Predicting risk on cardiovascular or cerebrovascular disease based on a physical activity cohort: Results from APAC study

Author:

Zhao Juan123,Yu Ye4,Zhu Xiaolan12,Xie Yuling12,Ai Songwei1,Lehmann H. Immo5,Deng Xuan4,Hu Feifei4,Li Guoping5,Zhou Yong4,Xiao Junjie12

Affiliation:

1. Institute of Geriatrics (Shanghai University), Affiliated Nantong Hospital of Shanghai University (The Sixth People's Hospital of Nantong), School of Medicine Shanghai University Nantong China

2. Cardiac Regeneration and Ageing Lab, Institute of Cardiovascular Sciences, Shanghai Engineering Research Center of Organ Repair, School of Life Science Shanghai University Shanghai China

3. School of Pharmacy Shanghai University of Traditional Chinese Medicine Shanghai China

4. Clinical Research Institute, Shanghai General Hospital Shanghai Jiaotong University School of Medicine Shanghai China

5. Cardiovascular Division of the Massachusetts General Hospital and Harvard Medical School Boston Massachusetts USA

Abstract

AbstractCommonly used prediction models have been primarily constructed without taking physical activity into account. Using the Kailuan physical activity cohorts from Asymptomatic Polyvascular Abnormalities in Community (APAC) study, we developed a 9‐year cardiovascular or cerebrovascular disease (CVD) risk prediction equation. Participants in this study were included from APAC cohort, which included 5440 participants from the Kailuan cohort in China. Cox proportional hazard regression model was applied to construct sex‐specific risk prediction equations for the physical activity cohort (PA equation). Proposed equations were compared with the 10‐year risk prediction model, which is developed for atherosclerotic cardiovascular disease risk in Chinese cohorts (China‐PAR equation).Cstatistics of PA equations were 0.755 (95% confidence interval, 0.750–0.758) for men and 0.801 (95% confidence interval, 0.790–0.813) for women. The estimated area under the receiver operating characteristic curves in the validation set shows that the PA equations perform as good as the China‐PAR. From calibration among four categories of predicted risks, the predicted risk rates by PA equations were almost identical to the Kaplan–Meier observed rates. Therefore, our developed sex‐specific PA equations have effective performance for predicting CVD for physically active cohorts in the physical activity cohort in Kailuan.

Funder

National Natural Science Foundation of China

Science and Technology Commission of Shanghai Municipality

Publisher

Wiley

Subject

Cell Biology,Biochemistry (medical),Genetics (clinical),Computer Science Applications,Drug Discovery,Genetics,Oncology,Immunology and Allergy

Reference43 articles.

1. Heart Disease and Stroke Statistics—2017 Update: A Report From the American Heart Association

2. Major Causes of Death among Men and Women in China

3. Study on environmental and lifestyle factors for the north–south differential of cardiovascular disease in China. Original Research;Wang M;Front Public Health,2021

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