Sweetened Beverages, Genetic Susceptibility, and Incident Atrial Fibrillation: A Prospective Cohort Study.

BACKGROUND:An association between sweetened beverages and several cardiometabolic diseases has been reported, but their association with atrial fibrillation (AF) is unclear. We aimed to investigate the associations between consumption of sugar-sweetened beverages (SSB), artificially sweetened beverages (ASB), and pure fruit juice (PJ) and risk of consumption with AF risk and further evaluate whether genetic susceptibility modifies these associations. METHODS:A total of 201 856 participants who were free of baseline AF, had genetic data available, and completed a 24-hour diet questionnaire were included. Cox proportional hazard models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS:During a median follow-up of 9.9 years, 9362 incident AF cases were documented. Compared with nonconsumers, individuals who consumed >2 L/wk of SSB or ASB had an increased risk of AF (HR, 1.10 [95% CI, 1.01-1.20] and HR, 1.20 [95% CI, 1.10-1.31]) in the multivariable-adjusted model. A negative association was observed between the consumption of ≤1 L/wk of PJ and the risk of AF (HR, 0.92 [95% CI, 0.87-0.97]). The highest HRs (95% CIs) of AF were observed for participants at high genetic risk who consumed >2 L/wk of ASB (HR, 3.51 [95% CI, 2.94-4.19]), and the lowest HR were observed for those at low genetic risk who consumed ≤1 L/wk of PJ (HR, 0.77 [95% CI, 0.65-0.92]). No significant interactions were observed between the consumption of SSB, ASB, or PJ and genetic predisposition to AF. CONCLUSIONS:Consumption of SSB and ASB at >2 L/wk was associated with an increased risk for AF. PJ consumption ≤1 L/wk was associated with a modestly lower risk for AF. The association between sweetened beverages and AF risk persisted after adjustment for genetic susceptibility to AF. This study does not demonstrate that consumption of SSB and ASB alters AF risk but rather that the consumption of SSB and ASB may predict AF risk beyond traditional risk factors.