A Case-Control Epidemiological Analysis of Breast Cancer Risk Factors Using Logistic Regression Modeling

Abstract

Breast cancer continues to be a major health problem worldwide with a complex etiology involving genetic, environmental, and lifestyle causes. The aim of this research is to explore the relationship between the most significant risk factors and breast cancer as well as determine the most frequent symptoms and most affected breast side in women. The case-control study had a sample size of 459 women and used chi-squared tests of independence and binary logistic regression to compare possible risk factors. The findings indicate that age at diagnosis, residential location, level of education, age at menarche, family history of breast cancer, menopausal status, history of breastfeeding, use of oral contraceptives, radiation exposure, drug use, number of children, and night shift work were all significantly related to breast cancer risk. On the other hand, marital status, age at marriage, abortion history, removal of ovaries, and physical activity are not observed to be statistically significant with the development of breast cancer. The results emphasize the need for public health intervention and education to reduce the risk of breast cancer through increased awareness and preventive interventions.