19 research outputs found

    INFLUENCE OF ENVIRONMENTAL FACTORS ON HYGIENE PREVALENCE OF CIRCULATORY DISEASES OF POPULATION OF THE PRIMORSKY KRAY BIOCLIMATIC ZONES

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    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 (Ο‡2) 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

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    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 К-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

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    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

    ΠœΠžΠ”Π•Π›Π¬ ΠžΠ Π“ΠΠΠ˜Π—ΠΠ¦Π˜Π˜ РАННЕЙ Π”Π˜ΠΠ“ΠΠžΠ‘Π’Π˜ΠšΠ˜ РАКА ПОЧКИ

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    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 – 1950, men – 1032) in the age range 29–75 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 – 22.0 %) and patients of the uncertainty group (447 – 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 I–II 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 ΠŸΡ€ΠΎΠ±Π»Π΅ΠΌΠ° Ρ€Π°Π½Π½Π΅ΠΉ диагностики ΠΈ скрининга Ρ€Π°ΠΊΠ° ΠΏΠΎΡ‡ΠΊΠΈ сущСствСнным ΠΎΠ±Ρ€Π°Π·ΠΎΠΌ влияСт Π½Π° Π·Π°ΠΏΡƒΡ‰Π΅Π½Π½ΠΎΡΡ‚ΡŒ ΠΈ ΡΠΌΠ΅Ρ€Ρ‚Π½ΠΎΡΡ‚ΡŒ ΠΎΡ‚ Π΄Π°Π½Π½ΠΎΠΉ ΠΏΠ°Ρ‚ΠΎΠ»ΠΎΠ³ΠΈΠΈ, Ρ‡Ρ‚ΠΎ Π΄ΠΈΠΊΡ‚ΡƒΠ΅Ρ‚ Π½Π΅ΠΎΠ±Ρ…ΠΎΠ΄ΠΈΠΌΠΎΡΡ‚ΡŒ Ρ€Π΅ΡˆΠ΅Π½ΠΈΡ ΠΏΡ€ΠΎΠ±Π»Π΅ΠΌ ΠΏΡ€ΠΎΡ„ΠΈΠ»Π°ΠΊΡ‚ΠΈΠΊΠΈ, ΡƒΠ»ΡƒΡ‡ΡˆΠ΅Π½ΠΈΡ Ρ€Π°Π½Π½Π΅ΠΉ диагностики ΠΈ ΠΎΡ€Π³Π°Π½ΠΈΠ·Π°Ρ†ΠΈΠΈ мСдицинской ΠΏΠΎΠΌΠΎΡ‰ΠΈ насСлСнию ΠŸΡ€ΠΈΠΌΠΎΡ€ΡΠΊΠΎΠ³ΠΎ края ΠΏΡ€ΠΈ злокачСствСнных новообразованиях (Π—ΠΠž) ΠΏΠΎΡ‡ΠΊΠΈ. ЦСлью исслСдования явилось созданиС ΠΌΠΎΠ΄Π΅Π»ΠΈ ΡΠΎΠ²Π΅Ρ€ΡˆΠ΅Π½ΡΡ‚Π²ΠΎΠ²Π°Π½ΠΈΡ Ρ€Π°Π½Π½Π΅ΠΉ диагностики Π—ΠΠž ΠΏΠΎΡ‡ΠΊΠΈ Π² ΠŸΡ€ΠΈΠΌΠΎΡ€ΡΠΊΠΎΠΌ ΠΊΡ€Π°Π΅ Π½Π° основС Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚ΠΊΠΈ ΠΈ внСдрСния Π² ΠΏΡ€Π°ΠΊΡ‚ΠΈΠΊΡƒ ΠΊΠΎΠΌΠΏΡŒΡŽΡ‚Π΅Ρ€Π½ΠΎΠΉ ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΡ‹ ΠΎΡ†Π΅Π½ΠΊΠΈ риска Ρ€Π°ΠΊΠ° ΠΏΠΎΡ‡ΠΊΠΈ – «ОРРП». Π­Ρ‚Π° модСль Π²ΠΊΠ»ΡŽΡ‡Π°Π΅Ρ‚ Π² сСбя Π°Π½ΠΊΠ΅Ρ‚ΠΈΡ€ΠΎΠ²Π°Π½ΠΈΠ΅ (опрос) насСлСния Π½Π° выявлСниС Ρ„Π°ΠΊΡ‚ΠΎΡ€ΠΎΠ² риска ΠΈ Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌ ΠΌΠ°Ρ€ΡˆΡ€ΡƒΡ‚ΠΈΠ·Π°Ρ†ΠΈΠΈ ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² («дороТная ΠΊΠ°Ρ€Ρ‚Π°Β») с  ΠΏΠΎΠ΄ΠΎΠ·Ρ€Π΅Π½ΠΈΠ΅ΠΌ Π½Π° Ρ€Π°ΠΊ ΠΏΠΎΡ‡ΠΊΠΈ для ΡƒΠ³Π»ΡƒΠ±Π»Π΅Π½Π½ΠΎΠ³ΠΎ обслСдования ΠΈ лСчСния.ΠœΠ°Ρ‚Π΅Ρ€ΠΈΠ°Π» ΠΈ ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹. ΠžΠ±ΡŠΠ΅ΠΊΡ‚ΠΎΠΌ исслСдования Π±Ρ‹Π»ΠΎ насСлСниС ΠŸΡ€ΠΈΠΌΠΎΡ€ΡΠΊΠΎΠ³ΠΎ края. ΠŸΡ€ΠΎΠ²Π΅Π΄Π΅Π½ΠΎ Π°Π½ΠΊΠ΅Ρ‚ΠΈΡ€ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΠΎ ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΠ΅ «ОРРП», Π² ΠΊΠΎΡ‚ΠΎΡ€ΠΎΠΌ приняли участиС 2982 ТитСля Π² возрастС ΠΎΡ‚ 29 Π΄ΠΎ 75 Π»Π΅Ρ‚ (ΠΆΠ΅Π½Ρ‰ΠΈΠ½ – 1950, ΠΌΡƒΠΆΡ‡ΠΈΠ½ – 1032). Π‘ Ρ†Π΅Π»ΡŒΡŽ поиска Π½Π°ΡƒΡ‡Π½Ρ‹Ρ… Ρ€Π΅ΡˆΠ΅Π½ΠΈΠΉ ΠΏΠΎ сниТСнию уровнясмСртности ΠΎΡ‚ Π½ΠΎΠ²ΠΎΠΎΠ±Ρ€Π°Π·ΠΎΠ²Π°Π½ΠΈΠΉ ΠΏΡ€ΠΎΠ²Π΅Π΄Π΅Π½ Π°Π½Π°Π»ΠΈΠ· ΠΏΡ€ΠΈΡ‡ΠΈΠ½Β  роста онкологичСской заболСваСмости ΠΈ смСртности насСлСния ΠŸΡ€ΠΈΠΌΠΎΡ€ΡΠΊΠΎΠ³ΠΎ края с использованиСм  мСдицинских ΠΊΠ°Ρ€Ρ‚ ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ², Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚ΠΎΠ² вСдомствСнных экспСртиз мСдицинских ΠΎΡ€Π³Π°Π½ΠΈΠ·Π°Ρ†ΠΈΠΉ, ΠΏΡ€ΠΎΡ‚ΠΈΠ²ΠΎΡ€Π°ΠΊΠΎΠ²Ρ‹Ρ… комиссий, ΠΊΠΎΠ»Π»Π΅Π³ΠΈΠΉ, Π°ΠΏΠΏΠ°Ρ€Π°Ρ‚Π½Ρ‹Ρ… совСщаний, ΠΌΠΎΠ½ΠΈΡ‚ΠΎΡ€ΠΈΠ½Π³Π° ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»Π΅ΠΉ государствСнной ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΡ‹ Β«Π Π°Π·Π²ΠΈΡ‚ΠΈΠ΅ здравоохранСния ΠŸΡ€ΠΈΠΌΠΎΡ€ΡΠΊΠΎΠ³ΠΎ края», «Плана мСроприятий ΠΏΠΎ сниТСнию смСртности насСлСния ΠΎΡ‚ Π½ΠΎΠ²ΠΎΠΎΠ±Ρ€Π°Π·ΠΎΠ²Π°Π½ΠΈΠΉ, Π²Ρ‚ΠΎΠΌ числС злокачСствСнных». Π Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹. По Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Π°ΠΌ опроса Ρƒ 1879 (63,0 %) Π»ΠΈΡ† Π½Π΅ выявлСно Ρ„Π°ΠΊΡ‚ΠΎΡ€ΠΎΠ² риска, ΠΈΠΌ Ρ€Π΅ΠΊΠΎΠΌΠ΅Π½Π΄ΠΎΠ²Π°Π½ΠΎ ΠΏΡ€ΠΎΠΉΡ‚ΠΈ ΠΊΠΎΠ½Ρ‚Ρ€ΠΎΠ»ΡŒΠ½ΠΎΠ΅ Π°Π½ΠΊΠ΅Ρ‚ΠΈΡ€ΠΎΠ²Π°Π½ΠΈΠ΅ Ρ‡Π΅Ρ€Π΅Π· 3 Π³ΠΎΠ΄Π°. ΠŸΠ°Ρ†ΠΈΠ΅Π½Ρ‚Ρ‹ Π³Ρ€ΡƒΠΏΠΏΡ‹ высокого риска (656 – 22,0 %) Π±Ρ‹Π»ΠΈ Π½Π°ΠΏΡ€Π°Π²Π»Π΅Π½Ρ‹ ΠΊ ΡƒΡ€ΠΎΠ»ΠΎΠ³Ρƒ для ΡƒΠ³Π»ΡƒΠ±Π»Π΅Π½Π½ΠΎΠ³ΠΎ обслСдования. ΠŸΠ°Ρ†ΠΈΠ΅Π½Ρ‚Ρ‹ Π³Ρ€ΡƒΠΏΠΏΡ‹ нСопрСдСлСнности (447 – 15,0 %) Π±Ρ‹Π»ΠΈ Π½Π°ΠΏΡ€Π°Π²Π»Π΅Π½Ρ‹ Π½Π° осмотр участкового Ρ‚Π΅Ρ€Π°ΠΏΠ΅Π²Ρ‚Π°. ВсСм ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚Π°ΠΌ Π³Ρ€ΡƒΠΏΠΏ нСопрСдСлСнности ΠΈ высокого риска Π½Π°Π·Π½Π°Ρ‡Π°Π»ΠΎΡΡŒ ΡƒΠ»ΡŒΡ‚Ρ€Π°Π·Π²ΡƒΠΊΠΎΠ²ΠΎΠ΅ исслСдованиС для ΠΈΡΠΊΠ»ΡŽΡ‡Π΅Π½ΠΈΡ новообразования ΠΏΠΎΡ‡Π΅ΠΊ. Π£ 156 (14,0 %) ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² выявлСна нСопухолСвая патология ΠΏΠΎΡ‡Π΅ΠΊ, Ρƒ 21 (1,9 %) ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚Π° – ΠΏΠΎΠ΄ΠΎΠ·Ρ€Π΅Π½ΠΈΠ΅ Π½Π° Π—ΠΠž ΠΏΠΎΡ‡Π΅ΠΊ, ΠΊΠΎΡ‚ΠΎΡ€ΠΎΠ΅ ΠΏΠΎΠ·ΠΆΠ΅ ΠΏΠΎΠ΄Ρ‚Π²Π΅Ρ€Π΄ΠΈΠ»ΠΎΡΡŒ (Ρƒ 17 ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² I–II стадии, Ρƒ 3 ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² – III стадии, Ρƒ 1 ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚Π° – IV стадии). По Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Π°ΠΌ Π°Π½Π°Π»ΠΈΠ·Π° Π°Π½ΠΊΠ΅Ρ‚ Π½Π° рост ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»Π΅ΠΉ заболСваСмости Ρ€Π°ΠΊΠΎΠΌ ΠΏΠΎΡ‡Π΅ΠΊ ΠΎΠΊΠ°Π·Π°Π»ΠΈ прСимущСствСнноС влияниС Π΄Π²Π΅ основныС Π³Ρ€ΡƒΠΏΠΏΡ‹ Ρ„Π°ΠΊΡ‚ΠΎΡ€ΠΎΠ². ΠŸΠ΅Ρ€Π²Π°Ρ Π³Ρ€ΡƒΠΏΠΏΠ° Ρ„Π°ΠΊΡ‚ΠΎΡ€ΠΎΠ² (65,0 %) обусловлСна ΠΊΡƒΡ€Π΅Π½ΠΈΠ΅ΠΌ,Β  Ρ‡Ρ€Π΅Π·ΠΌΠ΅Ρ€Π½Ρ‹ΠΌ ΡƒΠΏΠΎΡ‚Ρ€Π΅Π±Π»Π΅Π½ΠΈΠ΅ΠΌ алкоголя, ΠΈΠ·Π±Ρ‹Ρ‚ΠΎΡ‡Π½ΠΎΠΉ массой  Ρ‚Π΅Π»Π°, нСсбалансированным ΠΏΠΈΡ‚Π°Π½ΠΈΠ΅ΠΌ, влияниСм  ΠΊΠ°Π½Ρ†Π΅Ρ€ΠΎΠ³Π΅Π½ΠΎΠ². Вторая Π³Ρ€ΡƒΠΏΠΏΠ° Ρ„Π°ΠΊΡ‚ΠΎΡ€ΠΎΠ² (35,0 %) обусловлСна ΠΏΡ€ΠΎΠ±Π»Π΅ΠΌΠ°ΠΌΠΈ ΠΌΠ΅Π΄ΠΈΠΊΠΎ-ΡΠΎΡ†ΠΈΠ°Π»ΡŒΠ½ΠΎΠ³ΠΎ Ρ…Π°Ρ€Π°ΠΊΡ‚Π΅Ρ€Π°: низкая ΠΌΠ°Ρ‚Π΅Ρ€ΠΈΠ°Π»ΡŒΠ½ΠΎ-тСхничСская Π±Π°Π·Π° мСдицинских ΠΎΡ€Π³Π°Π½ΠΈΠ·Π°Ρ†ΠΈΠΉΒ  ΠΏΠ΅Ρ€Π²ΠΈΡ‡Π½ΠΎΠ³ΠΎ Π·Π²Π΅Π½Π°, нСдостаточная ΠΏΡ€ΠΎΡ„Π΅ΡΡΠΈΠΎΠ½Π°Π»ΡŒΠ½Π°ΡΒ  ΠΏΠΎΠ΄Π³ΠΎΡ‚ΠΎΠ²ΠΊΠ° мСдицинских Ρ€Π°Π±ΠΎΡ‚Π½ΠΈΠΊΠΎΠ² ΠΏΠΎ вопросам  ΠΏΡ€ΠΎΡ„ΠΈΠ»Π°ΠΊΡ‚ΠΈΠΊΠΈ, своСврСмСнной диагностики ΠΈ лСчСния онкологичСских Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΠΉ, Π² Ρ‚ΠΎΠΌ числС Ρ€Π°ΠΊΠ° ΠΏΠΎΡ‡ΠΊΠΈ. Π—Π°ΠΊΠ»ΡŽΡ‡Π΅Π½ΠΈΠ΅. Для осущСствлСния мСроприятий ΠΏΠΎ ΡƒΠ»ΡƒΡ‡ΡˆΠ΅Π½ΠΈΡŽ Ρ€Π°Π½Π½Π΅ΠΉ диагностики Π—ΠΠž ΠΏΠΎΡ‡Π΅ΠΊ Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚Π°Π½Π° прогностичСская модСль Π½Π° основС ΠΊΠΎΠΌΠΏΡŒΡŽΡ‚Π΅Ρ€Π½ΠΎΠΉ ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΡ‹ для ΠΎΡ†Π΅Π½ΠΊΠΈ ΠΈΠ½Π΄ΠΈΠ²ΠΈΠ΄ΡƒΠ°Π»ΡŒΠ½ΠΎΠ³ΠΎ риска развития Π—ΠΠž ΠΏΠΎΡ‡Π΅ΠΊ Ρƒ насСлСния  ΠŸΡ€ΠΈΠΌΠΎΡ€ΡΠΊΠΎΠ³ΠΎ края. АнкСтированиС насСлСния с использованиСм ΠΊΠΎΠΌΠΏΡŒΡŽΡ‚Π΅Ρ€Π½ΠΎΠΉ ΠΏΡ€ΠΎΠ³Ρ€Π°ΠΌΠΌΡ‹ «ОРРП» ΠΊΠ°ΠΊ ΠΏΠ΅Ρ€Π²ΠΎΠ³ΠΎ этапа популяционного скрининга ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ»ΠΎ ΡΡƒΠ·ΠΈΡ‚ΡŒ диагностичСский поиск, ΡΡ„ΠΎΡ€ΠΌΠΈΡ€ΠΎΠ²Π°Ρ‚ΡŒΠ³Ρ€ΡƒΠΏΠΏΡ‹ риска ΠΈ ΠΎΡΡƒΡ‰Π΅ΡΡ‚Π²ΠΈΡ‚ΡŒ ΡΡ„Ρ„Π΅ΠΊΡ‚ΠΈΠ²Π½ΡƒΡŽ ΠΌΠ°Ρ€ΡˆΡ€ΡƒΡ‚ΠΈΠ·Π°Ρ†ΠΈΡŽ ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² с ΠΏΠΎΠ΄ΠΎΠ·Ρ€Π΅Π½ΠΈΠ΅ΠΌ Π½Π° Π—ΠΠž ΠΏΠΎΡ‡ΠΊΠΈ для ΡƒΠ³Π»ΡƒΠ±Π»Π΅Π½Π½ΠΎΠ³ΠΎ обслСдования.

    EPIDEMIOLOGICAL ASPECTS THE INCIDENCE OF CANCER OF THE KIDNEY AND BLADDER IN PRIMORSKY KRAI

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    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

    ΠžΠ¦Π•ΠΠšΠ ΠœΠ•Π’ΠžΠ”Π ΠΠΠšΠ•Π’Π˜Π ΠžΠ’ΠΠΠ˜Π― И Π”ΠžΠ‘Π ΠžΠ’ΠžΠ›Π¬ΠΠžΠ“Πž ΠžΠ‘Π‘Π›Π•Π”ΠžΠ’ΠΠΠ˜Π― НА Π’Π˜Π§ Π”Π›Π― Π˜Π—Π£Π§Π•ΠΠ˜Π― Π Π˜Π‘ΠšΠžΠ’ΠΠΠΠžΠ“Πž ΠŸΠžΠ’Π•Π”Π•ΠΠ˜Π― Π–Π˜Π’Π•Π›Π•Π™ ΠŸΠ Π˜ΠœΠžΠ Π‘ΠšΠžΠ“Πž КРАЯ

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    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 finding 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’ цСлях опрСдСлСния информированности насСлСния ΠΈ выявлСния ΠΈΠ½Ρ„Π΅ΠΊΡ†ΠΈΠΈ вирусом ΠΈΠΌΠΌΡƒΠ½ΠΎΠ΄Π΅Ρ„ΠΈΡ†ΠΈΡ‚Π° Ρ‡Π΅Π»ΠΎΠ²Π΅ΠΊΠ° ΠΏΡ€ΠΎΠ²Π΅Π΄Π΅Π½ΠΎ исслСдованиС 3500 Ρ‡Π΅Π»ΠΎΠ²Π΅ΠΊ ΠΈΠ· числа Π½Π΅ ΠΏΠΎΠ΄Π»Π΅ΠΆΠ°Ρ‰ΠΈΡ… обслСдованию Π² ΠΎΠ±ΡΠ·Π°Ρ‚Π΅Π»ΡŒΠ½ΠΎΠΌ порядкС ΠΏΠΎ трСбованиям Π½ΠΎΡ€ΠΌΠ°Ρ‚ΠΈΠ²Π½Ρ‹Ρ… Π΄ΠΎΠΊΡƒΠΌΠ΅Π½Ρ‚ΠΎΠ². ΠžΡΠΎΠ±Π΅Π½Π½ΠΎΡΡ‚ΡŒΡŽ исслСдования стала Ρ„ΠΎΡ€ΠΌΠ° Π΅Π³ΠΎ провСдСния Π² Ρ€Π°ΠΌΠΊΠ°Ρ… мобильной Π²Ρ‹Π΅Π·Π΄Π½ΠΎΠΉ Ρ€Π°Π±ΠΎΡ‚Ρ‹, Π·Π° ΠΏΡ€Π΅Π΄Π΅Π»Π°ΠΌΠΈ мСдицинских ΠΎΡ€Π³Π°Π½ΠΈΠ·Π°Ρ†ΠΈΠΉ, Π² ΠΊΠ»ΡŽΡ‡Π΅Π²Ρ‹Ρ… Π³Ρ€ΡƒΠΏΠΏΠ°Ρ… насСлСния ΠΈ Ρ‚Ρ€ΡƒΠ΄ΠΎΠ²Ρ‹Ρ… ΠΊΠΎΠ»Π»Π΅ΠΊΡ‚ΠΈΠ²Π°Ρ… Π½Π° Ρ‚Π΅Ρ€Ρ€ΠΈΡ‚ΠΎΡ€ΠΈΠΈ 8 ΠΌΡƒΠ½ΠΈΡ†ΠΈΠΏΠ°Π»ΡŒΠ½Ρ‹Ρ… ΠΎΠ±Ρ€Π°Π·ΠΎΠ²Π°Π½ΠΈΠΉ ΠŸΡ€ΠΈΠΌΠΎΡ€ΡΠΊΠΎΠ³ΠΎ края. ΠœΠ°Ρ‚Π΅Ρ€ΠΈΠ°Π»Ρ‹ ΠΈ ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹. ΠŸΡ€ΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΎΡΡŒ Π΄ΠΎ- ΠΈ послСтСстовоС ΠΊΠΎΠ½ΡΡƒΠ»ΡŒΡ‚ΠΈΡ€ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΠΎ вопросам ΠΏΡ€ΠΎΡ„ΠΈΠ»Π°ΠΊΡ‚ΠΈΠΊΠΈ ΠΈΠ½Ρ„Π΅ΠΊΡ†ΠΈΠΈ вирусом ΠΈΠΌΠΌΡƒΠ½ΠΎΠ΄Π΅Ρ„ΠΈΡ†ΠΈΡ‚Π° Ρ‡Π΅Π»ΠΎΠ²Π΅ΠΊΠ° с использованиСм ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠ² ΠΈΠ½Ρ‚Π΅Ρ€Π²ΡŒΡŽΠΈΡ€ΠΎΠ²Π°Π½ΠΈΡ, опроса, прСдоставлСния ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΈ, обсуТдСния. Π Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹ исслСдования. Π˜ΡΡΠ»Π΅Π΄ΡƒΠ΅ΠΌΡ‹Π΅ проявили достаточный ΡƒΡ€ΠΎΠ²Π΅Π½ΡŒ информированности ΠΏΠΎ основным вопросам эпидСмиологии ΠΈ ΠΏΡ€ΠΎΡ„ΠΈΠ»Π°ΠΊΡ‚ΠΈΠΊΠΈ ΠΈΠ½Ρ„Π΅ΠΊΡ†ΠΈΠΈ вирусом ΠΈΠΌΠΌΡƒΠ½ΠΎΠ΄Π΅Ρ„ΠΈΡ†ΠΈΡ‚Π° Ρ‡Π΅Π»ΠΎΠ²Π΅ΠΊΠ°. Однако наибольшСС количСство Π½Π΅ΠΏΡ€Π°Π²ΠΈΠ»ΡŒΠ½Ρ‹Ρ… ΠΎΡ‚Π²Π΅Ρ‚ΠΎΠ² ΠΏΠΎΠ»ΡƒΡ‡Π΅Π½ΠΎ Π² возрастной Π³Ρ€ΡƒΠΏΠΏΠ΅ 30–49 Π»Π΅Ρ‚ (18,7% ΠΎΡ‚ числа всСх ΠΎΠΏΡ€ΠΎΡˆΠ΅Π½Π½Ρ‹Ρ… Π΄Π°Π½Π½ΠΎΠ³ΠΎ возраста), ΠΏΡ€Π΅ΠΎΠ±Π»Π°Π΄Π°ΡŽΡ‰Π΅ΠΉ срСди возрастных Π³Ρ€ΡƒΠΏΠΏ с Π²ΠΏΠ΅Ρ€Π²Ρ‹Π΅ выявлСнной ΠΈΠ½Ρ„Π΅ΠΊΡ†ΠΈΠ΅ΠΉ вирусом ΠΈΠΌΠΌΡƒΠ½ΠΎΠ΄Π΅Ρ„ΠΈΡ†ΠΈΡ‚Π° Ρ‡Π΅Π»ΠΎΠ²Π΅ΠΊΠ° Π½Π° Ρ‚Π΅Ρ€Ρ€ΠΈΡ‚ΠΎΡ€ΠΈΠΈ ΠŸΡ€ΠΈΠΌΠΎΡ€ΡΠΊΠΎΠ³ΠΎ края Π² послСдниС Π³ΠΎΠ΄Ρ‹. Π­Ρ‚ΠΎΡ‚ Ρ„Π°ΠΊΡ‚ΠΎΡ€ Π½Π΅ΠΎΠ±Ρ…ΠΎΠ΄ΠΈΠΌΠΎ ΡƒΡ‡ΠΈΡ‚Ρ‹Π²Π°Ρ‚ΡŒ ΠΏΡ€ΠΈ построСнии адрСсных профилактичСских ΠΈ ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… мСроприятий Π½Π° популяционном ΡƒΡ€ΠΎΠ²Π½Π΅. Π’Ρ‹ΡΠ²Π»ΡΠ΅ΠΌΠΎΡΡ‚ΡŒ ΠΈΠ½Ρ„Π΅ΠΊΡ†ΠΈΠΈ вирусом ΠΈΠΌΠΌΡƒΠ½ΠΎΠ΄Π΅Ρ„ΠΈΡ†ΠΈΡ‚Π° Ρ‡Π΅Π»ΠΎΠ²Π΅ΠΊΠ° ΠΏΡ€ΠΈ обслСдовании Π»ΠΈΡ†, Π½Π΅ ΠΏΠΎΠ΄Π»Π΅ΠΆΠ°Ρ‰ΠΈΡ… ΠΎΠ±ΡΠ·Π°Ρ‚Π΅Π»ΡŒΠ½ΠΎΠΌΡƒ мСдицинскому ΠΎΡΠ²ΠΈΠ΄Π΅Ρ‚Π΅Π»ΡŒΡΡ‚Π²ΠΎΠ²Π°Π½ΠΈΡŽ, составила 0,08%. 29% участников исслСдования ΡΡ‡ΠΈΡ‚Π°ΡŽΡ‚ Π½Π΅ΠΎΠ±Ρ…ΠΎΠ΄ΠΈΠΌΡ‹ΠΌ ΡƒΠ²Π΅Π»ΠΈΡ‡Π΅Π½ΠΈΠ΅ доступности ΠΏΡ€Π΅Π²Π΅Π½Ρ‚ΠΈΠ²Π½ΠΎΠ³ΠΎ скринингового обслСдования Π½Π° вирус ΠΈΠΌΠΌΡƒΠ½ΠΎΠ΄Π΅Ρ„ΠΈΡ†ΠΈΡ‚Π° Ρ‡Π΅Π»ΠΎΠ²Π΅ΠΊΠ°.</p

    ΠžΠ‘ΠžΠ‘Π•ΠΠΠžΠ‘Π’Π˜ Π ΠΠ—Π’Π˜Π’Π˜Π― Π­ΠŸΠ˜Π”Π•ΠœΠ˜Π§Π•Π‘ΠšΠžΠ“Πž ΠŸΠ ΠžΠ¦Π•Π‘Π‘Π Π’Π˜Π§-Π˜ΠΠ€Π•ΠšΠ¦Π˜Π˜ Π’ ПРИМОРБКОМ ΠšΠ ΠΠ•

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    The official statistical data of HIV Registry filed 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 define the region-specific features of the development of HIV epidemic in 2011–2016. 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 defined. 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.Π˜Π·ΡƒΡ‡Π΅Π½Π° Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠ° распространСния Π’Π˜Π§-ΠΈΠ½Ρ„Π΅ΠΊΡ†ΠΈΠΈ Π½Π° Ρ‚Π΅Ρ€Ρ€ΠΈΡ‚ΠΎΡ€ΠΈΠΈ ΠŸΡ€ΠΈΠΌΠΎΡ€ΡΠΊΠΎΠ³ΠΎ края Π·Π° вСсь ΠΏΠ΅Ρ€ΠΈΠΎΠ΄ рСгистрации ΠΈΠ½Ρ„Π΅ΠΊΡ†ΠΈΠΈ для выявлСния особСнностСй становлСния эпидСмии Π½Π° ΠΊΠΎΠ½ΠΊΡ€Π΅Ρ‚Π½ΠΎΠΉ Ρ‚Π΅Ρ€Ρ€ΠΈΡ‚ΠΎΡ€ΠΈΠΈ ΠΈ опрСдСлСния Ρ‚Π΅Π½Π΄Π΅Π½Ρ†ΠΈΠΉ развития эпидСмичСского процСсса Π² 2011–2016 Π³ΠΎΠ΄Π°Ρ…. Π’ Ρ€Π°Π±ΠΎΡ‚Π΅ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΠΎΠ²Π°Π½Ρ‹ ΠΎΡ„ΠΈΡ†ΠΈΠ°Π»ΡŒΠ½Ρ‹Π΅ статистичСскиС Π΄Π°Π½Π½Ρ‹Π΅ рСгистрации Π’Π˜Π§-ΠΈΠ½Ρ„Π΅ΠΊΡ†ΠΈΠΈ Π“Π‘Π£Π— Β«ΠšΡ€Π°Π΅Π²Π°Ρ клиничСская Π±ΠΎΠ»ΡŒΠ½ΠΈΡ†Π° β„– 2 β€” Π¦Π΅Π½Ρ‚Ρ€ ΠΏΠΎ ΠΏΡ€ΠΎΡ„ΠΈΠ»Π°ΠΊΡ‚ΠΈΠΊΠ΅ ΠΈ Π±ΠΎΡ€ΡŒΠ±Π΅ со Π‘ΠŸΠ˜Π” ΠΈ ΠΈΠ½Ρ„Π΅ΠΊΡ†ΠΈΠΎΠ½Π½Ρ‹ΠΌΠΈ заболСваниями».Β  Π‘ 2011Β  Π³ΠΎΠ΄Π° Π² ΠŸΡ€ΠΈΠΌΠΎΡ€ΡΠΊΠΎΠΌ ΠΊΡ€Π°Π΅ рСгистрируСтся подъСм заболСваСмости  Π’Π˜Π§-ΠΈΠ½Ρ„Π΅ΠΊΡ†ΠΈΠ΅ΠΉ. НСсмотря Π½Π° повсСмСстноС ΡƒΠ²Π΅Π»ΠΈΡ‡Π΅Π½ΠΈΠ΅ значимости ΠΏΠΎΠ»ΠΎΠ²ΠΎΠ³ΠΎ ΠΏΡƒΡ‚ΠΈ зараТСния Π’Π˜Π§, Π² ΠŸΡ€ΠΈΠΌΠΎΡ€ΡŒΠ΅ основным Ρ„Π°ΠΊΡ‚ΠΎΡ€ΠΎΠΌ риска остаСтся Π²Π½ΡƒΡ‚Ρ€ΠΈΠ²Π΅Π½Π½ΠΎΠ΅ Π²Π²Π΅Π΄Π΅Π½ΠΈΠ΅ Π½Π°Ρ€ΠΊΠΎΡ‚ΠΈΠΊΠΎΠ². ВыявлСна тСндСнция измСнСния Π³Π΅Π½Π΄Π΅Ρ€Π½ΠΎΠ³ΠΎ ΠΈ возрастного состава Π»ΠΈΡ†, ΠΆΠΈΠ²ΡƒΡ‰ΠΈΡ… с Π’Π˜Π§. Наибольший ΡƒΡ€ΠΎΠ²Π΅Π½ΡŒ пораТСнности Π’Π˜Π§-ΠΈΠ½Ρ„Π΅ΠΊΡ†ΠΈΠ΅ΠΉΒ  рСгистрируСтся срСди ΠΌΡƒΠΆΡ‡ΠΈΠ½ Π² возрастС 25–49Β  Π»Π΅Ρ‚ (1113,4 Π½Π° 100 тысяч муТского насСлСния), ΠΏΠΎΡ‡Ρ‚ΠΈ Π² Ρ‚Ρ€ΠΈ Ρ€Π°Π·Π° ΠΏΡ€Π΅Π²Ρ‹ΡˆΠ°Ρ ΠΊΡ€Π°Π΅Π²Ρ‹Π΅ ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»ΠΈ ΠΎΠΊΡ€ΡƒΠ³Π° (Π”Π€Πž).</p
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