Breast cancer prevention: Risk stratification by parity and menopausal status among women in OR Tambo District

Targeted screening and prevention strategies must be centered around an understanding of how reproductive variables affect breast cancer risk across different groups of women. Stratified by parity and menopausal status, this study assessed the association between age, age at menarche, age at first pregnancy, number of pregnancies, and number of children at risk for breast cancer. Stratified logistic regression models were used to evaluate data from a cohort of women (N = 213) in OR Tambo district. The binary outcome was breast cancer history (proxy: previously breast surgery or family history). Parity (nulliparous, 1–2, ≥3 children) and menopausal state (premenopausal and postmenopausal) were used to identify the subgroups. Within each subgroup, odds ratios (ORs) and 95% Confidence intervals (Cis) were computed for every predictor. Additionally, breastfeeding was assessed as a risk factor. Analyses were conducted using R studio (version 4.2.3). Age was associated with higher risk among premenopausal women (OR = 1.15, 95% CI: 0.85–1.56). Increase in age was linked to an increased risk of breast cancer in women with three or more children (OR = 1.09, 95% CI: 0.99–1.20; p = 0.072) though not statistically significant. Across strata, there were no consistent or significant correlations between risk and parity, age of menarche, or age at first pregnancy. Breastfed women have less risk than non-breastfed women (RR = 0.78, 95% CI: 0.25–2.37), however sample size limitations hindered the results from being statistically significant. Age proved to be the most consistently significant predictor across all subgroups by model diagnostics. These results highlight the need to use subgroup-specific risk models to guide preventive measures and individualized breast cancer screening.

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Publication Details

Journal
International Journal of Innovative Research and Scientific Studies
Published
2025-10-03
DOI
https://doi.org/10.53894/ijirss.v8i7.10482
Primary Topic
Diverse Scientific Research Studies
Type
article
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article

Breast cancer prevention: Risk stratification by parity and menopausal status among women in OR Tambo District

Olufunmilayo Olukemi Akapo, Anne Namugenyi
International Journal of Innovative Research and Scientific Studies
Diverse Scientific Research Studies
article

Breast cancer prevention: Risk stratification by parity and menopausal status among women in OR Tambo District

Olufunmilayo Olukemi Akapo, Anne Namugenyi
article en

Abstract

Targeted screening and prevention strategies must be centered around an understanding of how reproductive variables affect breast cancer risk across different groups of women. Stratified by parity and menopausal status, this study assessed the association between age, age at menarche, age at first pregnancy, number of pregnancies, and number of children at risk for breast cancer. Stratified logistic regression models were used to evaluate data from a cohort of women (N = 213) in OR Tambo district. The binary outcome was breast cancer history (proxy: previously breast surgery or family history). Parity (nulliparous, 1–2, ≥3 children) and menopausal state (premenopausal and postmenopausal) were used to identify the subgroups. Within each subgroup, odds ratios (ORs) and 95% Confidence intervals (Cis) were computed for every predictor. Additionally, breastfeeding was assessed as a risk factor. Analyses were conducted using R studio (version 4.2.3). Age was associated with higher risk among premenopausal women (OR = 1.15, 95% CI: 0.85–1.56). Increase in age was linked to an increased risk of breast cancer in women with three or more children (OR = 1.09, 95% CI: 0.99–1.20; p = 0.072) though not statistically significant. Across strata, there were no consistent or significant correlations between risk and parity, age of menarche, or age at first pregnancy. Breastfed women have less risk than non-breastfed women (RR = 0.78, 95% CI: 0.25–2.37), however sample size limitations hindered the results from being statistically significant. Age proved to be the most consistently significant predictor across all subgroups by model diagnostics. These results highlight the need to use subgroup-specific risk models to guide preventive measures and individualized breast cancer screening.

International Journal of Innovative Research and Scientific StudiesVol. 8(7)
Walter Sisulu University (ZA)
Openalex Percentile: Top 55%
Diverse Scientific Research Studies
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