Abstract

GISPERT MAGAROLAS, Rosa et al. Prevalence of the Disability in Spain for Autonomous Communities: the Paper of the Individual Factors and the Geographical Environment in the Variability. Rev. Esp. Salud Publica [online]. 2009, vol.83, n.6, pp.821-834. ISSN 2173-9110.

Background: The prevalence of disability shows a high geographical variability and the identification of factors that could explain these variations can be usuful to the heath and social welfare planning. Here the analysis of disability variations among autonomous regions in Spain is made taking into account individual and geographical setting factors together. Methods: Data come from the Spanish Disability, Impairment and Health Status survey of 1999 and from Inebase both of the National Institute for Statistics. The prevalence of disability crude and adjusted by age was calculated for each autonomous region. Individual factors related to disability are identified by means of a logistic regression. The analysis accounting for both, individual and geographical setting factors was performed by means of a logistic regression of two levels. Results: Disability prevalence showed a maximum difference of 5.75 points among regions. In a logistic regression the region of residence was statistically significant (OR: 3.35 in the highest rated region related to the lowest) beside several individual factors: age (OR 40-64= 1,78 OR 65-79= 1,87 and OR >79= 3,34), sex (OR women= 0,66), working status (OR unemployment=2,25 OR housewife/student=1,39 y OR other=2,03), health status (OR regular= 1,69 OR bad/very bad= 2,05) and chronic diseases (OR 1-3=1,56 OR 4-6=1,82 OR >6=2,59). Individual factors accounted for a very few variance at the two levels regression model (s=0,261) and none of the regional variables improved the model. Conclusions: Individual factors do not explain enough the observed disability variations among the regions and none factor related to the geographical setting has been identified as statistically significant.

Keywords : Disabled persons; Small areas analysis; Multilevel analysis; Spain.

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