BACKGROUND AND AIMS: Previous studies have reported a prevalence estimate of myasthenia gravis (MG) from 7.7 to 11.1 per 100,000 inhabitants in Europe. Moreover, the study of the geographical distribution of MG should be useful to generate specific hypotheses. The aims are to estimate MG prevalence and to investigate its geographical variation in a delimited area in Northern Italy. METHODS: The primary source of data was the MG database of the Neurological Institute of Pavia and all other sources of case collection in and outside the province. We adopted a Bayesian approach to analyze MG geographical variation within the finest geographical grid. RESULTS: We identified 119 live MG prevalent cases resident in the province of Pavia on December 31, 2008. The overall crude prevalence was 24 per 100,000 inhabitants. The Bayesian analysis identified a small cluster of higher MG prevalence in the northern area of the province. CONCLUSIONS: The estimated MG prevalence sets the province of Pavia among the high-risk areas. The identification of high/low MG risk areas deserves further investigation of genetic and environmental factors possibly related to a major risk of the disease in that area.
BACKGROUND AND AIMS: Previous studies have reported a prevalence estimate of myasthenia gravis (MG) from 7.7 to 11.1 per 100,000 inhabitants in Europe. Moreover, the study of the geographical distribution of MG should be useful to generate specific hypotheses. The aims are to estimate MG prevalence and to investigate its geographical variation in a delimited area in Northern Italy. METHODS: The primary source of data was the MG database of the Neurological Institute of Pavia and all other sources of case collection in and outside the province. We adopted a Bayesian approach to analyze MG geographical variation within the finest geographical grid. RESULTS: We identified 119 live MG prevalent cases resident in the province of Pavia on December 31, 2008. The overall crude prevalence was 24 per 100,000 inhabitants. The Bayesian analysis identified a small cluster of higher MG prevalence in the northern area of the province. CONCLUSIONS: The estimated MG prevalence sets the province of Pavia among the high-risk areas. The identification of high/low MG risk areas deserves further investigation of genetic and environmental factors possibly related to a major risk of the disease in that area.