{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T16:44:01Z","timestamp":1785516241804,"version":"3.56.0"},"reference-count":43,"publisher":"Public Library of Science (PLoS)","issue":"4","license":[{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:sec id=\"sec020\">\n<jats:title>Introduction<\/jats:title>\n<jats:p>Breast cancer is a global public health problem among reproductive-age women, with an estimated 670,000 deaths in 2022. It\u2019s also a pressing health challenge in Sub-Saharan African countries, driven by late-stage diagnoses and limited healthcare access, underscoring the urgent need for early screening and treatment initiatives to combat this growing epidemic. In Kenya, the burden was also significant, and multilevel factors such as individual, household, and community level factors that influence screening uptake are undermined. Furthermore, there were no nationally representative studies. Therefore, this study aimed to assess clinical breast cancer screening uptake (CBCSU) and associated factors among reproductive-age women: further analysis of Kenyan demographic and health survey (KDHS) 2022.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec021\">\n<jats:title>Methods<\/jats:title>\n<jats:p>This study used a weighted nationally representative sample of 16,649 women from the 2022 KDHS. A Multilevel mixed effects binary logistic regression analysis was performed and in the multivariable analysis, variables with a p-value less than 0.05 were considered statistically significant. The strength of the association was evaluated using Adjusted Odds Ratios (AOR) along with their corresponding 95% confidence intervals (CI). STATA version 17 software was to for data management and statistical analysis.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec022\">\n<jats:title>Results<\/jats:title>\n<jats:p>The weighted prevalence of CBCSU in Kenya was 13.91% (95% CI: 13.33, 14.44). Besides, women aged 25 to 34 years (AOR =\u2009 1.86, 95% CI: 1.57, 2.21), and 35 to 49 years (AOR =\u2009 2.87, 95% CI: 2.40, 3.42) had higher odds of CBCSU. Women with primary education (AOR =\u2009 2.14, 95% CI: 1.56, 2.94) and those with secondary or higher education (AOR =\u2009 3.09, 95% CI: 2.23, 4.28) had higher odds of CBCSU. In addition, the odds of CBCSU were higher among women with a middle (AOR =\u2009 1.41, 95% CI: 1.19, 1.67) and a rich wealth index (AOR =\u2009 2.19, 95% CI: 1.84, 2.61). On the other hand, CBCSU was lower among non-contraceptive user women (AOR 0.78, 95% CI: 0.69, 0.87). Furthermore, women in communities with a high proportion of media exposure had higher CBCSU (AOR =\u2009 1.17, 95% CI: 1.04, 1.33).<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec023\">\n<jats:title>Conclusion<\/jats:title>\n<jats:p>In this study, the prevalence of CBCSU among reproductive-age women in Kenya was found to be low. Besides, factors such as age, educational status, wealth index, family planning utilization, and community media exposure were identified as significant contributors to screening uptake. Therefore, policymakers and stakeholders should design interventions that address factors contributing to low breast cancer screening uptake, particularly targeting women in areas with limited media exposure, to increase the uptake of clinical breast cancer screening.<\/jats:p>\n<\/jats:sec>","DOI":"10.1371\/journal.pone.0320730","type":"journal-article","created":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T21:15:32Z","timestamp":1743542132000},"page":"e0320730","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":6,"title":["Clinical breast cancer screening uptake and associated factors among reproductive age women in Kenya: further analysis of Kenyan Demographic and Health Survey 2022"],"prefix":"10.1371","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9538-7612","authenticated-orcid":true,"given":"Habtamu Wagnew","family":"Abuhay","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gebrie Getu","family":"Alemu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7152-6435","authenticated-orcid":true,"given":"Mekuriaw Nibret","family":"Aweke","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tewodros Getaneh","family":"Alemu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Berhanu","family":"Mengistu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amare","family":"Mesfin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2025,4,1]]},"reference":[{"key":"pone.0320730.ref001","author":"WHO"},{"key":"pone.0320730.ref002","doi-asserted-by":"crossref","first-page":"839835","DOI":"10.3389\/fpubh.2022.839835","article-title":"Mapping cancer in Africa: a comprehensive and comparable characterization of 34 cancer types using estimates from GLOBOCAN 2020","volume":"10","author":"R Sharma","year":"2022","journal-title":"Frontiers in Public Health"},{"key":"pone.0320730.ref003","unstructured":"Annamalai N, Karickal J. 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