It has been established that the presence of depression is accompanied by an increased risk of morbidity and mortality in cerebrovascular and cardiovascular diseases and diabetes. The aim of this research was to estimate depressive symptom prevalence among the population in Central Kazakhstan and to define the relationship with social-demographic and behavioral factors. 1820 respondents of the population of Central Kazakhstan, aged 25 to 65, were performed. Participants included 777 urban and 1043 rural residents. Depressive symptoms assessed with the Patient Health Questionnaire (PHQ-9). The results showed that some degree of depressive symptoms was detected in 75.7% of the respondents. A minimal degree of depressive symptoms was observed in 28.51%, mild in 27.7%, moderate in 13.7%, and severe and very severe degree of depressive symptoms in 4.6% and 1.2%, respectively; the absence of depression symptoms was reported in 24.3% of the respondents. The study found a relationship between the prevalence of depressive symptoms and factors such as gender, education, income, presence of chronic diseases, and physical activity. We have not found a correlation between the frequencies of depressive symptoms with age, employment, character of labor, and marital status.

Lagged Poincaré plots have been successful in characterizing abnormal cardiac function. However, the current research practices do not favour any specific lag of Poincaré plots, thus complicating the comparison of results of different researchers in their analysis of heart rate of healthy subjects and patients. We researched the informative nature of lagged Poincaré plots in different states of the autonomic nervous system. It was tested in three models: different age groups, groups with different balance of autonomous regulation, and in hypertensive patients. Correlation analysis shows that for lag l = 6, SD1/SD2 has weak (r = 0.33) correlation with linear parameters of heart rate variability (HRV). For l more than 6 it displays even less correlation with linear parameters, but the changes in SD1/SD2 become statistically insignificant. Secondly, surrogate data tests show that the real SD1/SD2 is statistically different from its surrogate value and the conclusion could be made that the heart rhythm has nonlinear properties. Thirdly, the three models showed that for different functional states of the autonomic nervous system (ANS), SD1/SD2 ratio varied only for lags l = 5 and 6. All of this allow to us to give cautious recommendation to use SD1/SD2 with lags 5 and 6 as a nonlinear characteristic of HRV. The received data could be used as the basis for continuing the research in standardisation of nonlinear analytic methods.

We propose the method to compute the nonlinear parameters of heart rhythm (correlation dimensionD2and correlation entropyK2) using 5-minute ECG recordings preferred for screening of population. Conversion of RR intervals’ time series into continuous functionx(t)allows getting the new time series with different sampling ratedt. It has been shown that for alldt(250, 200, 125, and 100 ms) the cross-plots ofD2andK2against embedding dimensionmfor phase-space reconstruction start to level off atm=9. The sample sizeNat different sampling rates varied from 1200 atdt= 250 ms to 3000 atdt= 100 ms. Along with, theD2andK2means were not statistically different; that is, the sampling rate did not influence the results. We tested the feasibility of the method in two models: nonlinear heart rhythm dynamics in different states of autonomous nervous system and age-related characteristics of nonlinear parameters. According to the acquired data, the heart rhythm is more complex in childhood and adolescence with more influential parasympathetic influence against the background of elevated activity of sympathetic autonomous nervous system.