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Revista Cubana de Salud Pública

versión On-line ISSN 1561-3127

Resumen

ALEGRET RODRIGUEZ, Milagros; HERRERA, Manuela  y  GRAU ABALO, Ricardo. Spatial statistical techniques in health care research: Down´s syndrome case. Rev Cubana Salud Pública [online]. 2008, vol.34, n.4, pp. 0-0. ISSN 1561-3127.

Introduction One of the advantages of spatial statistical analysis techniques is that they can summarize the complex spatial pattern by making such complexity assimilable into the human eyes and mind, and decision-making and interventions more feasible. This reasoning is exemplified by means of the study of a health event in which the result of spatial analysis is compared with those of traditional epidemiological methods. Objectives To use spatial statistical analysis in a case study and to compare it with conventional epidemiological analysis in order to show the feasibility and advantages of this method in the event surveillance for the decision-making. Methods Data from 15 years of Down´s syndrome surveillance work carried out in Villa Clara province from 1985 to 2000 were used. Kulldorff´s cluster detection techniques were employed in the spatial analysis. Mapping was based on MapInfo v 5.0, importing the statistical results to the geographical information system. Epidemiological analyses included relative real risk assessment and the estimation of other relational and central tendency statistic. Results The differentiation of Down´s syndrome determinants associated to the spatial context was put in perspective, which served to supplement in a timely manner the case data-based analysis. This provided evidence that could not have been drawn if conventional analysis had solely been used. Conclusions The spatial analysis could quickly show findings and projections that were further backed up by the conventional analysis made in this case. The differentiation of Down´s syndrome determinants in rural and urban areas allowed implementing differentiated strategies to prevent this chromosome disorder in both settings.

Palabras clave : Spatial analysis; clusters; epidemiology; geographical information systems.

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