Exposure assessment in epidemiology: Does gender matter?

BACKGROUND: 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?" METHODS: 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. RESULTS AND CONCLUSIONS: 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.     

Modeling correlated data in epidemiology: mixed or marginal model?

Correlated observations (within centers, families, subjects,.) are common in epidemiology. Even when one is only interested in the modeling of means according to risk factors, it is also necessary to model the variance-covariance matrix of the observations in order to make correct inferences on the parameters of interest. All the more so when the aim of the survey is the measurement of these correlations or of the variance of the random effects from which they are assumed to originate. We discuss, within the framework of the linear and of the logistic models, the implications of two choices for the modeling of covariances. The mixed model shows the unobserved elements responsible for the similarity between certain observations. In a longitudinal survey, for instance, one can use a random effect, specific to each subject, expressing how much a subject's trajectory is translated as compared to what is expected according to its characteristics (age, sex,.). The marginal approach leads to modeling separately the means and the covariance matrix of the observations. The distinction between these two approaches is important for non linear models, in particular the logistic one. We insist on the interconnection between a mixed model formulation and a marginal one, as well as on the implication of the choice in terms of the parameters' interpretation.     

Web-based questionnaires: the future in epidemiology?

The traditional epidemiologic modes of data collection, including paper-and-pencil questionnaires and interviews, have several limitations, such as decreasing response rates over the last decades and high costs in large study populations. The use of Web-based questionnaires may be an attractive alternative but is still scarce in epidemiologic research because of major concerns about selective nonresponse and reliability of the data obtained. The authors discuss advantages and disadvantages of Web-based questionnaires and current developments in this area. In addition, they focus on some practical issues and safety concerns involved in the application of Web-based questionnaires in epidemiologic research. They conclude that many problems related to the use of Web-based questionnaires have been solved or will most likely be solved in the near future and that this mode of data collection offers serious benefits. However, questionnaire design issues may have a major impact on response and completion rates and on reliability of the data. Theoretically, Web-based questionnaires could be considered an alternative or complementary mode in the range of epidemiologic methods of data collection. Practice and comparisons with the traditional survey techniques should reveal whether they can fulfill their expectations.     

Is there epidemiology in Russia?

OBJECTIVE: To examine the current state of epidemiology in Russia. DESIGN: The structure of clinical research and statistical methods was used to shed light on the epidemiology in Russia. The frequencies of specific study designs were evaluated using Medline data for 1970-1997. To determine the proportion of advanced design clinical studies the frequency of cohort, prospective, follow up, or longitudinal studies, and controlled trials was evaluated. All diagnosis related studies were found to determine the usage of advanced statistical technique (ROC analysis). The adequacy of Medline information was checked by hand search of journals. All dissertations in epidemiology defended in Russia in 1995 and 1996 were evaluated for their methodology. The curriculum recommended by Ministry of Health to Medical Universities was evaluated. Available literature and library indexing of epidemiological terms examined. MAIN RESULTS: Russian medical research uses less frequently advanced study designs and methods of data analysis. Medical students are taught epidemiology as a science of spread of infectious diseases. There is no department of epidemiology in Russian universities where epidemiology is taught in the modern sense and no epidemiological and biostatistical periodicals available in Russia. CONCLUSION: Epidemiology in Russia remains in an archaic state of science of the spread of infectious diseases and it is detrimental to methodology of medical research in Russia.     

Weight of the evidence or wait for the evidence? Protecting underground miners from diesel particulate matter

A coalition of mine operators has used a variety of tactics to obstruct scientific inquiry and impede public health action designed to protect underground miners from diesel particulate matter. These workers are exposed to the highest level of diesel particulate matter compared with any other occupational group.This case study profiles a decade-long saga of the Methane Awareness Resource Group Diesel Coalition to impede epidemiological studies on diesel exhaust undertaken by the National Institute for Occupational Safety and Health and the National Cancer Institute, and to derail a health standard promulgated by the Mine Safety and Health Administration. The case study highlights the coalition's mastery of legislative, judicial, and executive branch operations and the reaction of policymakers.     

Atmospheric particulate matter and ozone under heat-wave conditions: do they cause an increase of mortality in Croatia?

In August 2003 Croatia experienced a heat-wave period during which elevated concentrations of particulate matter (PM10) and ozone in ambient air were measured. By applying the model of Stedman and Rooney et al., it was shown that a significant part of excess mortality during this period can be attributed to PM10 and ozone in ambient air.