[Study of variables associated with skin cancer in Chile using principal component analysis].
BACKGROUND
The incidence of skin cancer in Chile has increased in recent years.


OBJECTIVE
To associate variables with skin cancer in Chile through indices generated using multivariate descriptive statistical techniques.


METHODS
During May 2004, information was gathered from demographic, meteorological and clinical data from Chile corresponding to fiscal year 2001, the latest complete, official information available for the country's Health Services as a whole. The variables developed by the following were studied: the National Statistics Institute (INE), the Ministry of Health (MINSAL), the Ministry of Planning and Cooperation (MIDEPLAN), the National Health Fund (FONASA), the Chilean Meteorological Directorate, Federico Santa María Technical University and the Directorate-General for Water. A Principal Component Analysis (PCA) was then performed on the data obtained.


RESULTS
The first three principal components were selected, with a cumulative explained variance percentage of 54.48 %. The first principal component explains 24.92 % of the variance, and is related to climatic and geographic variables. The second principal component explains 15.77 % of the variance, and is mainly related to FONASA's beneficiary population and the poverty rate. The mortality rate from skin cancer runs significantly against this component. The third principal component explains 13.79 % of the variance, and is related to population characteristics, such as total catchment population, female population and urban population.


CONCLUSIONS
Performing PCA is useful in studying the factors associated with skin cancer.
Salinas
Hugo
H
Hospital Clínico J.J. Aguirre, Universidad de Chile, Santiago de Chile, Chile.
Almenara
José
J
Reyes
Alvaro
A
Silva
Paulina
P
Erazo
Marcia
M
Abellán
María J
MJ
D000328:Adult; D000368:Aged; D002391:Catchment Area, Health; D002677:Chile / Q000453:epidemiology; D003880:Dermatology; D005260:Female; D005843:Geography; D006761:Hospitals / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D008489:Medical Indigency / Q000706:statistics & numerical data; D008685:Meteorological Concepts; D008875:Middle Aged; D009381:Neoplasms, Radiation-Induced / Q000453:epidemiology; D011203:Poverty / Q000706:statistics & numerical data; D025341:Principal Component Analysis; D012307:Risk Factors; D012424:Rural Population / Q000706:statistics & numerical data; D012878:Skin Neoplasms / Q000453:epidemiology*; D013472:Sunlight / Q000009:adverse effects; D014505:Urban Population / Q000706:statistics & numerical data; D000078329:Workforce