19 research outputs found
INFLUENCE OF ENVIRONMENTAL FACTORS ON HYGIENE PREVALENCE OF CIRCULATORY DISEASES OF POPULATION OF THE PRIMORSKY KRAY BIOCLIMATIC ZONES
The article presents the results of the environmental and hygienic assessment of the prevalence of diseases of the circulatory system in the adult population in the Primorsky Kray. The analysis was conducted on the incidence of Form 12 for the period of 1991-2011. To characterize the habitat 8 sanitation (according to the Form 18 provided by Center of Hygiene and Epidemiology in the Primorsky Kray) and 7 climatic factors of the modular that were formalized in a 5-point scale based on the developed normalized rating scale were taken. Each module consisted of a factor of 3 to 10 parameters of the environment. To establish the connection between environmental factors and the level of circulatory diseases we used regression analysis of the statistical package SSP. It was revealed that for the last 6 years for the first time the disease circulatory system in the adult population began to occupy first place in the structure of the entire morbidity and reached 43-49 %. Ranging of the administrative territories of Primorsky Kray as habitat and morbidity. With the use of Pearson (Ο2) and regression analysis the patterns of environmental factors impacting on the level of cardiovascular diseases were determined. The prevalence of cardiovascular diseases in the adult population of the region depends on the bioclimatic zones, the degree of environmental stress of the situation and factors of the environment. The prevalence of cardiovascular diseases in adults as the organism's response to the impact of the environment influenced primarily hygienic parameters: the level of pollution of the atmospheric air, characterization of chemical pollution and adverse physical factors in urban and rural areas, transport load as well as the level of diseases of the circulatory system has a strong connection with climatic parameters: the number of days with BASR, latitude, speed of air movement
The effect of environmental factors on the immune-metabolic status of people living in industrial areas of Primorsky region
The estimation of the total effect of the environment on immune-metabolic parameters of people living in industrial areas of Primorsky region was conducted. The study involved 1128 healthy people living in the Primorsky region for at least 10 years. Integrated exposure index (HE) that takes into account the gradient of "response of the body" to the combined effects of multiple environmental factors (climatic, technological, socioeconomic, etc.) was developed. With use of gradient approach in Primorye 4 categories of areas were identified: the relatively favorable (IIE > 0,4), moderate (IIE = 0,3-0,4), relatively unfavorable (IIE = 0,2-0,3) and unfavorable environment (IIE 0,4). With the use of cluster analysis the classification of objects method Π-means was performed, which revealed three immune-metabolic phenotypes. Compensated phenotype corresponds to the first phase of the adaptation of the organism - the activation parameters. Increased exposure leads to the formation of subcompensated phenotype, and the destruction of the body of the adaptation fund - to the formation of decompensated phenotype. The distribution of the proportion of healthy individuals with selected phenotypes in the population living in the areas with different environmental pressure shows the following dependencies: compensated and subcompensated phenotypes prevalent in areas with better living conditions, the percentage of decompensated phenotype increased environmental degradation. In areas where environmental load exceeds the capability to adapt the body subcompensated and decompensated phenotypes prevail. Violations identified unfavorable combination of endogenous and exogenous risk factors may be the basis for the formation of disease
CHEMICAL STUDY OF SNOW OF VLADIVOSTOK CITY AND RUSSKY ISLAND
In the paper thefirst results of mass and spectrometer research of snow cover of the largest city in the Far East - Vladivostok (mainland and Island Russky), dropped-out on the November 19 2012, are presented. To exclude secondary pollution by anthropogenous aerosols we used the top layer (5-10 cm) of just dropped-out snow placed in the 3-liter sterile containers. In a couple of hours, when snow in containers thawed, 10 ml of liquid were gained from each sample and were analyzed on a mass spectrometer of high resolution with inductive-connected plasma (MS-ICP) Element XR (Thermo Scientific). Measurements were carried out with use of a technique of TsV3.18.05-2005 Fr.1.31.2005.01714. Tests were selected in 20 points: 16 points - Vladivostok, 3 points - Island Russky (DVFU campus, the bridge, the settlement) and a comparison point - the bay Hero in the southwest of Peter the Great Bay. For the first time application of the most highly sensitive chemical method for an applied ecological task is shown today. Distribution of Pb, Cr, Mn, Fe, Co, Ni, Cu and Zn in areas of Vladivostok different by anthropogenous loading and on Russian Island is revealed. In districts of Vladivostok with high transport loading high contents of metals (Mn, Cu, Zn) which source is motor transport (exhaustgases, autopaint, catalysts) are fixed also. Tests from districts of the Academic Town have traces of influence of the sea coast (halite and potassium-containing minerals) and railroad tracks (a microparticle of iron and its oxides) that strongly pollutes environment iron because of continuous movement of trains. In the tests taken on the Eagle hill, the highest point of Vladivostok, high concentrations of Mn (the highest concentration from all tests) and Cu (the third concentration from all tests) are recorded. This point of selection is in the downtown and, apparently, isn't ecologically clear. It should be noted that height above sea level in an urban environment isn't in sufficient condition for ecological safety. Russian Island is a pure zone with low background contents of heavy metals. The raised maintenance of Cu, Ni and Zn in snow cover of the bay Hero is shown
ΠΠΠΠΠΠ¬ ΠΠ ΠΠΠΠΠΠΠ¦ΠΠ Π ΠΠΠΠΠ ΠΠΠΠΠΠΠ‘Π’ΠΠΠ Π ΠΠΠ ΠΠΠ§ΠΠ
Β Challenges of early kidney cancer detection and screening significantly increase morbidity and mortality rates, thus dictating the need to improve prevention, early diagnosis and organization of medical care for the population of primorsky Krai. The aim of the study was to create a model for improving early diagnosis of kidney cancer in the primorsky Krai using the program for assessing the risk of kidney cancer (ARKC). The model included a population questionnaire to identify risk factors and algorithm of patient routing (Β«roadmapΒ») with suspected kidney cancer for in-depth examination and treatment. Material and Methods. 2982 residents of the primorsky Krai (women β 1950, men β 1032) in the age range 29β75 took part in the questionnaire survey using the ARKC program. Results. No risk factors were identified in 1879 (63.0 %) individuals. All patients at high risk for kidney cancer (656 β 22.0 %) and patients of the uncertainty group (447 β 15.0 %) were referred for physical and ultrasound examination to exclude kidney tumors. Non-tumor pathology of the kidneys was revealed in 156 (14.0 %) patients. Renal mass suspicious for renal cell carcinoma was revealed in 21 (1.9 %) patients (later confirmed in 17 patients with stage IβII cancer, in 3 patients with stage III, in 1 patient with stage IV). According to the results of the factor analysis, two main groups of factors had a predominant effect on the rise in the overall kidney cancer incidencer. The first group of factors (65.0 %) is caused by smoking, excessive alcohol consumption, overweight, unbalanced nutrition, and the influence of carcinogens. The second group of factors (35.0 %) is caused by problems of a medical and social nature: the low material and technical base of primary care medical organizations, the insufficient professional training of medical workers on the issues of cancer prevention and treatment, including kidney cancer.Conclusion. To improve the early detection of kidney cancer, a prognostic model with computer program for assessing the individual risk of developing kidney cancer was developed. population survey using the ARKC computer program allowed us to narrow the diagnostic search, form risk groups and effectively route patients with suspected kidney cancer for in-depth examination in accordance with the Β«road mapΒ».Β Β ΠΡΠΎΠ±Π»Π΅ΠΌΠ° ΡΠ°Π½Π½Π΅ΠΉ Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠΈ ΠΈ ΡΠΊΡΠΈΠ½ΠΈΠ½Π³Π° ΡΠ°ΠΊΠ° ΠΏΠΎΡΠΊΠΈ ΡΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠΌ ΠΎΠ±ΡΠ°Π·ΠΎΠΌ Π²Π»ΠΈΡΠ΅Ρ Π½Π° Π·Π°ΠΏΡΡΠ΅Π½Π½ΠΎΡΡΡ ΠΈ ΡΠΌΠ΅ΡΡΠ½ΠΎΡΡΡ ΠΎΡ Π΄Π°Π½Π½ΠΎΠΉ ΠΏΠ°ΡΠΎΠ»ΠΎΠ³ΠΈΠΈ, ΡΡΠΎ Π΄ΠΈΠΊΡΡΠ΅Ρ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎΡΡΡ ΡΠ΅ΡΠ΅Π½ΠΈΡ ΠΏΡΠΎΠ±Π»Π΅ΠΌ ΠΏΡΠΎΡΠΈΠ»Π°ΠΊΡΠΈΠΊΠΈ, ΡΠ»ΡΡΡΠ΅Π½ΠΈΡ ΡΠ°Π½Π½Π΅ΠΉ Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠΈ ΠΈ ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΠΈ ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΎΠΉ ΠΏΠΎΠΌΠΎΡΠΈ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ ΠΡΠΈΠΌΠΎΡΡΠΊΠΎΠ³ΠΎ ΠΊΡΠ°Ρ ΠΏΡΠΈ Π·Π»ΠΎΠΊΠ°ΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΡ
Π½ΠΎΠ²ΠΎΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΡΡ
(ΠΠΠ) ΠΏΠΎΡΠΊΠΈ. Π¦Π΅Π»ΡΡ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠ²ΠΈΠ»ΠΎΡΡ ΡΠΎΠ·Π΄Π°Π½ΠΈΠ΅ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΡΠΎΠ²Π΅ΡΡΠ΅Π½ΡΡΠ²ΠΎΠ²Π°Π½ΠΈΡ ΡΠ°Π½Π½Π΅ΠΉ Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠΈ ΠΠΠ ΠΏΠΎΡΠΊΠΈ Π² ΠΡΠΈΠΌΠΎΡΡΠΊΠΎΠΌ ΠΊΡΠ°Π΅ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠΈ ΠΈ Π²Π½Π΅Π΄ΡΠ΅Π½ΠΈΡ Π² ΠΏΡΠ°ΠΊΡΠΈΠΊΡ ΠΊΠΎΠΌΠΏΡΡΡΠ΅ΡΠ½ΠΎΠΉ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΡ ΠΎΡΠ΅Π½ΠΊΠΈ ΡΠΈΡΠΊΠ° ΡΠ°ΠΊΠ° ΠΏΠΎΡΠΊΠΈ β Β«ΠΠ Π ΠΒ». ΠΡΠ° ΠΌΠΎΠ΄Π΅Π»Ρ Π²ΠΊΠ»ΡΡΠ°Π΅Ρ Π² ΡΠ΅Π±Ρ Π°Π½ΠΊΠ΅ΡΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ (ΠΎΠΏΡΠΎΡ) Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ Π½Π° Π²ΡΡΠ²Π»Π΅Π½ΠΈΠ΅ ΡΠ°ΠΊΡΠΎΡΠΎΠ² ΡΠΈΡΠΊΠ° ΠΈ Π°Π»Π³ΠΎΡΠΈΡΠΌ ΠΌΠ°ΡΡΡΡΡΠΈΠ·Π°ΡΠΈΠΈ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² (Β«Π΄ΠΎΡΠΎΠΆΠ½Π°Ρ ΠΊΠ°ΡΡΠ°Β») ΡΒ ΠΏΠΎΠ΄ΠΎΠ·ΡΠ΅Π½ΠΈΠ΅ΠΌ Π½Π° ΡΠ°ΠΊ ΠΏΠΎΡΠΊΠΈ Π΄Π»Ρ ΡΠ³Π»ΡΠ±Π»Π΅Π½Π½ΠΎΠ³ΠΎ ΠΎΠ±ΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΈ Π»Π΅ΡΠ΅Π½ΠΈΡ.ΠΠ°ΡΠ΅ΡΠΈΠ°Π» ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ. ΠΠ±ΡΠ΅ΠΊΡΠΎΠΌ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π±ΡΠ»ΠΎ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΠ΅ ΠΡΠΈΠΌΠΎΡΡΠΊΠΎΠ³ΠΎ ΠΊΡΠ°Ρ. ΠΡΠΎΠ²Π΅Π΄Π΅Π½ΠΎ Π°Π½ΠΊΠ΅ΡΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΠΎ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ΅ Β«ΠΠ Π ΠΒ», Π² ΠΊΠΎΡΠΎΡΠΎΠΌ ΠΏΡΠΈΠ½ΡΠ»ΠΈ ΡΡΠ°ΡΡΠΈΠ΅ 2982 ΠΆΠΈΡΠ΅Π»Ρ Π² Π²ΠΎΠ·ΡΠ°ΡΡΠ΅ ΠΎΡ 29 Π΄ΠΎ 75 Π»Π΅Ρ (ΠΆΠ΅Π½ΡΠΈΠ½ β 1950, ΠΌΡΠΆΡΠΈΠ½ β 1032). Π‘ ΡΠ΅Π»ΡΡ ΠΏΠΎΠΈΡΠΊΠ° Π½Π°ΡΡΠ½ΡΡ
ΡΠ΅ΡΠ΅Π½ΠΈΠΉ ΠΏΠΎ ΡΠ½ΠΈΠΆΠ΅Π½ΠΈΡ ΡΡΠΎΠ²Π½ΡΡΠΌΠ΅ΡΡΠ½ΠΎΡΡΠΈ ΠΎΡ Π½ΠΎΠ²ΠΎΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΠΉ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ Π°Π½Π°Π»ΠΈΠ· ΠΏΡΠΈΡΠΈΠ½Β ΡΠΎΡΡΠ° ΠΎΠ½ΠΊΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠΉ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π΅ΠΌΠΎΡΡΠΈ ΠΈ ΡΠΌΠ΅ΡΡΠ½ΠΎΡΡΠΈ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ ΠΡΠΈΠΌΠΎΡΡΠΊΠΎΠ³ΠΎ ΠΊΡΠ°Ρ Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌΒ ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΈΡ
ΠΊΠ°ΡΡ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ², ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ² Π²Π΅Π΄ΠΎΠΌΡΡΠ²Π΅Π½Π½ΡΡ
ΡΠΊΡΠΏΠ΅ΡΡΠΈΠ· ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΈΡ
ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΠΉ, ΠΏΡΠΎΡΠΈΠ²ΠΎΡΠ°ΠΊΠΎΠ²ΡΡ
ΠΊΠΎΠΌΠΈΡΡΠΈΠΉ, ΠΊΠΎΠ»Π»Π΅Π³ΠΈΠΉ, Π°ΠΏΠΏΠ°ΡΠ°ΡΠ½ΡΡ
ΡΠΎΠ²Π΅ΡΠ°Π½ΠΈΠΉ, ΠΌΠΎΠ½ΠΈΡΠΎΡΠΈΠ½Π³Π° ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ Π³ΠΎΡΡΠ΄Π°ΡΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΡ Β«Π Π°Π·Π²ΠΈΡΠΈΠ΅ Π·Π΄ΡΠ°Π²ΠΎΠΎΡ
ΡΠ°Π½Π΅Π½ΠΈΡ ΠΡΠΈΠΌΠΎΡΡΠΊΠΎΠ³ΠΎ ΠΊΡΠ°ΡΒ», Β«ΠΠ»Π°Π½Π° ΠΌΠ΅ΡΠΎΠΏΡΠΈΡΡΠΈΠΉ ΠΏΠΎ ΡΠ½ΠΈΠΆΠ΅Π½ΠΈΡ ΡΠΌΠ΅ΡΡΠ½ΠΎΡΡΠΈ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ ΠΎΡ Π½ΠΎΠ²ΠΎΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΠΉ, Π²ΡΠΎΠΌ ΡΠΈΡΠ»Π΅ Π·Π»ΠΎΠΊΠ°ΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΡ
Β». Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. ΠΠΎ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ°ΠΌ ΠΎΠΏΡΠΎΡΠ° Ρ 1879 (63,0 %) Π»ΠΈΡ Π½Π΅ Π²ΡΡΠ²Π»Π΅Π½ΠΎ ΡΠ°ΠΊΡΠΎΡΠΎΠ² ΡΠΈΡΠΊΠ°, ΠΈΠΌ ΡΠ΅ΠΊΠΎΠΌΠ΅Π½Π΄ΠΎΠ²Π°Π½ΠΎ ΠΏΡΠΎΠΉΡΠΈ ΠΊΠΎΠ½ΡΡΠΎΠ»ΡΠ½ΠΎΠ΅ Π°Π½ΠΊΠ΅ΡΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΡΠ΅ΡΠ΅Π· 3 Π³ΠΎΠ΄Π°. ΠΠ°ΡΠΈΠ΅Π½ΡΡ Π³ΡΡΠΏΠΏΡ Π²ΡΡΠΎΠΊΠΎΠ³ΠΎ ΡΠΈΡΠΊΠ° (656 β 22,0 %) Π±ΡΠ»ΠΈ Π½Π°ΠΏΡΠ°Π²Π»Π΅Π½Ρ ΠΊ ΡΡΠΎΠ»ΠΎΠ³Ρ Π΄Π»Ρ ΡΠ³Π»ΡΠ±Π»Π΅Π½Π½ΠΎΠ³ΠΎ ΠΎΠ±ΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ. ΠΠ°ΡΠΈΠ΅Π½ΡΡ Π³ΡΡΠΏΠΏΡ Π½Π΅ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π½ΠΎΡΡΠΈ (447 β 15,0 %) Π±ΡΠ»ΠΈ Π½Π°ΠΏΡΠ°Π²Π»Π΅Π½Ρ Π½Π° ΠΎΡΠΌΠΎΡΡ ΡΡΠ°ΡΡΠΊΠΎΠ²ΠΎΠ³ΠΎ ΡΠ΅ΡΠ°ΠΏΠ΅Π²ΡΠ°. ΠΡΠ΅ΠΌ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠ°ΠΌ Π³ΡΡΠΏΠΏ Π½Π΅ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π½ΠΎΡΡΠΈ ΠΈ Π²ΡΡΠΎΠΊΠΎΠ³ΠΎ ΡΠΈΡΠΊΠ° Π½Π°Π·Π½Π°ΡΠ°Π»ΠΎΡΡ ΡΠ»ΡΡΡΠ°Π·Π²ΡΠΊΠΎΠ²ΠΎΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ Π΄Π»Ρ ΠΈΡΠΊΠ»ΡΡΠ΅Π½ΠΈΡ Π½ΠΎΠ²ΠΎΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΡ ΠΏΠΎΡΠ΅ΠΊ. Π£ 156 (14,0 %) ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Π²ΡΡΠ²Π»Π΅Π½Π° Π½Π΅ΠΎΠΏΡΡ
ΠΎΠ»Π΅Π²Π°Ρ ΠΏΠ°ΡΠΎΠ»ΠΎΠ³ΠΈΡ ΠΏΠΎΡΠ΅ΠΊ, Ρ 21 (1,9 %) ΠΏΠ°ΡΠΈΠ΅Π½ΡΠ° β ΠΏΠΎΠ΄ΠΎΠ·ΡΠ΅Π½ΠΈΠ΅ Π½Π° ΠΠΠ ΠΏΠΎΡΠ΅ΠΊ, ΠΊΠΎΡΠΎΡΠΎΠ΅ ΠΏΠΎΠ·ΠΆΠ΅ ΠΏΠΎΠ΄ΡΠ²Π΅ΡΠ΄ΠΈΠ»ΠΎΡΡ (Ρ 17 ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² IβII ΡΡΠ°Π΄ΠΈΠΈ, Ρ 3 ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² β III ΡΡΠ°Π΄ΠΈΠΈ, Ρ 1 ΠΏΠ°ΡΠΈΠ΅Π½ΡΠ° β IV ΡΡΠ°Π΄ΠΈΠΈ). ΠΠΎ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ°ΠΌ Π°Π½Π°Π»ΠΈΠ·Π° Π°Π½ΠΊΠ΅Ρ Π½Π° ΡΠΎΡΡ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π΅ΠΌΠΎΡΡΠΈ ΡΠ°ΠΊΠΎΠΌ ΠΏΠΎΡΠ΅ΠΊ ΠΎΠΊΠ°Π·Π°Π»ΠΈ ΠΏΡΠ΅ΠΈΠΌΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠ΅ Π²Π»ΠΈΡΠ½ΠΈΠ΅ Π΄Π²Π΅ ΠΎΡΠ½ΠΎΠ²Π½ΡΠ΅ Π³ΡΡΠΏΠΏΡ ΡΠ°ΠΊΡΠΎΡΠΎΠ². ΠΠ΅ΡΠ²Π°Ρ Π³ΡΡΠΏΠΏΠ° ΡΠ°ΠΊΡΠΎΡΠΎΠ² (65,0 %) ΠΎΠ±ΡΡΠ»ΠΎΠ²Π»Π΅Π½Π° ΠΊΡΡΠ΅Π½ΠΈΠ΅ΠΌ,Β ΡΡΠ΅Π·ΠΌΠ΅ΡΠ½ΡΠΌ ΡΠΏΠΎΡΡΠ΅Π±Π»Π΅Π½ΠΈΠ΅ΠΌ Π°Π»ΠΊΠΎΠ³ΠΎΠ»Ρ, ΠΈΠ·Π±ΡΡΠΎΡΠ½ΠΎΠΉ ΠΌΠ°ΡΡΠΎΠΉΒ ΡΠ΅Π»Π°, Π½Π΅ΡΠ±Π°Π»Π°Π½ΡΠΈΡΠΎΠ²Π°Π½Π½ΡΠΌ ΠΏΠΈΡΠ°Π½ΠΈΠ΅ΠΌ, Π²Π»ΠΈΡΠ½ΠΈΠ΅ΠΌΒ ΠΊΠ°Π½ΡΠ΅ΡΠΎΠ³Π΅Π½ΠΎΠ². ΠΡΠΎΡΠ°Ρ Π³ΡΡΠΏΠΏΠ° ΡΠ°ΠΊΡΠΎΡΠΎΠ² (35,0 %) ΠΎΠ±ΡΡΠ»ΠΎΠ²Π»Π΅Π½Π° ΠΏΡΠΎΠ±Π»Π΅ΠΌΠ°ΠΌΠΈ ΠΌΠ΅Π΄ΠΈΠΊΠΎ-ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎΠ³ΠΎ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠ°: Π½ΠΈΠ·ΠΊΠ°Ρ ΠΌΠ°ΡΠ΅ΡΠΈΠ°Π»ΡΠ½ΠΎ-ΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠ°Ρ Π±Π°Π·Π° ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΈΡ
ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΠΉΒ ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ Π·Π²Π΅Π½Π°, Π½Π΅Π΄ΠΎΡΡΠ°ΡΠΎΡΠ½Π°Ρ ΠΏΡΠΎΡΠ΅ΡΡΠΈΠΎΠ½Π°Π»ΡΠ½Π°ΡΒ ΠΏΠΎΠ΄Π³ΠΎΡΠΎΠ²ΠΊΠ° ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΈΡ
ΡΠ°Π±ΠΎΡΠ½ΠΈΠΊΠΎΠ² ΠΏΠΎ Π²ΠΎΠΏΡΠΎΡΠ°ΠΌΒ ΠΏΡΠΎΡΠΈΠ»Π°ΠΊΡΠΈΠΊΠΈ, ΡΠ²ΠΎΠ΅Π²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠΈ ΠΈ Π»Π΅ΡΠ΅Π½ΠΈΡ ΠΎΠ½ΠΊΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΡ
Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΠΉ, Π² ΡΠΎΠΌ ΡΠΈΡΠ»Π΅ ΡΠ°ΠΊΠ° ΠΏΠΎΡΠΊΠΈ. ΠΠ°ΠΊΠ»ΡΡΠ΅Π½ΠΈΠ΅. ΠΠ»Ρ ΠΎΡΡΡΠ΅ΡΡΠ²Π»Π΅Π½ΠΈΡ ΠΌΠ΅ΡΠΎΠΏΡΠΈΡΡΠΈΠΉ ΠΏΠΎ ΡΠ»ΡΡΡΠ΅Π½ΠΈΡ ΡΠ°Π½Π½Π΅ΠΉ Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠΈ ΠΠΠ ΠΏΠΎΡΠ΅ΠΊ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½Π° ΠΏΡΠΎΠ³Π½ΠΎΡΡΠΈΡΠ΅ΡΠΊΠ°Ρ ΠΌΠΎΠ΄Π΅Π»Ρ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΊΠΎΠΌΠΏΡΡΡΠ΅ΡΠ½ΠΎΠΉ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΡ Π΄Π»Ρ ΠΎΡΠ΅Π½ΠΊΠΈ ΠΈΠ½Π΄ΠΈΠ²ΠΈΠ΄ΡΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΠΈΡΠΊΠ° ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΠΠ ΠΏΠΎΡΠ΅ΠΊ Ρ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡΒ ΠΡΠΈΠΌΠΎΡΡΠΊΠΎΠ³ΠΎ ΠΊΡΠ°Ρ. ΠΠ½ΠΊΠ΅ΡΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΠΊΠΎΠΌΠΏΡΡΡΠ΅ΡΠ½ΠΎΠΉ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΡ Β«ΠΠ Π ΠΒ» ΠΊΠ°ΠΊ ΠΏΠ΅ΡΠ²ΠΎΠ³ΠΎ ΡΡΠ°ΠΏΠ° ΠΏΠΎΠΏΡΠ»ΡΡΠΈΠΎΠ½Π½ΠΎΠ³ΠΎ ΡΠΊΡΠΈΠ½ΠΈΠ½Π³Π° ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ»ΠΎ ΡΡΠ·ΠΈΡΡ Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΡΠ΅ΡΠΊΠΈΠΉ ΠΏΠΎΠΈΡΠΊ, ΡΡΠΎΡΠΌΠΈΡΠΎΠ²Π°ΡΡΠ³ΡΡΠΏΠΏΡ ΡΠΈΡΠΊΠ° ΠΈ ΠΎΡΡΡΠ΅ΡΡΠ²ΠΈΡΡ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΡΡ ΠΌΠ°ΡΡΡΡΡΠΈΠ·Π°ΡΠΈΡ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΠΏΠΎΠ΄ΠΎΠ·ΡΠ΅Π½ΠΈΠ΅ΠΌ Π½Π° ΠΠΠ ΠΏΠΎΡΠΊΠΈ Π΄Π»Ρ ΡΠ³Π»ΡΠ±Π»Π΅Π½Π½ΠΎΠ³ΠΎ ΠΎΠ±ΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ.
EPIDEMIOLOGICAL ASPECTS THE INCIDENCE OF CANCER OF THE KIDNEY AND BLADDER IN PRIMORSKY KRAI
Urinary system cancer is a malignancy caused by environmental exposures, the prevalence of which directly depends on the impact of environmental and anthropogenic factors. The aim of the study was to assess the kidney and bladder cancer incidence in different ecological and bioclimatic zones of Primorsky Krai. Material and methods. The incidence of kidney and bladder cancers in Primorsky Krai for the period between 1994 and 2014 was analyzed. In assessing the risk of kedney and bladder cancers in bioclimatic zones (marine climate, marine to continental transition and continental climate), environmental problems of the territories of Primorsky Krai were classified using the following ranks: critical, stress-like, satisfactory, and relatively favorable. The risk assessment was conducted using the guidance on Human Health Risk Assessment forΒ Environmental Impact Assessment. To calculate the environmental impact on risk of urinary system cancer, the information entropy analysis was used. Results. The territories with low, medium and high incidence of bladder and kidney cancers were identified. The high incidences of kidney and bladder cancers were registered in the territories with environmental problems ranked as critical and stress-like, affected by coal, mining and chemical industries, and in the territories with intensive use of chemical pesticides. The incidence of bladder cancer in men tended to rise from the continental bioclimatic zone to the coast in all ecological zones mainly due to differences in the structure of the bioclimate between the coast and continental areas of Primorsky Krai. The increased risk of urinary system cancer was shown to be associated with parameters, such as the quality of drinking water, total pollution of the environment, chemical composition of groundwater, and the sanitary condition of the soil. Conclusion. The environmental risk assessment and ranking of territories by risk allow the cancer prevention and control programs to be developed and the need for increased cancer screening in certain areas to be identified
ΠΠ¦ΠΠΠΠ ΠΠΠ’ΠΠΠ ΠΠΠΠΠ’ΠΠ ΠΠΠΠΠΠ― Π ΠΠΠΠ ΠΠΠΠΠ¬ΠΠΠΠ ΠΠΠ‘ΠΠΠΠΠΠΠΠΠ― ΠΠ ΠΠΠ§ ΠΠΠ― ΠΠΠ£Π§ΠΠΠΠ― Π ΠΠ‘ΠΠΠΠΠΠΠΠΠ ΠΠΠΠΠΠΠΠΠ― ΠΠΠ’ΠΠΠΠ ΠΠ ΠΠΠΠ Π‘ΠΠΠΠ ΠΠ ΠΠ―
To evaluate public HIV awareness and to reveal HIV cases, 3500 subjects who were not obliged by law to pass examinations were interviewed and tested for HIV. This investigation was carried out by mobile groups outside of health care institutions among target population groups and employees of different enterprises in eight municipalities of Primosrkiy Region. Interviews associated with counselling and discussions were conducted before and after HIV tests. On a whole, the subjects showed acceptable awareness of HIV epidemiology and prevention issues; however, a high rate of wrong answers in questionnaires (18,7%) was noticed among people aged 30 to 49 years who in recent years were predominant among newly found HIV cases in Primorskiy Region. This ο¬nding should be taken into accounted in the designs of preventive and educational interventions. HIV detection rate among people who are not obliged by law to pass HIV testing has been found to amount to 0,08%. Twenty-nine percent of study subjects believe that preventive voluntary screening for HIV should be more available.Π ΡΠ΅Π»ΡΡ
ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΈΠ½ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½Π½ΠΎΡΡΠΈ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ ΠΈ Π²ΡΡΠ²Π»Π΅Π½ΠΈΡ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΈ Π²ΠΈΡΡΡΠΎΠΌ ΠΈΠΌΠΌΡΠ½ΠΎΠ΄Π΅ΡΠΈΡΠΈΡΠ° ΡΠ΅Π»ΠΎΠ²Π΅ΠΊΠ° ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ 3500 ΡΠ΅Π»ΠΎΠ²Π΅ΠΊ ΠΈΠ· ΡΠΈΡΠ»Π° Π½Π΅ ΠΏΠΎΠ΄Π»Π΅ΠΆΠ°ΡΠΈΡ
ΠΎΠ±ΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π² ΠΎΠ±ΡΠ·Π°ΡΠ΅Π»ΡΠ½ΠΎΠΌ ΠΏΠΎΡΡΠ΄ΠΊΠ΅ ΠΏΠΎ ΡΡΠ΅Π±ΠΎΠ²Π°Π½ΠΈΡΠΌ Π½ΠΎΡΠΌΠ°ΡΠΈΠ²Π½ΡΡ
Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠΎΠ². ΠΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΡΡ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΡΠ°Π»Π° ΡΠΎΡΠΌΠ° Π΅Π³ΠΎ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΡ Π² ΡΠ°ΠΌΠΊΠ°Ρ
ΠΌΠΎΠ±ΠΈΠ»ΡΠ½ΠΎΠΉ Π²ΡΠ΅Π·Π΄Π½ΠΎΠΉ ΡΠ°Π±ΠΎΡΡ, Π·Π° ΠΏΡΠ΅Π΄Π΅Π»Π°ΠΌΠΈ ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΈΡ
ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΠΉ, Π² ΠΊΠ»ΡΡΠ΅Π²ΡΡ
Π³ΡΡΠΏΠΏΠ°Ρ
Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ ΠΈ ΡΡΡΠ΄ΠΎΠ²ΡΡ
ΠΊΠΎΠ»Π»Π΅ΠΊΡΠΈΠ²Π°Ρ
Π½Π° ΡΠ΅ΡΡΠΈΡΠΎΡΠΈΠΈ 8 ΠΌΡΠ½ΠΈΡΠΈΠΏΠ°Π»ΡΠ½ΡΡ
ΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΠΉ ΠΡΠΈΠΌΠΎΡΡΠΊΠΎΠ³ΠΎ ΠΊΡΠ°Ρ. ΠΠ°ΡΠ΅ΡΠΈΠ°Π»Ρ ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ. ΠΡΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΎΡΡ Π΄ΠΎ- ΠΈ ΠΏΠΎΡΠ»Π΅ΡΠ΅ΡΡΠΎΠ²ΠΎΠ΅ ΠΊΠΎΠ½ΡΡΠ»ΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΠΎ Π²ΠΎΠΏΡΠΎΡΠ°ΠΌ ΠΏΡΠΎΡΠΈΠ»Π°ΠΊΡΠΈΠΊΠΈ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΈ Π²ΠΈΡΡΡΠΎΠΌ ΠΈΠΌΠΌΡΠ½ΠΎΠ΄Π΅ΡΠΈΡΠΈΡΠ° ΡΠ΅Π»ΠΎΠ²Π΅ΠΊΠ° Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² ΠΈΠ½ΡΠ΅ΡΠ²ΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ, ΠΎΠΏΡΠΎΡΠ°, ΠΏΡΠ΅Π΄ΠΎΡΡΠ°Π²Π»Π΅Π½ΠΈΡ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ, ΠΎΠ±ΡΡΠΆΠ΄Π΅Π½ΠΈΡ. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ. ΠΡΡΠ»Π΅Π΄ΡΠ΅ΠΌΡΠ΅ ΠΏΡΠΎΡΠ²ΠΈΠ»ΠΈ Π΄ΠΎΡΡΠ°ΡΠΎΡΠ½ΡΠΉ ΡΡΠΎΠ²Π΅Π½Ρ ΠΈΠ½ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½Π½ΠΎΡΡΠΈ ΠΏΠΎ ΠΎΡΠ½ΠΎΠ²Π½ΡΠΌ Π²ΠΎΠΏΡΠΎΡΠ°ΠΌ ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΠΎΠ»ΠΎΠ³ΠΈΠΈ ΠΈ ΠΏΡΠΎΡΠΈΠ»Π°ΠΊΡΠΈΠΊΠΈ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΈ Π²ΠΈΡΡΡΠΎΠΌ ΠΈΠΌΠΌΡΠ½ΠΎΠ΄Π΅ΡΠΈΡΠΈΡΠ° ΡΠ΅Π»ΠΎΠ²Π΅ΠΊΠ°. ΠΠ΄Π½Π°ΠΊΠΎ Π½Π°ΠΈΠ±ΠΎΠ»ΡΡΠ΅Π΅ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²ΠΎ Π½Π΅ΠΏΡΠ°Π²ΠΈΠ»ΡΠ½ΡΡ
ΠΎΡΠ²Π΅ΡΠΎΠ² ΠΏΠΎΠ»ΡΡΠ΅Π½ΠΎ Π² Π²ΠΎΠ·ΡΠ°ΡΡΠ½ΠΎΠΉ Π³ΡΡΠΏΠΏΠ΅ 30β49 Π»Π΅Ρ (18,7% ΠΎΡ ΡΠΈΡΠ»Π° Π²ΡΠ΅Ρ
ΠΎΠΏΡΠΎΡΠ΅Π½Π½ΡΡ
Π΄Π°Π½Π½ΠΎΠ³ΠΎ Π²ΠΎΠ·ΡΠ°ΡΡΠ°), ΠΏΡΠ΅ΠΎΠ±Π»Π°Π΄Π°ΡΡΠ΅ΠΉ ΡΡΠ΅Π΄ΠΈ Π²ΠΎΠ·ΡΠ°ΡΡΠ½ΡΡ
Π³ΡΡΠΏΠΏ Ρ Π²ΠΏΠ΅ΡΠ²ΡΠ΅ Π²ΡΡΠ²Π»Π΅Π½Π½ΠΎΠΉ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠ΅ΠΉ Π²ΠΈΡΡΡΠΎΠΌ ΠΈΠΌΠΌΡΠ½ΠΎΠ΄Π΅ΡΠΈΡΠΈΡΠ° ΡΠ΅Π»ΠΎΠ²Π΅ΠΊΠ° Π½Π° ΡΠ΅ΡΡΠΈΡΠΎΡΠΈΠΈ ΠΡΠΈΠΌΠΎΡΡΠΊΠΎΠ³ΠΎ ΠΊΡΠ°Ρ Π² ΠΏΠΎΡΠ»Π΅Π΄Π½ΠΈΠ΅ Π³ΠΎΠ΄Ρ. ΠΡΠΎΡ ΡΠ°ΠΊΡΠΎΡ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎ ΡΡΠΈΡΡΠ²Π°ΡΡ ΠΏΡΠΈ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΠΈ Π°Π΄ΡΠ΅ΡΠ½ΡΡ
ΠΏΡΠΎΡΠΈΠ»Π°ΠΊΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΠΌΠ΅ΡΠΎΠΏΡΠΈΡΡΠΈΠΉ Π½Π° ΠΏΠΎΠΏΡΠ»ΡΡΠΈΠΎΠ½Π½ΠΎΠΌ ΡΡΠΎΠ²Π½Π΅. ΠΡΡΠ²Π»ΡΠ΅ΠΌΠΎΡΡΡ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΈ Π²ΠΈΡΡΡΠΎΠΌ ΠΈΠΌΠΌΡΠ½ΠΎΠ΄Π΅ΡΠΈΡΠΈΡΠ° ΡΠ΅Π»ΠΎΠ²Π΅ΠΊΠ° ΠΏΡΠΈ ΠΎΠ±ΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΈ Π»ΠΈΡ, Π½Π΅ ΠΏΠΎΠ΄Π»Π΅ΠΆΠ°ΡΠΈΡ
ΠΎΠ±ΡΠ·Π°ΡΠ΅Π»ΡΠ½ΠΎΠΌΡ ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΎΠΌΡ ΠΎΡΠ²ΠΈΠ΄Π΅ΡΠ΅Π»ΡΡΡΠ²ΠΎΠ²Π°Π½ΠΈΡ, ΡΠΎΡΡΠ°Π²ΠΈΠ»Π° 0,08%. 29% ΡΡΠ°ΡΡΠ½ΠΈΠΊΠΎΠ² ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΡΠΈΡΠ°ΡΡ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΡΠΌ ΡΠ²Π΅Π»ΠΈΡΠ΅Π½ΠΈΠ΅ Π΄ΠΎΡΡΡΠΏΠ½ΠΎΡΡΠΈ ΠΏΡΠ΅Π²Π΅Π½ΡΠΈΠ²Π½ΠΎΠ³ΠΎ ΡΠΊΡΠΈΠ½ΠΈΠ½Π³ΠΎΠ²ΠΎΠ³ΠΎ ΠΎΠ±ΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π½Π° Π²ΠΈΡΡΡ ΠΈΠΌΠΌΡΠ½ΠΎΠ΄Π΅ΡΠΈΡΠΈΡΠ° ΡΠ΅Π»ΠΎΠ²Π΅ΠΊΠ°.</p
ΠΠ‘ΠΠΠΠΠΠΠ‘Π’Π Π ΠΠΠΠΠ’ΠΠ― ΠΠΠΠΠΠΠΠ§ΠΠ‘ΠΠΠΠ ΠΠ ΠΠ¦ΠΠ‘Π‘Π ΠΠΠ§-ΠΠΠ€ΠΠΠ¦ΠΠ Π ΠΠ ΠΠΠΠ Π‘ΠΠΠ ΠΠ ΠΠ
The official statistical data of HIV Registry ο¬led at Regional Center for Prevention and Control of AIDS and infectious Diseases were used in assessing the time course of HIV epidemic in Primorkiy Region to deο¬ne the region-speciο¬c features of the development of HIV epidemic in 2011β2016. HIV prevalence is increasing in the Region since 2011. Although the importance of the sexual route of HIV transmissionΒ is on the rise, the main route is still injection drug use. Trends in changes in the gender and age structureΒ of HIV-infected population are deο¬ned. The highestΒ HIV prevalence is found among males aged 25 to 49 years: 1113.4 per 100 000 male population, almost three times higher than the average value.ΠΠ·ΡΡΠ΅Π½Π° Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠ° ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½ΠΈΡ ΠΠΠ§-ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΈ Π½Π° ΡΠ΅ΡΡΠΈΡΠΎΡΠΈΠΈ ΠΡΠΈΠΌΠΎΡΡΠΊΠΎΠ³ΠΎ ΠΊΡΠ°Ρ Π·Π° Π²Π΅ΡΡ ΠΏΠ΅ΡΠΈΠΎΠ΄ ΡΠ΅Π³ΠΈΡΡΡΠ°ΡΠΈΠΈ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΈ Π΄Π»Ρ Π²ΡΡΠ²Π»Π΅Π½ΠΈΡ ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠ΅ΠΉ ΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½ΠΈΡ ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΠΈ Π½Π° ΠΊΠΎΠ½ΠΊΡΠ΅ΡΠ½ΠΎΠΉ ΡΠ΅ΡΡΠΈΡΠΎΡΠΈΠΈ ΠΈ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΡΠ΅Π½Π΄Π΅Π½ΡΠΈΠΉ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΡΠΏΠΈΠ΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΏΡΠΎΡΠ΅ΡΡΠ° Π² 2011β2016 Π³ΠΎΠ΄Π°Ρ
. Π ΡΠ°Π±ΠΎΡΠ΅ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½Ρ ΠΎΡΠΈΡΠΈΠ°Π»ΡΠ½ΡΠ΅ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ Π΄Π°Π½Π½ΡΠ΅ ΡΠ΅Π³ΠΈΡΡΡΠ°ΡΠΈΠΈ ΠΠΠ§-ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΈ ΠΠΠ£Π Β«ΠΡΠ°Π΅Π²Π°Ρ ΠΊΠ»ΠΈΠ½ΠΈΡΠ΅ΡΠΊΠ°Ρ Π±ΠΎΠ»ΡΠ½ΠΈΡΠ° β 2 β Π¦Π΅Π½ΡΡ ΠΏΠΎ ΠΏΡΠΎΡΠΈΠ»Π°ΠΊΡΠΈΠΊΠ΅ ΠΈ Π±ΠΎΡΡΠ±Π΅ ΡΠΎ Π‘ΠΠΠ ΠΈ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠΎΠ½Π½ΡΠΌΠΈ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΡΠΌΠΈΒ».Β Π‘ 2011Β Π³ΠΎΠ΄Π° Π² ΠΡΠΈΠΌΠΎΡΡΠΊΠΎΠΌ ΠΊΡΠ°Π΅ ΡΠ΅Π³ΠΈΡΡΡΠΈΡΡΠ΅ΡΡΡ ΠΏΠΎΠ΄ΡΠ΅ΠΌ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π΅ΠΌΠΎΡΡΠΈΒ ΠΠΠ§-ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠ΅ΠΉ. ΠΠ΅ΡΠΌΠΎΡΡΡ Π½Π° ΠΏΠΎΠ²ΡΠ΅ΠΌΠ΅ΡΡΠ½ΠΎΠ΅ ΡΠ²Π΅Π»ΠΈΡΠ΅Π½ΠΈΠ΅ Π·Π½Π°ΡΠΈΠΌΠΎΡΡΠΈ ΠΏΠΎΠ»ΠΎΠ²ΠΎΠ³ΠΎ ΠΏΡΡΠΈ Π·Π°ΡΠ°ΠΆΠ΅Π½ΠΈΡ ΠΠΠ§, Π² ΠΡΠΈΠΌΠΎΡΡΠ΅ ΠΎΡΠ½ΠΎΠ²Π½ΡΠΌ ΡΠ°ΠΊΡΠΎΡΠΎΠΌ ΡΠΈΡΠΊΠ° ΠΎΡΡΠ°Π΅ΡΡΡ Π²Π½ΡΡΡΠΈΠ²Π΅Π½Π½ΠΎΠ΅ Π²Π²Π΅Π΄Π΅Π½ΠΈΠ΅ Π½Π°ΡΠΊΠΎΡΠΈΠΊΠΎΠ². ΠΡΡΠ²Π»Π΅Π½Π° ΡΠ΅Π½Π΄Π΅Π½ΡΠΈΡ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡ Π³Π΅Π½Π΄Π΅ΡΠ½ΠΎΠ³ΠΎ ΠΈ Π²ΠΎΠ·ΡΠ°ΡΡΠ½ΠΎΠ³ΠΎ ΡΠΎΡΡΠ°Π²Π° Π»ΠΈΡ, ΠΆΠΈΠ²ΡΡΠΈΡ
Ρ ΠΠΠ§. ΠΠ°ΠΈΠ±ΠΎΠ»ΡΡΠΈΠΉ ΡΡΠΎΠ²Π΅Π½Ρ ΠΏΠΎΡΠ°ΠΆΠ΅Π½Π½ΠΎΡΡΠΈ ΠΠΠ§-ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠ΅ΠΉΒ ΡΠ΅Π³ΠΈΡΡΡΠΈΡΡΠ΅ΡΡΡ ΡΡΠ΅Π΄ΠΈ ΠΌΡΠΆΡΠΈΠ½ Π² Π²ΠΎΠ·ΡΠ°ΡΡΠ΅ 25β49Β Π»Π΅Ρ (1113,4 Π½Π° 100 ΡΡΡΡΡ ΠΌΡΠΆΡΠΊΠΎΠ³ΠΎ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ), ΠΏΠΎΡΡΠΈ Π² ΡΡΠΈ ΡΠ°Π·Π° ΠΏΡΠ΅Π²ΡΡΠ°Ρ ΠΊΡΠ°Π΅Π²ΡΠ΅ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΠΈ ΠΎΠΊΡΡΠ³Π° (ΠΠ€Π).</p