Seasonality and suicide: the role of regional features of suicide dynamics in Ukraine in 2005-2021 in the development of a statistical model for their prediction

Abstract

Summary Background. Suicidal behavior has traditionally been considered by medicine to be a serious public health problem. Suicides are the 13th leading cause of death in the general population, claiming more than 58,000 lives in Europe each year. The National Institute of Mental Health (NIMH), the United Kingdom's Office for National Statistics, and other developed countries' statistics provide accurate observations of the dynamics of this indicator. State Statistics Service of Ukraine and Ptoukha Institute for Demography and Social Studies of the National Academy of Sciences of Ukraine only in 2021 provided complete information on the number of deaths and their causes in Ukraine for a long time - from 2005 to 2021, which made our study possible. Objective. The aim of our study was to establish and compare the features of regional dynamic characteristics of changes in the number of deaths due to intentional self-harm. Based on this goal, the tasks were: construction of time series of the such deaths number in the period 2005 - 2021 for each region of Ukraine; study and mathematical and statistical analysis of the dynamic characteristics of these time series; identification of possible causes that explain the identified features of the identified dynamics of the such deaths number; construction of a statistical forecast of the dynamics of the number of suicides for each region for one year with the possibility of its further verification. Methods and materials. Research material - data from the State Statistics Service of Ukraine and the Institute of Demography and Social Research on the number of deaths due to intentional self-harm during 2005 - 2021. Research methods - analysis of time series using autocorrelation analysis based on Leung-Box statistics and the method of seasonal exponential smoothing. Results. In order to study the trends in the dynamics of suicidal activity in the regions of Ukraine, an autocorrelation of absolute indicators of the number of completed suicides was carried out and correlograms of time series of suicide numbers for each region were constructed. Further analysis of the constructed correlograms indicated that they should be divided into four groups. According to the calculation of the coefficient of determination, it was found that a fairly high share of the total variation of the series, both Ukraine (average R2 = 0.656) and all individual regions (average R2 = 0.731 ± 0.051), can be explained by our model, and the model itself may evaluate as consistent. According to the results of the analysis, it is possible to say that for most regions of Ukraine and for the state as a whole, the periods with the highest mortality rates due to completed suicides are the period from March to May, and July, and, to a lesser extent, January 2022. The period characterized by a gradual decrease in the number of completed suicides - August - December, as well as a sudden decrease in the number of deaths in February and June. We refused to analyze the results of the forecast of separate regions, taking into account socio-demographic features, namely, a very high demographic mobility of a large part of the population of Ukraine. We assume that the unacceptable results of mathematical and statistical analysis of reports of mortality due to completed suicides in many areas may be caused by a distorted picture of reporting data due to socio-demographic reasons, so they do not fully reflect the true picture of phenomenon. Conclusions. The statistical forecasting model built by us assumes that the seasonal periodicity in September 2021 - August 2022 should be characterized by a decrease in the number of suicides during September - December 2021, February, June and August 2022 with an increase in their number in January, March - May and June 2022. The studied chronobiological aspects are promising for further research to improve general and regional suicide prevention programs in Ukraine. Keywords: suicides, seasonality, time series, exponential smoothing, autocorrelation analysis, statistical prognostic model