Association between body composition and subsequent cardiovascular diseases among 5-year breast cancer survivors

Author:

Kim Ji Soo1,Song Jihun2,Choi Seulggie1,Kim Sung Min2,Park Young Jun3,Park Sun Jae2,Cho Yoosun4,Oh Yun Hwan5,Jeong Seogsong5,Kim Kyae Hyung1,Park Sang Min1ORCID

Affiliation:

1. Seoul National University Hospital

2. Seoul National University Graduate School Department of Biomedical Science

3. Seoul National University Medical Research Center

4. Kangbuk Samsung Medical Center Total Healthcare Center

5. Chung-Ang University Gwangmyeong Hospital

Abstract

Abstract Purpose: Cardiovascular diseases (CVDs) remain one of the leading causes of mortality in breast cancer survivors. This study aimed to investigate the association between body composition and subsequent CVDs in breast cancer survivors.Methods: A retrospective cohort study of more than 70 thousand 5-year breast cancer survivors aged 40 years or older was conducted using data from the National Health Insurance Service of South Korea. Based on the percentage of predicted lean body mass (pLBMP), appendicular skeletal muscle mass (pASMP), and body fat mass (pBFMP), which were calculated using prediction equations with anthropometric data and health habits, groups were equally divided into quartiles. The risk of CVD was evaluated using multivariate Cox proportional hazards regression.Results: Compared to those with the lowest pLBMP and pASMP, those with the highest pLBMP and pASMP had a 37% and 42% lower risk of CVDs, respectively. In contrast, those with the highest pBFMP had a 57% higher risk of CVDs compared to those with the lowest pBFMP. Each 1 % increase in pLBMP and pASMP was associated with a decreased risk of CVDs [pLBMP, adjusted hazard ratio (aHR): 0.96, 95% CI 0.94–0.98, p<0.05; pASMP, aHR: 0.91, 95% CI 0.87–0.95, p<0.05] while each 1 % increase in pBFMP was associated with the increased risk of CVDs (aHR: 1.05, 95% CI 1.03–1.07, p<0.01). Conclusions: In this cohort study, high pLBMP, a high pASMP, and a low pBFMP were associated with reduced risk of CVDs.

Publisher

Research Square Platform LLC

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3