epidemiological study is being planned. If so, these data should be reviewed to determine how well the target population has been covered, how many years of data are represented in the files, and how easily the measurements can be linked to jobs, work areas and individuals. These determinations will be helpful both in assessing the feasibility of the epidemiological study and in identifying data gaps that could be remedied with additional exposure sampling.

The issue of how best to link measurement data to specific jobs and individuals is a particularly important one. Area and breathing zone sampling may be helpful to industrial hygienists in identifying emission sources for corrective actions, but could be less useful in characterizing actual employee exposures unless careful time studies of employee work activities have been performed. For example, continuous area monitoring may identify excursion exposures at certain times in the day, but the question remains as to whether or not employees were in the work area at that time.

Personal sampling data generally provide more accurate estimates of employee exposure as long as the sampling is carried out under representative conditions, the use of personal protective gear is properly taken into account, and the job tasks and process conditions are relatively constant from day to day. Personal samples may be readily linked to the individual employee through the use of personal identifiers. These data may be generalized to other employees in the same jobs and to other time periods as warranted. However, based on their own experience, Rappaport et al. (1993) have cautioned that exposure concentrations may be highly variable even among employees assigned to what are considered homogeneous exposure groups. Again, expert judgement is needed in deciding whether or not homogeneous exposure groups can be presumed.

Researchers have successfully combined a job-exposure matrix approach with utilization of environmental measurement data to estimate exposures within the cells of the matrix. When measurement data are found to be lacking, it may be possible to fill in data gaps through the use of exposure modelling. Generally, this involves developing a model for relating environmental concentrations to more easily assessed determinants of exposure concentrations (e.g., production volumes, physical characteristics of the facility including the use of exhaust ventilation systems, agent volatility and nature of the work activity). The model is constructed for work settings with known environmental concentrations and then used to estimate concentrations in similar work settings lacking measurement data but having information on such parameters as constituent ingredients and production volumes. This approach may be particularly helpful for the retrospective estimation of exposures.

Another important assessment issue is the handling of exposure to mixtures. First, from an analytic viewpoint, separate detection of chemically related compounds and elimination of interferences from other substances present in the sample may not be within the capability of the analytic procedure. The various limitations in the analytic procedures used to provide measurement data need to be evaluated and the study objectives modified accordingly. Secondly, it may be that certain agents are almost always used together and hence occur in approximately the same relative proportions throughout the work environment under study. In this situation, internal statistical analyses per se will not be useful in distinguishing whether or not effects are due to one or the other agents or due to a combination of the agents. Such judgements would only be possible based on review of external studies in which the same agent combinations had not occurred. Finally, in situations where different materials are used interchangeably depending on product specifications (e.g., the use of different colourants to obtain desired colour contrasts), it may be impossible to attribute effects to any specific agent.

Biological Monitoring

Biomarkers are molecular, biochemical or cellular alterations that can be measured in biological media such as human tissue, cells or fluids. A primary reason for developing biomarkers of exposure is to provide an estimate of internal dose for a particular agent. This approach is especially useful when multiple routes of exposure are likely (e.g., inhalation and skin absorption), when protective gear is worn intermittently, or when the conditions of exposure are unpredictable. Biomonitoring can be especially advantageous when the agents of interest are known to have relatively long biological half-lives. From a statistical perspective, an advantage of biological monitoring over air monitoring may be seen with agents having a half-life as short as ten hours, depending upon the degree of environmental variability (Droz and Wu 1991). The exceedingly long half-lives of materials such as chlorinated dioxins (measured in years) make these compounds ideal candidates for biological monitoring. As with analytical methods for measuring air concentrations, one must be aware of potential interferences. For example, before utilizing a particular metabolite as a biomarker, it should be determined whether or not other common substances, such as those contained in certain medications and in cigarette smoke, could be metabolized to the same end point. In general, basic knowledge of the pharmacokinetics of an agent is needed before biological monitoring is utilized as a basis for exposure assessment.

The most frequent points of measurement include alveolar air, urine and blood. Alveolar air samples may be helpful in characterizing high short-term solvent exposures that have occurred within minutes or hours of when the sample was collected. Urinary samples are typically collected to determine excretion rates for metabolites of the compound of interest. Blood samples may be collected for direct measurement of the compound, for measurement of metabolites, or for determination of protein or DNA adducts (e.g., albumin or haemoglobin adducts, and DNA adducts in circulating lymphocytes). Accessible tissue cells, such as epithelial cells from the buccal area of the mouth, may also be sampled for identification of DNA adducts.

Determination of cholinesterase activity in red blood cells and plasma exemplifies the use of biochemical alterations as a measure of exposure. Organophosphorus pesticides inhibit cholinesterase activity and hence measurement of that activity before and after likely exposure to these compounds can be a useful indicator of exposure intensity. However, as one progresses along the spectrum of biological alterations, it becomes more difficult to distinguish between biomarkers of exposure and those of effect. In general, effect measures tend to be non-specific for the substance of interest and, therefore, other potential explanations of the effect may need to be assessed in order to support using that parameter as an exposure measure. Exposure measures should either be directly tied to the agent of interest or there should be a sound basis for linking any indirect measure to the agent. Despite these qualifications, biological monitoring holds much promise as a means for improving exposure assessment in support of epidemiological studies.


In making comparisons in occupational epidemiology studies, the need is to have a group of workers with exposure to compare against a group of workers without exposure. Such distinctions are crude, but can be helpful in identifying problem areas. Clearly, however, the more refined the measure of exposure, the more useful will be the study, specifically in terms of its ability to identify and develop appropriately targeted intervention programmes.



Read 5027 times Last modified on Tuesday, 26 July 2022 19:11

" DISCLAIMER: The ILO does not take responsibility for content presented on this web portal that is presented in any language other than English, which is the language used for the initial production and peer-review of original content. Certain statistics have not been updated since the production of the 4th edition of the Encyclopaedia (1998)."


Epidemiology and Statistics References

Ahlbom, A. 1984. Criteria of causal association in epidemiology. In Health, Disease, and Causal Explanations in Medicine, edited by L Nordenfelt and BIB Lindahl. Dordrecht: D Reidel.

American Conference of Government Industrial Hygienists (ACGIH). 1991. Exposure Assessment for Epidemiology and Hazard Control, edited by SM Rappaport and TJ Smith. Chelsea, Mich.:Lewis.

Armstrong, BK, E White, and R Saracci. 1992. Principles of Exposure Measurement in Epidemiology. Oxford: Oxford Univ. Press.

Ashford, NA, CI Spadafor, DB Hattis, and CC Caldart. 1990. Monitoring the Worker for Exposure and Disease. Baltimore: Johns Hopkins Univ. Press.

Axelson, O. 1978. Aspects on confounding in occupational health epidemiology. Scand J Work Environ Health 4:85-89.

—. 1994. Some recent developments in occupational epidemiology. Scand J Work Environ Health 20 (Special issue):9-18.

Ayrton-Paris, JA. 1822. Pharmacologia.

Babbie, E. 1992. The Practice of Social Research. Belmont, Calif.: Wadsworth.

Beauchamp, TL, RR Cook, WE Fayerweather, GK Raabe, WE Thar, SR Cowles, and GH Spivey. 1991. Ethical Guidelines for Epidemiologists. J Clin Epidemiol 44 Suppl. I:151S-169S.

Bell, B. 1876. Paraffin epithelioma of the scrotum. Edinburgh Med J 22:135.

Blondin, O and C Viau. 1992. Benzo(a)pyrene-blood protein adducts in wild woodchucks used as biological sentinels of environmental polycyclic aromatic hydrocarbons contamination. Arch Environ Contam Toxicol 23:310-315.

Buck, C. 1975. Popper’s philosophy for epidemiologists. Int J Epidemiol 4:159-168.

Case, RAM and ME Hosker. 1954. Tumour on the urinary bladder as an occupational disease in the rubber industry in England and Wales. Brit J Prevent Soc Med 8:39-50.

Checkoway, H, NE Pearce, and DJ Crawford-Brown. 1989. Research Methods in Occupational Epidemiology. New York: Oxford Univ. Press.

Clayson, DB. 1962. Chemical Carcinogenesis. London: JA Churchill.

Clayton, D. 1992. Teaching statistical methods in epidemiology. In Epidemiology. What You Should Know and What You Could Do, edited by J Olsen and D Trichopoulos. Oxford: Oxford Univ. Press.

Clayton, D and M Hills. 1993. Statistical Models in Epidemiology. New York: Oxford Univ. Press.

Cornfield, J. 1954. Statistical relationships and proof in medicine. Am Stat 8:19-21.

Council for International Organizations of Medical Sciences (CIOMS). 1991. International Guidelines for Ethical Review of Epidemiologic Studies. Geneva: CIOMS.

Czaja, R and J Blair. 1996. Designing Surveys. Thousand Oaks, Calif: Pine Forge Press.

Doll, R. 1952. The causes of death among gas-workers with special reference to cancer of the lung. Brit J Ind Med 9:180-185.

—. 1955. Mortality from lung cancer in asbestos workers. Brit J Ind Med 12:81-86.

Droz, PO and MM Wu. 1991. Biological monitoring strategies. In Exposure Assessment for Epidemiology and Hazard Control, edited by SM Rappaport and TJ Smith. Chelsea, Mich.: Lewis.

Gamble, J and R Spirtas. 1976. Job classification and utilization of complete work histories in occupational epidemiology. J Med 18:399-404.

Gardner, MJ and DG Altman. 1989. Statistics With Confidence. Confidence Intervals and Statistical Guidelines. London: BMJ Publishing House.

Garfinkel, L. 1984. Classics in oncology; E. Cuyler Hammond, ScD. Ca-Cancer Journal for Clinicians. 38(1): 23-27

Giere, RN. 1979. Understanding Scientific Reasoning. New York: Holt Rinehart & Winston.

Glickman, LT. 1993. Natural exposure studies in pet animals: Sentinels for environmental carcinogens. Vet Can Soc Newslttr 17:5-7.

Glickman, LT, LM Domanski, TG Maguire, RR Dubielzig, and A Churg. 1983. Mesothelioma in pet dogs associated with exposure of their owners to asbestos. Environmental Research 32:305-313.

Gloyne, SR. 1935. Two cases of squamous carcinoma of the lung occurring in asbestosis. Tubercle 17:5-10.

—. 1951. Pneumoconiosis: Histological survey of necropsy material in 1,205 cases. Lancet 1:810-814.

Greenland, S. 1987. Quantitative methods in the review of epidemiological literature. Epidemiol Rev 9:1-30.

—. 1990. Randomization, statistics, and causal inference. Epidemiology 1:421-429.

Harting, FH and W Hesse. 1879. Der Lungenkrebs, die bergkrankheit in den Schneeberger Gruben. Vierteljahrsschr Gerichtl Med Offentl Gesundheitswesen CAPS 30:296-307.

Hayes, RB, JW Raatgever, A de Bruyn, and M Gerin. 1986. Cancer of the nasal cavity and paranasal sinuses, and formaldehyde exposure. Int J Cancer 37:487-492.

Hayes, HM, RE Tarone, HW Casey, and DL Huxsoll. 1990. Excess of seminomas observed in Vietnam service US military working dogs. J Natl Cancer Inst 82:1042-1046.

Hernberg, S. 1992. Introduction to Occupational Epidemiology. Chelsea, Mich.: Lewis.
Hill, AB. 1965. The environment and disease: Association or causation? Proc Royal Soc Med 58:295-300.

Hume, D. 1978. A Treatise of Human Nature. Oxford: Clarendon Press.

Hungerford, LL, HL Trammel, and JM Clark. 1995. The potential utility of animal poisoning data to identify human exposure to environmental toxins. Vet Hum Toxicol 37:158-162.

Jeyaratnam, J. 1994. Transfer of hazardous industries. In Occupational Cancer in Developing Countries, edited by NE Pearce, E Matos, H Vainio, P Boffetta, and M Kogevinas. Lyon: IARC.

Karhausen, LR. 1995. The poverty of Popperian epidemiology. Int J Epidemiol 24:869-874.

Kogevinas, M, P Boffetta, and N Pearce. 1994. Occupational exposure to carcinogens in developing countries. In Occupational Cancer in Developing Countries, edited by NE Pearce, E Matos, H Vainio, P Boffetta, and M Kogevinas. Lyon: IARC.

LaDou, J. 1991. Deadly migration. Tech Rev 7:47-53.

Laurell, AC, M Noriega, S Martinez, and J Villegas. 1992. Participatory research on workers’ health. Soc Sci Med 34:603-613.

Lilienfeld, AM and DE Lilienfeld. 1979. A century of case-control studies: progress? Chron Dis 32:5-13.

Loewenson, R and M Biocca. 1995. Participatory approaches in occupational health research. Med Lavoro 86:263-271.

Lynch, KM and WA Smith. 1935. Pulmonary asbestosis. III Carcinoma of lung in asbestos-silicosis. Am J Cancer 24:56-64.

Maclure, M. 1985. Popperian refutation in epidemiolgy. Am J Epidemiol 121:343-350.

—. 1988. Refutation in epidemiology: Why else not? In Causal Inference, edited by KJ Rothman. Chestnut Hill, Mass.: Epidemiology Resources.

Martin, SW, AH Meek, and P Willeberg. 1987. Veterinary Epidemiology. Des Moines: Iowa State Univ. Press.

McMichael, AJ. 1994. Invited commentary -"Molecular epidemiology": New pathway or new travelling companion? Am J Epidemiol 140:1-11.

Merletti, F and P Comba. 1992. Occupational epidemiology. In Teaching Epidemiology. What You Should Know and What You Could Do, edited by J Olsen and D Trichopoulos. Oxford: Oxford Univ. Press.

Miettinen, OS. 1985. Theoretical Epidemiology. Principles of Occurrence Research in Medicine. New York: John Wiley & Sons.

Newell, KW, AD Ross, and RM Renner. 1984. Phenoxy and picolinic acid herbicides and small-intestinal adenocarcinoma in sheep. Lancet 2:1301-1305.

Olsen, J, F Merletti, D Snashall, and K Vuylsteek. 1991. Searching for Causes of Work-Related Diseases. An Introduction to Epidemiology At the Work Site. Oxford: Oxford Medical Publications, Oxford Univ. Press.

Pearce, N. 1992. Methodological problems of time-related variables in occupational cohort studies. Rev Epidmiol Med Soc Santé Publ 40 Suppl: 43-54.

—. 1996. Traditional epidemiology, modern epidemiology and public health. Am J Public Health 86(5): 678-683.

Pearce, N, E Matos, H Vainio, P Boffetta, and M Kogevinas. 1994. Occupational cancer in developing countries. IARC Scientific Publications, no. 129. Lyon: IARC.

Pearce, N, S De Sanjose, P Boffetta, M Kogevinas, R Saracci, and D Savitz. 1995. Limitations of biomarkers of exposure in cancer epidemiology. Epidemiology 6:190-194.

Poole, C. 1987. Beyond the confidence interval. Am J Public Health 77:195-199.

Pott, P. 1775. Chirurgical Observations. London: Hawes, Clarke & Collins.

Proceedings of the Conference on Retrospective Assessment of Occupational Exposures in Epidemiology, Lyon, 13-15 April, 1994. 1995. Lyon: IARC .

Ramazzini, B. 1705. De Morbis Artificum Diatriva. Typis Antonii Capponi. Mutinae, MDCC. London: Andrew Bell & Others.

Rappaport, SM, H Kromhout, and E Symanski. 1993. Variation of exposure between workers in homogeneous exposure groups. Am Ind Hyg Assoc J 54(11):654-662.

Reif, JS, KS Lower, and GK Ogilvie. 1995. Residential exposure to magnetic fields and risk of canine lymphoma. Am J Epidemiol 141:3-17.

Reynolds, PM, JS Reif, HS Ramsdell, and JD Tessari. 1994. Canine exposure to herbicide-treated lawns and urinary excretion of 2,4-dichlorophenoxyacetic acid. Canc Epidem, Biomark and Prevention 3:233-237.

Robins, JM, D Blevins, G Ritter, and M Wulfsohn. 1992. G-estimation of the effect of prophylaxis therapy for pneumocystis carinii pneumonia on the survival of Aids patients. Epidemiology 3:319-336.

Rothman, KJ. 1986. Modern Epidemiology. Boston: Little, Brown & Co.

Saracci, R. 1995. Epidemiology: Yesterday, today, tomorrow. In Lectures and Current Topics in Epidemiology. Florence: European Educational Programme in Epidemiology.

Schaffner, KF. 1993. Discovery and Explanation in Biology and Medicine. Chicago: Univ. of Chicago Press.

Schlesselman, JJ. 1987. “Proof” of cause and effect in epidemiologic studies: Criteria for judgement. Prevent Med 16:195-210.

Schulte, P. 1989. Interpretation and communcication of the results of medical field investigations. J Occup Med 31:5889-5894.

Schulte, PA, WL Boal, JM Friedland, JT Walker, LB Connally, LF Mazzuckelli, and LJ Fine. 1993. Methodological issues in risk communications to workers. Am J Ind Med 23:3-9.

Schwabe, CW. 1993. The current epidemiological revolution in veterinary medicine. Part II. Prevent Vet Med 18:3-16.

Seidman, H, IJ Selikoff, and EC Hammond. 1979. Short-term asbestos work exposure and long-term observation. Ann NY Acad Sci 330:61-89.

Selikoff, IJ, EC Hammond, and J Churg. 1968. Asbestos exposure, smoking and neoplasia. JAMA 204:106-112.

—. 1964. Asbestos exposure and neoplasia. JAMA 188, 22-26.

Siemiatycki, J, L Richardson, M Gérin, M Goldberg, R Dewar, M Désy, S Campbell, and S Wacholder. 1986. Associations between several sites of cancer and nine organic dusts: Results from an hypothesis-generating case-control study in Montreal, 1979-1983. Am J Epidemiol 123:235-249.

Simonato, L. 1986. Occupational cancer risk in developing countries and priorities for epidemiological research. Presented at International Symposium On Health and Environment in Developing Countries, Haicco.

Smith, TJ. 1987. Exposure asssessment for occupational epidemiology. Am J Ind Med 12:249-268.

Soskolne, CL. 1985. Epidemiological research, interest groups, and the review process. J Publ Health Policy 6(2):173-184.

—. 1989. Epidemiology: Questions of science, ethics, morality and law. Am J Epidemiol 129(1):1-18.

—. 1993. Introduction to misconduct in science and scientific duties. J Expos Anal Environ Epidemiol 3 Suppl. 1:245-251.

Soskolne, CL, D Lilienfeld, and B Black. 1994. Epidemiology in legal proceedings in the United States. In The Identification and Control of Environmental and Occupational Diseases. Advances in Modern Environmental Toxicology: Part 1, edited by MA Mellman and A Upton. Princeton: Princeton Scientific Publishing.

Stellman, SD. 1987. Confounding. Prevent Med 16:165-182.

Suarez-Almazor, ME, CL Soskolne, K Fung, and GS Jhangri. 1992. Empirical assessment of the effect of different summary worklife exposure measures on the estimation of risk in case-referent studies of occupational cancer. Scand J Work Environ Health 18:233-241.

Thrusfield, MV. 1986. Veterinary Epidemiology. London: Butterworth Heinemann.

Trichopoulos, D. 1995. Accomplishments and prospects of epidemiology. In Lectures and Current Topics in Epidemiology. Florence: European Educational Programme in Epidemiology.

Van Damme, K, L Cateleyn, E Heseltine, A Huici, M Sorsa, N van Larebeke, and P Vineis. 1995. Individual susceptibility and prevention of occupational diseases: scientific and ethical issues. J Exp Med 37:91-99.

Vineis, P. 1991. Causality assessment in epidemiology. Theor Med 12:171-181.

Vineis, P. 1992. Uses of biochemical and biological markers in occupational epidemiology. Rev Epidmiol Med Soc Santé Publ 40 Suppl 1: 63-69.

Vineis, P and T Martone. 1995. Genetic-environmental interactions and low-level exposure to carcinogens. Epidemiology 6:455-457.

Vineis, P and L Simonato. 1991. Proportion of lung and bladder cancers in males resulting from occupation: A systematic approach. Arch Environ Health 46:6-15.

Vineis, P and CL Soskolne. 1993. Cancer risk assessment and management: An ethical perspective. J Occup Med 35(9):902-908.

Vineis, P, H Bartsch, N Caporaso, AM Harrington, FF Kadlubar, MT Landi, C Malaveille, PG Shields, P Skipper, G Talaska, and SR Tannenbaum. 1994. Genetically based N-acetyltransferase metabolic polymorphism and low level environmental exposure to carcinogens. Nature 369:154-156.

Vineis, P, K Cantor, C Gonzales, E Lynge, and V Vallyathan. 1995. Occupational cancer in developed and developing countries. Int J Cancer 62:655-660.

Von Volkmann, R. 1874. Ueber Theer-und Russkrebs. Klinische Wochenschrift 11:218.

Walker, AM and M Blettner. 1985. Comparing imperfect measures of exposure. Am J Epidemiol 121:783-790.

Wang, JD. 1991. From conjectures and refutation to the documentation of occupational diseases in Taiwan. Am J Ind Med 20:557-565.

—. 1993. Use of epidemiologic methods in studying diseases caused by toxic chemicals. J Natl Publ Health Assoc 12:326-334.

Wang, JD, WM Li, FC Hu, and KH Fu. 1987. Occupational risk and the development of premalignant skin lesions among paraquat manufacturers. Brit J Ind Med 44:196-200.

Weed, DL. 1986. On the logic of causal inference. Am J Epidemiol 123:965-979.

—. 1988. Causal criteria and popperian refutation. In Causal Inference, edited by KJ Rothman. Chestnut Hill, Mass.: Epidemiology Resources.

Wood, WB and SR Gloyne. 1930. Pulmonary asbestosis. Lancet 1:445-448.

Wyers, H. 1949. Asbestosis. Postgrad Med J 25:631-638.