Background: Tools for the prediction of atrial fibrillation ( AF ) may identify high‐risk individuals more likely to benefit from preventive interventions and serve as a benchmark to test novel putative risk factors. Methods and Results: Individual‐level data from 3 large cohorts in the U nited S tates (Atherosclerosis Risk in Communities [ ARIC ] study, the Cardiovascular Health Study [ CHS ], and the Framingham Heart Study [ FHS ]), including 18 556 men and women aged 46 to 94 years (19% A frican A mericans, 81% whites) were pooled to derive predictive models for AF using clinical variables. Validation of the derived models was performed in 7672 participants from the Age, Gene and Environment—Reykjavik study ( AGES ) and the Rotterdam Study ( RS ). The analysis included 1186 incident AF cases in the derivation cohorts and 585 in the validation cohorts. A simple 5‐year predictive model including the variables age, race, height, weight, systolic and diastolic blood pressure, current smoking, use of antihypertensive medication, diabetes, and history of myocardial infarction and heart failure had good discrimination (C‐statistic, 0.765; 95% CI , 0.748 to 0.781). Addition of variables from the electrocardiogram did not improve the overall model discrimination (C‐statistic, 0.767; 95% CI , 0.750 to 0.783; categorical net reclassification improvement, −0.0032; 95% CI , −0.0178 to 0.0113). In the validation cohorts, discrimination was acceptable ( AGES C‐statistic, 0.664; 95% CI , 0.632 to 0.697 and RS C‐statistic, 0.705; 95% CI , 0.664 to 0.747) and calibration was adequate. Conclusion: A risk model including variables readily available in primary care settings adequately predicted AF in diverse populations from the U nited S tates and E urope.

Background—: Atrial fibrillation (AF) is an important risk factor for stroke and overall mortality, but information about the preventable burden of AF is lacking. The aim of this study was to determine what proportion of the burden of AF in blacks and whites could theoretically be avoided by the maintenance of an optimal risk profile. Methods and Results—: This study included 14 598 middle-aged Atherosclerosis Risk in Communities (ARIC) Study cohort members. Previously established AF risk factors, namely high blood pressure, elevated body mass index, diabetes mellitus, cigarette smoking, and prior cardiac disease, were categorized into optimal, borderline, and elevated levels. On the basis of their risk factor levels, individuals were classified into 1 of these 3 groups. The population-attributable fraction of AF resulting from having a nonoptimal risk profile was estimated separately for black and white men and women. During a mean follow-up of 17.1 years, 1520 cases of incident AF were identified. The age-adjusted incidence rates were highest in white men and lowest in black women (7.45 and 3.67 per 1000 person-years, respectively). The overall prevalence of an optimal risk profile was 5.4% but varied according to race and gender: 10% in white women versus 1.6% in black men. Overall, 56.5% of AF cases could be explained by having ≥1 borderline or elevated risk factors, of which elevated blood pressure was the most important contributor. Conclusion—: As with other forms of cardiovascular disease, more than half of the AF burden is potentially avoidable through the optimization of cardiovascular risk factors levels.