Context Obesity is associated with atrial enlargement and ventricular diastolic
dysfunction, both known predictors of atrial fibrillation (AF). However, it
is unclear whether obesity is a risk factor for AF.
Objective To examine the association between body mass index (BMI) and the risk
of developing AF.
Design, Setting, and Participants Prospective, community-based observational cohort in Framingham, Mass.
We studied 5282 participants (mean age, 57 [SD, 13] years; 2898 women [55%])
without baseline AF (electrocardiographic AF or arterial flutter). Body mass
index (calculated as weight in kilograms divided by square of height in meters)
was evaluated as both a continuous and a categorical variable (normal defined
as <25.0; overweight, 25.0 to <30.0; and obese, ≥30.0). In addition
to adjusting for clinical confounders by multivariable techniques, we also
examined models including echocardiographic left atrial diameter to examine
whether the influence of obesity was mediated by changes in left atrial dimensions.
Main Outcome Measure Association between BMI or BMI category and risk of developing new-onset
Results During a mean follow-up of 13.7 years, 526 participants (234 women)
developed AF. Age-adjusted incidence rates for AF increased across the 3 BMI
categories in men (9.7, 10.7, and 14.3 per 1000 person-years) and women (5.1,
8.6, and 9.9 per 1000 person-years). In multivariable models adjusted for
cardiovascular risk factors and interim myocardial infarction or heart failure,
a 4% increase in AF risk per 1-unit increase in BMI was observed in men (95%
confidence interval [CI], 1%-7%; P = .02)
and in women (95% CI, 1%-7%; P = .009).
Adjusted hazard ratios for AF associated with obesity were 1.52 (95% CI, 1.09-2.13; P = .02) and 1.46 (95% CI, 1.03-2.07; P = .03) for men and women, respectively, compared with individuals
with normal BMI. After adjustment for echocardiographic left atrial diameter
in addition to clinical risk factors, BMI was no longer associated with AF
risk (adjusted hazard ratios per 1-unit increase in BMI, 1.00 [95% CI, 0.97-1.04], P = .84 in men; 0.99 [95% CI, 0.96-1.02], P = .56 in women).
Conclusions Obesity is an important, potentially modifiable risk factor for AF.
The excess risk of AF associated with obesity appears to be mediated by left
atrial dilatation. These prospective data raise the possibility that interventions
to promote normal weight may reduce the population burden of AF.
The prevalence of atrial fibrillation (AF), the most common cardiac
dysrhythmia, is expected to increase several-fold in the coming decades.1 Because the onset of AF is associated with considerable
morbidity and mortality despite contemporary therapies, the identification
of potentially modifiable risk factors for AF is an important goal.2,3 Prior studies have demonstrated that
advanced age, diabetes, hypertension, and cardiovascular disease increase
the risk of developing AF.4-7 Obesity
occurs in association with most of these conditions, but it is unclear whether
obesity itself predisposes to AF. The rationale for hypothesizing such a link
comes from experimental and clinical data suggesting that adiposity influences
atrial and ventricular structure,8-11 autonomic
tone,12 and ventricular diastolic function.13 Prior epidemiologic studies have yielded conflicting
results regarding whether obesity is a risk factor for AF, but these studies
were potentially limited by short-term follow-up, failure to account for interim
cardiovascular events, and lack of echocardiographic data.4-7
The availability of long-term follow-up in the Framingham Heart Study
provided an opportunity to examine the association of obesity with the risk
of developing AF, after adjustment for other risk factors and interim events.
Because echocardiograms were routinely performed on study participants, we
also had the ability to investigate the hypothesis that obesity predisposes
to AF through its influence on left atrial structure.8
The design and selection criteria of the Framingham Heart Study and
the Framingham Offspring Study have been detailed previously.14,15 Participants
attending the 16th examination of the original cohort (n = 2351;
1979-1982) or the second examination of the offspring cohort (n = 3867;
1979-1983) were eligible for the present investigation. We chose these examinations
because they included routine echocardiograms and reflected more contemporary
experience than earlier examinations but still provided a long period of follow-up.
We excluded participants for the following reasons, in hierarchical fashion:
age younger than 35 years (n = 701), prior or current AF (n = 127),
or underweight (body mass index [BMI] <18.5, n = 108). Underweight
participants were excluded to reduce the possibility of including individuals
with cachexia from an existing medical condition. A total of 5282 participants
(2898 women [55%]) remained eligible. All protocols were approved by the Boston
Medical Center institutional review board, and participants provided written
Clinical Evaluation and Definitions
Medical history, physical examination, and electrocardiography were
routinely administered at each Framingham Heart Study examination.14,15 Height and weight were directly measured
using a standardized protocol. Body mass index was calculated by dividing
weight in kilograms by the square of the height in meters. Hypertension was
defined as systolic blood pressure greater than or equal to 140 mm Hg, diastolic
blood pressure greater than or equal to 90 mm Hg, or use of antihypertensive
therapy. Criteria for diabetes mellitus were a fasting glucose level of 126
mg/dL (7.0 mmol/L) or greater, random glucose level of 200 mg/dL (11.1 mmol/L)
or greater, or use of insulin or medications used to treat hyperglycemia.
Electrocardiographic left ventricular hypertrophy was defined as increased
voltage with accompanying lateral repolarization abnormalities.16 A
standardized 2-dimensional guided M-mode echocardiogram was also performed
at the baseline examinations.17 Left atrial
diameter at end-systole was measured according to American Society of Echocardiography
Medical records were obtained for all hospitalizations and physician
visits related to cardiovascular disease during follow-up and were reviewed
by a committee of 3 investigators. Atrial fibrillation was diagnosed if AF
or atrial flutter was present on an electrocardiogram obtained from a hospital
or physician chart, or from 1 of the routine Framingham clinic examinations
(every 2 years in the original cohort and every 4 years in the offspring cohort).
The electrocardiographic interpretation of AF was confirmed by 1 of 2 Framingham
Heart Study cardiologists (D.L., E.J.B.). Criteria for other cardiovascular
events, including myocardial infarction (MI) and congestive heart failure,
have been described previously.19
Body mass index was analyzed as both a continuous and a categorical
variable, using the World Health Organization/National Institutes of Health
classification scheme (normal defined as <25.0; overweight, 25.0 to <30.0;
and obese, ≥30.0).20 Sex-specific Kaplan-Meier
curves were plotted to depict the probability of developing AF according to
We examined the association between BMI or BMI category and the risk
of developing new-onset AF using sex-specific Cox proportional hazards regressions.21 Death was treated as a censoring event. Follow-up
was also censored after 16 years, with the final participant censored in this
manner in October 1999. There was no significant interaction between follow-up
time and BMI for prediction of AF in the primary Cox model, suggesting that
the proportional hazards assumption was appropriate. We estimated age-adjusted
models as well as multivariable models. Covariates selected for adjustment
were based on prior reports4 and included age,
systolic blood pressure, use of antihypertensive therapy, diabetes mellitus,
electrocardiographic left ventricular hypertrophy, history of MI or congestive
heart failure, regular use of cigarettes in the prior year, and significant
systolic murmur (grade 3 out of 6 or greater) or any diastolic murmur. The
3 BMI categories were modeled with 2 dichotomous predictor variables (for
overweight and obese); we also estimated separate models with an ordinal predictor
variable for BMI category to test for a linear trend across BMI categories.
In additional models, we examined whether obesity predisposed to AF through
an interim (ie, occurring after the baseline examination and before the onset
of AF) MI or heart failure event (considered as time-dependent covariates).
We tested for effect modification by age, sex, or systolic blood pressure
by including multiplicative interaction terms with these variables and BMI.
We assessed the influence of different degrees of obesity by incorporating
categorical variables for stage 1 obesity (BMI 30 to <35) and stage 2 or
3 obesity (BMI ≥35). We also performed an additional analysis excluding
individuals with BMI of 30 or greater to determine whether an association
with BMI was observed in nonobese individuals. This analysis was sex-pooled
(to maximize statistical power) and adjusted for all covariates, including
sex. Additional secondary analyses were performed that eliminated the exclusion
of younger individuals (<35 years) or underweight individuals (BMI <18.5),
adjusted for alcohol use (as a continuous or dichotomous variable), adjusted
for cohort status (original cohort vs offspring cohort), and excluded individuals
who developed atrial flutter. To remove the contribution of parental history
of AF, we repeated the primary Cox analyses with stratification for cohort
We hypothesized that the relation between obesity and AF may be mediated
by the influence of obesity on left atrial structure.8,9 To
examine this hypothesis, we constructed additional sex-specific models with
adjustment for echocardiographic left atrial size measured at the baseline
examination, before any of the participants had developed AF.
All analyses were performed with SAS version 8.0 (SAS Institute, Cary,
NC). A 2-sided P<.05 was considered statistically
Baseline characteristics of the 5282 participants in the study sample
are provided in Table 1. The mean age
was 56 (range, 35 to 90) years in men and 58 (range, 35 to 90) years in women.
Of the 2384 men, 1216 (51%) were overweight and 413 (17%) were obese; of the
2898 women, 898 (31%) were overweight and 464 (16%) were obese.
During a mean of 13.7 years of follow-up, 292 men and 234 women developed
AF. Prior to developing AF, 43 men and 22 women had experienced an MI, and
36 men and 29 women had experienced congestive heart failure. During the follow-up
period, 1452 participants (715 women) died, of whom 1168 (572 women) were
free of AF.
Age-adjusted incidence rates for AF increased across categories of BMI
in both men and women (Table 2). The Figure displays Kaplan-Meier curves showing that
the probability of developing AF over time increased across categories of
Results of the multivariable Cox proportional hazards regressions are
shown in Table 3. After adjustment for
age alone, each 1-unit increase in BMI was associated with increases of 5%
in the risk of AF for men (P = .002) and
4% for women (P = .001). These relations
remained significant in multivariable-adjusted models, with a 4% increase
in risk of AF per 1-unit increase in BMI for both men (P = .02) and women (P = .01).
Similarly, age-adjusted and fully-adjusted hazard ratios (HRs) for AF increased
across BMI categories in both men and women (Table 3). Multivariable-adjusted HRs for AF were 1.49 (95% confidence
interval [CI], 1.06-2.09) for obese men and 1.45 (95% CI, 1.03-2.05) for obese
women, compared with men and women with normal BMI. These findings were not
attenuated in models adjusting for interim MI or congestive heart failure
in addition to baseline covariates. Each 1-unit increase in BMI was associated
with a 4% increase in AF risk in men (P = .02)
and women (P = .009). The multivariable-adjusted
HRs for AF were 1.52 (95% CI, 1.09-2.13) for obese men and 1.46 (95% CI, 1.03-2.07)
for obese women.
The association between BMI and risk of AF did not vary by age, sex,
or systolic blood pressure (P>.10 for all interaction
terms). To assess the influence of different degrees of obesity, we estimated
regressions with 4 BMI categories (normal, overweight, stage 1 obesity, and
stage 2 or 3 obesity). Age-adjusted HRs for AF increased progressively across
these 4 BMI categories in men (1.00, 1.12 [95% CI, 0.85-1.48], 1.61 [95% CI,
1.14-2.27], 2.30 [95% CI, 1.22-4.33]; P = .001
for trend) and women (1.00, 1.20 [95% CI, 0.90-1.61], 1.46 [95% CI, 1.00-2.15],
1.93 [95% CI, 1.15-3.25]; P = .005 for
trend). After adjustment for clinical variables and interim MI or heart failure,
these findings remained significant in men (1.00, 1.10 [95% CI, 0.84-1.46],
1.48 [95% CI, 1.04-2.10], 1.88 [95% CI, 0.93-3.79]; P = .01
for trend) and women (1.00, 1.13 [95% CI, 0.84-1.52], 1.39 [95% CI, 0.94-2.05],
1.67 [95% CI, 0.98-2.85]; P = .03 for trend).
In a secondary analysis restricted to nonobese individuals (BMI <30),
the association between BMI and risk for AF remained significant (sex-pooled
multivariable-adjusted HR per 1-unit increase in BMI, 1.06; 95% CI, 1.02-1.10; P = .002). Results were also unchanged when analyses
were repeated to include younger individuals (<35 years) or underweight
individuals (BMI <18.5) and in analyses adjusting for cohort status (original
cohort vs offspring cohort) or alcohol use. Multivariable-adjusted HRs for
AF associated with BMI were also similar after excluding the 49 individuals
who developed atrial flutter. We repeated the Cox analyses with stratification
for cohort status, with findings similar to those in the original model (adjusted
HR per 1-unit increase in BMI: men, 1.04; 95% CI, 1.01-1.07; P = .02; women, 1.03; 95% CI, 1.01-1.06; P = .02).
Because we hypothesized that the influence of obesity on risk of AF
may be mediated by left atrial enlargement, we performed subsequent analyses
adjusting for echocardiographic left atrial diameter (available in 2229 men
[93%] and 2698 women [93%]) in addition to clinical covariates. Mean (SD)
left atrial diameter was higher in obese men (4.4 [0.5] cm) compared with
overweight men (4.1 [0.4] cm) (P<.001) and those
with normal BMI (3.8 [0.4] cm) (P<.001). The difference
in left atrial diameter between overweight men and those with normal BMI was
also significant (P<.001). Similarly, mean left
atrial diameter was higher in obese women (4.0 [0.4] cm) compared with overweight
women (3.8 [0.5] cm) (P<.001) and those with normal
BMI (3.5 [0.5] cm) (P<.001) and higher in overweight
women compared with those with normal BMI (P<.001).
Adjustment for left atrial diameter markedly attenuated the effect of BMI
on risk of AF, rendering it statistically nonsignificant (adjusted HRs per
1-unit increment in BMI: men, 1.00; 95% CI, 0.97-1.04; P = .84; women, 0.99; 95% CI, 0.96-1.02; P = .56). Similarly, after adjustment for left atrial diameter,
there was no significant trend in multivariable-adjusted HRs across BMI categories
in men (1.00, 0.90 [95% CI, 0.66-1.21], and 1.11 [95% CI, 0.76-1.61]; P = .66 for trend) or women (1.00, 0.87 [95%
CI, 0.64-1.20], and 0.89 [95% CI, 0.59-1.32]; P = .47
for trend). Left atrial diameter was strongly associated with incident AF
(multivariable-adjusted HRs per 1-mm increment in left atrial diameter: 1.06
[95% CI, 1.04-1.09] in men, and 1.10 [95% CI, 1.07-1.13] in women; both P<.001).
These prospective, community-based data indicate that obesity is a risk
factor for AF. The association of obesity with subsequent development of AF
persists even after accounting for concomitant conditions such as hypertension,
diabetes, and MI. The validity of our results is supported by the large sample
size, long duration of follow-up, and their consistency in multiple analyses
adjusting for known confounders in men and women. Furthermore, our findings
have biological plausibility because obesity is associated with an important “intermediate”
phenotype for AF, left atrial enlargement.9,23 Indeed,
the results of our analyses suggest that the excess risk of AF associated
with obesity may be attributable to differences in left atrial size between
lean and obese individuals.
We observed that obesity was associated with a 50% increase in the risk
of AF. This value may underestimate the aggregate impact of obesity on AF
risk, because it adjusts for conditions such as hypertension and diabetes
that predispose to AF and are common sequelae of obesity. Furthermore, whereas
the influence of obesity on the chances of developing AF in any given patient
may be modest, the implication of these results for the population burden
of AF may be substantial, because obesity is highly prevalent and potentially
modifiable.24 Thus, even a small decrease in
the prevalence of obesity could lead to a large reduction in the incidence
The observation that HRs for overweight did not reach statistical significance
may reflect either a threshold effect or reduced statistical power to find
an effect among overweight individuals (given the smaller relative risk associated
with being overweight). We estimate that the statistical power to detect the
observed HRs in the overweight group ranged from 40% (men) to 69% (women).
Furthermore, when we excluded individuals with obesity (BMI ≥30) from the
sample, BMI remained significantly associated with risk of AF, which suggests
that the elevated AF risk was not restricted to obese individuals.
Left atrial enlargement is an important precursor of AF,23 and
prior studies have shown that BMI is one of the most powerful determinants
of left atrial size.8,9,25 Elevated
plasma volume,26 ventricular diastolic dysfunction,13 and enhanced neurohormonal activation27 accompany
obesity and may contribute to left atrial enlargement and electrical instability.
Furthermore, recent studies suggest that adiposity may have a direct influence
on myocardial structure, perhaps via increased oxidative stress28 or
Extracardiac factors that may increase atrial arrhythmogenicity in obese
individuals include autonomic dysfunction12 and
sleep apnea.29 Kanagala et al29 reported
an association between obstructive sleep apnea and recurrence of AF after
cardioversion, postulating that hypoxemia, increased afterload, or pulmonary
vasoconstriction may play roles.
Comparison With Prior Studies
A previous report from the Framingham Heart Study did not find a significant
association between BMI and the risk of AF, but that study pooled repeated
observations over a 2-year follow-up period.4 Relations
of BMI with the short-term risk of AF may be weak, in part because AF is a
disease of elderly individuals and BMI frequently decreases with age and illness.
A few epidemiologic studies have suggested an association between BMI and
AF, but these studies were retrospective,6 limited
to men,5,7 or the diagnosis of
AF was based on hospital admission codes.7
The present investigation extends the results of prior studies to a
large, prospective, community-based cohort that has been under continuous
surveillance for AF and cardiovascular events for several decades. We used
contemporary criteria for categorizing BMI as recommended by the World Health
Organization and National Institutes of Health.20 Another
important feature of this investigation was the ability to adjust for interim
cardiovascular events and baseline echocardiographic data.
Despite the strengths listed above, several limitations deserve mention.
Although ascertainment of AF was based on electrocardiograms obtained directly
from physician offices, hospitals, and routine Framingham Heart Study examinations,
we cannot exclude the possibility that some episodes of AF were missed because
they were asymptomatic or minimally symptomatic and transient. However, such
misclassification would not be expected to affect obese and nonobese individuals
differentially; random misclassification might have led to a conservative
bias. Additionally, we included all episodes of new-onset AF and did not distinguish
between chronic and paroxysmal AF. It is possible that the influence of obesity
differed according to the type of AF. Similarly, we included both atrial flutter
and AF in our end point; we had too few cases of atrial flutter to study this
arrhythmia separately. Whereas many individuals with atrial flutter subsequently
experience AF,30 the former may have a distinct
pathogenesis and risk factors.
Atrial electrophysiological changes may play a critical role in the
pathogenesis and maintenance of AF.31,32 Given
the observational nature of our cohort, we were limited to characterizing
atrial size (with echocardiography). Thus, further studies are necessary to
understand the atrial changes in obese individuals that precede AF. Although
we adjusted for interim MI and heart failure, we did not account for the development
of other events or noncardiac surgeries that may have affected the risk of
AF. Because variation in baseline left atrial size appeared to account for
the link between obesity and AF, we do not believe that there was substantial
confounding from these unmeasured risk factors. Additionally, we did not study
the influence of changes in BMI over time. Participants attending multiple
examinations, in whom serial BMI measurements would be available, may be healthier
and less likely to develop AF than those attending fewer examinations. Also,
standardized echocardiographic data were not available at every follow-up
Because we used BMI as a surrogate measure of adiposity, it is possible
that we misclassified individuals with high muscle mass. This misclassification
may have affected men more than women, particularly in the overweight category.
Although we did not find evidence of effect modification by sex in analyses
incorporating sex interaction terms, these analyses may have been underpowered
to detect modest interactions. Also, we did not measure waist-hip ratio or
waist circumference at these examinations; these measures of abdominal adiposity
may add incremental information to BMI in the prediction of cardiovascular
risk.33,34 Because parental history
may be a risk factor for AF, we performed stratified analyses separating parents
and offspring who were members of the Framingham original and offspring cohorts,
respectively.22 While these analyses did not
account for sibling influences, the lack of attenuation of our findings in
the stratified analyses suggests that the association with BMI is not explained
by AF heritability.
The results of this study may not be generalizable to individuals with
very advanced age or those with severe hypertension, because of the low prevalence
of these characteristics in the study sample. Because age and age-related
risk factors are powerfully related to the risk of AF,4 we
cannot exclude the possibility that our findings would have differed in a
substantially older population. Also, our cohort is predominantly white; thus,
our findings may not apply to nonwhite individuals.
Obesity has become increasingly prevalent in the United States.24 Our findings suggest that obesity is a risk factor
for AF, the most common disturbance of cardiac rhythm. Because management
of AF remains a difficult clinical challenge, the identification of potentially
modifiable risk factors may have important public health implications.
Although our study was observational, it raises the intriguing possibility
that weight reduction may decrease the risk of AF. In this regard, it is interesting
to note that weight reduction has been linked to regression of left atrial
enlargement.35 Further studies are needed to
understand the influence of adiposity on cardiac remodeling, to document the
effects of weight loss on the risk of new AF, and to investigate the interaction
between obesity and therapies for chronic or paroxysmal AF.
Corresponding Author: Emelia J. Benjamin,
MD, ScM, Framingham Heart Study, 73 Mount Wayte Ave, Suite 2, Framingham,
MA 01702-5827 (email@example.com).
Author Contributions: Dr Benjamin had full
access to all of the data in the study and takes responsibility for the integrity
of the data and the accuracy of the data analyses. Drs Vasan and Benjamin
contibuted equally to this article.
Study concept and design: Wang, D’Agostino,
Wolf, Vasan, Benjamin.
Acquisition of data: Wang, Levy, D’Agostino,
Analysis and interpretation of data: Wang,
Parise, Levy, D’Agostino, Vasan, Benjamin.
Drafting of the manuscript: Wang, Parise, D’Agostino,
Critical revision of the manuscript for important
intellectual content: Parise, Levy, D’Agostino, Wolf, Vasan,
Statistical analysis: Parise, D’Agostino.
Obtained funding: Wolf, Benjamin.
Administrative, technical, or material support:
Study supervision: Vasan, Benjamin.
Funding/Support: This work was supported by
National Institutes of Health/National Heart, Lung, and Blood Institute (NHLBI)
grants NO1-HC-25195, 6R01-NS-17950, and K23-HL074077-01 (Dr Wang) and K24-HL-04334
Role of the Sponsor: The NHLBI had no role
in the study design, analyses, or drafting of the manuscript. The NHLBI reviews
all manuscripts submitted for publication but it was not involved in the decision
Go AS, Hylek EM, Phillips KA.
et al. Prevalence of diagnosed atrial fibrillation in adults: national implications
for rhythm management and stroke prevention: the Anticoagulation and Risk
Factors in Atrial Fibrillation (ATRIA) Study. JAMA
. 2001;285:2370-237511343485Google ScholarCrossref
Benjamin EJ, Wolf PA, D'Agostino RB, Silbershatz H, Kannel WB, Levy D. Impact of atrial fibrillation on the risk of death: the Framingham
Heart Study. Circulation
. 1998;98:946-9529737513Google ScholarCrossref
Wyse DG, Waldo AL, DiMarco JP.
et al. A comparison of rate control and rhythm control in patients with atrial
fibrillation. N Engl J Med
. 2002;347:1825-183312466506Google ScholarCrossref
Benjamin EJ, Levy D, Vaziri SM, D'Agostino RB, Belanger AJ, Wolf PA. Independent risk factors for atrial fibrillation in a population-based
cohort: the Framingham Heart Study. JAMA
. 1994;271:840-8448114238Google ScholarCrossref
Krahn AD, Manfreda J, Tate RB, Mathewson FA, Cuddy TE. The natural history of atrial fibrillation: incidence, risk factors,
and prognosis in the Manitoba Follow-up Study. Am J Med
. 1995;98:476-4847733127Google ScholarCrossref
Ruigomez A, Johansson S, Wallander MA, Rodriguez LA. Incidence of chronic atrial fibrillation in general practice and its
treatment pattern. J Clin Epidemiol
. 2002;55:358-36311927203Google ScholarCrossref
Wilhelmsen L, Rosengren A, Lappas G. Hospitalizations for atrial fibrillation in the general male population:
morbidity and risk factors. J Intern Med
. 2001;250:382-38911887972Google ScholarCrossref
Vaziri SM, Larson MG, Lauer MS, Benjamin EJ, Levy D. Influence of blood pressure on left atrial size: the Framingham Heart
. 1995;25:1155-11607768556Google ScholarCrossref
Pritchett AM, Jacobsen SJ, Mahoney DW, Rodeheffer RJ, Bailey KR, Redfield MM. Left atrial volume as an index of left atrial size: a population-based
study. J Am Coll Cardiol
. 2003;41:1036-104312651054Google ScholarCrossref
Lauer MS, Anderson KM, Kannel WB, Levy D. The impact of obesity on left ventricular mass and geometry: the Framingham
Heart Study. JAMA
. 1991;266:231-2361829117Google ScholarCrossref
Zhou YT, Grayburn P, Karim A.
et al. Lipotoxic heart disease in obese rats: implications for human obesity. Proc Natl Acad Sci U S A
. 2000;97:1784-178910677535Google ScholarCrossref
Pelat M, Verwaerde P, Merial C.
et al. Impaired atrial M(2)-cholinoceptor function in obesity-related hypertension. Hypertension
. 1999;34:1066-107210567183Google ScholarCrossref
Iacobellis G, Ribaudo MC, Leto G.
et al. Influence of excess fat on cardiac morphology and func tion: study
in uncomplicated obesity. Obes Res
. 2002;10:767-77312181385Google ScholarCrossref
Dawber TR, Meadors GF, Moore FEJ. Epidemiological approaches to heart disease: the Framingham Study. Am J Public Health
. 1951;41:279-28614819398Google ScholarCrossref
Kannel WB, Feinleib M, McNamara PM, Garrison RJ, Castelli WP. An investigation of coronary heart disease in families: the Framingham
Offspring Study. Am J Epidemiol
. 1979;110:281-290474565Google Scholar
Kannel WB, Gordon T, Offutt D. Left ventricular hypertrophy by electrocardiogram: prevalence, incidence,
and mortality in the Framingham Study. Ann Intern Med
. 1969;71:89-1054239887Google ScholarCrossref
Savage DD, Garrison RJ, Kannel WB, Anderson SJ, Feinleib M, Castelli WP. Considerations in the use of echocardiography in epidemiology: the
Framingham Study. Hypertension
. 1987;9:II40-II443804399Google Scholar
Sahn DJ, DeMaria A, Kisslo J, Weyman A. Recommendations regarding quantitation in M-mode echocardiography:
results of a survey of echocardiographic measurements. Circulation
. 1978;58:1072-1083709763Google ScholarCrossref
Kannel WB, , Wolf PA, , Garrison RJ, . Some Risk Factors Related to the Annual Incidence
of Cardiovascular Disease and Death in Pooled Repeated Biennial Measurements:
Framingham Heart Study, 30 Year Follow-up. Bethesda, Md: US Dept of Health and Human Services; 1987. Section
Clinical Guidelines on the Identification, Evaluation,
and Treatment of Overweight and Obesity in Adults. Bethesda, Md: National Heart, Lung, and Blood Institute; 1998
Cox DR. Regression models and life tables. J R Stat Soc [B]
. 1972;34:187-220Google Scholar
Fox CS, Parise H, D'Agostino RB Sr.
et al. Parental atrial fibrillation as a risk factor for atrial fibrillation
in offspring. JAMA
. 2004;291:2851-285515199036Google ScholarCrossref
Vaziri SM, Larson MG, Benjamin EJ, Levy D. Echocardiographic predictors of nonrheumatic atrial fibrillation: the
Framingham Heart Study. Circulation
. 1994;89:724-7308313561Google ScholarCrossref
Mokdad AH, Ford ES, Bowman BA.
et al. Prevalence of obesity, diabetes, and obesity-related health risk factors,
. 2003;289:76-7912503980Google ScholarCrossref
Gerdts E, Oikarinen L, Palmieri V.
et al. Correlates of left atrial size in hypertensive patients with left ventricular
hypertrophy: the Losartan Intervention For Endpoint Reduction in Hypertension
(LIFE) Study. Hypertension
. 2002;39:739-74311897755Google ScholarCrossref
Messerli FH, Ventura HO, Reisin E.
et al. Borderline hypertension and obesity: two prehypertensive states with
elevated cardiac output. Circulation
. 1982;66:55-607083520Google ScholarCrossref
Engeli S, Sharma AM. The renin-angiotensin system and natriuretic peptides in obesity-associated
hypertension. J Mol Med
. 2001;79:21-2911327100Google ScholarCrossref
Vincent HK, Powers SK, Stewart DJ, Shanely RA, Demirel H, Naito H. Obesity is associated with increased myocardial oxidative stress. Int J Obes Relat Metab Disord
. 1999;23:67-7410094579Google ScholarCrossref
Kanagala R, Murali NS, Friedman PA.
et al. Obstructive sleep apnea and the recurrence of atrial fibrillation. Circulation
. 2003;107:2589-259412743002Google Scholar
Halligan SC, Gersh BJ, Brown RD Jr.
et al. The natural history of lone atrial flutter. Ann Intern Med
. 2004;140:265-26814970149Google ScholarCrossref
Allessie M, Ausma J, Schotten U. Electrical, contractile and structural remodeling during atrial fibrillation. Cardiovasc Res
. 2002;54:230-24612062329Google ScholarCrossref
Kistler PM, Sanders P, Fynn SP.
et al. Electrophysiologic and electroanatomic changes in the human atrium
associated with age. J Am Coll Cardiol
. 2004;44:109-11615234418Google ScholarCrossref
Rexrode KM, Carey VJ, Hennekens CH.
et al. Abdominal adiposity and coronary heart disease in women. JAMA
. 1998;280:1843-18489846779Google ScholarCrossref
Rimm EB, Stampfer MJ, Giovannucci E.
et al. Body size and fat distribution as predictors of coronary heart disease
among middle-aged and older US men. Am J Epidemiol
. 1995;141:1117-11277771450Google Scholar
Alaud-din A, Meterissian S, Lisbona R, MacLean LD, Forse RA. Assessment of cardiac function in patients who were morbidly obese. Surgery
. 1990;108:809-8182218895Google Scholar