Factor analysis, a more accurate method to be used in epidemiological studies of blood pressure in children.
The aim of our study is to evaluate whether factor analysis is better able to explain the variability of systolic blood pressure (SBP) and diastolic blood pressure (DBP) when compared with regression analysis, which is the usual tool to study a set of variables related to blood pressure (BP). SBP, DBP, weight, height, BMI, triceps skin-fold, sexual maturation and rurality were studied in 889 children aged 5-18 years (389 boys and 500 girls). The proposed method transforms any set of variables into a set of new variables (factors) which are uncorrelated with each other. One of the factors obtained clearly explains the BP variance of the. With this method, the algorithm accepts all meaningful variables, while regressions reject most of them. This method also explains a larger amount of BP variability, losing as little information as possible. In our sample the percentage of the total variance (communality) explained by the three factors was 80.3% for SBP, 88.1% for DBP in males, 79.3% for SBP and 90.7% for DBP in females. For the same sample, regressions only explained 41.2% in males and 41.9% in females for SBP, 40.9% in males and 47.2% in females for DBP. In conclusion, this method is more accurate for epidemiological studies producing a better overall score than regression analysis, losing almost no information from the sample. Two important strengths of the proposed methodology are as follows. First, it yields a unique, easy to calculate and flexible cardiovascular index for children, thus circumventing the problem of making decisions based on two variables (SBP and DBP). Second, such an index is the result of a methodology where specific BP variability is isolated rather than explained.
Macedo
M A
MA
Serviço de Medicina II, Faculdade de Medicina do Porto.
Trigueiros
D
D
de Freitas
A F
AF
D000293:Adolescent; D001794:Blood Pressure; D002648:Child; D002675:Child, Preschool; D004812:Epidemiologic Methods; D005163:Factor Analysis, Statistical; D005260:Female; D006801:Humans; D006973:Hypertension / Q000453:epidemiology; D008297:Male; D011174:Portugal / Q000453:epidemiology; D012044:Regression Analysis; D017678:Sex Distribution