In this cohort of female health care professionals without prior evidence of CVD, BMI is strongly associated with subsequent development of AF even after accounting for the interim development of CVD and other important AF risk factors such as diabetes and hypertension. The relationship is linear, with a 4.7% increase in risk of incident AF for each kg/m2 increase in BMI. In our full multivariable models, 1.65–1.77-fold elevations in AF risk were observed among the obese (BMI >30 kg/m2), with greater than two-fold elevations in risk among obese women who were 60 years of age or younger at study entry. Adjustment for inflammatory markers measured at baseline in the biomarker cohort only minimally attenuated the obesity-associated risk of AF, suggesting that inflammation is not a major mediator of the AF risk associated with obesity.
When BMI was updated over the course of the study, significant short-term elevations in risk were associated with elevated BMI in both the overweight and obese ranges even after adjustment for updated biologic intermediaries. Study participants who became obese during the first 60 months of follow up had a 41% adjusted increase in risk of developing AF (p=0.02) compared to those who maintained BMI <30 kg/m2. These results on short term risk suggest that the AF risk associated with obesity may be modifiable by weight change.
To our knowledge, this is one of the first studies examining the short-term influence of BMI changes over time and subsequent risk of AF. Our results utilizing updated BMI measures are consistent with data from other population based cohort studies utilizing a single measure of BMI8, 9, 22–24
, although the linear relationship observed here was not apparent in all of the individual studies. In a meta-analysis of 5 population based cohorts 10
, baseline BMI was associated with a graded risk of AF, with estimated risk elevations of 39% and 87% in the overweight and obese respectively as compared to those of normal weight. A recent study of 6903 Swedish men demonstrated that long-term weight gain from age 20 to midlife was associated with an increased risk of AF consistent with our findings on short-term risk.25
Prior population-based studies did not report AF risk according to subgroups, and the reason for the interaction between age and obesity-associated AF risk in our data is not clear. We observed a similar age-interaction for the AF risk associated with habitual vigorous exercise among men in the Physicians Health Study,26
and it is possible that the influence of other AF risk factors may differ according to age. Women with a genetic or physiologic predisposition to developing obesity-associated AF may do so at a younger age, and therefore, these women would be excluded from analyses of older populations. This finding warrants further investigation since it raises potential alternative mechanisms for the rapid increase in the prevalence of new onset AF not reliant on the aging of the U.S. population.
There are many reasons why dynamic changes in BMI might be expected to modify AF risk independent of obesity associated co-morbidities. Obesity is associated with increased left atrial size and decreased left ventricular diastolic function which itself leads to increased left atrial pressure.9, 27
Weight reduction has also been linked to regression of left atrial enlargement.28
Dynamic changes in left atrial size and pressure likely affect both the atrial substrate and triggers for AF. Increased left atrial pressure may acutely lead to increases in atrial ectopy that triggers AF.11
Further, more prolonged BMI-mediated left atrial stretch may lead to development of fibrosis and atrial enlargement on a structural basis.29
Some of these obesity-associated atrial changes could be reversible or modifiable with weight loss, while other changes may be irreversible.
If the observed dynamic associations between BMI and AF are causal, the public health impact of the current obesity epidemic on the growing AF burden could be quite substantial with respect to clinical outcomes, quality of life and health care costs associated with AF. In our study, the prevalence of obesity increased over the course of the study from 18.0% to 24.2%, and 12.2% of incident AF cases were estimated to be attributable to obesity independent of other measured risk factors. When one also takes into account the modestly but significantly elevated risks observed in over a third of the women who were overweight, the percentage of AF cases attributable to an elevated BMI increases to 18.3%. Given the even higher prevalence of obesity and overweight in most Western populations, with current estimates for obesity approaching one third of the population,7
the attributable risk proportion associated with obesity and overweight in the general population is likely even higher.
The present study has several strengths and limitations that warrant consideration. Strengths of the present study include its prospective design, large sample size, updated measures of BMI, and long-term follow-up with a large number of confirmed events. Several limitations should also be considered. First, cases of AF were identified by self report and electrocardiographic screening was not performed in this cohort. Therefore, asymptomatic cases of AF would have been missed if not detected through the participant’s usual medical care. Although the percentage of AF cases that were asymptomatic in this health professional cohort with access to healthcare was similar to that in cohorts employing screening electrocardiograms30, 31
, it is likely that a more rigorous electrocardiographic screening method such as ambulatory ECG monitoring may have detected more asymptomatic episodes32
. Additionally, due to the sometimes subtle nature of symptoms, AF onset can be difficult to ascertain exactly.
Second, body weight and height, as well as data on all potential confounders, were self-reported, potentially leading to some misclassification; which if non-differential would bias our results towards the null. However high correlations have been demonstrated between self-reported and directly measured weight (r
=0.96) in a comparable cohort of female health professionals.33
BMI as a measure of adiposity in general may also misclassify those with high muscle mass, though BMI is highly correlated with absolute fat mass in women.34
Third, the selective nature of the cohort, initially healthy, middle-aged women health professionals primarily of Caucasian origin may limit the generalizability of the findings specifically to men or other non-Caucasian female populations where risk factors for AF may differ. Lastly, we were not able to include echocardiographic measures in our multivariable analysis, as these were not measured systematically in the entire cohort.