[Principal components analysis].

Abstract

OBJECTIVE: This study wants to identify factors or components latent besides health indicators from Spanish regions, and its graphic output. DESIGN: Observational study. SETTING: Twenty eight indicators from regions were used: mortality, morbidity, communicable and no-communicable diseases, diet, dwelling and sanitary resources. Measurement was made between 1980-1988. INTERVENTIONS: Principal component analysis has been applied to the indicators, reducing data dimension. MEASUREMENT AND MAIN RESULTS: Eight factors have been extracted, which explain 90% of the original information. This analysis, as can be seen from communnalities, represents correctly the set of original variables. The factors with more easily interpretation were: shortage sanitary resources, develop diet, mortality, chronic diseases and accidental. CONCLUSIONS: Only reduction data dimension could be justify the use of principal component analysis. Behind the agrupation of variables is mostly the socioeconomic background.