Atrial fibrillation risk in metabolically healthy obesity: A nationwide population-based study

Lee, Hyun Jung; Lee, Seung Hwan; Han, Kyung Do; Rhee, Tae Min; Park, Chan Soon; Lee, So‐Ryoung; Choe, Won Seok; Lim, Woo Hyun; Kang, Si Hyuck; Jin, Myung; Oh, Seil

doi:10.1016/j.ijcard.2017.03.103

Cited by 70 publications

(54 citation statements)

References 35 publications

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“…Because various CVD outcomes are studied as composite outcomes, it is possible that obesity and metabolic health may have different associations with those outcomes, leading to heterogeneous results. Consistent with this statement, MHO was associated with atrial fibrillation but not with ischemic stroke when investigators used the same cohort to study these associations separately . In addition, the use of various MetS components to define metabolic health, which may or may not increase the cardiometabolic risk, could have also led to inconsistencies .…”

Section: Discussionmentioning

confidence: 93%

Association of Obesity Phenotypes with Electrocardiographic Markers of Poor Outcomes in the General Population

Ahmad

Mongraw‐Chaffin

Lewis

et al. 2019

Obesity

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Objective This study aimed to investigate the association of metabolically healthy obesity (MHO) and other obesity phenotypes with electrocardiographic (ECG) markers to understand the pathophysiological basis of increased cardiovascular disease (CVD) risk associated with these phenotypes. Methods A total of 3,700 participants (58.7 ± 13.6 years, 52% women) without CVD from the third National Health and Nutrition Examination Survey (NHANES III) were included. Logistic regression was used to examine the cross‐sectional association between obesity phenotypes (metabolically healthy without obesity [MHNO; reference], metabolically unhealthy without obesity, MHO, and metabolically unhealthy obesity) with ECG markers (PR interval, P‐wave duration, QRS duration, and QT interval). Results Higher odds of prolonged PR interval, P‐wave duration, and QRS duration were observed among all phenotypes compared with MHNO, with the highest in participants with obesity with or without metabolic syndrome. However, for QT interval, the trend of association with obesity phenotypes was as follows, from the strongest to the least strong: metabolically unhealthy obesity, metabolically healthy without obesity, and then MHO, compared with MHNO. Conclusions An association of obesity phenotypes with ECG abnormalities further raises doubt about the concept of MHO as a healthy state. Variations in associations with ECG markers may suggest that metabolic syndrome and obesity have a different relationship with different CVD outcomes and may explain some of the inconsistent CVD estimates for MHO.

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Section: Discussionmentioning

confidence: 93%

Association of Obesity Phenotypes with Electrocardiographic Markers of Poor Outcomes in the General Population

Ahmad

Mongraw‐Chaffin

Lewis

et al. 2019

Obesity

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“…To our knowledge, only two studies have investigated AF risk in relation to metabolically healthy obesity . A Swedish study followed up 4,021 participants for a mean of 13.6 years.…”

Section: Discussionmentioning

confidence: 99%

“…To the best of our knowledge, only two studies have investigated the associations between metabolically healthy obesity and AF risk, and the results were conflicting . A Swedish study suggested essentially similar risk among those with healthy and unhealthy obesity , whereas the risk for the latter group was much more pronounced in a Korean study . The Swedish study had a sample size of just over 4,000 individuals, and in both studies, follow‐up was based only on administrative health registers.…”

Section: Introductionmentioning

confidence: 99%

Metabolically Healthy Obesity and Risk for Atrial Fibrillation: The HUNT Study

Feng

Malmo

Strand

et al. 2019

Obesity

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Objective: Atrial fibrillation (AF) is the most common arrhythmia and has been described as a global epidemic. Although AF is associated with both obesity and its metabolic consequences, little is known about the association between metabolically healthy obesity and AF. Methods: In a population-based study, 47,870 adults were followed for incident AF from 2006 to 2008 until 2015. Participants were classified according to BMI and metabolic status (using waist circumference, triglycerides, high-density lipoprotein cholesterol, blood pressure, and glucose) at baseline. Results: During a median follow-up of 8.1 years, 1,758 participants developed AF. Compared with metabolically healthy individuals with BMI < 25 kg/m 2 , the multivariable-adjusted hazard ratios for metabolically healthy and unhealthy obesity were 1.6 (95% CI: 1.2 to 2.1) and 1.6 (95% CI: 1.3 to 1.9), respectively. AF risk increased according to the severity of obesity. Conclusions: Metabolically healthy and unhealthy obesity increased AF risk to a similar extent. Severity of obesity was positively associated with AF risk regardless of metabolic status.

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“…The FMI facilitates accurate classification of patients into fat mass categories and may more precisely identify those at increased risk for future heart failure, atrial fibrillation, and death [24][25][26][27][28]. Quantification of fat and lean mass provides additional prognostic information because lean mass is associated with lower risk of major adverse cardiovascular events [15].…”

Section: Discussionmentioning

confidence: 99%

Fat Mass Index Better Identifies Metabolic Syndrome: Insights from Patients in Early Outpatient Cardiac Rehabilitation

Bonikowske

Barillas-Lara

Koepp

et al. 2019

JCM

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Body mass index (BMI) does not differentiate fat and lean mass or the distribution of adipose tissue. The purpose of this study was to examine the prevalence of metabolic syndrome (MetS) among patients entering outpatient cardiac rehabilitation (CR) across fat mass index (FMI) categories compared with BMI. This retrospective cross-sectional study evaluated dual-energy x-ray absorptiometry in 483 CR patients from 1 January 2014, through 31 December 2017. Clinical data were extracted from the electronic health record. Patients were grouped by FMI and BMI categories. Mean (SD) age of patients was 64.3 (14) years. The normal FMI category had 15 patients; excess fat, 74; and obese, 384. In contrast, 93, 174, and 216 were in the normal, overweight, and obese BMI categories, respectively. Prevalence of MetS was 0 (0%) in normal, 5 (1%) in excess fat, and 167 (54%) in obese FMI, with 97% in the obese category. MetS prevalence was 4 patients (0.8%) in normal, 39 (8%) in overweight, and 129 (27%) in obese BMI categories, with 75% of MetS in the obese category. FMI more accurately classified CR patients with metabolically abnormal fat (p < 0.001). FMI is a more sensitive index than BMI for metabolically abnormal fat of outpatient CR patients.

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Atrial fibrillation risk in metabolically healthy obesity: A nationwide population-based study

Cited by 70 publications

References 35 publications

Association of Obesity Phenotypes with Electrocardiographic Markers of Poor Outcomes in the General Population

Association of Obesity Phenotypes with Electrocardiographic Markers of Poor Outcomes in the General Population

Metabolically Healthy Obesity and Risk for Atrial Fibrillation: The HUNT Study

Fat Mass Index Better Identifies Metabolic Syndrome: Insights from Patients in Early Outpatient Cardiac Rehabilitation

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