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https://orcid.org/0009-0009-6865-8400
UDC: 614 212 362 147 3553
SOCIO-HYGIENIC ANALYSIS OF THE HEALTH STATUS OF MILITARY PERSONNEL IN
THE REPUBLIC OF UZBEKISTAN ANALYSIS OF THE HEALTH STATUS OF MILITARY
PERSONNEL OF THE REPUBLIC OF UZBEKISTAN (2015-2020)
Doctor of medical sciences, associate professor
Mirrakhimova S.Sh.
1.
; Doctor of medical
sciences, associate professor
M.G. Mukhammedova
2.
; PhD.
Ganiev B.S.
3.
1.
Research Institute of the Military Medical Academy of the Armed Forces of the Republic
of Uzbekistan.
2.
Deputy Head of the Academy for Innovation and Scientific Work Military Medical
Academy the Armed Forces of the Republic of Uzbekistan.
3.
The Main Medical Department under the Administration of the President of the Republic
of Uzbekistan.
To assess the state of health of the military personnel of the Republic of Uzbekistan, we use the
health indicator, which is calculated using the formula:
UZ=(1-B⁄P)*100%
Where UZ is the level of health;
B is the number of sick military personnel for the period (year). The classes of diseases registered
in medical institutions calculate the total incidence of military personnel.
P is the total number of military personnel for the period (for the period 2016-2023 P = 68,000
people [73]).
Based on open data from the Government of the Republic of Uzbekistan, bull calculated the
health level of the republic's military personnel (Fig. 1).
Figure 1 – The health level of the military personnel
of the Republic of Uzbekistan for the period 2016-2023, %
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The graph in Fig. 1 clearly shows the linear nature of the increase in the level of health of military
personnel over the period under review (an increase of 5.7%). The linear nature of the growth is
confirmed by the very close to 1 value of the coefficient of determination R2 = 0.9475 of the
linear trend equation. When analyzing the schedule, attention is drawn to the fact that the health
level of military personnel during the COVID-19 pandemic (2020 – 2021) has not decreased,
which is proof of the effectiveness of preventive measures in the Armed Forces of Uzbekistan.
Next, we will calculate the health level of military personnel in the context of the regions of the
Republic of Uzbekistan (Table 2).
Analyzing the data in the table, we note that the health levels of military personnel in different
regions differ markedly. In 2023, the spread was 10% - from 80.2% in Tashkent to 90.2% in
Bukhara region. The increase in the level of health also varies significantly from 0.5% in
Namangan region to 15.4% in Samarkand region.
Table 2 – Health level of military personnel in the regional context.
Region (region)
2016 2017 2018 2019 2020 2021 2022 2023 Growth, %
Republic
of
Karakalpakstan
80,4
81,2
81,8
83,1
85,0
85,4
85,7
86,1
5,7
Andijan
80,0
80,8
81,3
81,4
82,5
82,9
83,9
84,4
4,4
Bukharа
81,9
82,7
83,2
83,4
83,8
83,8
83,1
85,3
3,4
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Region (region)
2016 2017 2018 2019 2020 2021 2022 2023 Growth, %
Jizzakh
85,4
86,1
86,4
87,7
90,1
90,3
90,3
90,2
4,7
Kashkadarya
86,4
87,0
87,3
85,6
86,7
88,4
87,2
87,3
0,9
Navoi
86,0
86,6
87,0
87,2
87,6
89,4
89,7
89,3
3,3
Namangan
85,2
85,8
86,2
84,9
86,4
86,9
89,3
85,9
0,7
Samarqand
86,6
87,2
87,5
87,2
87,5
88,0
87,8
87,1
0,5
Surkhandarya
70,5
71,8
72,5
83,4
85,1
85,2
85,7
86,0
15,4
Syrdarya
84,2
84,9
85,3
85,7
88,9
88,9
88,0
89,7
5,5
Tashkent
84,1
84,7
85,2
84,1
88,6
87,9
88,6
89,5
5,4
Ferghana
82,1
82,9
83,3
83,4
84,5
84,6
85,3
85,9
3,7
Khorezms
77,5
78,5
79,1
79,5
83,0
83,3
84,9
84,4
6,9
Tashkent city
79,2
80,1
80,6
80,4
81,9
82,8
83,9
84,5
5,3
Republic
of
Karakalpakstan
69,9
71,1
71,9
73,8
78,5
78,3
78,5
80,2
10,3
Therefore, it is necessary to select factors characterizing the peculiarities of healthcare in the
regions that can explain the observed differences. Since the health level of military personnel is
quite high, the most significant explanatory factors are indicators related to polyclinic and
outpatient activities of medical institutions in the regions. From the data provided by the Ministry
of Health of the Republic of Uzbekistan, the following indicators are the most adequate for the
task:
1. The capacity of outpatient clinics in terms of the number of visits per shift per 10,000 people;
2. The number of doctors of all specialties per 10,000 people;
3. The number of doctors with less than 5 years of experience per 10,000 people;
4. The number of secondary medical staff per 10,000 people;
5. The number of examined, in % of the number of persons, subject to professional examinations.
To establish the relationship between the level of health and the regional factors listed above, we
will use statistical analysis.
The initial data for statistical analysis are presented in Appendix A.
Since the tools of the SPSS statistical package with their specific requirements for naming
variables will be used for statistical data processing, we will designate the relevant factors
according to tab. 3.
Table 3 – Designation of variables in the SPSS package
Factor
Designation
when
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calculating in SPSS
Health level
Health level
Capacity of outpatient clinics in terms of the number of visits per
shift per 10,000 people.
per month see APU
The number of doctors of all specialties per 10,000 people.
Doctors
The number of doctors with less than 5 years of experience per
10,000 people.
The doctor has less than 5
years of experience
The number of nursing staff per 10,000 people.
Average medical staff
Number of people examined, as a percentage of the number of
persons subject to professional examinations.
Coverage of occupational
examinations
In addition, the Region category (nominal variable) will be introduced, taking 14 values from 1 to
14 according to Tab. 4.
Table 4 – Designation of the Region category.
Region (region)
Designation
Republic of Karakalpakstan
1
Andijan
2
Bukharа
3
Jizzakh
4
Kashkadarya
5
Navoi
6
Namangan
7
Samarqand
8
Surkhandarya
9
Syrdarya
10
Tashkent
11
Ferghana
12
Khorezms
13
Tashkent city
14
Region (region Pic in the cm of the APU of Doctors, my doctor is 5 years of experience, Average
medical staff, professional examination coverage
The level of health Pic in the cm of the APU of Doctors, my doctor is 5 years of experience,
Average medical staff, professional examination coverage
Table 5 – Average values and standard deviation of variables (by year).
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Region (region)
Th
e
le
ve
l
of
he
al
th
Th
e
pi
c
is
in
th
e
cm
of
th
e
A
PU
.
D
oc
to
rs
,
Th
e
do
ct
or
ha
s
le
ss
th
an
5
ye
ar
s
A
ve
ra
ge
m
ed
ic
al
st
af
f
Pr
of
es
sio
na
l
ex
am
in
at
io
n
co
ve
ra
ge
1
Republic
of
Karakalpakstan
Average
82,15
110,26
23,66
4,61
93,76
95,08
Standard
deviation
1,54
5,67
2,33
1,05
1,69
1,90
2 Andijan
Standard
deviation
83,40
121,09
21,50
4,35
93,99
96,70
Standard
deviation
0,99
8,58
1,09
1,08
2,82
1,76
3 Bukharа
Standard
deviation
88,31
105,23
26,60
4,00
119,40
97,81
Standard
deviation
2,14
11,83
0,62
1,51
2,96
1,89
4 Jizzakh
Standard
deviation
86,99
103,48
15,31
1,83
96,31
90,90
Standard
deviation
0,81
9,10
1,26
0,42
11,00
7,15
5 Kashkadarya
Standard
deviation
87,85
73,33
15,86
2,31
106,54
95,74
Standard
deviation
1,42
6,33
0,34
0,65
4,23
2,40
6 Navoi
Standard
deviation
86,33
103,66
21,05
3,35
123,65
96,53
Standard
deviation
1,36
2,61
0,55
0,90
3,78
4,06
7 Namangan
Standard
deviation
87,36
80,40
16,51
1,99
99,79
93,14
Standard
deviation
0,44
5,07
0,54
0,78
3,82
3,74
8 Samarqand
Standard
deviation
80,03
76,25
22,33
4,64
75,93
90,29
Standard
deviation
7,04
6,11
1,01
1,66
1,58
3,09
9 Surkhandarya
Standard
86,95
72,83
14,73
1,95
84,01
93,93
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Region (region)
Th
e
le
ve
l
of
he
al
th
Th
e
pi
c
is
in
th
e
cm
of
th
e
A
PU
.
D
oc
to
rs
,
Th
e
do
ct
or
ha
s
le
ss
th
an
5
ye
ar
s
A
ve
ra
ge
m
ed
ic
al
st
af
f
Pr
of
es
sio
na
l
ex
am
in
at
io
n
co
ve
ra
ge
deviation
Standard
deviation
2,15
5,25
0,60
0,73
2,96
2,26
10 Syrdarya
Standard
deviation
86,59
139,71
17,46
2,56
146,64
85,65
Standard
deviation
2,27
12,66
0,59
0,63
3,91
6,85
11 Tashkent
Standard
deviation
84,00
148,69
16,58
2,09
101,28
93,60
Standard
deviation
1,29
4,95
0,32
0,61
3,47
4,45
12 Ferghana
Standard
deviation
81,28
104,94
18,75
3,48
113,25
94,46
Standard
deviation
2,92
6,62
0,35
0,91
4,06
3,70
13 Khorezms
Standard
deviation
81,68
99,99
24,54
4,46
83,81
93,64
Standard
deviation
1,91
6,55
0,42
0,95
2,44
2,26
14 Tashkent city
Standard
deviation
75,28
116,13
29,91
4,08
81,28
97,34
Standard
deviation
4,04
8,31
3,66
0,71
9,42
3,55
The table data shows that for each variable there is a significant difference in the average values
depending on the region. These differences can be more clearly identified from the graphs in
Figure 2-7.
Figure 2 – The health level of military personnel.
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In this figure, each figure corresponding to one of the 14 regions has an average value, and the
vertical size of the figure is equal to the increase from the lower edge (value in 2016) to the upper
edge (value in 2023). As before, the largest increase corresponds to the Samarkand region (8), and
the largest average is the Bukhara region. regions (3).
Figure 3 - Visits per 10,000 APU shift.
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The highest number of visits per shift to outpatient clinics in the Tashkent region (11) is an
average of 148.69, and the highest drop is in Bukhara (3, standard deviation = 11.83).
The fact that in each region there is a drop in the indicator for the period 2016-2023 is not
surprising, since it plays a significant role in the formation of the indicator. the role of population
growth. It follows that with an undoubted increase in the absolute indicator of "Visits per shift of
the APU", due to population growth, the value of the indicator of "Visits per shift of the APU per
10,000" is falling.
Figure 4 - Doctors per 10,000 people.
The largest number of doctors per 10,000 people is in Tashkent (14), the average value for the
period 2016-2023 is 29.91, and the highest drop in the indicator for the period was recorded in
Tashkent (the average deviation is 3.66), with the largest increase occurring at the beginning of
the period (the line in the figure is shifted to the top).
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Figure 5 - Doctors (experience < 5 liters) per 10,000 people
The largest average number of young doctors is in the Khorezm region, and the largest change
over the period is in the Bukhara region due to the most significant population growth. The lowest
average number of young doctors in the Jizzakh region is 1.83 per 10,000 inhabitants.
Figure 6 - Average medical staff for 10,000 hours
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The medical institutions of the Syrdarya region are the most provided with average medical staff
(146.64 per 10,000 people), the least – in the Samarkand region (75.93).
Figure 7 - Coverage by professional examination, %
The number of people examined, as a percentage of the number of persons subject to professional
examinations, is most common in Tashkent (97.24%), and least in the Syrdarya region (85.65),
which is also very significant.
According to all indicators, there are differences in the average values for the regions of the
Republic of Uzbekistan. To check whether these differences are not random, but statistically
significant, we will use the nonparametric Kruskal-Wallace test.
Table 6 – The Kruskal-Wallace criterion
№
Null Hypothesis
Criterion
Significance Solution
1
The distribution of the Level
of Health is the same for the
categories Region.
83,2
,000
The null hypothesis is
rejected..
2
The distribution in CM_AP is
the same for the Region
categories.
98,7
,000
The null hypothesis is
rejected.
3
The distribution of Doctors is
the same for the Region 105,8
,000
The null hypothesis is
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№
Null Hypothesis
Criterion
Significance Solution
categories.
rejected..
4
The
distribution
of
the
Clinice_men_5l_stage is the
same
for
the
Region
categories.
66,1
,000
The null hypothesis is
rejected..
5
The
distribution
of
Media_medical staff is the
same
for
the
Region
categories.
103,3
,000
The null hypothesis is
rejected..
6
The coverage distribution of
the Survey is the same for the
Region categories.
46,4
,000
The null hypothesis is
rejected..
The asymptotic signicances are derived. The significance level is ,05.
According to the calculated criterion, the differences of all factors (for different regions) are not
random (the null hypothesis is rejected), but are statistically significant.
Let's determine the influence of the five factors under consideration on the dependent variable
Health level using correlation and regression analysis.
Due to the fact that it is more convenient to build the most complete multiple regression models in
the GRETL statistical package, we introduce designations for the dependent variable and
independent factors (regressors) according to Tab. 7.
Table 7 – Designations used to build a regression model in the GRETL package
Factor
Designation
when
calculating in GRETL
Dependent variable
Health Level
UZ
Regressors
The capacity of outpatient clinics in terms of the number of visits
per shift per 10,000 people.
PS
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Number of doctors of all specialties per 10,000 people
V
Number of doctors with less than 5 years of experience per 10,000
people
V5y
Number of nursing staff per 10,000 people.
SM
Number of people examined, as a percentage of the number of
persons subject to professional examinations
OP
The initial panel data (for 8 years for 14 regions) for further calculations are given in Appendix B.
To do this, we first construct the Pearson correlation matrix.
Table 8 – Correlation coefficients, observations 1:1 - 14:8, 5% critical values (two-sided) =
0.1887 for n = 112
UZ
PS
V
V5y
SM
OP
1
-0,2351
-0,5092
-0,2921
0,3852
-0,2156
UZ
1
0,153
0,0221
0,3881
-0,0144
PS
1
0,6714
-0,1723
0,3307
V
1
-0,1956
0,1424
V5y
1
-0,122
SM
1
OP
The relationship above the average value of 0.5 for the dependent variable UZ is observed only
with the regressor V (number of doctors per 10,000 hours), and this relationship is reversed (the "-
" sign), which means the following:
- since it was previously established that the health level of military personnel in each of the
regions is increasing, the decrease in the number of doctors per 10,000 people is due not to an
absolute decrease in the number of doctors, but to an outstripping population growth.;
- the same conclusions are valid for the V5y and OP regressors;
- the most interesting result is a direct relationship with the independent variable SM, which
means that the number of average medical staff is growing faster than the population. This fact is
favorable, since it is the average medical staff that plays an essential role in conducting medical
procedures, medical examinations and professional examinations.
Another fact worth paying attention to when building a multiple regression model is the high
relationship between variables V and V5y (0.6714), which may mean that redundancy of variables
is possible in the model.
Next, we will build a least squares multiple regression model (OLS model).
LIST OF SOURCES USED
1.
The Law of the Republic of Uzbekistan dated March 27, 2023 №. ZRU-827 "On
Amendments to the Code of the Republic of Uzbekistan on Administrative Responsibility in
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connection with the establishment of liability for obstructing the legitimate medical activities of a
medical worker"
2.
Decree of the President of the Republic of Uzbekistan Sh.M. Mirziyoyev "On
comprehensive measures to radically improve the healthcare system of the Republic of
Uzbekistan" dated December 7, 2018 [Electronic resource] free access mode
https://lex.uz/docs/4143186 (accessed 11/16/2024)
3.
On aPDroval of the regulations on medical and sanatorium-resort provision in the armed
forces of the Republic of Uzbekistan. 11.02.2011. Resolution of the Cabinet of Ministers of the
Republic
of
Uzbekistan
No.
26.
URL:https://www.norma.uz/zdravoohranenie_fizicheskaya_kultura_i_sport_turizm/ob_utverjdeni
i_polojeniya_o_medicinskom_i_sanatorno-
kurortnom_obespechenii_v_voorujennyh_silah_respubliki_uzbekistan
4.
Regulations on medical examination in the Armed Forces of the Republic of Uzbekistan
for peacetime and wartime (APDendix No. 1 to the Decree of the President of the Republic of
Uzbekistan dated December 25, 2018 N PD-4076).
5.
Regulations on medical and sanatorium-resort provision in the Armed Forces of the
Republic of Uzbekistan, aPDroved by Resolution of the Cabinet of Ministers of the Republic of
Uzbekistan dated 02/01/2011 No. 26.
6.
Resolution of the Cabinet of Ministers of the Republic of Uzbekistan dated 04/30/2024 No.
253 "On aPDroval of the Regulations on the procedure for providing prosthetic and orthopedic
products and technical means of rehabilitation to persons in need"
7.
Resolution of the Cabinet of Ministers of the Republic of Uzbekistan dated 06/24/2024 No.
352 "On aPDroval of the Regulations on the organization of medical and sanatorium-resort
provision in the Armed Forces of the Republic of Uzbekistan".
8.
Resolution of the President of the Republic of Uzbekistan dated December 25, 2018 №.
PD-4076 "On aPDroval of the Regulations on medical examination in the Armed Forces of the
Republic of Uzbekistan for peacetime and wartime".
9.
Resolution of the President of the Republic of Uzbekistan dated December 25, 2018 №.
PD-4076 "On aPDroval of the Regulations on medical examination in the Armed Forces of the
Republic of Uzbekistan for peacetime and wartime"
10.
Resolution of the President of the Republic of Uzbekistan dated December 25, 2018
№.PD-4076 "On aPDroval of the Regulations on medical examination in the Armed Forces of the
Republic of Uzbekistan for peacetime and wartime" (As amended by Resolutions of the President
of the Republic of Uzbekistan dated September 12, 2019 No.PD-4447, December 24, 2019 №
PD-4552, Decree of the President of the Republic of Uzbekistan dated 04/22/2020 №UP-5983,
Decree of the President of the Republic of Uzbekistan dated 02/27/2021 №PD-5010, Decree of
the President of the Republic of Uzbekistan dated 04/30/2021 №UP-6218, Decree of the President
of the Republic of Uzbekistan dated 05/04/2021 PD-5102, Decrees of the President of the
Republic of Uzbekistan dated 11/29/2021 №UP-26, 04/20/2022 №UP-112, 12/27/2023 №UP-
216).
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