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Tomsk 2012

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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

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

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).

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.

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.)

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

Distribution by factors of heliogeophysical parameters

Distribution of morbidity by factors

Distribution of mortality indicator by factors

Distribution by factors of dynamics of major morbidity and mortality factors

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

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

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

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).

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

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!

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

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

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

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

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

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

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

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

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

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

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.

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.

Thank you for your attention!

Conclusion

R

Conclusion

Alfven Hannes

Otto Schumann

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

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

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.