Geographical Heterogeneity of Multiple Sclerosis Prevalence in France

Abstract

INTRODUCTION Geographical variation in the prevalence of multiple sclerosis (MS) is controversial. Heterogeneity is important to acknowledge to adapt the provision of care within the healthcare system. We aimed to investigate differences in prevalence of MS in departments in the French territory. METHODS We estimated MS prevalence on October 31, 2004 in 21 administrative departments in France (22% of the metropolitan departments) by using multiple data sources: the main French health insurance systems, neurologist networks devoted to MS and the Technical Information Agency of Hospitalization. We used a spatial Bayesian approach based on estimating the number of MS cases from 2005 and 2008 capture-recapture studies to analyze differences in prevalence. RESULTS The age- and sex-standardized prevalence of MS per 100,000 inhabitants ranged from 68.1 (95% credible interval 54.6, 84.4) in Hautes-Pyrénées (southwest France) to 296.5 (258.8, 338.9) in Moselle (northeast France). The greatest prevalence was in the northeast departments, and the other departments showed great variability. DISCUSSION By combining multiple data sources into a spatial Bayesian model, we found heterogeneity in MS prevalence among the 21 departments of France, some with higher prevalence than anticipated from previous publications. No clear explanation related to health insurance coverage and hospital facilities can be advanced. Population migration, socioeconomic status of the population studied and environmental effects are suspected.

DOI: 10.1371/journal.pone.0167556

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@inproceedings{Pivot2016GeographicalHO, title={Geographical Heterogeneity of Multiple Sclerosis Prevalence in France}, author={Diane Pivot and Marc Debouverie and Michel Grzebyk and David Brassat and Michel G Clanet and Pierre Clavelou and Christian Confavreux and Gilles Edan and Emmanuelle Leray and Thibault Moreau and Sandra Vukusic and Guy H{\'e}delin and Francis Guillemin}, booktitle={PloS one}, year={2016} }