Many studies have demonstrated that cold and hot temperatures are associated with increased deaths and hospitalization rates; new findings indicate also an association with more specific cardiac risk factors. Most of these existing studies have relied on few weather stations to characterize exposures; few have used residence-specific estimates of temperature, or examined the exposure-response function. We investigated the association of arrhythmia episodes with spatial and temporal variation in temperature. We also evaluated the association btween monitored ambient temperature (central) and the same outcome. This longitudinal analysis included 701 older men participating in the VA Normative Aging Study. Arrhythmia episodes were measured as ventricular ectopy (VE) (bigeminy, trigeminy, or couplets episodes) by 4-min electrocardiogram (ECG) monitoring in repeated visits during 2000-2010. The outcome was defined as having or not VE episodes during a study visit. We applied a mixed-effect logistic regression model with a random intercept for subject, controlling for seasonality, weekday, medication use, smoking, diabetes status, body mass index, and age. We also examined effect modification by personal characteristics, confounding by air pollution, and the exposure-response function. For 1°C increase in the same day residence-specific temperature, the odds of having VE episodes was 1.10 (95% confidence interval [CI]: 1.04-1.17). The odds associated with 1°C increase in central temperature was 1.05 (95% CI: 1.02-1.09). The exposure-response function was nonlinear for averages of temperature, presenting a J-shaped pattern, suggesting greater risk at lower and higher temperatures. Increased warm temperature and decreased cold temperature may increase the risk of ventricular arrhythmias.
Implications: This is the first study to provide evidence that residence-specific temperature exposure is associated with increased risk of ventricular arrhythmias in cohort of elderly subjects without known chronic medical conditions; that the delayed effect of temperature has a nonlinear relationship; and therefore that both warm and cold temperature increase the risk of having ventricular arrhythmias. Moreover, we show that the use of residence-specific temperature data reduces downward bias due to exposure error, by comparing the estimated health effect based on our spatiotemporal exposure prediction model to those based on a single local weather monitor.