Réflexions sur la médecine du travail en Suisse

International Journal of Public Health - La nouvelle ordonnance fédérale du 23 décembre 1960 relative à la prévention des maladies professionnelles constitue un...     

Contribution à l'épidémiologie de Cyclospora cayetanensis à partir d'une étude sur 12 mois réalisée sur l'eau de distribution à Hanoï (Viêt-Nam)

Summary-A new contribution to the epidemiological survey of Cyclospora cayetanensis in Hanoï water supplies (Viet-Nam); a 12-month longitudinal study. Cyclospora cayetanensis is a protozoan agent responsible for acute diarrheal diseases, frequently reported in inter-tropical areas. It affects the local population as well as travelers. A year-long epidemiological survey of public drinking water supplies was carried out in Hanoï, to determine if this pathogen was found in water, and if seasonal variation was noted. For this purpose, water samples were first examined by common microscope observation and then complete identification was confirmed by molecular biology assays based on PCR and sequencing. Cyclospora cayetanensis was found in water supplies and water taps in Hanoï, suggesting that drinking water is probably an important coccidial source of contamination.     

Épidémiologie des hémopathies malignes en Basse-Normandie

BackgroundThe study was designed to present the incidence of all the haematological malignancies in Basse-Normandie over the period 1997–2004. We extracted the data from the “Registre régional des hémopathies malignes de Basse-Normandie (RRHMBN)”, a French registry which belongs to the Association of the French Cancer Registries (FRANCIM). All the malignant haematological diseases were coded using the third edition of the International Classification for Oncologic Diseases (ICD-O-3) and the ADICAP classification, a special version adapted in 2001 for haematology. Five thousand five hundred and ten new cases of malignant haematological disorders were registered over the period 1997–2004. Whatever the department constituting the Basse-Normandie (Calvados, Manche and Orne), no significant difference of incidence was detected. In men, the more frequent malignant disorders were non-Hodgkin's malignant lymphomas (NHML) followed by chronic lymphocytic leukemia and other mature neoplasms, myelodysplastic syndromes (MDS), multiple myeloma (MM), myeloproliferative disorders (MPD), acute myeloid leukemias (AML), Hodgkin's lymphomas (HL), Waldenström's macroglobulinemia (WM) and acute lymphoblastic leukemia (ALL). In women, MM is the third more frequent haematological disorders after NHML and lymphocytic leukaemia and other mature neoplasms, MPD, MDS, AML, Hodgkin's lymphomas, WM and ALL. The other haematological disorders are very rare. We provide the incidence for the main haematological disorders and for the first time we also present the incidence of the different subtypes of the Hodgkin's and non-Hodgkin's malignant lymphomas, mature lymphoid neoplasms, MPD and also MDS. These results are useful for the organization and follow-up of medical care. The development of specialized haematology and active protocols can optimize the management of the older patients. A high quality of the collected data remains necessary for a continuous watching and research on patients with malignant haematological diseases.     

Approches d’analyse causale en épidémiologie

Epidemiological research is mostly based on observational studies. Whether such studies can provide evidence of causation remains discussed. Several causal analysis methods have been developed in epidemiology. This paper aims at presenting an overview of these methods: graphical models, path analysis and its extensions, and models based on the counterfactual approach, with a special emphasis on marginal structural models. Graphical approaches have been developed to allow synthetic representations of supposed causal relationships in a given problem. They serve as qualitative support in the study of causal relationships. The sufficient-component cause model has been developed to deal with the issue of multicausality raised by the emergence of chronic multifactorial diseases. Directed acyclic graphs are mostly used as a visual tool to identify possible confounding sources in a study. Structural equations models, the main extension of path analysis, combine a system of equations and a path diagram, representing a set of possible causal relationships. They allow quantifying direct and indirect effects in a general model in which several relationships can be tested simultaneously. Dynamic path analysis further takes into account the role of time. The counterfactual approach defines causality by comparing the observed event and the counterfactual event (the event that would have been observed if, contrary to the fact, the subject had received a different exposure than the one he actually received). This theoretical approach has shown limits of traditional methods to address some causality questions. In particular, in longitudinal studies, when there is time-varying confounding, classical methods (regressions) may be biased. Marginal structural models have been developed to address this issue. In conclusion, “causal models”, though they were developed partly independently, are based on equivalent logical foundations. A crucial step in the application of these models is the formulation of causal hypotheses, which will be a basis for all methodological choices. Beyond this step, statistical analysis tools recently developed offer new possibilities to delineate complex relationships, in particular in life course epidemiology.     

Une brève histoire du concept de biais en épidémiologie

BackgroundBias is a major methodological issue for epidemiology. However, only a few studies have been dedicated to the past and present formulations of the concept of bias. Moreover, the classical definition of bias as systematic deviation from the truth of results or inferences, definition which can be found in dictionaries of epidemiology, does not seem to either match the way epidemiologists use it in practice, or correspond to the different definitions given throughout its history. It is consequently important to elucidate this paradox.MethodsIn this historical and conceptual article, we study the different uses of the word “bias” in epidemiological literature, from classic articles in the 1950's about the link between smoking and lung cancer to the most recent epidemiology textbooks, the objective being to analyze the ways in which epidemiologists have defined, applied and modified this concept over time.ResultsWe show that D.L. Sackett's article on bias in analytic research, published in 1979, put an end, at least temporarily, to reflection in populational epidemiology that started thirty years before. More precisely, we show that Sackett's definition of bias corresponds more to the needs and goals of clinical epidemiology than to those of populational epidemiology. Concomitantly, populational epidemiologists such as K.J. Rothman redefined bias as a threat to the internal validity of a study, and epidemiological study as an “exercise in measurement of an effect rather than as a criterion-guided process for deciding whether an effect is present or not”.ConclusionIt is thereby important to draw a distinction between two notions pertaining to bias: an epidemiological concept of bias, viewed as the lack of internal validity of an observational study; and a medical concept of bias, defined as deviation from the truth. The former concerns the design and methodology of epidemiological studies; the latter is more general and impels epidemiologists and physicians to be skeptical, and even critical, towards their own inferences.