Population Based Study of 12 Autoimmune Diseases in Sardinia, Italy: Prevalence and Comorbidity

BACKGROUND: The limited availability of prevalence data based on a representative sample of the general population, and the limited number of diseases considered in studies about co-morbidity are the critical factors in study of autoimmune diseases. This paper describes the prevalence of 12 autoimmune diseases in a representative sample of the general population in the South of Sardinia, Italy, and tests the hypothesis of an overall association among these diseases. METHODS: Data were obtained from 21 GPs. The sample included 25,885 people. Prevalence data were expressed with 95% Poisson C.I. The hypothesis of an overall association between autoimmune diseases was tested by evaluating the co-occurrence within individuals. RESULTS: Prevalence per 100,000 are: 552 rheumatoid arthritis, 124 ulcerative colitis, 15 Crohn's disease, 464 type 1 diabetes, 81 systemic lupus erythematosus, 124 celiac disease, 35 myasthenia gravis, 939 psoriasis/psoriatic arthritis, 35 systemic sclerosis, 224 multiple sclerosis, 31 Sjogren's syndrome, and 2,619 autoimmune thyroiditis. An overall association between autoimmune disorders was highlighted. CONCLUSIONS: The comparisons with prevalence reported in current literature do not show outlier values, except possibly for a few diseases like celiac disease and myasthenia gravis. People already affected by a first autoimmune disease have a higher probability of being affected by a second autoimmune disorder. In the present study, the sample size, together with the low overall prevalence of autoimmune diseases in the population, did not allow us to examine which diseases are most frequently associated with other autoimmune diseases. However, this paper makes available an adequate control population for future clinical studies aimed at exploring the co-morbidity of specific pairs of autoimmune disease

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Support of relationships among moving objects on networks

Efficient support of moving objects on networks is receiving increasing attention. An interesting issue is to analyze the interactions of objects within a network. In order to support queries related to the dynamic behaviour of two or more moving objects in conjunction, topological information must be maintained which relates the moving objects to the network as well as the moving objects among another. As typical application areas tend to generate large data volumes, an adequate storage representation and the resulting effort to evaluate such topological relationships are crucial in practice. To face that challenge, we propose a new representation model for moving objects, which enables a rather compact representation of both, information on the network and information on the moving objects on this network. This, in turn, allows to efficiently evaluate respective queries