Literature DB >> 23804137

Association between mammographic breast density and lifestyle in Japanese women.

Setsuko Ishihara1, Naruto Taira, Kensuke Kawasaki, Youichi Ishibe, Taeko Mizoo, Keiko Nishiyama, Takayuki Iwamoto, Tomohiro Nogami, Takayuki Motoki, Tadahiko Shien, Junji Matsuoka, Hiroyoshi Doihara, Yoshifumi Komoike, Shuhei Sato, Susumu Kanazawa.   

Abstract

A high mammographic breast density is considered to be a risk factor for breast cancer. However, only a small number of studies on the association between breast density and lifestyle have been performed. A cross-sectional study was performed using a survey with 29 questions on life history and lifestyle. The breast density on mammography was classified into 4 categories following the BI-RADS criteria. The subjects were 522 women with no medical history of breast cancer. The mean age was 53.3 years old. On multivariate analysis, only BMI was a significant factor determining breast density in premenopausal women (parameter estimate, -0.403; p value, 0.0005), and the density decreased as BMI rose. In postmenopausal women, BMI (parameter estimate, -0.196; p value, 0.0143) and number of deliveries (parameter estimate, -0.388; p value, 0.0186) were significant factors determining breast density;breast density decreased as BMI and number of deliveries increased. Only BMI and number of deliveries were identified as factors significantly influencing breast density. BMI was inversely correlated with breast density before and after menopause, whereas the influence of number of deliveries on breast density was significant only in postmenopausal women in their 50 and 60s.

Entities:  

Mesh:

Year:  2013        PMID: 23804137     DOI: 10.18926/AMO/50407

Source DB:  PubMed          Journal:  Acta Med Okayama        ISSN: 0386-300X            Impact factor:   0.892


  11 in total

1.  Impact of childbirth history on dense breast in mammographic screening: a cross-sectional study.

Authors:  Tomohiro Ochi; Hiroko Tsunoda; Hideko Yamauchi; Osamu Takahashi
Journal:  BMC Womens Health       Date:  2022-05-26       Impact factor: 2.742

2.  Portable impulse-radar detector for breast cancer: a pilot study.

Authors:  Shinsuke Sasada; Norio Masumoto; Hang Song; Keiko Kajitani; Akiko Emi; Takayuki Kadoya; Koji Arihiro; Takamaro Kikkawa; Morihito Okada
Journal:  J Med Imaging (Bellingham)       Date:  2018-06-13

3.  Association between alcohol consumption and mammographic density: a hospital-based cross-sectional study.

Authors:  Takahide Okamoto; Akemi Ito
Journal:  Breast Cancer       Date:  2019-01-24       Impact factor: 4.239

4.  Factors Associated with Mammographic Density in Postmenopausal Women.

Authors:  Emel Kiyak Caglayan; Kasim Caglayan; Ismet Alkis; Ergin Arslan; Aylin Okur; Oktay Banli; Yaprak Engin-Ustün
Journal:  J Menopausal Med       Date:  2015-08-28

5.  Breast cancer risk factors and mammographic density among high-risk women in urban China.

Authors:  Hyuna Sung; Jiansong Ren; Jing Li; Min Dai; Xiaohong R Yang; Jie He; Ruth M Pfeiffer; Yong Wang; Jennifer L Guida; Yi Fang; Jufang Shi; Kai Zhang; Ni Li; Shen Wang; Luopei Wei; Nan Hu; Gretchen L Gierach
Journal:  NPJ Breast Cancer       Date:  2018-02-06

6.  Prevalence of Women with Dense Breasts in Korea: Results from a Nationwide Cross-sectional Study.

Authors:  Hye-Mi Jo; Eun Hye Lee; Kyungran Ko; Bong Joo Kang; Joo Hee Cha; Ann Yi; Hae Kyoung Jung; Jae Kwan Jun
Journal:  Cancer Res Treat       Date:  2019-01-29       Impact factor: 4.679

7.  Factors associated with mammographic breast density among women in Karachi Pakistan.

Authors:  Uzma Shamsi; Shaista Afzal; Azra Shamsi; Iqbal Azam; David Callen
Journal:  BMC Womens Health       Date:  2021-12-31       Impact factor: 2.809

8.  A multicenter, hospital-based and non-inferiority study for diagnostic efficacy of automated whole breast ultrasound for breast cancer in China.

Authors:  Yujing Xin; Xinyuan Zhang; Yi Yang; Yi Chen; Yanan Wang; Xiang Zhou; Youlin Qiao
Journal:  Sci Rep       Date:  2021-07-06       Impact factor: 4.379

9.  Mammographic Breast Density Evaluation in Korean Women Using Fully Automated Volumetric Assessment.

Authors:  Inyoung Youn; SeonHyeong Choi; Shin Ho Kook; Yoon Jung Choi
Journal:  J Korean Med Sci       Date:  2016-02-23       Impact factor: 2.153

10.  A deep learning-based automated diagnostic system for classifying mammographic lesions.

Authors:  Takeshi Yamaguchi; Kenichi Inoue; Hiroko Tsunoda; Takayoshi Uematsu; Norimitsu Shinohara; Hirofumi Mukai
Journal:  Medicine (Baltimore)       Date:  2020-07-02       Impact factor: 1.817

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.