Analysis of Factors Causing Infertility in Women Using Statistical Analysis and Association Rule Mining

Statistical Hypothesis Testing methods and Association Rule Mining through Frequent Item-set Mining have been used to analyze and mine knowledge on significant factors causing infertility in women. Even though there are a number of factors causing infertility in women, only three significant factors namely Age, Body Mass Index and Thyroid Stimulating Hormone Levels during prenatal periods have been taken for analysis. Sample data was collected from the case sheets of outpatients visiting a Fertility centre and Maternity Hospital at Trichy. Out of several independent attributes collected about outpatients, only three attributes considered to be significant have been taken up for preliminary study. The aim of the study is to assess the significance of the said factors in the light of fertility in women. Common attributes have been considered among an equal sample size of fertile and infertile outpatients. The results of the study show that the attributes considered are significant in determining fertility of women both individually and together. It is found that age significantly influences Body Mass Index and Thyroid Stimulating Hormone Levels. It is also found that obesity triggers changes in hormonal levels.