Suppr超能文献

骨骼肌质量与乳腺 X 线摄影密度的相关性。

Association between skeletal muscle mass and mammographic breast density.

机构信息

Department of Surgery, Bucheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.

Department of Pathology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea.

出版信息

Sci Rep. 2021 Aug 18;11(1):16785. doi: 10.1038/s41598-021-96390-9.

Abstract

Mammographic density (MD) of the breast and body mass index (BMI) are inversely associated with each other, but have inconsistent associations with respect to the risk of breast cancer. Skeletal muscle mass index (SMI) has been considered to reflect a relatively accurate fat and muscle percentage in the body. So, we evaluated the relation between SMI and MD. A cross-sectional study was performed in 143,456 women who underwent comprehensive examinations from 2012 to 2016. BMI was adjusted to analyze whether SMI is an independent factor predicting dense breast. After adjustment for confounding factors including BMI, the odds ratios for MD for the dense breasts was between the highest and lowest quartiles of SMI at 2.65 for premenopausal women and at 2.39 for postmenopausal women. SMI was a significant predictor for MD, which could be due to the similar growth mechanism of the skeletal muscle and breast parenchymal tissue. Further studies are needed to understand the causal link between muscularity, MD and breast cancer risk.

摘要

乳房的乳腺密度(MD)与身体质量指数(BMI)呈负相关,但与乳腺癌的风险之间的关联并不一致。骨骼肌质量指数(SMI)被认为可以反映身体内相对准确的脂肪和肌肉百分比。因此,我们评估了 SMI 与 MD 之间的关系。我们对 2012 年至 2016 年间接受全面检查的 143456 名女性进行了一项横断面研究。调整 BMI 以分析 SMI 是否是预测致密乳腺的独立因素。在调整了包括 BMI 在内的混杂因素后,SMI 最高和最低四分位的绝经前女性和绝经后女性的 MD 比值分别为 2.65 和 2.39。SMI 是 MD 的重要预测因子,这可能是由于骨骼肌和乳腺实质组织的相似生长机制所致。需要进一步的研究来了解肌肉质量、MD 和乳腺癌风险之间的因果关系。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a498/8373895/3c74cd9d725b/41598_2021_96390_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验