Figure 3.

Seasonality of all-cause mortality, and its peak and trough days before (solid) and after (dashed) temperature adjustment. The seasonality is assessed using a time-series regression model with a cyclic spline function with 4 degrees of freedom. The relative risk (RR) is the ratio of mortality estimates on the day of year x to daily minimum mortality estimates at the trough day with 95% confidence intervals (95% CI):

$$\mathsf{ }\mathsf{Relative}\mathsf{ }\mathsf{risk}=\frac{\mathsf{mortality}\mathsf{ }\mathsf{estimate}\mathsf{ }\mathsf{on}\mathsf{ }\mathsf{the}\mathsf{ }\mathsf{day}-\mathsf{of}-\mathsf{year}\mathsf{ }\mathsf{x}}{\mathsf{minimum}\mathsf{ }\mathsf{mortality}\mathsf{ }\mathsf{estimate}\mathsf{ }\mathsf{at}\mathsf{ }\mathsf{the}\mathsf{ }\mathsf{trough}}\mathsf{ }$$

The day of year with maximum and minimum mortality estimates is identified as the peak (triangle) and trough (circle) day, respectively, of the seasonality of mortality. Monte Carlo simulation was used to obtain empirical confidence intervals for peak and trough days