Relation between temperature and suicide mortality in Japan in the presence of other confounding factors using time-series analysis with a semiparametric approach

Abstract

Objectives: The objective of this study was to assess the relation between temperature and suicide mortality in Japan using time series analysis with a semiparametric approach.

Methods: We analyzed the relation between daily fluctuations in suicide mortality and maximum temperatures for all regions in Japan over the period of time from 1972 to 1995 using a generalized additive model. The model controls for the time trend, season, selected meteorological parameters, day of the week, and holiday. Adjustment was based using penalized splines and the decision on the amount of smoothness was based on minimizing the unbiased risk estimation criterion.

Results: The results show that suicide mortality in Japan has a seasonal character and it varies from year to year, with the highest occurrence in April, as well as in the first part of the week, especially on Mondays and Tuesdays. As for the day of the week, there were only few suicide cases on Saturdays and holidays. We found that for all regions in Japan when temperature increased the suicide mortality increased on the same day (lag = 0). Analysis by method of suicide showed that when temperature increased mortality significantly increased only for suicide by a violent method. The pattern of the relation for other methods remained unclear.

Conclusions: This study suggests that an increase in temperature has a short-term effect on suicide mortality in Japan.

Fig. 1

Time-series and structural time-series of suicide mortality in Japan (1972–1995)

Fig. 2

Basic residual plots for checking the generalized additive model (GAM) model fitting process (Kanto region). The upper left normal (Q-Q) plot is very close to a straight line, suggesting reasonable distributional assumption. The upper right plot suggests that variance is approximately constant as the mean increases. The histogram of residuals at the lower left appears consistent with normality. The lower right plot of response against fitted values shows a positive linear relation with a good deal of scatter: nothing problematic. Resids. residuals, pred. predictor, Q-Q Quantiles-Quantiles

Fig. 3

Autocorrelation and partial autocorrelation functions for the maximum temperature suicide model residuals obtained by GAM Poisson model. ACF autocorrelation function

Fig. 4

The GAM-estimated effect of time component on suicide mortality for 8 regions in Japan (excluding Okinwa) (1972–1995). The continuous lines are the function estimates, and the shaded areas delimit the 95% confidence interval for the function. The numbers on each y-axis are the effective degrees of freedom of the term being plotted. The numbers on the x-axis indicate days starting from January 1st, 1972. Smoothing parameters are estimated by unbiased risk estimation (UBRE)/Akaike information criterion (AIC) [36]

Fig. 5

The GAM-estimated effect of maximum temperature (°C) on suicide mortality for 8 regions in Japan (excluding Okinawa). The continuous lines are the function estimates, and the shaded areas delimit the 95% confidence interval for the function. The numbers on each y-axis are the effective degrees of freedom of the term being plotted. Smoothing parameters are estimated by UBRE/AIC

Fig. 6

The GAM-estimated effect of sunshine duration (h) on suicide mortality for 8 regions in Japan (excluding Okinawa). The continuous lines are the function estimates, and the shaded areas delimit the 95% confidence interval for the function. The numbers on each y-axis are the effective degrees of freedom of the term being plotted. Smoothing parameters are estimated by UBRE/AIC

Fig. 7

Correlation estimates of suicide deaths and the residuals on different timescales. Residuals were taken after regressing the suicide deaths and temperature on the hours of daylight. R1–R9 represent regions of Japan from Hokkaido (R1) to Okinawa (R9)

Fig. 8

The GAM-estimated effect of maximum temperature on suicide mortality for different methods. This is an example of the Tohoku region, where the suicide mortality was highest. The continuous lines are the function estimates, and the shaded areas delimit the 95% confidence interval for the function. The numbers on each y-axis are the effective degrees of freedom of the term being plotted. Smoothing parameters are estimated by UBRE/AIC