Literature DB >> 31299298

Effect of the variability of blood pressure, glucose level, total cholesterol level, and body mass index on the risk of atrial fibrillation in a healthy population.

So-Ryoung Lee1, Eue-Keun Choi1, Kyung-Do Han2, Seung-Hwan Lee3, Seil Oh4.   

Abstract

BACKGROUND: The variability of metabolic parameters might have an impact on the pathophysiology of atrial fibrillation (AF).
OBJECTIVE: The purpose of this study was to evaluate the effect of the variability of 4 metabolic components including systolic blood pressure (BP), glucose level, total cholesterol (TC) level, and body mass index (BMI) on the risk of AF in the healthy population without hypertension, diabetes, or dyslipidemia.
METHODS: We identified 6,819,829 adult subjects without hypertension, diabetes, or dyslipidemia who had ≥3 health checkups provided by the Korean National Health Insurance Corporation between 2005 and 2012. Glucose level, BP, TC level, and BMI were measured at each visit. Variability was defined as variability independent of the mean (VIM), and VIM of each parameter was divided into 4 groups. High variability was defined as having values in the highest quartile of each parameter.
RESULTS: During a mean follow-up of 5.3 ± 1.1 years, 31,302 subjects were newly diagnosed with AF (0.86 per 1000 person-years). Subjects with the highest VIM quartile of BP, TC level, and BMI showed an increased risk of AF compared with those with the lowest VIM quartile, whereas glucose level variability had a marginal association. The composite of the high variability of metabolic parameters showed a graded risk of AF. After multivariable adjustment, subjects having 1, 2, 3, and 4 parameters of the highest VIM had an ∼7%, 13%, 20%, and 35% increased risk of AF compared with those without any highest variability of metabolic parameters.
CONCLUSION: The variability of metabolic parameters showed a close association with the risk of AF in those without cardiovascular comorbidities.
Copyright © 2019 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Atrial fibrillation; Blood pressure; Body mass index; Glucose; Metabolic variability; Total cholesterol

Mesh:

Substances:

Year:  2019        PMID: 31299298     DOI: 10.1016/j.hrthm.2019.07.006

Source DB:  PubMed          Journal:  Heart Rhythm        ISSN: 1547-5271            Impact factor:   6.343


  12 in total

1.  Elevated levels of body mass index and waist circumference, but not high variability, are associated with an increased risk of atrial fibrillation.

Authors:  Maoxiang Zhao; Lulu Song; Qianqian Zhao; Yating Chen; Bin Li; Zhonghui Xie; Zihao Fu; Nan Zhang; Xiaowei Cheng; Xiaoqian Li; Miao Wang; Shouling Wu; Hao Xue; Yang Li
Journal:  BMC Med       Date:  2022-06-29       Impact factor: 11.150

Review 2.  Effects of Cardiovascular Risk Factor Variability on Health Outcomes.

Authors:  Seung-Hwan Lee; Mee Kyoung Kim; Eun-Jung Rhee
Journal:  Endocrinol Metab (Seoul)       Date:  2020-06-24

Review 3.  Cardiovascular Research Using the Korean National Health Information Database.

Authors:  Eue Keun Choi
Journal:  Korean Circ J       Date:  2020-05-20       Impact factor: 3.243

Review 4.  On-demand mobile health infrastructures to allow comprehensive remote atrial fibrillation and risk factor management through teleconsultation.

Authors:  Astrid N L Hermans; Rachel M J van der Velden; Monika Gawalko; Dominique V M Verhaert; Lien Desteghe; David Duncker; Martin Manninger; Hein Heidbuchel; Ron Pisters; Martin Hemels; Laurent Pison; Afzal Sohaib; Arian Sultan; Daniel Steven; Petra Wijtvliet; Robert Tieleman; Dhiraj Gupta; Dobromir Dobrev; Emma Svennberg; Harry J G M Crijns; Nikki A H A Pluymaekers; Jeroen M Hendriks; Dominik Linz
Journal:  Clin Cardiol       Date:  2020-10-08       Impact factor: 2.882

5.  Variability of Metabolic Risk Factors: Causative Factor or Epiphenomenon?

Authors:  Hye Jin Yoo
Journal:  Diabetes Metab J       Date:  2022-03-24       Impact factor: 5.376

6.  Non-alcoholic Fatty Liver Disease and the Risk of Incident Atrial Fibrillation in Young Adults: A Nationwide Population-Based Cohort Study.

Authors:  JungMin Choi; So-Ryoung Lee; Eue-Keun Choi; Hyo-Jeong Ahn; Soonil Kwon; Sang-Hyeon Park; HuiJin Lee; Jaewook Chung; MinJu Han; Seung-Woo Lee; Kyung-Do Han; Seil Oh; Gregory Y H Lip
Journal:  Front Cardiovasc Med       Date:  2022-03-23

7.  Gender differences and daily variation in atrial fibrillation risk factor profiles: Considerations for risk factor management.

Authors:  Nikki A H A Pluymaekers; Astrid N L Hermans; Melissa E Middeldorp; Kadhim Kadhim; Harry J G M Crijns; Prashanthan Sanders; Dominik Linz
Journal:  Int J Cardiol Heart Vasc       Date:  2019-11-19

8.  Association between clustering of unhealthy lifestyle factors and risk of new-onset atrial fibrillation: a nationwide population-based study.

Authors:  So-Ryoung Lee; Eue-Keun Choi; Hyo-Jeong Ahn; Kyung-Do Han; Seil Oh; Gregory Y H Lip
Journal:  Sci Rep       Date:  2020-11-05       Impact factor: 4.379

9.  Effect of Variability in Blood Pressure, Glucose and Cholesterol Concentrations, and Body Weight on Emergency Hospitalization and 30-Day Mortality in the General Population.

Authors:  Seung-Hwan Lee; Kyungdo Han; Hyuk-Sang Kwon; Kun-Ho Yoon; Mee Kyoung Kim
Journal:  J Am Heart Assoc       Date:  2020-11-06       Impact factor: 5.501

10.  Higher long-term visit-to-visit glycemic variability predicts new-onset atrial fibrillation in patients with diabetes mellitus.

Authors:  Jung-Chi Hsu; Yen-Yun Yang; Shu-Lin Chuang; Chih-Chieh Yu; Lian-Yu Lin
Journal:  Cardiovasc Diabetol       Date:  2021-07-23       Impact factor: 9.951

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