Applying machine learning to explore association models between environmental hormones, breast cancer, and a dietary and health education improvement program: an investigative study

Traditional risk factor screening for breast cancer focuses on reproductive and family history. However, an increasing number of young patients without these risk factors have been diagnosed with breast cancer. This study employed an exploratory design to investigate the relationship between environmental hormone-related lifestyle habits and breast cancer, as well as to develop a dietary and health program. In the first phase, laboratory data were analyzed using logistic regression to identify environmental hormone-related risk factors. Breast cancer was significantly associated with elevated blood lead (OR = 3.433, 95%CI: 1.090-10.809), chloramphenicol exposure (OR = 4.335, 95%CI: 1.196-15.716), and the phthalate metabolite MEP (OR = 3.238, 95%CI: 1.039-10.094). In the second phase, lifestyle habits of patients with breast cancer were collected and matched with these environmental hormone-related risk factors to construct an association model and a dietary and health program. The findings suggest that environmental hormones contributing to breast cancer include heavy metals (e.g. lead, copper, zinc, mercury and chromium) and plasticizers, which are related to patients' lifestyles and dietary habits.<b>Clinical trial registration</b>: NCT06765395 on 3 January 2025.