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A trial fibrillation (AF) is the mostcommon, sustained arrhythmia diag-nosed in clinical practice. Given
that it is associated with significant mor-bidity and mortality, it is concerning thatthere is a steadily rising prevalence of AFworldwide (1,2). As a result, a greater under-
standing of modifiable, predisposing risk factors iswarranted in an attempt to slow the rising populationand economic burden of AF (3).
Obesity is a risk factor with increasingly broadimplications for health in both developed and devel-oping countries undergoing epidemiologic transition(4,5). Our evolving understanding regarding therelationship between AF and measures of obesity,body size, and weight change are, therefore, partic-ularly significant given the rising prevalence of bothAF and obesity (6). Although analyses have studiedthe association between obesity and AF in the past,these have been limited by the heterogeneous mea-sures of obesity reported in individual studies (7–9).In addition, there has since been increasing recogni-tion that obesity may influence the risk of AF in otherclinical scenarios, such as after cardiac surgery orcatheter ablation procedures (6,10). Given that anaccurate and reliable characterization of AF riskassociated with obesity would be immensely infor-mative to clinical practice, we sought to describethe association between obesity and AF in differentsettings, with standardization of obesity measuresallowing for a more comprehensive inclusion of
se search leading to study selection.
eligible studies and detailed calculation of excess riskfor each incremental increase in obesity.
METHODS
This systematic review was performed in accor-dance with both the Meta-Analysis of ObservationalStudies in Epidemiology and Strengthening theReporting of Observational Studies in Epidemiologyguidelines (11).
SEARCH STRATEGY AND ELIGIBILITY CRITERIA. Weperformed a comprehensive, systematic search ofobservational studies in Medline and EMBASE data-bases available through January 2012. This was sup-plemented by manual searching of the reference listsof individual studies and review papers. Search termsincluded obesity, overweight, body mass index (BMI),arrhythmia, and atrial fibrillation. Studies were in-cluded if they were cross-sectional, case-control, orcohort studies that allowed for assessment of associ-ations between BMI and incident AF, post-operativeAF, or post-ablation AF. Studies reporting risk esti-mates with BMI as either a continuous or categoricalvariable were both included. Post-operative AF wasdefined as AF following cardiac surgery, and post-ablation AF was defined as recurrent AF followinga catheter ablation procedure. Two investigators(C.X.W. and M.T.S.) independently performed thesearches and reviewed all identified studies for in-clusion. The decision to include studies was hierar-chical, initially on the basis of the study title,followed by the abstract, and then the full text of eachremaining paper. When duplicate reports from thesame study or cohort were identified, only the mostrecent publication or the one with the longest follow-up period was included. Disagreements were resolvedby consensus with a third investigator (P.S.).
DATA EXTRACTION. Data from included studieswere extracted independently by 2 investigators(C.X.W. and M.T.S.) using a standard table. The fol-lowing were tabulated where applicable: type of AFstudied (incident, post-operative, or post-ablation),study type, inclusion and exclusion criteria, cohortsource, study dates, study country, number of patientsenrolled, baseline patient characteristics, number ofprocedures, method of event determination, eventnumbers, duration of follow-up, risk estimates, andother covariates adjusted for in any multivariatemodels.
STATISTICAL ANALYSIS. Odds ratios (ORs) per unitincrease in BMI were abstracted or calculated fromobservational studies reporting associations betweenBMI and AF. Where risk estimates were reported as a
TABLE 1 Obesity and AF: Cohort Studies
First Author(Ref. #), Year Cohort Source
Dates ofEnrollment Country
Subjects(% Women)
Mean Age(yrs)
Body MassIndex (kg/m2)
Body Mass IndexData Reported
Follow-Up(yrs)
Cases of AF(%) AF Diagnosis Other Covariates in Model
Mean 20.0 175 (1.1%) National hospitalizationand death registries
Age, sex, systolic blood pressure,diabetes, cholesterol, forcedexpiratory volume, smoking,social class
Gami et al.(29), 2007
Mayo Clinic 1987–2003 UnitedStates
3,542 (34%) 49 Mean 33 Continuous Mean 4.7 133 (3.8%) ECG Age, sex, smoking, hypertension,diabetes, ischemic heart disease,heart failure
Rosengren et al.(14), 2009
Swedish PrimaryPreventionStudy
1970–1973 Sweden 6,903 (0%) 52 Mean 22.4 Continuous andcategorical
Maximum34.3
1,253 (18.2%) National hospitalizationregistry
Age, systolic blood pressure,antihypertensive therapy,diabetes, smoking, alcohol,social class
Tedrow et al.(13), 2010
Women’s HealthStudy
1993–2004 UnitedStates
34,309 (100%) 55 16,765 (49%)overweightor obese
Continuous andcategorical
Mean 12.9 834 (2.4%) ECG or medical record Age, ethnicity, hypertension,hypercholesterolemia, diabetes,alcohol consumption, smoking,physical activity, inflammatorymarkers
Smith et al.(30), 2009
Malmo Diet andCancer Study
1991–1996 Sweden 30,447 (60%) 58 Mean 25.8 Continuous andcategorical
Mean 11.2 1,430 (4.7%) National hospitalizationand death registries
AF ¼ atrial fibrillation; ECG ¼ electrocardiogram.
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FIGURE 2 Obesity and AF in Cohort Studies
Relation between 5-U increases in body mass index and atrial fibrillation (AF) from cohort studies. The point estimate (center of each gray
square), statistical size (proportional area of square) and 95% confidence interval (CI) (horizontal line) for estimate of each study are shown.
The overall summary estimate is also shown (blue diamond). AGES ¼ Age, Gene/Environment Susceptibility-Reykjavik Study; CHS ¼ Cardio-
vascular Health Study; OR ¼ odds ratio.
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series of dose-specific risk estimates compared with areference BMI category, these were transformed intorisk estimates per unit of BMI (12). Authors werecontacted for additional data allowing transformation(e.g., patient and event numbers within BMI cate-gories) where it was not reported in the publication.To assess the validity of this transformation, weplotted the natural logarithm of the AF risk estimatesfor studies that assessed at least 3 different BMIgroups against the assigned BMI dose for this cate-gory, after subtracting a factor b1 � (XAref � 22.5),where XAref is the assigned dose in the referencecategory, as previously described (12). There wassome evidence of deviation, but overall evidence wasof linearity consistent with that described in indi-vidual studies (Online Figure 1) (13,14). If both dose-specific risk estimates compared with a referenceBMI category and risk estimates per unit of BMI werereported, the latter were preferentially used. Asan additional test, we also transformed categoricalBMI risk estimates using the previously mentionedmethod in these studies, and transformed risk esti-mates per unit of BMI were comparable to those re-ported by the investigators. Risk estimates for every
5-U increase in BMI were subsequently calculatedand pooled using random effects meta-analysis (15).Where risk estimates were reported separately by sexor other subgroups only, these were pooled sepa-rately. Risk estimates from multivariate modelsadjusting for potential confounders were used whereavailable. Heterogeneity across studies was assessedusing I2 statistics and, where present, the potentialrole of study characteristics (age, sex, year, geo-graphic region, study numbers, AF diagnosticmethod, follow-up duration, and AF type) exploredvia subgroup analyses and meta-regression tech-niques (16). The presence of publication bias wasassessed using funnel plots of effect size againststandard error. A 2-tailed value of p < 0.05 wasconsidered statistically significant, and all analyseswere performed using SAS version 9.3 (SAS InstituteInc., Cary, North Carolina) and Stata version 12.0(Stata Corp., College Station, Texas).
RESULTS
SEARCH RESULTS. The systematic search of elec-tronic databases identified 2,001 papers, from which
TABLE 2 Obesity and AF—Case Control Studies
First Author(Ref. #) Cohort Source
Dates ofStudy Country
Subjects(% Women)
Mean Age(yrs)
Body MassIndex (kg/m2)
Body Mass IndexData Reported
Cases of AF(%) AF Diagnosis Other Covariates in Model
ADVANCENT ¼ National Registry to Advance Heart Health; FAMA ¼ Prevalence of Atrial Fibrillation in the Portuguese population aged 40 and over; HDL ¼ high-density lipoprotein; NYHA ¼ New York Heart Association; other abbreviations as in Table 1.
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FIGURE 3 Obesity and AF in Case-Control Studies
Relation between 5-U increases in body mass index and AF from case-control studies. See Figure 2 legend for definition of symbols.
Abbreviations as in Figure 2.
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we identified 399 potentially relevant studies formore detailed full-text assessment after screening ofstudy titles and review of abstracts (Figure 1). Anadditional 7 were identified by manual searching ofreference lists. After full-text assessment, a total of 51studies were included. A total of 23 studies reportedon incident AF, 12 on post-operative AF, and 16 onpost-ablation AF.
OBESITY AND AF. A total of 9 cohort studiesinvolving 157,518 individuals and 6,088 cases of AFwere identified (mean age 59 years, mean 53% female,and mean follow-up 10 months) (Table 1). Three of thestudies provided sex-specific estimates and 1 studyprovided race-specific estimates on the associationbetween BMI and AF; thus, 13 separate risk estimatescontributed to this analysis. The overall summaryestimate from the 13 separate risk estimates com-bined indicated that there was a 29% greater excessrisk of developing AF for every 5-U increase in BMI(OR: 1.29, 95% confidence interval [CI]: 1.23 to 1.36)(Figure 2). There was significant heterogeneity due tobetween-study differences (I2 statistic 54.7%), withsome evidence of smaller estimates in studies fromNorth America (p ¼ 0.02) and studies diagnosing
AF using electrocardiograms (p ¼ 0.007) (OnlineFigures 2 and 3). There was no evidence of signifi-cant publication bias.
A total of 14 case-control studies involving 401,061individuals and 65,546 cases of AF were identified(mean age 60 years, mean 43% female) (Table 2).Pooled analysis from these studies similarly revealeda significantly greater 19% risk of AF for every 5-Uincrease in BMI (OR: 1.19, 95% CI: 1.13 to 1.26)(Figure 3). There was significant heterogeneity due tobetween-study differences (I2 statistic 80%), withagain some evidence of smaller estimates in studiesfrom North America (p < 0.001) (Online Figure 4).There was no evidence of significant publication bias.
OBESITY AND POST-OPERATIVE AF. A total of 12studies involving 62,160 individuals and 16,768 casesof post-operative AF were identified (mean age 64years, mean 26% female) (Table 3). One study pro-vided sex-specific estimates, and thus, 13 separaterisk estimates contributed to this analysis. The over-all summary estimate indicated that there was a 10%greater excess risk of post-operative AF for every 5-Uincrease in BMI (OR: 1.10, 95% CI: 1.04 to 1.17)(Figure 4). There was significant heterogeneity due to
TABLE 3 Obesity and Post-Operative AF
First Author(Ref. #) Dates of Study Country
Subjects(% Women)
Mean Age(yrs)
Body MassIndex (kg/m2)
Body Mass IndexData Reported
Post-OperativeCases of AF (%) AF Diagnosis Other Covariates in Model
Age, sex, ethnicity, obstructive sleep apnea, hypertension, diabetes,family history of coronary artery disease, myocardial infarction,heart failure, ejection fraction, stroke, chronic kidney disease,operation urgency, smoking, hypercholesterolemia, medications,graft number
Tadic et al.(56)
2006–2008 Serbia 322 (28%) 60 Mean 26.2 Categorical 72 (22.4%) Continuousmonitoringor ECG
Age, sex, hypertension, diabetes, hypercholesterolemia, smoking,medications, left atrial diameter, left ventricular kineticdisturbances, triple vessel disease, leukocytosis
CCS ¼ Canadian Cardiovascular Society; N/A ¼ not available; other abbreviations as in Tables 1 and 2.
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FIGURE 4 Obesity and Post-Operative AF
Relation between 5-U increases in body mass index and post-operative AF. See Figure 2 legend for definition of symbols. Abbreviations as in
Figure 2.
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between-study differences (I2 statistic 82.9%), withsome evidence of larger estimates in studies fromAsia (p ¼ 0.003) and in studies diagnosing AF withcontinuous monitoring or electrocardiograms (p ¼0.045) (Online Figures 5 and 6). There was no evi-dence of significant publication bias.
OBESITY AND POST-ABLATION AF. A total of 16studies involving 5,864 individuals were included(mean age 56 years, mean 30% female, mean follow-up 20 months) (Table 4). The overall summary esti-mate indicated that there was a 13% greater excessrisk of recurrent AF post-ablation for every 5-Uincrease in BMI (OR: 1.13, 95% CI: 1.06 to 1.22)(Figure 5). There was significant heterogeneity due todifferences between studies (I2 statistic 78.6%),although exploratory analyses could not identifyany significant contributing factors. There was noevidence of significant publication bias.
DISCUSSION
MAJOR FINDINGS. The present meta-analysis pooleddata from 51 studies and more than 600,000 in-dividuals in a range of clinical settings. For every 5-U
increase in BMI, there were 10% to 29% greater excessrisks of incident, post-operative, and post-ablationAF. These findings provide a comprehensive quanti-fication of the relationship between incremental in-creases in obesity and the risk of AF in these differentclinical settings.
THE EPIDEMIC OF AF. AF is increasingly recognizedas a major public health burden. The worldwideprevalence of AF is already estimated at 33 million,and this is possibly a significant underestimate of thetrue figure given the likelihood of study methodo-logical limitations and under-diagnosis (17,18). Theannual incremental cost of AF is estimated at $26billion in the United States alone, and hospitaliza-tions, the major driver of cost, appear to be increasingmore rapidly than other cardiovascular conditions(2,17). Given that the risk of AF increases rapidly withgreater age, an already rising prevalence is expectedto further accelerate given aging population struc-tures. Studies suggest, however, that the age-specificincidence of AF is increasing in addition to anyeffect from population aging (19). It is likely that theepidemiologic transition in both developed anddeveloping countries toward increased longevity and
FIGURE 5 Obesity and Post-Ablation AF
Relation between 5-U increases in body mass index and post-ablation atrial fibrillation. See Figure 2 legend for definition of symbols.
Abbreviations as in Figure 2.
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unhealthy lifestyles is resulting in an increasingprevalence and multiplicative effect of AF risk factors(4). A greater focus on and effort to reduce these riskfactors is thus required to prevent the initial devel-opment and the subsequent burden of AF (20).OBESITY AND AF. Obesity is an important contrib-utor to the burden of AF, explaining one-fifth of all AFcases (21). It has also been estimated that obesity mayaccount for approximately 60% of the rising age- andsex-adjusted incidence of AF (1). From a public healthperspective, obesity is, therefore, a modifiable riskfactor that could be profitably targeted. Moreover,dietary and lifestyle improvements addressingobesity would also favorably affect other AF riskfactors, such as hypertension and diabetes, reducingthe burden of AF greater than that attributable toobesity alone. We and other investigators have pre-viously shown that obesity is associated with dele-terious electrical, structural, and hemodynamicabnormalities in the left atria, predisposing to AF(22,23). More recently, we described how a weightand risk factor management program can improve
such cardiac remodeling and subsequent arrhythmiaburden in people with AF (24,25).
Although previous analyses have studied theobesity-related risk of AF in different clinical set-tings individually, the present report provides themost comprehensive summary estimates to date(7–9). Key differences compared with prior studiesinclude the greater power of our meta-analysis(51 studies, n ¼ 626,603), the inclusion of studiesreporting risk estimates with either BMI as a cate-gorical or continuous variable, and the comparisonof obesity-related risk across different clinical set-tings (7–9). Our results suggest that there is a 10% to29% excess risk of AF associated with every 5-U in-crease in BMI in the general population, after cardiacsurgery, and after catheter ablation procedures. Theconsistency of obesity-related risk across thesedifferent settings lends further weight to the reli-ability of obesity as an AF risk factor. Thus, evenmoderate reductions in population body mass in-dexes are likely to have a significant effect on thepublic health burden of AF.
TABLE 4 Obesity and Post-Ablation AF
First Author(Ref. #)
Dates ofStudy Country
Subjects(% Women)
MeanAge(yrs)
Body MassIndex (kg/m2)
Body Mass IndexData Reported
AF Type(% Paroxysmal)
Follow-Up(Months)
Follow-UpFrequency
Method ofAF Detection
Procedures(n)
FreedomFrom AF
(%)Other Covariates
in Model
Richter et al.(57)
2002–2004 Austria 234 (28%) 57 Mean 26.6 Continuous 70.5 Median 13 3-monthly for1 yr, then3–6 monthly
ECG and Holtermonitorat follow-ups,additional ifsymptomatic
1.0 61.5(at 6 months)
Age, sex, AF type, leftventricular ejectionfraction, left atrial size,structural heart disease,antiarrhythmic use,ablation technique,inducibility
Jongnarangsinet al. (58)
2005–2006 UnitedStates
324 (24%) 57 266 (82%)overweightor obese
Continuous andcategorical
72.2 Mean 7 3–6 monthly ECG at follow-ups,additional ifsymptomatic,event monitorif in sinusrhythm at3-6 months
1.0 60.1 Age, sex, AF type, AFduration, left atrial size,left ventricular ejectionfraction
Shah et al.(59)
#2008 UnitedStates
264 (29%) 57 Mean 30 Continuous 87.0 Mean 34 1, 3, 6, and12 months,then annually
94 (20%) 59 Mean 25.0 Categorical 0.0 Mean 20 1, 3, 6, and12 months
ECG and Holtermonitor
1.0 66.0 Age, sex, AF type, AFduration, hypertension,diabetes, left atrialdiameter, leftventricular ejectionfraction
Letsas et al.(70)
#2011 Germany 226 (19%) 56 Mean 26.6 Continuous 59.3 Mean 14 3 and 6 months,then at meanof 14 months
Holter monitor 1.0 58.0 None
Ejima et al.(71)
#2011 Japan 80 (19%) 58 Mean 24 Continuous 81.3 Median 17 1, 2, 3, 6, 9, and12 months, then6-monthly
ECG and Holtermonitor
1.1 90.0 None
Abbreviations as in Table 1.
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PERSPECTIVES
COMPETENCY IN MEDICAL KNOWLEDGE:
Incremental increases in obesity are associated with
incident, post-operative, and post-ablation AF. For
every 5-U increase in BMI, there is a 10% to 29%
greater risk of AF in these clinical settings.
TRANSLATIONAL OUTLOOK: Given the associa-
tion between obesity and AF, further studies are
warranted to characterize the effect that weight
reduction may have not only in preventing incident
AF, but also in managing patients with established AF.
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STUDY LIMITATIONS. The overall summary esti-mates obtained in these analyses may be over-estimates due to coexistent confounding factors.Although most studies are adjusted for other co-morbid AF risk factors, it is not possible to fully takeinto account the possible effect on the observed as-sociations. However, overall summary estimates mayalso be underestimates due to the underdiagnosis ofAF in some included studies, the magnitude of whichhas only recently become apparent with increasinglysensitive diagnostic modalities. Significant hetero-geneity was also observed in the present analysesdue to between-study differences. Subgroup analysesand meta-regression techniques suggested that thismay in part be due to differing study populationcharacteristics (such as geographic region) and diag-nostic methods of ascertaining AF. Despite this het-erogeneity, however, our findings appeared to beconsistent across a broad range of clinical settings,and thus they provide the most comprehensiveanalysis so far with regard to the obesity-relatedrisk of AF.
CONCLUSIONS
Incremental increases in BMI are associated witha significant excess risk of AF in different clinicalsettings. For every 5-U increase in BMI, there were10% to 29% greater excess risks of incident, post-
operative, and post-ablation AF. Given that bur-geoning rates of obesity are likely to have anincreasing effect on an already rising burden of AF,these data suggest that achieving even moderatereductions in body mass indexes is likely to havesignificant clinical and public health impact.
REPRINT REQUESTS AND CORRESPONDENCE: Dr.Prashanthan Sanders, Centre for Heart Rhythm Dis-orders, Department of Cardiology, Royal AdelaideHospital, Adelaide SA 5000, Australia. E-mail: [email protected].
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KEY WORDS atrial fibrillation, body massindex, cardiac surgery, catheter ablation,obesity, substrate, weight reduction
APPENDIX For supplemental figures, pleasesee the online version of this article.
