[Principal components analysis].
OBJECTIVE
This study wants to identify factors or components latent besides health indicators from Spanish regions, and its graphic output.


METHODS
Observational study.


METHODS
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.


METHODS
Principal component analysis has been applied to the indicators, reducing data dimension.


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.
López del Val
J A
JA
Unidad Docente de Medicinia Familiar y Comunitaria de Zaragoza.
Alonso Pérez de Agreda
J P
JP
D006305:Health Status Indicators; D011320:Primary Health Care / Q000706:statistics & numerical data*; D013030:Spain
Análisis de componentes principales.