ABSTRACT
INTRODUCTION AND OBJECTIVES: Cardiovascular diseases continue to lead the ranking of mortality in Spain. The implementation of geostatistical analysis techniques in the clinical laboratory are innovative tools that allow the design of new strategies in primary prevention of cardiovascular disease. The aim of this study was to study the prevalence and geolocation of severe dyslipidemia in the health areas under study in order to implement prevention strategies in primary care. A retrospective cohort study of low-density protein-bound cholesterol, triglyceride and lipoprotein (a) levels in the years 2019 and 2020 were carried out. In addition, a geostatistical analysis was performed including representation in choropleth maps and the detection of clustering clusters, using geographic information in zip code format included in the demographic data of each analytic. RESULTS: The analytical data included in the study were triglycerides (n=365,384), low density protein-bound cholesterol (n=289,594) and lipoprotein to lipoprotein (a) (n=502). Areas with the highest and lowest percentage of cases were identified for the established cut-off points of LDL-C>190mg/dL and TG>150mg/dL. Two clustering clusters with statistical significance were detected for cLDL>190mg/dL and a total of 6 clusters for TG values>150mg/dL. CONCLUSIONS: The detection of clusters, as well as the representation of choropleth maps, can be of great help in detecting geographic areas that require greater attention to intervene and improve cardiovascular risk.
