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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. - PowerPoint PPT Presentation
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Tomsk 2012
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
A.S. Borodin, A.G. Kolesnik,
V.V. Kalyuzhin, M.V. Gudina, O.E. Shuba
Phenomenological features of the dynamics of mortality and morbidity depending on the parameters of heliogeophysical activity
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
Goal of the first part of the research
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 resources http://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 using principal 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
Z1- Infectious and parasitic diseasesZ2- NeoplasmsZ3- 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 systemZ7- Diseases of the respiratory organsZ8- Diseases of the digestive organsZ9- Diseases of the urogenital systemZ10- Complications of pregnancy, act of delivery and postnatal period Z11- Diseases of skin and hypoderm Z12- Diseases of the musculoskeletal systemand connective tissue Z14- Traumas and poisoningsZ15- Malignant neoplasms (per 100 000 of population.)
Morbidity on basic nosological classes
Mortality depending on the reasons
S1- Mortality caused by infectious and parasitic diseasesS2- Mortality caused by neoplasmsS3- Mortality caused by the diseases of the endocrine system, eating disorders, dysmetabolism and dysimmunityS8- Mortality caused by the diseases of the blood circulatory systemS9- Mortality caused by hypertensive diseaseS10- Mortality caused by acute myocardial infarctionS11- Mortality caused by the diseases of the respiratory organsS12- Mortality caused by the diseases of the digestive organsS14- Mortality caused by the diseases of the urogenital systemS17- Mortality caused by congenital anomalies S18- Mortality caused by conditions observed during the perinatal periodS19- Mortality caused by symptoms and inaccurately defined conditionsS20- Mortality caused by accidents, poisonings and traumas
Fig. 1 – Dynamics of solar activity indicators (XM) and mortality caused by congenital anomalies (S17)
r =0.60
Fig. 2 – Dynamics of geomagnetic storm indicators (ApM) and mortality observed during the perinatal period (S18)
r = 0.55
Dynamics of some indicators
year
year
sta
nd
ard
ize
d in
de
xst
an
da
rdiz
ed
ind
ex
Distribution by factors of heliogeophysical parameters
Heliogeophysical parameters Factor 1 Factor 2 Factor 3
XM 0.751188 0.408861 0.489293
XS 0.426124 0.415981 0.800876
XX 0.431747 0.384971 0.811857
ApM 0.413675 0.859303 0.249933
ApS 0.340177 0.827759 0.437899
ApX 0.464902 0.688882 0.512274
SM 0.902610 0.267525 0.324475
SS 0.886097 0.348986 0.284867
SX 0.889963 0.320121 0.314265
FM 0.867003 0.345070 0.348868
FS 0.835176 0.416574 0.339304
FX 0.813275 0.450380 0.356550
Proper values5.937787 3.177844 2.705727
Explainable share of dispersion of
factors (%)49,4 26,4 22,5
Morbidity classes Factor 1Z Factor 2Z Factor 3Z
Z1 – infectious diseases 0.147395 0.950640 -0.171662
Z2 - neoplasms 0.895387 0.359937 0.049113
Z3 – endocrine system 0.483074 0.830433 0.086437
Z5 – nervous system 0.477469 0.802803 0.249378
Z6 – blood circulation 0.435403 0.828108 0.271684
Z7 – respiratory organs -0.244085 0.210945 -0.921257
Z8 – digestive -0.951662 -0.149408 -0.166466
Z9 - urogenital 0.562165 0.490332 0.627510
Z10 – complications of pregnancy
0.877522 0.048840 0.331640
Z11 – skin 0.337088 0.899074 -0.188156
Z12 – musculoskeletal -0.628733 0.709963 -0.203051
Z14 – traumas and poisonings
-0.354750 0.899685 0.076810
Z15 – malignant neoplasms
0.791270 0.212897 0.557330
Proper values 4.786558 5.529917 1.948680
Explainable share of dispersion of factors
(%)36,8 42,5 14,9
Distribution of morbidity by factors
Mortality classes Factor 1S Factor 2S Factor 3S Factor 4S Factor 5S
S1 – infectious -0.146031 0.450613 -0.064101 0.824059 -0.218721
S2 – neoplasms 0.802470 0.515752 -0.136455 0.253716 -0.035020
S3 – endocrine -0.938247 -0.057622 -0.049817 -0.250011 0.198468
S8 – blood circulation 0.397702 0.844115 0.182248 0.220368 0.212061
S9 – hypertensive disease
-0.955519 0.155320 0.014434 0.221923 0.043484
S10 – miocardial infarction
0.861264 0.479270 -0.110324 -0.056029 -0.075357
S11 – respiratory 0.164109 0.955793 0.141160 0.129297 -0.051043
S12 – digestive 0.701640 0.571076 0.229042 0.274326 0.160555
S14 – urogenital 0.227290 0.159760 0.135788 0.915696 -0.075371
S17 – congenital anomalities
0.702011 -0.265806 0.020677 -0.589605 0.281919
S18 – perinatal -0.169043 0.198374 0.347470 -0.323681 0.836166
S19 – inaccurate condition
-0.028836 0.198514 0.951199 0.072312 0.218465
S20 – accident -0.147521 0.912604 0.074857 0.312551 0.128944
Proper values4.473430 3.686176 1.193174 2.392695 1.018063
Explainable share of dispersion of factors (%) 34,4 28,3 9,1 18,4 7,8
Distribution of mortality indicator by factors
Factors of morbidity and mortality classes
Factor 1ZS Factor 2ZS Factor 3ZS Factor 4ZS Factor 5ZS
Factor 1 by morbidity classes 0.984886 -0.048738 -0.062311 0.089883 0.057554
Factor 2 by morbidity classes 0.012755 0.648490 0.074137 -0.264508 0.700656
Factor 3 by morbidity classes 0.001913 0.093051 -0.911345 -0.311304 -0.090659
Factor 1 by mortality classes 0.991604 0.024748 0.016158 -0.045632 -0.027897
Factor 2 by mortality classes 0.042372 -0.049503 -0.968663 0.116982 0.027370
Factor 3 by mortality classes -0.023666 0.995912 -0.047839 0.030638 0.012310
Factor 4 by mortality classes 0.020320 -0.016485 0.017474 0.034779 0.993477
Factor 5 by mortality classes 0.034641 -0.022088 0.100701 0.988157 -0.042598
Proper values 1.957413 1.427236 1.791233 1.169322 1.492941
Explainable share of dispersion of factors
(%)24,4 % 17,8 % 22,3 % 14,6 % 18,6 %
Distribution by factors of dynamics of major morbidity and mortality factors
Factors of heliogeophysical
parameters
Factor 1ZS
Factor 2ZS
Factor 3ZS
Factor 4ZS
Factor 5ZS
Factor 1 of heliogeophysical parameters
0.15 0.08 0.84 0.47 0.05
Factor 2 of heliogeophysical parameters
-0.64 0.34 0.11 0.10 -0.45
Factor 3 of heliogeophysical parameters
0.46 0.15 0.03 -0.18 -0.78
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
Figure 4 – Dynamics of variables: factor 1 (cumulative solar activity), factor 4ZS (mortality caused by conditions during the perinatal period)
r = 0.47
year
year
sta
nd
ard
ize
d in
de
xst
an
da
rdiz
ed
ind
ex
factor 1factor 3ZS
factor 1factor 4ZS
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
Figure 6 – 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
sta
nd
ard
ize
d in
de
xst
an
da
rdiz
ed
ind
ex
year
year
factor 3factor 1ZS
factor 3factor 5ZS
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 period correlate 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 infarction correlate 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
The outburst energy on November 4th, 2003 would be enough to supply
electricity to such city as Moscow for 200 million years!
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!
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
METHODS AND MATERIALS OF THE RESEARCH
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
Data on the number of calls to the ambulanceTable. Format of the original database
Time of reception Address Name Age Diagnosis Hospitalization
01:12 7 Govorova str. Apt 21
Ivanov V.P. 42 years CHD: myocardial infraction
Yes
…. …. …. …. …. ….
Classes of diseases Total number of calls
Cl. 1 Chronic coronary heart disease 384
Cl. 2 Acute coronary syndrome 526
Cl. 3 – Acute cerebrovascular diseases 490
Cl. 4 Chronic cerebrovascular diseases 121
Cl. 5 Arterial hypertension 3086
Cl. 6 Heart rhythm disturbance and asequence 692
Cl. 7 Functional disorders of the nervous system 772
Cl. 8 Thromboembolism of the main pulmonary artery 10
Cl. 9 Traumas 67
Cl. 10 Suicides 80
Cl. 11 Pregnancy pathologies 154
Cl. 12 Biological death 444
1i ix x x where x- current change in the integral of the function
- Formula used to reveal the total accumulated tendency in changes of epidemiological indicators
Results of the research
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
Wa
tt/
me
tre2
Number of a three-hour interval Number of a three-hour interval
Nu
mb
er
of
calls
Х (on the left)
K-index (on the right)
Va
lue
of
K-in
de
x
-0.16-0.11
0.220.27
0.17
0.27 0.28
0.14
-0.35-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
кл.1 кл.2 кл.3 кл.4 кл.5 кл.6 кл.7 кл.9 кл.12
нозологические переменные
зн
ач
ен
ие к
оэф
иц
иен
та к
ор
рел
яц
ии
коэфиценткорреляции
Results of the research(statistically significant bonds are presented)
Figure 9. Connection between the frequency of calls to the ambulance and the power of X-ray flow (lg(Х))
Figure 10. Connection between the frequency of calls to the ambulance and the value of K-index
Val
ue o
f а c
orre
latio
n co
effic
ient
correlation coefficient
-0,15
0,11
0,58
0,10
0,300,37
0,45 0,430,49
0,08
-0,20
-0,10
0,00
0,10
0,20
0,30
0,40
0,50
0,60
0,70
кл.2 кл.3 кл.4 кл.5 кл.6 кл.7 кл.9 кл.10 кл.11 кл.12
знач
ен
ие к
оэф
иц
иен
та к
ор
рел
яц
ии
нозологические переменные
коэфициент корреляцииcorrelation coefficient
Val
ue o
f а c
orre
latio
n co
effic
ient
Classes of nosologic units
Classes of nosologic units
Cl .2 Cl. 3 Cl. 4 Cl. 5 Cl. 6 Cl. 7 Cl. 9 Cl. 10 Cl. 11 Cl. 12
Cl .1 Cl. 2 Cl. 3 Cl. 4 Cl. 5 Cl. 6 Cl. 7 Cl. 9 Cl. 12
Results of the research
r = 0. 58
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
Wa
tt/
me
tre
2
Number of a three-hour interval
Nu
mb
er
of
calls
(st
an
da
rdiz
ed
ind
ex)
Lg Х (on the left)Cl.4 (on the right)
Results of the research
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
r = 0. 17
Number of a three-hour interval
Nu
mb
er
of
calls
(st
an
da
rdiz
ed
ind
ex)
Poi
nt
K-index (on the left)
Cl.5 (on the right)
Results of the research
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
r = 0.30
Wa
tt/
me
tre2
Nu
mb
er
of
calls
(st
an
da
rdiz
ed
ind
ex)
Number of a three-hour interval
Lg Х (on the left)Cl. 6 (on the right)
Results of the research
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
r = 0.27
Nu
mb
er
of
calls
(st
an
da
rdiz
ed
ind
ex)
Poi
nt
Number of a three-hour interval
K-index (on the left)
Cl. 6 (on the right)
Results of the research
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
r = 0.37А Б
r = 0.28
Nu
mb
er
of
calls
(st
an
da
rdiz
ed
ind
ex)
Nu
mb
er
of
calls
(st
an
da
rdiz
ed
ind
ex)
Poi
nt
Wa
tt/
me
tre2
Number of a three-hour interval Number of a three-hour interval
Lg Х (on the left)
Cl. 7 (on the right)
K-index (on the left)
Cl. 7 (on the right)
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 and asequence 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!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.
iст
x
x xX
1
n
ii
xx
N
2 2
2 1 1
1
1
n n
i ini i
ii
x
x xx
NN
N 33
n
ix_
x
Standardization of values
- standardized value
- current value
- average value
- mean-square deviation
ordinal number of the row value
total number of values
х
Хст
(1)
( 2 )
( 3 )
(1 )*
0,
nL L COS
NWn
при n N
Hamming filter window:
Wn output value for the original row value
N total number of points used in the filter
n Ordinal number of the row value
0,54L const Hamming window constant
Data conversion
(4)
Method of principle components is expansion of the time series into eigen-functions on orthogonal basis.
Method of principle components
R V = V
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.
,where