Are daylight saving time transitions associated with changes in myocardial infarction incidence? Results from the German MONICA/KORA Myocardial Infarction Registry.

BACKGROUND

Some studies suggest that transitions to and from daylight saving time (DST) have an influence on acute myocardial infarction (AMI) incidence. However, the available publications have a number of limitations e.g. regarding sample size, exclusion of fatal AMI cases, precise assessment of AMI onset, and consideration of possible confounders, and they were conducted in countries with different geographical location. The objective of this study was to examine the association of DST transitions with AMI incidence recorded in the population-based German MONICA/KORA Myocardial Infarction Registry.

METHODS

The study sample consisted of 25,499 coronary deaths and non-fatal AMI cases aged 25-74 years. We used Poisson regression with indicator variables for the 3 days or the week after the spring and the autumn transition and adjusted for potential confounders to model the association between DST transitions and AMI incidence. In addition, we built an excess model by calculating observed over expected events per day.

RESULTS

Overall, no significant changes of AMI risk during the first 3 days or 1 week after the transition to and from DST were found. However, subgroup analyses on the spring transition revealed significantly increased risks for men in the first 3 days after transition (RR 1.155, 95 % CI 1.000-1.334) and for persons who took angiotensine converting enzyme (ACE) inhibitors prior to the AMI (3 days: RR 1.489, 95 % CI 1.151-1.927; 1 week: RR 1.297, 95 % CI 1.063-1.582). After the clock shift in autumn, patients with a prior infarction had an increased risk to have a re-infarction (3 days: RR 1.319, 95 % CI 1.029-1.691; 1 week: RR 1.270, 95 % CI 1.048-1.539).

CONCLUSIONS

Specific subgroups such as men and persons with a history of AMI or prior treatment with ACE inhibitors, may have a higher risk for AMI during DST. Further studies which include data on chronotype and sleep duration are needed in order to confirm these results.