Reproducible epidemiologic research

The replication of important findings by multiple independent investigators is fundamental to the accumulation of scientific evidence. Researchers in the biologic and physical sciences expect results to be replicated by independent data, analytical methods, laboratories, and instruments. Epidemiologic studies are commonly used to quantify small health effects of important, but subtle, risk factors, and replication is of critical importance where results can inform substantial policy decisions. However, because of the time, expense, and opportunism of many current epidemiologic studies, it is often impossible to fully replicate their findings. An attainable minimum standard is "reproducibility," which calls for data sets and software to be made available for verifying published findings and conducting alternative analyses. The authors outline a standard for reproducibility and evaluate the reproducibility of current epidemiologic research. They also propose methods for reproducible research and implement them by use of a case study in air pollution and health.     

Georeferenced data in epidemiologic research

This paper reviews some conceptual and practical issues regarding the application of georeferenced data in epidemiologic research. Starting with the disease mapping tradition of geographical medicine, topics such as types of georeferenced data, implications for data analysis, spatial autocorrelation and main analytical approaches are heuristically discussed, relying on examples from the epidemiologic literature, most of them concerning mapping disease distribution, detection of disease spatial clustering, evaluation of exposure in environmental health investigation and ecological correlation studies. As for concluding remarks, special topics that deserve further development, including the misuses of the concept of space in epidemiologic research, issues related to data quality and confidentiality, the role of epidemiologic designs for spatial research, sensitivity analysis and spatiotemporal modeling, are presented.     

Biological markers in epidemiologic research

This paper identifies some of the issues relevant to the use of biological markers in epidemiologic research. Foremost among these are clarity of definitions and marker classification. Illustrations of markers in the categories of internal dose, biological effective dose, biological response, disease, and susceptibility are presented with a theoretical model for the interrelationship among these. Issues faced by epidemiologists in selecting markers for specific studies concern exposure complexity, marker specificity, marker persistence, time to appearance, and the use of target vs. surrogate biological media. Feasibility issues concern sample collection, transport, storage, and characteristics of the laboratory assay. The rationale for biological markers in epidemiologic research is strong in that markers have the potential for (1.) improving the accuracy of our "exposure variables," (2.) permitting the identification of preclinical disease and providing opportunities for prevention, (3.) allowing for more homogeneous and etiologically relevant classifications of disease, and (4.) enhancing our understanding of the biological processes leading to disease occurrence, thereby strengthening the interpretation of epidemiologic data and the theoretical framework from which we formulate research questions.     

Dermal exposure assessment in occupational epidemiologic research

Recognition of the importance of skin exposure in industrial settings has steadily increased over the last few decades. Unfortunately, the growing attention to dermal exposure in industrial hygiene has often not been reflected in the field of occupational epidemiology. An extensive literature survey was conducted to identify dermal exposure assessment methods that have been applied in epidemiologic studies. Subsequently, methodologies are postulated that could be applied to epidemiologic research. Attention is given to intensity, frequency, and duration of exposure, the exposed surface area, and personal, temporal and spatial variability in dermal exposure and uptake. It is anticipated that, in the near future, dermal exposure assessment in epidemiologic research will be based generally on expert judgment and to some degree on process-specific exposure models. Field studies collecting quantitative dermal exposure data and statistical modeling to identify exposure determinants will, however, be imperative if progress is to be made in the field of dermal exposure assessment for epidemiologic purposes.     

Musculoskeletal diseases--a continuing challenge for epidemiologic research

In this paper some quality issues of epidemiologic studies on work-related musculoskeletal diseases are discussed. The advantages and disadvantages of different types of epidemiologic studies are described, among them the rarely applied case-crossover design. Problems in the ascertainment of disease, as well as the assessment of exposure to physical load, are also brought up. The importance of understanding the pathomechanisms of the diseases under study is stressed.     

Reproductive epidemiologic research in developing countries.

This paper discusses the scientific rationale for carrying out reproductive epidemiologic research in developing countries, and the generalizability of results of research done in developed countries to developing countries. Practical problems encountered in doing research in developing countries include limited resources, overcommitted researchers, cost, and study monitoring. Cultural differences that affect the design and conduct of research activities in developing countries are also discussed.     

病因流行病学研究方法进展

流行病学是病因学研究的重要方法,病因学研究是流行病学研究的重要领域。由于面临的病因研究问题越来越复杂,促进了病因流行病学研究方法的快速发展。本文从病因概念与模型、混杂因素的控制、交互作用的研究、流行病学与组学研究的结合、分子病理学的概念与发展、病因判断标准这六个方面,对病因流行病学研究方法的进展做一全面总结。     

Uses of ecologic analysis in epidemiologic research.

Despite the widespread use of ecologic analysis in epidemiologic research and health planning, little attention has been given by health scientists and practitioners to the methodological aspects of this approach. This paper reviews the major types of ecologic study designs, the analytic methods appropriate for each, the limitations of ecologic data for making causal inferences and what can be done to minimize these problems, and the relative advantages of ecologic analysis. Numerous examples are provided to illustrate the important principles and methods. A careful distinction is made between ecologic studies that generate or test etiologic hypotheses and those that evaluate the impact of intervention programs or policies (given adequate knowledge of disease etiology). Failure to recognize this difference in the conduct of ecologic studies can lead to results that are not very informative or that are misinterpreted by others.     

Positional accuracy of geocoded addresses in epidemiologic research

BACKGROUND: Geographic information systems (GIS) offer powerful techniques for epidemiologists. Geocoding is an important step in the use of GIS in epidemiologic research, and the validity of epidemiologic studies using this methodology depends, in part, on the positional accuracy of the geocoding process. METHODS: We conducted a study comparing the validity of positions geocoded with a commercially available program to positions determined by Global Positioning System (GPS) satellite receivers. Addresses (N = 200) were randomly selected from a recently completed case-control study in Western New York State. We geocoded addresses using ArcView 3.2 on the GDT Dynamap/2000 U.S. Street database. In addition, we measured the longitude and latitude of these addresses with a GPS receiver. The distance between the locations obtained by these two methods was calculated for all addresses. RESULTS: The distance between the geocoded point and the GPS point was within 100 m for the majority of subject addresses (79%), with only a small proportion (3%) having a distance greater than 800 m. The overall median distance between GPS points and geocoded points was 38 m (90% confidence interval [CI] = 34-46). Distances were not different for cases and controls. Urban addresses (median = 32 m; CI = 28-37) were slightly more accurate than nonurban addresses (median = 52 m; CI = 44-61). CONCLUSIONS: This study indicates that the suitability of geocoding for epidemiologic research depends on the level of spatial resolution required to assess exposure. Although sources of error in positional accuracy for geocoded addresses exist, geocoding of addresses is, for the most part, very accurate.