Tomsk 2012

1. National Research Tomsk State University Research and Education Center«Physics of the ionosphere and electromagnetic environment» TSU SBEI of HPE SSMU of the Ministry of Healthcare and Social Development of Russia Emergency ward, Tomsk Phenomenological features of the dynamics of mortality and morbidity depending on the parameters of heliogeophysical activity A.S. Borodin, A.G. Kolesnik, V.V. Kalyuzhin, M.V. Gudina, O.E. Shuba Tomsk 2012

2. Goal of the first part of the research Evaluation of the degree of bio-efficiency of the factors of heliogeophysical situation by analyzing the contingence of dynamics of these factors with alterations in the epidemiological data on morbidity and mortality of population in Tomsk for the period of time from 1990 through 2008

3. Objects of the research 1) Medical statistical indicators for the period of time from 1990 through 2008, obtained at Tomsk Regional Analytical Department: – morbidity of Tomsk population on major disease classes, calculated per 1000 of population for each year of the evaluated period; – mortality of Tomsk population, calculated per 100 000 of population considering the structure of death causes. 2)Indicators of heliogeophysical situation gathered from the following Internet resourceshttp://spidr.ngdc.noaa.gov,http://sosrff.tsu.ru: –X-ray radiation(X), – Wolf numbers(S), – electromagnetic emission flow in spectral window (F), –Ap-index of geomagnetic storm(А).

4. Methods of the research 1) In order to eliminate the influence of inhomogenuity of dimensions of the analyzed variables on the comparison results of their dynamics, a standardization of the analyzed values was carried out. 2) Maximal (M) and average (M) values as well as standard deviations (S) of indicators have been calculated during the correspondent years. 3) In order to better visualize time series of the data, the Hemming filter was used for smoothing the indicators. 4) Analysis of the studied indicators was performed usingprincipal component analysis to reduce the number of analyzed variables and to identify common factors and main trends in the change of dynamics of the analyzed variables.

5. Conventions for epidemiological indicators Morbidity on basic nosological classes Mortality depending on the reasons S1- Mortality caused by infectious and parasitic diseases S2- Mortality caused by neoplasms S3- Mortality caused by the diseases of the endocrine system, eating disorders, dysmetabolism and dysimmunity S8- Mortality caused by the diseases of the blood circulatory system S9- Mortality caused by hypertensive disease S10- Mortality caused by acute myocardial infarction S11- Mortality caused by the diseases of the respiratory organs S12- Mortality caused by the diseases of the digestive organs S14- Mortality caused by the diseases of the urogenital system S17- Mortality caused by congenital anomalies S18- Mortality caused by conditions observed during the perinatal period S19- Mortality caused by symptoms and inaccurately defined conditions S20- Mortality caused by accidents, poisonings and traumas Z1-Infectious and parasitic diseases Z2-Neoplasms Z3- Diseases of the endocrine system, eating disorders, dysmetabolism and dysimmunity Z5- Diseases of the nervous system and sense organs Z6- Diseases of the blood circulatory system Z7- Diseases of the respiratory organs Z8- Diseases of the digestive organs Z9- Diseases of the urogenital system Z10-Complications of pregnancy, act of delivery and postnatal period Z11- Diseases of skin and hypoderm Z12-Diseases of the musculoskeletal system and connective tissue Z14-Traumas and poisonings Z15-Malignant neoplasms (per 100 000 of population.)

6. Dynamics of some indicators Fig. 1 – Dynamics of solar activity indicators (XM) and mortality caused by congenital anomalies (S17) r =0.60 standardized index year Fig.2 – Dynamics of geomagnetic storm indicators (ApM) and mortality observed during the perinatal period (S18) r = 0.55 standardized index year

7. Distribution by factors of heliogeophysical parameters

8. Distribution of morbidity by factors

9. Distribution of mortality indicator by factors

10. Distribution by factors of dynamics of major morbidity and mortality factors

11. Contingence between the five designated factors of morbidity and mortality and the three factors of heliogeophysical parameters

12. Figure 3 – Dynamics of variables: factor 1 (cumulative solar activity), factor 3ZS (diseases of respiratory organs) r = 0,84 standardized index factor 1 factor 3ZS year Figure 4 – Dynamics of variables: factor 1 (cumulative solar activity), factor 4ZS (mortality caused by conditions during the perinatal period) r = 0.47 standardized index factor 1 factor 4ZS year

13. Figure 5 – Dynamics of variables: factor 3 (variations of X-ray radiation), factor 1ZS (neoplasms, mortality caused by congenital defects, hypertensive disease, acute myocardial infarction) r = 0.46 standardized index factor 3 factor1ZS year Figure6 – Dynamics of variables: factors 3 (variations of X-ray radiation) and factor 5ZS (infectious diseases, diseases of endocrine and nervous systems, skin diseases) r = - 0.78 standardized index factor 3 factor5ZS year

14. Conclusion 1 As result of the study, the impact of parameters of heliogeophysical situation on indicators of morbidity and mortality of population in Tomsk, general factors were singled out from the entire aggregation of health indicators of population, which are accurately correlated with alterations in solar activity indicators as well as the indicators of geomagnetic storm, and namely: F 3ZS – diseases of respiratory organs and mortality caused by the diseases of respiratory organs, blood circulatory system, accidents, F 4ZS – mortality caused by conditions during the perinatal periodcorrelate with F 1 – cumulative solar activity (r=0,84;r=0,47). F 1ZS – neoplasms, complications of pregnancy and act of delivery, diseases of digestive organs, mortality caused by neoplasms, congenital developmental anomalities,diseases of digestive organs, endocrine system, hypertensive disease, acute myocardial infarctioncorrelate with F 2 – geomagnetic storm (r= - 0,64). F 5ZS - infectious diseases, diseases of the endocrine and nervous systems, skin, musculoskeletal system, blood circulatory system, traumas and poisonings, mortality caused by infectious diseases and diseases of urogenital system correlate with F 3 – variations of X-ray radiation(r= - 0,78).

15. Goal of the second part of the research Evaluation of the impact of geomagnetic storms on the frequency of emergency calls to ambulance during one of the most powerful geomagnetic storms of October – November, 2003

16. End of October — beginning of November, 2003 was rarely “stormy” from the point of view of magnetic situation: outbursts in the Sun turned out to be the most powerful for the entire history of the observational astronomy! The outburst energy on November 4th, 2003 would be enough to supply electricity to such city as Moscow for 200 million years!

17. TECHNOLOGY AND MATERIALS OF THE RESEARCH A database was formed containing indicators of solar activity alterations, local geomagnetic storm and number of calls to the ambulance, which were all coordinated according to time. Vadim

18. Heliogeophysical features (from 01.10.2003 to 25.11.2003) The power of X-radiation flow in the range 1-8 Ǻ (Х, W/m2) (http://spidr.ngdc.noaa.gov) Local (Tomsk) geomagnetic disturbane (К, points) (http://sosrff.tsu.ru) METHODS AND MATERIALS OF THE RESEARCH

19. METHODS AND MATERIALS OF THE RESEARCH Data on the number of calls to the ambulance Table. Format of the original database - Formula used to reveal the total accumulated tendency in changes of epidemiological indicators - current change in the integral of the function where

20. Results of the research Valueof K-index Number of calls Watt/ metre2 Х (on the left) K-index(on the right) Number of a three-hour interval Number of a three-hour interval Figure 7. Dynamics of X-ray flow (Х) and geomagnetic disturbance (К) in October-November, 2003 Figure 8. Dynamics of the frequency of calling the ambulance (N) in Tomsk in October-November, 2003

21. Results of the research (statistically significant bonds are presented) Value of а correlation coefficient correlation coefficient Cl .2 Cl. 3 Cl. 4 Cl. 5 Cl. 6 Cl. 7 Cl. 9 Cl. 10 Cl. 11 Cl. 12 Classesof nosologic units Figure 9. Connection between the frequency of calls to the ambulance and the power of X-ray flow (lg(Х)) correlation coefficient Value of а correlation coefficient Cl .1 Cl. 2 Cl. 3 Cl. 4 Cl. 5 Cl. 6 Cl. 7 Cl. 9 Cl. 12 Classesof nosologic units Figure 10. Connection between the frequency of calls to the ambulance and the value of K-index

22. Results of the research Number of calls (standardized index) Watt/ metre2 r = 0. 58 Lg Х (on the left) Cl.4 (on the right) Number of a three-hour interval Figure11. Dynamics of the frequency of calls to the ambulance to patients with chronic cerebrovascular disease (cl.4) in Tomsk and the power of X-ray flow (lg(Х)) over the analyzed period of time

23. Results of the research Number of calls (standardized index) Point r = 0.17 K-index (on the left) Cl.5 (on the right) Number of a three-hour interval Figure 12. Dynamics of the number of calls to the ambulance to patients with arterial hypertension (cl.5) and the value of K-index in Tomsk over the analyzed period of time

24. Results of the research Number of calls (standardized index) Watt/ metre2 r = 0.30 Lg Х (on the left) Cl. 6 (on the right) Number of a three-hour interval Figure 13. Dynamics of the number of calls to the ambulance to patients with heart rhythm disturbances (cl.6) in Tomsk and the power of X-ray flow (lg(Х)) over the analyzed period of time

25. Results of the research Number of calls (standardized index) Point r = 0.27 K-index (on the left) Cl. 6 (on the right) Number of a three-hour interval Figure 14. Dynamics of the number of calls to the ambulance to patients with heart rhythm disturbances (Cl.6) and the value of K-index in Tomsk over the analyzed period of time

26. Results of the research А Б r = 0.37 r = 0.28 Number of calls (standardized index) Number of calls (standardized index) Point Watt/ metre2 K-index (on the left) Cl. 7 (on the right) Lg Х (on the left) Cl. 7 (on the right) Number of a three-hour interval Number of a three-hour interval Figure 15 (А, B) . Dynamics of the number of calls to the ambulance to patients with functional nervous sytem disorders (cl.7), on the one hand, and the power of X-ray flow (A) as well as the value of K-index in Tomsk (B) over the analyzed period of time, on the other hand

27. Conclusion 2 The carried out research allowed to reveal statistically and clinically significant correlation bonds between the number of calls to the ambulance in Tomsk to patients with the most widespread socially significant diseases, on the one hand, and local geomagnetic disturbance as well as the power of X-ray flow, on the other hand.

28. SUMMARY • We carried out the epidemiological research on the effect of heliogeophysical activity in various timeframes on the basis of the regional data. • We evaluated the degree of bioeffectiveness of the factors of heliogeophysical setting over one-year periods, taken on the basis of Karhunen-Loeve method and epidemiological data of mortality and morbidity of Tomsk population from 1990 to 2008. The analysis of the effect of changes in solar activity and geomagnetic disturbances on the indicators of mortality and morbidity has shown, that among all the indicators in various nosological classes we can reveal general factors which credibly correlate with major components of variances of characteristic indicators of solar activity and geomagnetic disturbance. • We determined the features of the degree of effect of heliogeophysical activity over the frequency of emergency calls to the ambulance in Tomsk, with 3-hour intervals for data averaging, during one of the most powerful disturbances of 2003. It was discovered that X-ray flow and geomagnetic disturbance are positively correlated with such classes of diseases as cerebrovascular diseases, arterial hypertension, heart rhythm disturbance andasequence as well as functional nervous system disorders. Herewith, variations of epidemiological indicators are connected both with independent effect of X-ray flow and geomagnetic disturbance and with joint effect of these factors.

29. Thank you for your attention!

30. Conclusion R

31. Conclusion Alfven Hannes Otto Schumann

32. Evaluation of the effect of variations of the environmental complex of physical fields on functioning of the human cardio-vascular system.

33. Data conversion Hamming filter window: Standardization of values (1) (4) ( 2 ) output value for the original row value total number of points used in the filter ( 3 ) Ordinal number of the row value Hamming window constant Хст - standardized value - current value - average value - mean-square deviation ordinal number of the row value 33 total number of values

34. Method of principle components Method of principle components is expansion of the time series into eigen-functions on orthogonal basis. R V = V , where R – mattix array for which the solution is sought; V– desired eigen-vector, - eigen-value The number of revealed factors is usually determined by the number of eigen-values which are more or equal to 1.