Factors Associated with Breast Cancer Risk in Women: A Literature Review
DOI:
https://doi.org/10.30683/1929-2279.2026.15.06Keywords:
Breast cancer, breast cancer risk factors, breast cancer screening, breast cancer diagnosis, epidemiology, etiology, risk stratification, individual risk modelAbstract
Breast cancer is a disease with a multifactorial etiology shaped by genetic, hormonal, reproductive, phenotypic, environmental, and socio-behavioral determinants. This narrative review with a systematic search strategy aimed to systematize factors associated with breast cancer risk and incidence, with an emphasis on their applicability in risk-oriented early detection models. The literature search was conducted in PubMed/MEDLINE, Scopus, eLIBRARY.ru, and additional sources for the period from 19 December 2020 to 19 December 2025. The review included narrative reviews, systematic reviews, and meta-analyses, as well as a limited number of original studies meeting predefined eligibility criteria (Population, Exposure, Outcome, and Study design). The final corpus comprised 48 publications. Risk factors were grouped into thematic domains and qualitatively classified according to the degree of epidemiological consistency and suitability for inclusion in individual risk models (categories A–C). The most robust associations were identified for age, mammographic density, hereditary and family history, several hormonal and reproductive characteristics, smoking, and night shift work. For environmental exposures, obesity, and certain chemical factors, the evidence base was characterized by greater heterogeneity, whereas for psychoemotional factors and radiofrequency electromagnetic fields it remained limited and should be considered hypothesis-generating. This review demonstrates the uneven quality and consistency of contemporary evidence on breast cancer risk factors and highlights the need for their critical interpretation within risk-oriented approaches. The resulting list of candidate factors may serve as a basis for predictor selection and subsequent prospective validation in the development of individual risk models aimed at optimizing early diagnosis.
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