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

Prognostic Impact of Body Mass Index in Atrial Fibrillation

Background/Objectives: Contradictory results have been reported regarding the influence of obesity on the prognosis of atrial fibrillation (AF). The present study aimed to explore the potential association of body mass index (BMI) with the clinical outcomes of hospitalized patients with AF. Methods: In this retrospective, post hoc analysis of the MISOAC-AF randomized trial, 1113 AF patients were included and stratified as the following: underweight (BMI < 18 kg/m2), normal weight (BMI 18-24.9 kg/m2), overweight (BMI 25-29.9 kg/m2), and obese (BMI ≥ 30 kg/m2). The primary outcome was all-cause mortality; the secondary composite outcome was any hospitalization related to AF, heart failure (HF), or stroke. Cox regression analysis, survival analysis, and spline curve models were utilized. Results: Of the patients (median age: 76 years (IQR: 13), male: 54.6%), the majority were overweight (41.4%), followed by obese (33%), normal weight (24%), and underweight (1.6%). During a median 31-month follow-up, 436 (39.2%) patients died and 657 (59%) were hospitalized due to AF, HF, or stroke. Underweight, overweight, and obesity groups were significantly associated with an increased risk of all-cause mortality (p-values 0.02, 0.001, and <0.001, respectively), while overweight and obesity were significantly associated with the composite endpoint (p-values 0.01, <0.001, respectively) compared to normal weight. The spline curve analyses yielded that BMIs > 26.3 and > 25 were incrementally associated with all-cause mortality and the composite endpoint, respectively. A J-shaped relationship between BMI and AF prognosis was deduced. Conclusions: In conclusion, in recently hospitalized AF patients, BMI values outside the normal range were independently associated with poorer prognosis; therefore, it is essential that AF patients maintain a normal weight.

Obesity as a risk factor in atrial fibrillation and heart failure

Objectives

The aim of this article is to provide an insight into the role of obesity as a risk factor, and as a potential etiologic agent of atrial fibrillation (AF) and heart failure (HF).

Methods

A narrative (non-systematic) review article summarizing currently available data regarding the interaction between obesity, AF and HF.

Results

Obesity is considered a risk factor of AF and chronic HF. Multiple recent studies indicate that obesity is also a potential causal factor in the development of AF and HF, the elucidation of pathological mechanisms of which could help devise new diagnostic and therapeutic modalities for these conditions. The discussion about obesity in relation to HF cannot omit the so-called obesity paradox, which represents a dilemma for clinicians, and it is still a source of irregularities regarding the strategy of weight reduction in obese patients with HF. Recently, the obesity paradox has also been assumed to play a role in the relationship between obesity and thromboembolic complications of AF.

Conclusions

Obesity is an independent and modifiable risk factor for AF and HF. In addition, there is an increasing volume of experimental and clinical data that suggests an important role of the epicardial adipose tissue in the pathophysiology of AF. However, several issues, such as the issue of optimal pharmacotherapy and weight reduction strategy in obese patients with HF remains still unanswered, and open for future investigation.

Feasibility study of Glucagon-like peptide-1 analogues for the optimization of Outcomes in obese patients undergoing AbLation for Atrial Fibrillation (GOAL-AF) protocol

BACKGROUND

Catheter ablation for atrial fibrillation is recommended for symptomatic patients after failed medical therapy. Ablation has a higher failure rate in obese patients, and both the prevalence of atrial fibrillation and obesity are increasingly globally. The outcome of ablation can be improved if obese patients can achieve goal-oriented weight reduction prior to ablation. Conventional weight loss strategies, however, can be difficult to access and can delay ablation, thereby risking a lower chance of maintaining sinus rhythm. Effective weight-loss medications, such as the glucagon-like peptide inhibitor-1 drugs, offer the potential for incremental impact on weight loss over a shorter period of time as a bridging therapy. The aim of this study is to assess the feasibility of using liraglutide, a glucagon-like peptide inhibitor-1, in producing weight loss in obese patients before catheter ablation.

METHODS

The study is an open-label, uncontrolled, prospective single-centre feasibility study of daily liraglutide injections in the treatment of obese patients for at least 13 weeks before and 52 weeks after AF ablation. Adult patients with symptomatic AF whose body mass index ≥ 30 will be recruited from those planning to undergo ablation. Feasibility will be determined based on the recruitment rate, adherence to the medication, and the amount of weight loss achieved over the study period. Exploratory outcomes include changes in atrial structure, function, and fibrosis with weight loss evaluated by cardiac magnetic resonance imaging, electroanatomic mapping, and patient-reported outcome measure.

DISCUSSION

This study will allow us to determine whether the use of liraglutide in obese patients with atrial fibrillation undergoing ablation is feasible with adequate recruitment. The additional information on adherence and average weight loss over the study period will inform the design of a future definitive randomized controlled trial.

TRIAL REGISTRATION

ClinicalTrials.gov ( NCT05221229 ). Registered on 2 February 2022.

TRIAL FUNDING

Metchley Park Medical Society and University of Birmingham Starter Fellowship, British Heart Foundation Accelerator Grant, Abbott Investigator-Initiated Study Grant.

The association between triglyceride glucose-body mass index and all-cause mortality in critically ill patients with atrial fibrillation: a retrospective study from MIMIC-IV database

BACKGROUND

The TyG-BMI index, which is a reliable indicator of insulin resistance (IR), has been found to have a significant correlation with the occurrence of cardiovascular events. However, there still lacks study on the TyG-BMI index and prognosis in patients with atrial fibrillation (AF). The objective of the present study was to evaluate the relationship between TyG-BMI index at admission to ICU and all-cause mortality in critically ill patients with AF.

METHODS

The patient's data were extracted from Medical Information Mart for Intensive Care IV(MIMIC-IV) database. All patients were divided into four groups according to TyG-BMI index. Outcomes include primary and secondary endpoints, with the primary endpoint being the 30-day and 365-day all-cause mortality and the secondary endpoint being the 90-day and 180-day all-cause mortality. TyG-BMI index was quartile and Kaplan-Meier curve was used to compare the outcome of each group. Cox proportional-hazards regression model and restricted cubic splines (RCS) were conducted to assess the relationship between TyG-BMI index and outcomes.

RESULTS

Out of a total of 2509 participants, the average age was 73.26 ± 11.87 years, with 1555 (62.0%) being males. Patients with lower level of TyG-BMI had higher risk of 30-day, 90-day, 180-day and 365-day all-cause mortality, according to the Kaplan-Meier curves (log-rank P < 0.001). In addition, cox proportional-hazards regression analysis revealed that the risk of 30-day, 90-day, 180-day and 365-day all-cause mortality was significantly higher in the lowest quartile of TyG-BMI. Meanwhile, the RCS analysis indicated that L-typed relationships between TyG-BMI index and all-cause mortality, with inflection points at 223.60 for 30-day and 255.02 for 365-day all-cause mortality, respectively. Compared to patients with TyG-BMI levels below the inflection points, those with higher levels had a 1.8% lower risk for 30-day all-cause mortality (hazard ratio [HR] 0.982, 95% confidence interval [CI] 0.9676-0.988) and 1.1% lower risk for 365-day all-cause mortality (HR 0.989, 95% CI 0.986-0.991).

CONCLUSION

In critically ill patients with AF, a lower TyG-BMI level is significantly associated with a higher risk of 30-day, 90-day, 180-day and 365-day all-cause mortality. TyG-BMI index could be used as a valid indicator for grading and treating patients with AF in the ICU.

Intersection of sepsis, atrial fibrillation, and severe obesity: a population-based analysis in the United States

BACKGROUND

Atrial fibrillation (AF) is an indicator of poor prognosis in patients with sepsis and can increase the risk of stroke and mortality. Data on the impact of severe obesity on the outcomes of sepsis complicated by AF remains poorly understood.

METHODS

National Inpatient Sample (2018) and ICD-10 CM codes were used to identify the principal sepsis admissions with AF. We assessed comorbidities and outcomes of sepsis in people without obesity (BMI < 30) vs. non-severe obesity (BMI 30-35) and severe obesity (BMI > 35) cohorts. We also did a subgroup analysis to further stratify obesity based on metabolic health and analyzed the findings. The primary outcomes were the prevalence and adjusted odds of AF, AF-associated stroke, and all-cause mortality in sepsis by obesity status. Multivariable regression analyses were adjusted for patient- and hospital-level characteristics and comorbidities.

RESULTS

Our main analysis showed that of the 1,345,595 sepsis admissions, the severe obesity cohort was the youngest (median age 59 vs. non-severe 64 and people without obesity 68 years). Patients with obesity, who were often female, were more likely to have hypertension, diabetes, congestive heart failure, chronic pulmonary disease, and chronic kidney disease. The crude prevalence of AF was highest in non-severe obesity (19.9%). The adjusted odds of AF in non-severe obesity (OR 1.21; 95% CI:1.16-1.27) and severe obesity patients with sepsis (OR 1.49; 95% CI:1.43-1.55) were significantly higher than in people without obesity (p < 0.001). Paradoxically, the rates of AF-associated stroke (1%, 1.5%, and 1.7%) and in-hospital mortality (3.3%, 4.9%, and 7.1%) were lowest in the severe obesity cohort vs. the non-severe and people without obesity cohorts, respectively. On multivariable regression analyses, the all-cause mortality revealed lower odds in sepsis-AF patients with severe obesity (OR 0.78; 95% CI:0.67-0.91) or non-severe obesity (OR 0.63; 95% CI:0.54-0.74) vs. people without obesity. There was no significant difference in stroke risk.

CONCLUSIONS

A higher prevalence of cardiovascular comorbidities can be linked to a higher risk of AF in people with obesity and sepsis. Paradoxically, lower rates of stroke and all-cause mortality secondary to AF in people with obesity and sepsis warrant further investigation.

ANMCO (Italian Association of Hospital Cardiologists) scientific statement: obesity in adults-an approach for cardiologists

Obesity is a complex, chronic disease requiring a multidisciplinary approach to its management. In clinical practice, body mass index and waist-related measurements can be used for obesity screening. The estimated prevalence of obesity among adults worldwide is 12%. With the expected further increase in overall obesity prevalence, clinicians will increasingly be managing patients with obesity. Energy balance is regulated by a complex neurohumoral system that involves the central nervous system and circulating mediators, among which leptin is the most studied. The functioning of these systems is influenced by both genetic and environmental factors. Obesity generally occurs when a genetically predisposed individual lives in an obesogenic environment for a long period. Cardiologists are deeply involved in evaluating patients with obesity. Cardiovascular risk profile is one of the most important items to be quantified to understand the health risk due to obesity and the clinical benefit that a single patient can obtain with weight loss. At the individual level, appropriate patient involvement, the detection of potential obesity causes, and a multidisciplinary approach are tools that can improve clinical outcomes. In the near future, we will probably have new pharmacological tools at our disposal that will facilitate achieving and maintaining weight loss. However, pharmacological treatment alone cannot cure such a complex disease. The aim of this paper is to summarize some key points of this field, such as obesity definition and measurement tools, its epidemiology, the main mechanisms underlying energy homeostasis, health consequences of obesity with a focus on cardiovascular diseases and the obesity paradox.Level of evidence V: report of expert committees.

Increased circulating progranulin is not sufficient to induce cardiac dysfunction or supraventricular arrhythmia

Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia, and the incidence of new-onset AF has been increasing over the past two decades. Several factors contribute to the risk of developing AF including age, preexisting cardiovascular disease, chronic kidney disease, and obesity. Concurrent with the rise in AF, obesity has followed the same two-decade trend. The contribution of circulating proteins to obesity-related AF is of particular interest in the field. In this study, we investigated the effects of increased circulating levels of the glycoprotein progranulin on the development of supraventricular arrhythmias and changes to cardiac function. AAV8-mediated overexpression of full-length mouse progranulin was used to increase plasma protein levels and determine susceptibility to supraventricular arrhythmias and changes in cardiac structure and function. C57Bl/6N mice were subjected to increased circulating levels of progranulin for 20 weeks. Cardiac conduction was evaluated by surface ECG with and without isoproterenol challenge, and cardiac structure and function were measured by echocardiography after 20 weeks of circulating progranulin overexpression. Increased circulating levels of progranulin were maintained throughout the 20-week study. The cardiac structure and function remained unchanged in mice with increased circulating progranulin. ECG indices (P wave duration, P amplitude, QRS interval) were unaffected by increased progranulin levels and no arrhythmogenic events were observed following the isoproterenol challenge. In our model, increased levels of circulating progranulin were not sufficient to induce changes in cardiac structure and function or elicit ECG abnormalities suggestive of susceptibility to supraventricular arrhythmias.

Association of predicted body composition with occurrence of atrial fibrillation

Background

Body mass index (BMI) is insufficient evidence as a risk factor for numerous health disorders. Body composition may be more appropriate for confirming the association with cardiovascular diseases, including atrial fibrillation (AF). This study aimed to examine the association between body composition and the occurrence of AF.

Methods

A total of 2,673,108 participants (48.6% women) without AF at baseline from the Korean national health insurance data were included. Body composition including appendicular skeletal muscle mass, body fat mass, and lean body mass were indirectly measured through validated anthropometric prediction equations. The diagnosis of AF and comorbidities were defined.

Results

With a median of 9.5 (interquartile range 9.2-10.1) years' follow-up, 25,841 (0.96%) cases of incident AF were included. In multivariable analysis, higher appendicular skeletal muscle was related to low risk of AF [hazard ratio (HR) 0.829, 95% confidence interval (CI) 0.753-0.912 for men (fifth quintile) and HR 0.888, 95% CI 0.792-0.995 for women (fifth quintile)]. In contrast, a higher body fat mass [HR 1.345, 95% CI 1.221-1.483 for men (fifth quintile) and HR 1.420, 95% CI 1.274-1.591 for women (fifth quintile)] and lean body mass [HR 2.241, 95% CI 2.182-2.303 for men (fifth quintile) and HR 1.516, 95% CI 1.368-1.667 for women (fifth quintile)] were associated with the occurrence of AF.

Conclusions

In this study, body composition parameters were associated with the occurrence of AF. It should be noted that when appendicular skeletal muscle mass decreases and body fat mass and lean body mass increase, the risk of AF may be increased in general population except underweighted BMI group.

Obesity phenotypes and cardiovascular risk: From pathophysiology to clinical management

Obesity epidemic reached the dimensions of a real global health crisis with more than one billion people worldwide living with obesity. Multiple obesity-related mechanisms cause structural, functional, humoral, and hemodynamic alterations with cardiovascular (CV) deleterious effects. A correct assessment of the cardiovascular risk in people with obesity is critical for reducing mortality and preserving quality of life. The correct identification of the obesity status remains difficult as recent evidence suggest that different phenotypes of obesity exist, each one associated with different degrees of CV risk. Diagnosis of obesity cannot depend only on anthropometric parameters but should include a precise assessment of the metabolic status. Recently, the World Heart Federation and World Obesity Federation provided an action plan for management of obesity-related CV risk and mortality, stressing for the instauration of comprehensive structured programs encompassing multidisciplinary teams. In this review we aim at providing an updated summary regarding the different obesity phenotypes, their specific effects on CV risk and differences in clinical management.

Obesity and atrial fibrillation: a narrative review from arrhythmogenic mechanisms to clinical significance

The prevalence of obesity and atrial fibrillation (AF), which are inextricably linked, is rapidly increasing worldwide. Obesity rates are higher among patients with AF than healthy individuals. Some epidemiological data indicated that obese patients were more likely to develop AF, but others reported no significant correlation. Obesity-related hypertension, diabetes, and obstructive sleep apnea are all associated with AF. Additionally, increased epicardial fat, systemic inflammation, and oxidative stress caused by obesity can induce atrial enlargement, inflammatory activation, local myocardial fibrosis, and electrical conduction abnormalities, all of which led to AF and promoted its persistence. Weight loss reduced the risk and reversed natural progression of AF, which may be due to its anti-fibrosis and inflammation effect. However, fluctuations in weight offset the benefits of weight loss. Therefore, the importance of steady weight loss urges clinicians to incorporate weight management interventions in the treatment of patients with AF. In this review, we discuss the epidemiology of obesity and AF, summarize the mechanisms by which obesity triggers AF, and explain how weight loss improves the prognosis of AF.

Associations of adenovirus-reactive immunoglobulins with atrial fibrillation and body mass index

Adenovirus (AdV) has been suggested to be involved in pathogenesis of atrial fibrillation (AF). We aimed to evaluate an association between AdV-specific immunoglobulins G in the serum (AdV-IgG) and AF. The present case-control study comprised two cohorts, including cohort 1 of patients with AF and cohort 2 of asymptomatic subjects. Initially, two groups, MA and MB, were selected from the cohorts 1 and 2, respectively, for serum proteome profiling using an antibody microarray to identify possible relevant protein targets. The data of microarray analysis indicated a possible overall increase in the total adenovirus signals in the group MA vs. group MB, suggesting potential relevance of adenoviral infection to AF. Then, the groups A (with AF) and B (control) were selected from the cohorts 1 and 2, respectively, to assay the presence and levels of AdV-IgG- by ELSA. The prevalence of AdV-IgG-positive status demonstrated a 2-fold increase in the group A (AF) compared with that in the group B (asymptomatic subjects); odds ratio 2.06 (95%CI: 1.11-3.84; P = 0.02). The prevalence of obesity demonstrated an approximately 3-fold increase in AdV-IgG-positive patients of the group A compared with that in AdV-IgG-negative patients of the same group A (odds ratio 2.7; 95% CI: 1.02-7.1; P = 0.04). Thus, AdV-IgG-positive reactivity was independently associated with AF, and AF was independently associated with BMI, indicating that adenoviral infection may be a possible etiological factor for AF.

Associations of metabolic heterogeneity of obesity with frailty progression: Results from two prospective cohorts

BACKGROUND

Previous studies indicated that obesity would accelerate frailty progression. However, obesity is heterogeneous by different metabolic status. The associations of metabolic heterogeneity of obesity with frailty progression remain unclear.

METHODS

A total of 6730 participants from the China Health and Retirement Longitudinal Study (CHARLS) and 4713 from the English Longitudinal Study of Ageing (ELSA) were included at baseline. Metabolic heterogeneity of obesity was evaluated based on four obesity and metabolic phenotypes as metabolically healthy normal weight (MHNW), metabolically unhealthy normal weight (MUNW), metabolically healthy overweight/obesity (MHOO), and metabolically unhealthy overweight/obesity (MUOO). Frailty status was assessed by the frailty index (FI) ranging from 0 to 100 and frailty was defined as FI ≥ 25. Linear mixed-effect models were used to analyse the associations of metabolic heterogeneity of obesity with frailty progression.

RESULTS

In the CHARLS, MUOO and MUNW presented the accelerated FI progression with additional annual increases of 0.284 (95% CI: 0.155 to 0.413, P < 0.001) and 0.169 (95% CI: 0.035 to 0.303, P = 0.013) as compared with MHNW. MHOO presented no accelerated FI progression (β: -0.011, 95% CI: -0.196 to 0.173, P = 0.904) as compared with MHNW. In the ELSA, the accelerated FI progression was marginally significant for MUOO (β: 0.103, 95% CI: -0.005 to 0.210, P = 0.061) and MUNW (β: 0.157, 95% CI: -0.011 to 0.324, P = 0.066), but not for MHOO (β: -0.047, 95% CI: -0.157 to 0.062, P = 0.396) in comparison with MHNW. The associations of MUOO and MUNW with the accelerated FI progression were stronger after excluding the baseline frail participants in both cohorts. The metabolic status changed over time. When compared with stable MHNW, participants who changed from MHNW to MUNW presented the accelerated FI progression with additional annual increases of 0.356 (95% CI: 0.113 to 0.599, P = 0.004) and 0.255 (95% CI: 0.033 to 0.477, P = 0.024) in the CHARLS and ELSA, respectively. The accelerated FI progression was also found in MHOO participants who transitioned to MUOO (CHARLS, β: 0.358, 95% CI: 0.053 to 0.663, P = 0.022; ELSA, β: 0.210, 95% CI: 0.049 to 0.370, P = 0.011).

CONCLUSIONS

Metabolically unhealthy overweight/obesity and normal weight, but not metabolically healthy overweight/obesity, accelerated frailty progression as compared with metabolically healthy normal weight. Regardless of obesity status, transitions from healthy metabolic status to unhealthy metabolic status accelerated frailty progression as compared with stable metabolically healthy normal weight. Our findings highlight the important role of metabolic status in frailty progression and recommend the stratified management of obesity based on metabolic status.

Long-term metabolic fate and mortality in obesity without metabolic syndrome

BACKGROUND

Obesity and metabolic syndrome (MetS) are known to expose to atrial fibrillation (AF), cardiovascular diseases (CVD) and mortality. Metabolically healthy obesity refers to obesity without MetS. This study aimed to investigate how obesity and MetS modify the risk of CVD, AF and mortality in very long-time follow-up.

METHODS

Finnish middle-aged subjects (n = 1045) were grouped into four subgroups according to the presence of obesity and MetS. CVD events and AF were followed for 24 years and total mortality for 30 years. Moreover, 600 available patients had a follow-up visit for metabolic examinations after approximately 22 years.

RESULTS

One-hundred and sixty-two (30%) subjects without obesity or MetS died during the follow-up. Ninety-two (17%) of the patients in this group had a CVD event and 58 (11%) were diagnosed with AF. As compared to them, obese subjects without MetS had similar metabolic fate and mortality (mortality 26 (38%), p = .143; CVD event 12 (18%), p = .858 and AF 7 (10%), p = .912, respectively), whereas subjects with obesity and MetS had greater mortality (102 (49%), p < .001), more CVD (71 (34%), p < .001) and AF (49 (23%), p < .001). Non-obese individuals with MetS had greater rates of mortality (96 (44%), p < .001) and CVD (80 (37%), p < .001), but not of AF (26 (12%), p = .606). Of the 40 subjects with obesity but without MetS at baseline and available for the follow-up visit, 15 (38%) were metabolically healthy at the follow-up visit.

CONCLUSIONS

In the present long-term follow-up study, the presence of MetS, but not obesity only, implies a greater risk of mortality and CVD. The risk of AF is increased only in subjects with both obesity and MetS. However, obesity without MetS tends to progress eventually to obesity with MetS. Key messagesThe presence of metabolic syndrome (MetS), but not obesity only, entails a greater risk of mortality and cardiovascular diseases.The risk of atrial fibrillation is increased only in subjects with both obesity and MetS.Obesity without MetS tends to progress eventually to obesity with MetS.

Effects of Blood Pressure According to Age on End-Stage Renal Disease Development in Patients With Diabetes: A Nationwide Population-Based Cohort Study

Background:

Recent hypertension guidelines have recommended lower blood pressure (BP) targets in high-risk patients. However, there are no specific guidelines based on age or systolic and diastolic blood pressure (SBP and DBP, respectively). We aimed to assess the effects of age-related BP on development of end-stage renal disease (ESRD) in patients with diabetes.

Methods:

A total of 2 563 870 patients with diabetes aged >20 years were selected from the Korean National Health Screening Program from 2009 to 2012 and followed up until the end of 2019. Participants were categorized into age and BP groups, and the hazard ratios for ESRD were calculated.

Results:

During a median follow-up of 7.15 years, the incidence rates of ESRD increased with increasing SBP and DBP. The hazard ratio for ESRD was the highest in patients younger than 40 years of age with DBP≥100 mm Hg. The effect of SBP and DBP on ESRD development was attenuated with age (interaction P was <0.0001 for age and SBP, and 0.0022 for age and DBP). The subgroup analysis for sex, antihypertension medication, and history of chronic kidney disease showed higher hazard ratios for ESRD among males, younger than 40 years, not taking antihypertension medications and chronic kidney disease compared to those among females, older than 40 years, antihypertension medication, and nonchronic kidney disease groups.

Conclusions:

Higher SBP and DBP increase the risk of developing ESRD in patients with diabetes, and in particular, younger individuals face greater risk. Therefore, intensive BP management is warranted in younger patients to prevent ESRD.

Transition of Metabolic Phenotypes and Risk of Atrial Fibrillation According to BMI: Kailuan Study

Objective

Atrial fibrillation (AF) is associated with both obesity and its metabolic consequences. However, there is a paucity of information on whether the dynamic change of metabolic health and obesity phenotypes affect the risk of AF. We aimed to prospectively examine the association between metabolic health and its change over time and AF risk across body mass index (BMI) categories.

Methods

A total of 58,483 participants without history of cancer, and cardiovascular diseases from the Kailuan study were included in the present study. Transition of metabolic phenotypes was evaluated between 1st survey (2006–2007) and the 2nd survey (2008–2009). The hazard ratios (HRs) and 95% confidence intervals (CIs) for AF were assessed by Cox proportional hazards regression.

Results

During a median follow-up of 3 years, we documented 580 cases of AF. Compared with metabolically healthy individuals with normal weight, the multivariable-adjusted hazard ratios for metabolically healthy and unhealthy overweight/obese were 1.27 (95% CI: 1.01, 1.59) and 1.37 (95% CI: 1.09, 1.72), respectively. However, when transition was taken into account, overweight/obese people who maintained metabolically healthy status were not associated with increased long-term risk (HR, 1.11;95% CI: 0.70, 1.78), whereas participants who converted from metabolically healthy overweight/obese status to an unhealthy phenotype had higher AF risk than those who maintained metabolically healthy normal weight (HR 1.59, 95% CI: 1.11, 2.26). When BMI and metabolically healthy status were updated over the course of the study, significant short-term elevations in AF risk were associated with individuals with stable MU-OW/OB status.

Conclusion

In this community-based cohort study, metabolically healthy overweight/obese individuals have increased risks of AF. Obesity remains a risk factor for AF independent of major metabolic factors. Our data further suggested that metabolic phenotype was a dynamic condition, and maintenance of metabolic health and normal weight might alleviate the risk of AF.

Body Mass Index and the Risk of Atrial Fibrillation: A Mendelian Randomization Study

Although observational studies have shown positive associations between body mass index (BMI) and the risk of atrial fibrillation (AF), the causal relationship is still uncertain owing to the susceptibility to confounding and reverse causation. This study aimed to examine the potential causality of BMI on AF by conducting a two-sample Mendelian randomization (TSMR) study.

METHODS

The independent genetic variants associated with BMI (n = 303) at the genome-wide significant level were derived as instrumental variables (IV) from the Genetic Investigation of Anthropometric Traits (GIANT) consortium consisting of 681,275 individuals of European ancestry. We then derived the outcome data from a GWAS meta-analysis comprised of 60,620 cases and 970,216 controls of European ancestry. The TSMR analyses were performed in five methods, namely inverse variance weighted (IVW) method, MR-Egger regression, the weighted median estimator (WME), the generalized summary data-based Mendelian randomization (GSMR), and the robust adjusted profile score (RAPS), to investigate whether BMI was causally associated with the risk of AF.

RESULTS

We found a genetically determined 1-standard deviation (SD) increment of BMI causally increased a 42.5% risk of AF (OR = 1.425; 95% CI, 1.346 to 1.509) based on the IVW method, which was consistent with the results of MR-Egger regression, WME, GSMR, as well as RAPS. The Mendelian randomization assumptions did not seem to be violated.

CONCLUSION

This study provides evidence that higher BMI causally increased the risk of AF, suggesting control of BMI and obesity for prevention of AF.

Effect of weight loss on recurrence of atrial fibrillation after ablative therapy: a systematic review and meta-analysis

BACKGROUND

Landmark trials have shown superiority of ablative therapy over medical therapy in certain subpopulation with atrial fibrillation (AF). Previous studies have demonstrated an association between weight loss and reduced rates of recurrence of AF after ablation. The objective of this study is to determine if weight loss reduces the recurrence of AF after ablation.

METHODS

An extensive literature search and systematic review of studies of weight loss on recurrence of AF after ablative therapy was performed. Risk ratio (RR) and 95% confidence intervals were measured for weight loss group versus control group in each study, and comparative analysis as well as subgroup analysis was made.

RESULTS

Eight studies with a total of 1,425 patients were included. Overall, studies of patients who lost weight demonstrated lower recurrence of AF (RR 0.35; 95% CI 0.18-0.67). However, subgroup analysis of studies which included patients who lost ≥10% weight loss from baseline showed lower recurrence of AF (RR 0.18; 95% 0.03-0.89), whereas studies which included patients with <10% weight loss did not (RR 1.00; 95% 0.51-1.96). Studies of patients who had less than 12-month history of AF (RR 0.24; 95% CI 0.11-0.57) and those who lost weight prior to ablation (RR 0.40; 95% CI 0.20-0.79) also had lower recurrence of AF.

CONCLUSION

Weight loss is associated with lower long-term recurrence of AF after ablative therapy. Studies of patients with ≥10% weight loss, less than 12-month history of AF, and weight loss prior to ablation experience lower recurrence of AF.

A Bayesian Network Analysis of the Probabilistic Relationships Between Various Obesity Phenotypes and Cardiovascular Disease Risk in Chinese Adults: Chinese Population-Based Observational Study

BACKGROUND

Cardiovascular disease (CVD) risk among individuals with different BMI levels might depend on their metabolic health. The extent to which metabolic health status and BMI affect CVD risk, either directly or through a mediator, in the Chinese population remains unclear.

OBJECTIVE

In this study, the Bayesian network (BN) perspective is adopted to characterize the multivariable probabilistic connections between CVD risk and metabolic health and obesity status and identify potential factors that influence these relationships among Chinese adults.

METHODS

The study population comprised 6276 Chinese adults aged 30 to 74 years who participated in the China Health and Nutrition Survey 2009. BMI was used to categorize participants as normal weight, overweight, or obese, and metabolic health was defined by the Adult Treatment Panel-3 criteria. Participants were categorized into 6 phenotypes according to their metabolic health and BMI categorization. The 10-year risk of CVD was determined using the Framingham Risk Score. BN modeling was used to identify the network structure of the variables and compute the conditional probability of CVD risk for the different metabolic obesity phenotypes with the given structure.

RESULTS

Of 6276 participants, 64.67% (n=4059), 20.37% (n=1279), and 14.95% (n=938) had a low, moderate, and high 10-year CVD risk. An averaged BN with a stable network structure was constructed by learning 300 bootstrapped networks from the data. Using BN reasoning, the conditional probability of high CVD risk increased as age progressed. The conditional probability of high CVD risk was 0.43% (95% CI 0.2%-0.87%) for the 30 to 40 years age group, 2.25% (95% CI 1.75%-2.88%) for the 40 to 50 years age group, 16.13% (95% CI 14.86%-17.5%) for the 50 to 60 years age group, and 52.02% (95% CI 47.62%-56.38%) for those aged ≥70 years. When metabolic health and BMI categories were instantiated to their different statuses, the conditional probability of high CVD risk increased from 7.01% (95% CI 6.27%-7.83%) for participants who were metabolically healthy normal weight to 10.47% (95% CI 7.63%-14.18%) for their metabolically healthy obese (MHO) counterparts and up to 21.74% and 34.48% among participants who were metabolically unhealthy normal weight and metabolically unhealthy obese (MUO), respectively. Sex was a significant modifier of the conditional probability distribution of metabolic obesity phenotypes and high CVD risk, with a conditional probability of high CVD risk of only 2.02% and 22.7% among MHO and MUO women, respectively, compared with 21.92% and 48.21% for their male MHO and MUO counterparts, respectively.

CONCLUSIONS

BN modeling was applied to investigate the relationship between CVD risk and metabolic health and obesity phenotypes in Chinese adults. The results suggest that both metabolic health and obesity status are important for CVD prevention; closer attention should be paid to BMI and metabolic status changes over time.

Graves' disease, its treatments, and the risk of atrial fibrillation: A Korean population-based study

BACKGROUND

Atrial fibrillation (AF) is occasionally diagnosed in individuals with Graves' disease. Definite treatments, including radioactive iodine therapy (RAIT) or surgery might lower the risk of AF in the literature. However, no studies have compared the effects of anti-thyroid drugs (ATDs), RAIT, and surgery on the risk of AF.

METHODS

This retrospective cohort study included 94,060 newly diagnosed Graves' disease patients and 470,300 controls from the Korean National Health Insurance database. The incidence of AF was evaluated in patients and controls. Patients were categorized based on treatment method into ATD (95.6%), RAIT (3.5%), and surgery (0.9%) groups. In the ATD group, the dose and duration of ATDs were calculated for each patient. In the RAIT and surgery groups, remission was defined as levothyroxine prescription.

RESULTS

Graves' disease patients had a 2.2-fold higher risk of developing AF than controls. Regardless of demographic factors, the patient group had a consistently higher risk of AF than controls, with the highest risk of AF (HR, 5.49) in the younger patient group. The surgery group had a similar risk of AF compared with controls, whereas the ATD (HR, 2.23) and RAIT (HR, 2.00) groups had increased risks of AF, even in patients reaching hypothyroid status after RAIT. Patients with higher dose or longer treatment duration of ATDs were at greater risk of AF.

CONCLUSION

We observed differing risks of AF according to methods of treatment for Graves' disease, and that definite treatment can be an option for subjects needing sustained medical treatment considering the risk of AF.

Underweight and Weight Change Increases End-Stage Renal Disease Risk in Patients with Diabetes: A Nationwide Population-Based Cohort Study

Weight variability has known as a risk factor for cardiovascular events and mortality. However, its effect on end-stage renal disease (ESRD) development remains controversial. We investigated the relationship between weight change and ESRD risk. Overall, 97,029 patients with DM aged >20 years were selected from the Korean National Health Screening Program 2009–2012. Weight change was defined as differences in body weight from the index year to 2 years later. Newly diagnosed ESRD was observed until 2017 end. Over a 5.1-year median follow-up period, ESRD was newly diagnosed in 7932 (4.81%) DM patients. BMI < 18.5 kg/m² and waist circumferences <85/80 and >100/95 cm were ESRD risk factors. ESRD risk increased with increasing weight change; ≥10% weight loss (hazard ratio [HR], 1.247) followed by ≥10% weight gain (1.247) was associated with a higher HR than ≤5% weight change after adjusting for several confounding factors. The association between weight change and ESRD risk in a subgroup analysis was significantly stronger in patients aged <65 years, without proteinuria, with BMI ≥ 25, with DM duration <5 years, and prescribed less than 3 classes of DM medication. Underweight patients showed higher ESRD risks than overweight patients. Weight loss >10% was associated with the fastest decline in renal function.

Occurrence of Arrhythmias in Women with Thyroid Cancer Receiving Suppressive Doses of Levothyroxine

Aim of the study: To assess the occurrence of cardiac arrhythmias caused by high doses of levothyroxine in patients with thyroid cancer with subclinical hyperthyroidism. Materials and Methods: This prospective study included 98 women divided into three groups according to plasma thyroid stimulating hormone (TSH) concentration: <0.1 µU/mL, 0.1–0.39 µU/mL, or 0.4–4.0 µU/mL (control group). All participants underwent laboratory tests and an electrocardiography (ECG) Holter test to assess their heart rate and the occurrence of arrhythmias. Statistical analysis assessed differences between groups in all clinical parameters and factors influencing the occurrence of arrhythmias. Results: There were no differences between groups in the maximum, average, or minimum heart rate or in the incidence of the studied cardiac arrhythmias. Heart rate in women with a TSH concentration of <0.1 µU/mL depended on age and the presence of arterial hypertension, and heart rate in women with a TSH concentration of 0.4–4.0 µU/mL depended on free triiodothyronine concentration and the presence of arterial hypertension; no relationship was identified for women with a TSH concentration of 0.1–0.39 µU/mL. One-way logistic regression analysis did not identify any factors influencing the occurrence of arrhythmias. Conclusions: While maintaining normal free triiodothyronine levels, the use of suppressive doses of levothyroxine after thyroidectomy for differentiated thyroid cancer does not induce clinically significant arrhythmias or affect average heart rate. None of the studied clinical parameters influenced the risk of arrhythmia.

Obesity and Atrial Fibrillation: Epidemiology, Pathogenesis and Effect of Weight Loss

The obesity epidemic continues its relentless advance and is paralleled by an increase in the incidence of AF. Several epidemiological studies have highlighted obesity as an independent risk factor for the development of AF. This relationship is likely multifactorial through a number of interacting mechanisms. Weight loss through lifestyle changes or surgery has been associated with reverse remodelling of the atrial substrate and subsequent reduction in AF, making it an essential pillar in the management of AF in obese patients. In this review, the epidemiological data that support the obesity–AF relationship, the current insights into the underlying pathophysiological mechanism, the impact of weight loss on reverse remodelling and AF reduction, and the strategies to achieve weight loss in patients with AF are discussed.

Obesity phenotypes and their relationships with atrial fibrillation

Background

This study assessed the associations of metabolic obesity phenotypes with the risk of atrial fibrillation (Afib).

Methods

This prospective cohort study categorized Taiwanese adults according to their body mass index (BMI) and metabolic health status at baseline. We assigned the participants to the underweight (BMI < 18.5 kg/m²), normal weight (BMI = 18.5-23.9 kg/m²), and overweight/obesity groups (BMI ≥ 24 kg/m²). Metabolically healthy was defined as absence of hypertension, diabetes, and hyperlipidemia and the presence of healthy metabolic profiles.

Results

In total, 5,742 adults were included. During a median follow-up of 13.7 years, 148 patients developed Afib. Compared to the metabolically healthy normal weight group, the risk of Afib was significantly higher than those in the metabolically unhealthy overweight/obesity (hazard ratio = 2.20, 95% confidence interval [1.12-4.33]) and metabolically unhealthy normal weight groups (HR = 2.64, 95% CI [1.34-5.17]). Additionally, the point estimate suggested a 1.97-fold greater risk among the metabolically healthy overweight/obesity group, although this difference was not significant given the wide confidence interval (HR = 1.97, 95% CI [0.80-4.86]).

Conclusion

Our results demonstrated the relationships of metabolic health and weight regarding the risk of Afib in Taiwanese adults. The Afib risk among metabolic and obesity phenotypes is associated with a metabolically unhealthy status. A trend toward a higher Afib risk with obesity among metabolically healthy subjects was observed. However, the result was not robust and it still suggested further study.

Association Between Change in Metabolic Syndrome Status and Risk of Incident Atrial Fibrillation: A Nationwide Population-Based Study

Backgroud There is a paucity of information on whether changes in metabolic syndrome (MetS) status affect the risk of new-onset atrial fibrillation (AF). We aimed to evaluate whether changes in MetS status and components of MetS affect AF risk using data from a nationwide observational cohort. Methods and Results A total of 7 565 531 adults without prevalent AF (mean age, 47±14 years) who underwent 2 serial health examinations by the Korean National Health Insurance Cooperation were identified. The patients were categorized into 4 groups according to the change in MetS status in serial evaluations, as follows: patients with persistent MetS (n=1 388 850), healthy patients newly diagnosed with MetS in the second evaluation (n=608 158), patients with MetS who were healthy in the second evaluation (n=798 555), and persistently healthy individuals (n=4 769 968). During a mean 7.9-year follow-up, incident AF was diagnosed in 139 305 (1.8%) patients. After multivariable adjustment, the AF risk was higher by 31% in the patients with persistent MetS , 26% in the patients with MetS who were healthy in the second evaluation, and 16% in the healthy patients newly diagnosed with MetS in the second evaluation compared with the persistently healthy individuals. Regardless of the MetS component type, the AF risk correlated with changes in the number of components. The risk of AF was strongly correlated with MetS status changes in the young and middle-age groups (20-39 years and 40-64 years, respectively) than in the elderly group (≥65 years). Conclusions Dynamic changes in MetS status and persistent MetS were associated with an increased risk of AF in a large-scale Asian population.

Healthy Food on Instagram Social Network: Vegan, Homemade and Clean Eating

Social media platforms have become part of many people's lives. Users are spending more and more time on these platforms, creating an active and passive digital footprint through their interaction. This footprint has high research potential in many research areas because understanding people's communication on social media is essential in understanding their values, attitudes, experiences and behaviors. Researchers found that the use of social networking sites impacts adolescents' eating behavior. If we define adolescents as individuals between ages 10 and 24 (WHO's definition), 76% of USA young people at age 18-⁠24 use Instagram, so the Instagram social network analysis is important for understanding young people's expressions in the context of healthy food. This study aims to identify the main topic associated with healthy food on the Instagram social network via hashtag and community analysis based on 2,045,653 messages created by 427,936 individual users. The results show that users most associate Healthy food with healthy lifestyle, fitness, weight loss and diet. In terms of food, these are foods that are Vegan, Homemade, Clean and Plant-based. Given that young people change their behavior in relation to people's behavior on social networks, it is possible to use this data to predict their future association with healthy food characteristics.

Healthy Food on the Twitter Social Network: Vegan, Homemade, and Organic Food

Online social networks have become an everyday aspect of many people’s lives. Users spend more and more time on these platforms and, through their interactions on social media platforms, they create active and passive digital footprints. These data have a strong potential in many research areas; indeed, understanding people’s communication on social media is essential for understanding their attitudes, experiences, behaviors and values. Researchers have found that the use of social networking sites impacts eating behavior; thus, analyzing social network data is important for understanding the meaning behind expressions used in the context of healthy food. This study performed a communication analysis of data from the social network Twitter, which included 666,178 messages posted by 168,134 individual users. These data comprised all tweets that used the #healthyfood hashtag between 2019 and 2020 on Twitter. The results revealed that users most commonly associate healthy food with a healthy lifestyle, diet, and fitness. Foods associated with this hashtag were vegan, homemade, and organic. Given that people change their behavior according to other people’s behavior on social networks, these data could be used to identify current and future associations with current and future perceptions of healthy food characteristics.

High Bodyweight Variability Increases Depression Risk in Patients With Type 2 Diabetes Mellitus: A Nationwide Cohort Study in Korea

Objectives: Although obesity is associated with increased risk for depression in patients with type 2 diabetes mellitus (DM), the relationship between body weight variability (BWV) and depression remains poorly studied. This study was to investigate the incidence of depression in patients with type 2 DM according to their BWV. Methods: Intraindividual variation in body weight were measured in the nationwide, population-based retrospective cohort of 540,293 patients with type 2 DM from the Korean national health insurance system between 2009 and 2010. The diagnoses of new-onset depression occurring until the end of 2017 were ascertained. Risk of new-onset depression was examined using multivariate-adjusted Cox proportional hazards regression analysis by BWV quartile. Results: 93,149 (17.2%) patients developed new-onset depression for the follow up. BWV was significantly associated with an increased risk of depression after adjusting for confounding factors. The highest BWV quartile group had a hazard ratio (HR) of 1.17 (95% CI 1.15-1.19) compared to the lowest BWV quartile group as a reference. Obese patients in the highest BWV quartile group showed 12% increased risk of depression (HR 1.12, 95% CI 1.09-1.15) while non-obese patients in the highest BWV quartile group showed 20% increased risk of depression (HR: 1.20, 95% CI: 1.17-1.23) compared to their respective lowest BWV quartile groups. Conclusion: A higher BWV was significantly associated with an increased risk of depression in patients with type 2 DM. Thus, BWV may serve as an indicator for early detection of depression in type 2 DM patients.

Comparison of the Incidence of Cardiovascular Diseases in Weight Groups with Healthy and Unhealthy Metabolism

BACKGROUND

We aimed to identify the relationship between metabolically healthy obesity (MHO), a special subtype of obesity, and the incidence of cardiovascular disease (CVD) in rural Xinjiang.

METHODS

Body mass index (BMI) and the Joint Interim Statement criteria were utilized to define obesity and metabolic status, respectively. A baseline survey was conducted between 2010 and 2012. The cohort was followed-up until 2017, including 5059 participants (2953 Uyghurs and 2106 Kazakhs) in the analysis.

RESULTS

During 6.78 years of follow-up, 471 individuals developed CVD, 10.8% (n=545) of whom were obese, and the prevalence of MHO and MHNW was 5.2% and 54.5%, respectively. Compared with metabolically healthy normal weight subjects, the subjects with MHO had an increased risk of CVD (hazard ratio [HR]=1.76, 95% confidence interval [CI]: 1.23-2.51), while the metabolically unhealthy obesity (MUO) group had an even higher risk (HR=3.80, 95% CI: 2.87-5.03). Additionally, there were sex differences in the relationship between BMI-metabolic status and incident CVD (P _interaction =0.027). Compared with the subjects with MHO, those with MUO had an increased risk of CVD (HR=1.84, 95% CI: 1.26-2.71).

CONCLUSION

MHO was associated with a high risk of CVD among adults in rural Xinjiang. In each BMI category, metabolically unhealthy subjects had a higher risk of developing CVD than did metabolically healthy subjects.

A Review of Obesity, Physical Activity, and Cardiovascular Disease

PURPOSE OF REVIEW

The focus of this review is to discuss obesity, physical activity (and physical inactivity/sedentary behavior), cardiovascular disease (CVD), and their often interrelated health implications. The authors summarize the pathophysiological changes associated with obesity, which lead to the development of CVD, recommendations for interventions such as diet, increased physical activity, and weight loss according to current literature and guidelines, and the critical importance of cardiorespiratory fitness (CRF).

RECENT FINDINGS

Clinical trials continue to demonstrate improved outcomes among overweight or obese individuals who achieve a healthy weight using various methods. Increasing CRF levels appears to demonstrate the largest health improvements, regardless of underlying comorbidities or achieving weight loss. CRF, which is perhaps the single most important predictor of overall health, seems more important than weight loss alone regarding improved CVD outcomes in the obese population. These findings are reproduced in studies involving patients with various forms of CVD and CVD risk factors. The importance of CRF is well established; future endeavors to establish specific CRF targets for various patient cohorts are needed.

Hospitalization for heart failure incidence according to the transition in metabolic health and obesity status: a nationwide population-based study

BACKGROUND

We aimed to investigate the hazard of hospitalization for heart failure (hHF) according to the transitions in metabolic health and obesity status.

METHODS

The Korean National Health Insurance Service datasets from 2002 to 2017 were used for this nationwide, longitudinal, population-based study. The hazard of hHF was analyzed according to the eight groups stratified by stability in metabolic health and transition in obesity status among initially metabolically healthy adults who underwent two cycles of health examinations in 2009-2010 and 2013-2014 (N = 7,148,763).

RESULTS

During two examinations, 48.43% of the initially metabolically healthy obese (MHO) individuals and 20.94% of the initially metabolically healthy non-obese (MHNO) individuals showed changes in their metabolic health and obesity status. During a mean follow-up of 3.70 years, 3151 individuals were hospitalized for HF. When stable MHNO individuals were set as the reference, transition to metabolically unhealthy phenotype was associated with an increased hazard of hHF; the hazard ratio (HR) and 95% confidence interval (CI) in the individuals who transformed from MHO to metabolically unhealthy non-obese was 2.033 (1.579-2.616). The constant MHO group had a 17.3% increased hazard of hHF compared with the stable MHNO group [HR (95% CI) 1.173 (1.039-1.325)]. Individuals who shifted from MHO to MHNO showed a 34.3% lower hazard of hHF compared with those who maintained the MHO category [HR (95% CI) 0.657 (0.508-0.849)].

CONCLUSION

Dynamic changes in metabolic health and obesity status were observed during a relatively short interval of 3-5 years. Loss of metabolic health was significantly associated with an increased hazard of hHF. Even if metabolic health was maintained, persistent obesity remained as a risk factor for hHF, and transition from MHO to MHNO had a protective effect against hHF. Therefore, the prevention and control of obesity while maintaining metabolic health would be crucial in preventing hHF.

High variability in bodyweight is associated with an increased risk of atrial fibrillation in patients with type 2 diabetes mellitus: a nationwide cohort study

Background

Bodyweight variability is a risk factor for atrial fibrillation (AF). We aimed to examine the relationship between bodyweight variability and the risk of AF in patients with type 2 diabetes mellitus (DM), and whether this relationship was affected by baseline body mass index (BMI), weight change, or advanced diabetic stage.

Methods

A nationwide population-based cohort of 670,797 patients with type 2 DM from the Korean National Health Insurance Service database without a history of AF and with ≥ 3 measurements of bodyweight over a 5-year period were followed up for AF development. Intra-individual bodyweight variability was calculated using variability independent of mean, and high bodyweight variability was defined as the quintile with the highest variability with the lower four quintiles as reference.

Results

During a median of 7.0 years of follow-up, 22,019 patients (3.3%) newly developed AF. After multivariate adjustment, those in the highest quintile of bodyweight variability showed a higher risk of incident AF (HR 1.16, 95% CI 1.12–1.20) compared to those in the lower 4 quintiles with reference bodyweight variability, irrespective of baseline BMI group and direction of overall weight change. This association was greater in magnitude in subjects with lower BMI, those on insulin, and those with a DM duration of greater than 5 years. In sensitivity analyses, high bodyweight variability was consistently associated with AF development using other indices of variability and adjusting for glycemic variability.

Conclusions

High variability in bodyweight was associated with AF development, independently of traditional cardiovascular risk factors and baseline BMI. This association was stronger in underweight patients and with advanced diabetic stage. Weight fluctuation may interfere with the beneficial effects of weight loss and should be avoided when possible in weight control regimens for DM patients.

Increased incidence of bladder cancer with metabolically unhealthy status: analysis from the National Health Checkup database in Korea

We assessed the association between metabolic health status and the incidence of bladder cancer using nationally representative data from the National Health Insurance System and National Health Checkups (NHC) databases in South Korea. Data for 11,781,768 men who participated in the NHC between 2009 and 2012 were analysed. The normal-weight and physically obese categories were defined as body mass indexes (BMI) < 25 and ≥25 kg/m², respectively. Metabolically obese was defined as the presence of ≥3 components of metabolic syndrome. The participants were stratified into metabolically healthy, normal-weight (MHNW); metabolically obese, normal-weight (MONW); metabolically healthy, obese (MHO); metabolically obese, obese (MOO). Multivariate-adjusted Cox regression analysis was conducted to examine the association between metabolic health status and the incidence of bladder cancer. The study participants included 17,777 men newly registered with bladder cancer. Analysis according to metabolic health status classification revealed a higher multivariable-adjusted hazard ratio in the MOO, MONW group than in the MHO group (1.307 [95% CI: 1.258–1.358], 1.183 [95% CI: 1.137–1.231] and 1.066 [95% CI: 1.017–1.119], respectively; hazard ratios given relative to MHNW group) We found an association between metabolic health status and the incidence of bladder cancer, with an increasing risk according to the number of metabolic health status components.

Obesity and atrial fibrillation: making inroads through fat

The global prevalence of obesity has reached epidemic proportions, paralleled by a rise in cases of atrial fibrillation (AF). Data from epidemiological cohorts support the role of obesity as an independent risk factor for AF. Increasing evidence indicates that obesity may contribute to the AF substrate through a number of pathways including by altering epicardial adipose tissue biology, inflammatory pathways, structural cardiac remodelling, and inducing atrial fibrosis. Due to changes in pharmacokinetics and pharmacodynamics, specific therapeutic considerations are required to guide management of patients with AF including anticoagulation and rhythm control. Also, weight loss in patients with AF has been associated with reduced progression from paroxysmal to persistent AF and indeed regression from persistent to proximal AF. However, the role of dietary intervention in AF control remains to be fully elucidated and hard prospective outcome data to support weight loss are required in AF to determine its role as part of a comprehensive risk factor management strategy for AF in obese patients.

Tooth Loss Predicts Myocardial Infarction, Heart Failure, Stroke, and Death

We investigated whether oral health, represented by missing teeth, was associated with an increased risk of cardiovascular disease, including myocardial infarction (MI), heart failure (HF), stroke, and all-cause mortality. Subjects who underwent routine dental examinations and health checkups provided by the Korean National Health Insurance from 2007 to 2008 ( n = 4,440,970) were followed up for incident MI, HF, stroke, and death until 2016. During follow-up of 7.56 y, 68,063 (1.5%) subjects died, and 31,868 (0.7%) were admitted for MI, 22,637 (0.5%) for HF, and 30,941 (0.7%) for stroke. Cardiovascular events and mortality increased in proportion to tooth loss. Tooth loss was an independent risk factor for cardiovascular events after multivariable analysis adjusted for cardiovascular risk, behavioral, and income factors. Each missing tooth was associated with an approximately 1% increase in MI (HR, 1.010; 95% CI, 1.007 to 1.014), 1.5% increase in HF (HR, 1.016; 95% CI, 1.013 to 1.019) and stroke (HR, 1.015; 95% CI, 1.012 to 1.018), and 2% increase in mortality (HR, 1.022; 95% CI, 1.020 to 1.023). Having ≥5 missing teeth substantially increased risk for cardiovascular outcomes, and even a small number of missing teeth (1 to 4) was associated with an increased risk for MI, stroke, and death. This association was consistent in subgroup analyses and especially strong among the younger subjects (age <65 y) and those with periodontitis. In this large Korean nationwide cohort study, we found that tooth loss showed a dose-dependent association with incident MI, HF, ischemic stroke, and all-cause death and was a good predictor of cardiovascular outcome. In clinical practice, the number of missing teeth can aid physicians in discriminating patients with a higher cardiovascular risk.

Risk of Atrial Fibrillation in Relation to the Time Course of Type 2 Diabetes Mellitus and Fasting Blood Glucose

The relation of progression of type 2 diabetes and detailed fasting glucose level with risk of atrial fibrillation (AF) is not well known. A total of 6,199,629 subjects not diagnosed with AF who underwent health check-up in 2009 were included from the Korean National Health Insurance Service database. Risk of AF was compared among subjects with normal fasting glucose (NFG), subjects with impaired fasting glucose (IFG), patients with diabetes duration <5 years (early diabetes mellitus [DM]), and patients with diabetes duration ≥5 years (late DM). Next, risk of AF stratified by fasting glucose level per 10 mg/dL was assessed. During a mean follow-up of 7.2 years, the risk of AF significantly increased across the time course of type 2 diabetes (adjusted hazard ratio (aHR) 1.04, 95% confidence interval (CI) 1.02 to 1.05 for IFG; aHR 1.06, 95% CI 1.04 to 1.08 for early DM; aHR 1.09, 95% CI 1.07 to 1.11 for late DM). The risk of AF was significantly higher in subjects who progressed to type 2 diabetes in the IFG group. Risk of AF increased with a 10 mg/dL increment of fasting blood glucose (p-for-trend <0.0001). However, there was a U-shape relationship between fasting blood glucose and risk of AF in those who received antidiabetic medication. In conclusion, the risk of AF increased with the time course of type 2 diabetes. However, low blood glucose in antidiabetic medication user was associated with an increased risk of AF.

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

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.

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

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.

Low Lipid Levels and High Variability are Associated With the Risk of New-Onset Atrial Fibrillation

Background

While high levels of lipids and lipid variability are established risk factors for atherosclerotic cardiovascular disease, their roles in the development of atrial fibrillation (AF) are unclear, with previous studies suggesting a “cholesterol paradox.”

Methods and Results

A nationwide population‐based cohort of 3 660 385 adults (mean age 43.4 years) from the Korean National Health Insurance Service database, with ≥3 annual lipid measurements from 2009 to 2012 and without a history of AF or prescription of lipid‐lowering medication before 2012, were identified. Total cholesterol, low‐density lipoprotein cholesterol, high‐density lipoprotein cholesterol, and triglycerides levels were measured, and lipid variability was calculated using variability independent of the mean. The cohort was divided into quartiles by lipid levels and lipid variability and followed up for incident AF. During a median 5.4 years of follow‐up, AF was newly diagnosed in 27 581 (0.75%). AF development was inversely associated with high lipid levels (for top versus bottom quartile; total cholesterol, HR 0.78, 95% CI 0.76–0.81; low‐density lipoprotein cholesterol, HR 0.81, 95% CI 0.78–0.84; high‐density lipoprotein cholesterol, HR 0.94, 95% CI 0.91–0.98; triglycerides, HR 0.88, 95% CI 0.85–0.92). Meanwhile, AF development was associated with high lipid variability (for top versus bottom quartile; total cholesterol, HR 1.09, 95% CI 1.06–1.13; low‐density lipoprotein cholesterol, HR 1.12, 95% CI 1.08–1.16; high‐density lipoprotein cholesterol, HR 1.08, 95% CI 1.04–1.12; triglycerides, HR 1.05, 95% CI 1.01–1.08). Men showed greater risk reduction with high triglyceride levels and greater risk with high triglyceride variability for incident AF.

Conclusions

Low cholesterol levels and high cholesterol variability were associated with a higher risk of AF development.

Bodyweight fluctuation is associated with increased risk of incident atrial fibrillation

BACKGROUND

Obesity and weight gain are established risk factors for atrial fibrillation (AF).

OBJECTIVE

The purpose of this study was to investigate whether bodyweight variability is also a risk factor for AF development.

METHODS

A nationwide population-based cohort of 8,091,401 adults from the Korean National Health Insurance Service database without a history of AF and with ≥3 measurements of bodyweight over a 5-year period were followed up for incident AF. Intraindividual bodyweight variability was calculated using variability independent of mean, and high bodyweight variability was defined as the quartile with the highest variability (Q4) with Q1-Q3 as reference.

RESULTS

During median 8.1 years of follow-up, each increase of 1 SD in bodyweight variability was associated with a 5% increased risk of AF development, and the quartile with the highest bodyweight variability showed 14% increased risk of AF development compared to the quartile with the lowest variability (hazard ratio 1.14; 95% confidence interval 1.12-1.15), after adjustment for baseline bodyweight, height, age, sex, lifestyle factors, and comorbidities. High bodyweight variability was significantly associated with AF development in all baseline body mass index (BMI) groups except the very obese (BMI ≥30), and this association was stronger in subjects with lower bodyweight. High bodyweight variability was associated with increased risk of incident AF in all weight change groups, with a stronger association in those who lost weight.

CONCLUSION

Bodyweight fluctuation was independently associated with an increased risk of AF development, especially in individuals with low bodyweight, and regardless of weight gain or loss.

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

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.

Association of Variability in Body Mass Index and Metabolic Health With Cardiometabolic Disease Risk

Background Metabolic syndrome is associated with high risk of cardiovascular disease, although risk may differ according to the specific conditions present and variability in those conditions. Methods and Results We defined obesity (body mass index [BMI] ≥30 kg/m2) and metabolic health (<2 nonobesity National Cholesterol Education Program Adult Treatment Panel III conditions) among 3632 Framingham Heart Study offspring cohort participants (mean age, 50.8 years; 53.8% women) who were followed up from 1987 to 2014. We defined participants whose variance independent of the mean for a metabolic syndrome-associated measure was in the top quintile as being "variable" for that measure. Variable metabolic health was defined as ≥2 variable nonobesity metabolic syndrome components. We investigated the interaction between obesity and metabolic health in their associations with cardiometabolic disease and cardiovascular disease using Cox proportional hazards regression. In addition, we estimated the associations of BMI variability and variable metabolic health with study outcomes within categories of obesity and metabolic health status, respectively. We observed 567 incident obesity (41 439 person-years), 771 incident metabolically unhealthy state (25 765 person-years), 272 incident diabetes mellitus (56 233 person-years), 503 incident hypertension (12 957 person-years), 589 cardiovascular disease (60 300 person-years), and 195 chronic kidney disease (47 370 person-years) events on follow-up. Obesity and being metabolically unhealthy were independently and positively associated with all outcomes. BMI variability, compared with stable BMI, was associated with 163%, 67%, 58%, and 74% higher risks of having obesity, becoming metabolically unhealthy, having diabetes mellitus, and having hypertension, respectively, among nonobese participants. Variable metabolic health, compared with stable metabolic health, was associated with a 28% higher risk of cardiovascular disease, among metabolically healthy participants. Conclusions We did not observe evidence for a positive interaction between obesity and metabolic health status with regard to study outcomes. BMI and metabolic health variability are associated with adverse health outcomes.

Obesity and Atrial Fibrillation: Epidemiology, Pathophysiology and Novel Therapeutic Opportunities

Obesity is already a major global public health issue, implicated in a vast array of conditions affecting multiple body systems. It is now also firmly established as an independent risk factor in the incidence and progression of AF. The rapidly rising morbidity, mortality and healthcare costs associated with AF despite implementation of the three pillars of AF management — anticoagulation, rate control and rhythm control — suggest other strategies need to be considered. Compelling data has unveiled novel insights into adipose tissue biology and its effect on arrhythmogenesis while secondary prevention strategies targeting obesity as part of a comprehensive risk factor management programme have been demonstrated to be highly effective. Here, the authors review the epidemiological basis of the obesity—AF relationship, consider its underlying pathophysiology and discuss new therapeutic opportunities on the horizon.

Incidence of Prostate Cancer according to Metabolic Health Status: a Nationwide Cohort Study

BACKGROUND

We assessed the association between metabolic health status and incidence of prostate cancer using the National Health Check-ups (NHC) database of Korea.

METHODS

A total of 11,771,252 men who participated in the NHC between 2009 and 2012 and 56,552 men who were newly diagnosed with prostate cancer were analyzed. Normal-weight and obesity were defined as body mass index (BMI) < 25 kg/m² and ≥ 25 kg/m², respectively. Metabolic obesity was defined as the presence ≥ 3 components of the metabolic syndrome. Participants were stratified into 4 groups: metabolically healthy, normal-weight; metabolically obese, normal-weight (MONW); metabolically healthy, obese (MHO); and metabolically obese, obese. Multivariate Cox regression analysis was performed to examine the relationship between metabolic health status and incidence of prostate cancer.

RESULTS

During a mean 5.4 ± 1.1 years of follow-up, 56,552 patients were registered with a diagnosis of prostate cancer. When analyzed according to metabolic health status classification, the multivariable-adjusted hazard ratio (HR) was 1.143 for the MONW group, 1.097 for the MHO group, showing the HR for the MONW group was higher than that for the MHO group. As the number of metabolic syndrome components increased, HR increased significantly. When stratified based on BMI, metabolically obese patients showed significantly higher HR than metabolically healthy patients in all BMI groups.

CONCLUSION

This population-based nationwide study revealed an association between metabolic health status and the incidence of prostate cancer, and the risk increased according to the number of components of the metabolic syndrome.

Association of metabolic syndrome and chronic kidney disease with atrial fibrillation: A nationwide population-based study in Korea

AIMS

Metabolic syndrome (MetS) and chronic kidney disease (CKD) are significant risk factors for incident atrial fibrillation (AF). Few studies have reported the synergistic effect of MetS and CKD on development of AF. We investigated the individual and synergistic effects of MetS and CKD on the risk of incident AF.

METHODS

We studied a retrospective cohort comprising 22,886,663 Koreans whose data was obtained from the national health claims database established by the Korean National Health Insurance Service between 2008 and 2013. Patients were classified into a MetS and a CKD group and followed-up until 2016 for new-onset AF. A Cox proportional hazards model assessed the independent and synergistic effect of MetS and CKD on the risk of incident AF.

RESULTS

The prevalence of MetS and CKD in these patients was 27.4% and 5.4%, respectively. During a mean follow-up of 5.4 years, AF developed in 225,529 patients (1% of the total cohort). The adjusted hazard ratio (HR) for incident AF was 1.38 (95% confidence interval [CI] 1.36-1.39) for MetS, and 1.35 (95% CI 1.34-1.37) for CKD. Patients with MetS and CKD showed a higher risk of AF (HR 1.75, 95% CI 1.73-1.78) than that observed in those without MetS and CKD.

CONCLUSIONS

The combination of MetS and CKD showed a high risk of development of AF in a large-scale nationwide cohort. Further studies are warranted to determine whether pharmacological and/or lifestyle interventions can control/manage these modifiable risk factors to reduce the risk of development of AF.

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

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/m² , 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.

Mortality and causes of death in patients with atrial fibrillation: A nationwide population-based study

Background

Patients with atrial fibrillation are known to have a high risk of mortality. There is a paucity of population-based studies about the impact of atrial fibrillation on the mortality risk stratified by age, sex, and detailed causes of death.

Methods

A total of 15,411 patients with atrial fibrillation from the Korean National Health Insurance Service-National Sample Cohort were enrolled, and causes of death were identified according to codes of the 10th revision of the International Classification of Diseases.

Results

From 2002 to 2013, a total of 4,479 (29%) deaths were confirmed, and the crude mortality rate for all-cause death was 63.3 per 1,000 patient-years. Patients with atrial fibrillation had a 3.7-fold increased risk of all-cause death compared with the general population. The standardized mortality ratio for all-cause death was the highest in young patients and decreased with increasing age (standardized mortality ratio 21.93, 95% confidence interval 7.60–26.26 in patients aged <20 years; standardized mortality ratio 2.77, 95% confidence interval 2.63–2.91 in patients aged ≥80 years). Women with atrial fibrillation exhibited a greater excess mortality risk than men (standardized mortality ratio 3.81, 95% confidence interval 3.65–3.98 in women; standardized mortality ratio 3.35, 95% confidence interval 3.21–3.48 in men). Cardiovascular disease was the leading cause of death (38.5%), and cerebral infarction was the most common specific disease. Patients with atrial fibrillation had an about 5 times increased risk of death due to cardiovascular disease compared with the general population.

Conclusions

Patients with atrial fibrillation had a 4 times increased risk of mortality compared with the general population. However, the impact of atrial fibrillation on mortality decreased with age and in men. Cerebral infarction was the most common cause of death, and more attention should be paid to reducing the risk of stroke.

A U-shaped relationship of body mass index on atrial fibrillation recurrence post ablation: A report from the Guangzhou atrial fibrillation ablation registry

Background

Obesity or overweight is related to worse outcomes in patients with atrial fibrillation (AF) following catheter ablation (CA). The role of being underweight in relation to recurrent arrhythmias post AF ablation is less certain. We conducted a retrospective study to investigate the association of body mass index (BMI) with arrhythmia outcomes in AF patients undergoing CA.

Methods

In a cohort of 1410 AF patients (mean age 57.2 ± 11.6 years; 68% male) undergoing single CA, the association between BMI and AF ablation outcome was analyzed using BMI as a continuous variable and by four BMI categories (<18.5 kg/m², 18.5-24 kg/m², 25-29 kg/m², and ≥ 30 kg/m²).

Result

We observed a positive association between a cut off value of BMI and risk of AF recurrence post AF ablation. BMI ≥26.36 kg/m² was related to more AF recurrence (c-statistic 0.55, 95%CI 0.51–0.58; P < 0.01) with 50% increased risk of AF recurrence (HR 1.50, 95% CI 1.22–1.86; P < 0.01). Recurrence rates in the four BMI categories were 33.3%, 23.2%, 27.2 and 41.8%, respectively (P < 0.01).

Kaplan-Meier analysis showed that BMI categories of <18.5 kg/m² and ≥ 30 kg/m² were all associated with more AF recurrence (P = 0.01). Both underweight (HR 1.85, 95%CI 1.12–3.08; P = 0.02) and obesity (HR 1.78, 95%CI 1.17–2.72; P = 0.01) significantly increased the risk of AF recurrence in a Cox proportional hazard model.

Conclusion

BMI had good predictive value for AF ablation outcomes with a cut off value of ≥26.36 kg/m². Apart from being obese/overweight, being underweight might also be a risk factor for AF recurrence post ablation.

Diabetes mellitus, blood glucose and the risk of atrial fibrillation: A systematic review and meta-analysis of cohort studies

BACKGROUND

Diabetes and elevated blood glucose have been associated with increased risk of atrial fibrillation in a number of epidemiological studies, however, the findings have not been entirely consistent. We conducted a systematic review and meta-analysis to clarify the association.

MATERIAL AND METHODS

We searched the PubMed and Embase databases for studies of diabetes and blood glucose and atrial fibrillation up to July 18th 2017. Cohort studies were included if they reported relative risk (RR) estimates and 95% confidence intervals (CIs) of atrial fibrillation associated with a diabetes diagnosis, prediabetes or blood glucose. Summary RRs were estimated using a random effects model.

RESULTS

Thirty four studies were included in the meta-analysis of diabetes, pre-diabetes or blood glucose and atrial fibrillation. Thirty two cohort studies (464,229 cases, >10,244,043 participants) were included in the analysis of diabetes mellitus and atrial fibrillation. The summary RR for patients with diabetes mellitus versus patients without diabetes was 1.30 (95% CIs: 1.03-1.66), however, there was extreme heterogeneity, I² = 99.9%) and evidence of publication bias with Begg's test, p < 0.0001. After excluding a very large and outlying study the summary RR was 1.28 (95% CI: 1.22-1.35, I² = 90%, n = 31, 249,772 cases, 10,244,043 participants). The heterogeneity was mainly due to differences in the size of the association between studies and the results persisted in a number of subgroup and sensitivity analyses. The summary RR was 1.20 (95% CI: 1.03-1.39, I² = 30%, n = 4, 2392 cases, 58,547 participants) for the association between prediabetes and atrial fibrillation. The summary RR was 1.11 (95% CI: 1.04-1.18, I² = 61%, n = 4) per 20 mg/dl increase of blood glucose in relation to atrial fibrillation (3385 cases, 247,447 participants) and there was no evidence of nonlinearity, p_nonlinearity = 0.34.

CONCLUSIONS

This meta-analysis suggest that prediabetes and diabetes increase the risk of atrial fibrillation by 20% and 28%, respectively, and there is a dose-response relationship between increasing blood glucose and atrial fibrillation. Any further studies should clarify whether the association between diabetes and blood glucose and atrial fibrillation is independent of adiposity.