Geographic variations of multiple sclerosis in France.
ABSTRACT France is located in an area with a medium to high prevalence of multiple sclerosis, where its epidemiology is not well known. We estimated the national and regional prevalence of multiple sclerosis in France on 31 October 2004 and the incidence between 31 October 2003 and 31 October 2004 based on data from the main French health insurance system: the Caisse Nationale d'Assurance Maladie des Travailleurs Salariés. The Caisse Nationale d'Assurance Maladie des Travailleurs Salariés insures 87% of the French population. We analysed geographic variations in the prevalence and incidence of multiple sclerosis in France using the Bayesian approach. On the 31 October 2004, 49 417 people were registered with multiple sclerosis out of the 52 359 912 insured with the Caisse Nationale d'Assurance Maladie des Travailleurs Salariés. Among these, 4497 were new multiple sclerosis cases declared between 31 October 2003 and 31 October 2004. After standardization for age, total multiple sclerosis prevalence in France was 94.7 per 100,000 (94.3-95.1); 130.5 (129.8-131.2) in females and 54.8 (54.4-55.3) in males. The national incidence of multiple sclerosis between 31 October 2003 and 31 October 2004 was 7.5 per 100,000 (7.3-7.6); 10.4 (10.2-10.6) in females and 4.2 (4.0-4.3) in males. The prevalence and incidence of multiple sclerosis were higher in North-Eastern France, but there was no obvious North-South gradient. This study is the first performed among a representative population of France (87%) using the same method throughout. The Bayesian approach, which takes into account spatial heterogeneity among geographical units and spatial autocorrelation, did not confirm the existence of a prevalence gradient but only a higher prevalence of multiple sclerosis in North-Eastern France and a lower prevalence of multiple sclerosis in the Paris area and on the Mediterranean coast.
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ABSTRACT: In this paper we discuss a number of issues that are pertinent to the analysis of disease mapping data. As an illustrative example we consider the mapping of larynx cancer across electoral wards in the North West Thames region of the U.K. Bayesian hierarchical models are now frequently employed to carry out such mapping. In a typical situation, a three-stage hierarchical model is specified in which the data are modelled as a function of area-specific relative risks at stage one; the collection of relative risks across the study region are modelled at stage two; and at stage three prior distributions are assigned to parameters of the stage two distribution. Such models allow area-specific disease relative risks to be 'smoothed' towards global and/or local mean levels across the study region. However, these models contain many structural and functional assumptions at different levels of the hierarchy; we aim to discuss some of these assumptions and illustrate their sensitivity. When relative risks are the endpoint of interest, it is common practice to assume that, for each of the age-sex strata of a particular area, there is a common multiplier (the relative risk) acting upon each of the stratum-specific risks in that area; we will examine this proportionality assumption. We also consider the choices of models and priors at stages two and three of the hierarchy, the effect of outlying areas, and an assessment of the level of smoothing that is being carried out. For inference, we concentrate on the description of the spatial variability in relative risks and on the association between the relative risks of larynx cancer and an area-level measure of socio-economic status.Statistics in Medicine 01/2000; 19(17-18):2493-519. · 2.04 Impact Factor
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ABSTRACT: State of the artAccording to the available previous studies, France is considered a zone of medium to high risk of multiple sclerosis (MS) with an estimated overall prevalence of at least 50/100,000 inhabitants, incidence rates were stable in some areas but increased over time in others and a strong ethnic effect on the incidence, clinical presentation, and course of MS is reported.ResultsBased on two health insurance survey the prevalence has been deduced. At January 1, 2003 from the data of agricultural health insurance the prevalence is evaluated at 65.5/100,000 inhabitants (95p.cent CI=62.5-67.5) with a gradient of North East towards South-West. The data from the national health insurance were very near. During the period 2000-2004, recent studies in Auvergne and Brittany demonstrated an annual incidence comprising between 4.2 and 5.1 per 100,000 inhabitants. In Lorraine, in a large population-based study, in December 31, 2004 the prevalence rate was 120/100,000 (95p.cent CI: 119 to 121). During the period 1990-2002, the average age- and sex-adjusted annual incidence rate was 5.5/100,000 (95p.cent CI: 4.4-6.6). In Lorraine, we found that the age-adjusted incidence rate increased during the period 1990-2002. The incidence of MS in women increased, whereas that in men did not change significantly during this period. Similarly, in Norway, North Ireland and Denmark, the incidence among women increased the most. The clinical features of MS were compared in 211 North Africans patients and 2 945 Europeans patients in two French MS centres (Lorraine and Nice) with definite MS according to McDonald's criteria. The course of MS appears more aggressive in North Africans than in Europeans patients. For example, we demonstrated a shorter time to reach the Expanded Disability Status Scale score of 4.0 (p=0.001) or 6.0 (p<0.0001) in North Africans patients.Perspectives and conclusionsThe incidence rates found in these studies were comparable to those reported in several European populations. This undoubtedly places France in the category of regions with a high risk zone of MS. The incidence of MS in women increased; thus, exogenous (or epigenetic) factors vary over time and may affect men and women differently. The course of MS appears more aggressive in North Africans than in Europeans patients.Revue Neurologique 01/2007; 163:637-645. · 0.51 Impact Factor
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ABSTRACT: There has been much recent interest in Bayesian image analysis, including such topics as removal of blur and noise, detection of object boundaries, classification of textures, and reconstruction of two- or three-dimensional scenes from noisy lower-dimensional views. Perhaps the most straightforward task is that of image restoration, though it is often suggested that this is an area of relatively minor practical importance. The present paper argues the contrary, since many problems in the analysis of spatial data can be interpreted as problems of image restoration. Furthermore, the amounts of data involved allow routine use of computer intensive methods, such as the Gibbs sampler, that are not yet practicable for conventional images. Two examples are given, one in archeology, the other in epidemiology. These are preceded by a partial review of pixel-based Bayesian image analysis.Annals of the Institute of Statistical Mathematics 02/1991; 43(1):1-20. · 0.74 Impact Factor