73 research outputs found
Parental labor in the Republic of Tuva in the context of the regional cluster structure of Russia's demographic space (1990-2019)
Despite the overall positive dynamics of demographic processes related to the natural reproduction of the population in the Republic of Tuva, the region currently experiences a fairly negative state of several spheres of human capital functioning and development. This may indicate a problematic state of the sphere of parental labor in the region. The article presents the results of identifying the place of the Republic of Tuva in the cluster structures of Russian regions. These structures were formed by the parameters of parental labor during the period from 1990 to 2019. The authors assess the place of the Republic of Tuva in the cluster space of Russian regions according to indicators that demonstrate the conditions, organization and results of parental labor. The research is based on an interdisciplinary concept of parental labor, which implies the labor character of parenthood and its compliance with all the features of work activity. The sources of the study are the data of the Federal State Statistics Service and the data of federal statistical observations on socio-demographic issues. Two key features of the position of the Republic of Tuva in the regional cluster structure have been identified. The first one is that Tuva either does not fit into the structure of the formed regional cluster space and is not included in any of the identified clusters, or it is geometrically located at a very far distance from the center of the cluster to which it is assigned. The second feature is that the profile of Tuva as part of the entire cluster is in most cases characterized by polarity and extreme ambiguity. Β© 2023 New Reaearch of Tuva. All rights reserved.SSβ1327.2022.2The research was conducted as part of the project βRussian Pro-Natalist Policy Support Institutions: Potential and Prospects for Influencing Birth Rate Growthβ supported by the Council for Grants of the President of the Russian Federation for State Support to Leading Scientific Schools of the Russian Federation (SSβ1327.2022.2)
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The global distribution of Bacillus anthracis and associated anthrax risk to humans, livestock and wildlife.
Bacillus anthracis is a spore-forming, Gram-positive bacterium responsible for anthrax, an acute infection that most significantly affects grazing livestock and wild ungulates, but also poses a threat to human health. The geographic extent of B. anthracis is poorly understood, despite multi-decade research on anthrax epizootic and epidemic dynamics; many countries have limited or inadequate surveillance systems, even within known endemic regions. Here, we compile a global occurrence dataset of human, livestock and wildlife anthrax outbreaks. With these records, we use boosted regression trees to produce a map of the global distribution of B. anthracis as a proxy for anthrax risk. We estimate that 1.83 billion people (95% credible interval (CI): 0.59-4.16 billion) live within regions of anthrax risk, but most of that population faces little occupational exposure. More informatively, a global total of 63.8 million poor livestock keepers (95% CI: 17.5-168.6 million) and 1.1 billion livestock (95% CI: 0.4-2.3 billion) live within vulnerable regions. Human and livestock vulnerability are both concentrated in rural rainfed systems throughout arid and temperate land across Eurasia, Africa and North America. We conclude by mapping where anthrax risk could disrupt sensitive conservation efforts for wild ungulates that coincide with anthrax-prone landscapes
Antileishmanial effect of silver nanoparticles and their enhanced antiparasitic activity under ultraviolet light
Leishmaniasis is a protozoan vector-borne disease and is one of the biggest health problems of the world. Antileishmanial drugs have disadvantages such as toxicity and the recent development of resistance. One of the best-known mechanisms of the antibacterial effects of silver nanoparticles (Ag-NPs) is the production of reactive oxygen species to which Leishmania parasites are very sensitive. So far no information about the effects of Ag-NPs on Leishmania tropica parasites, the causative agent of leishmaniasis, exists in the literature. The aim of this study was to investigate the effects of Ag-NPs on biological parameters of L. tropica such as morphology, metabolic activity, proliferation, infectivity, and survival in host cells, in vitro. Consequently, parasite morphology and infectivity were impaired in comparison with the control. Also, enhanced effects of Ag-NPs were demonstrated on the morphology and infectivity of parasites under ultraviolet (UV) light. Ag-NPs demonstrated significant antileishmanial effects by inhibiting the proliferation and metabolic activity of promastigotes by 1.5- to threefold, respectively, in the dark, and 2- to 6.5-fold, respectively, under UV light. Of note, Ag-NPs inhibited the survival of amastigotes in host cells, and this effect was more significant in the presence of UV light. Thus, for the first time the antileishmanial effects of Ag-NPs on L. tropica parasites were demonstrated along with the enhanced antimicrobial activity of Ag-NPs under UV light. Determination of the antileishmanial effects of Ag-NPs is very important for the further development of new compounds containing nanoparticles in leishmaniasis treatment
Comparative Analysis of Quality Requirements for Medicines Based on Horse-Chestnut Seeds
Scientific relevance. When harmonising conditions for qualitative and quantitative analysis of bioactive compounds in herbal medicines, the Institute of Pharmacopoeia and Medicinal Product Standardisation has discovered that horse-chestnut products lack national quality standards.Aim. This study aimed to review international quality standards in order to identify the most promising testing methods for the main groups of bioactive compounds in horse-chestnut seeds and draw upon these methods when drafting national pharmacopoeial monographs for horse-chestnut seed products.Discussion. The authors compared the requirements established by leading world pharmacopoeias for the identification and assay of herbal drugs and herbal drug preparations derived from horse-chestnut seeds.Conclusions. The study results show that, predominantly, identification tests are based on thin-layer chromatography, assays rely on spectrophotometry, and aescin is used as a pharmacopoeial reference standard. The authors drafted a pharmacopoeial monograph for the medicinal product Horse-Chestnut Seed Dry Extract + Thiamine Hydrochloride, Oral Solution, which requires using thin-layer chromatography and spectrophotometry for qualitative and quantitative testing
Models of grandparents' labour in the socio-economic space of Russia
ΠΠ·ΡΡΠ΅Π½ΠΈΠ΅ ΡΠ΅Π½ΠΎΠΌΠ΅Π½Π° ΠΏΡΠ°ΡΠΎΠ΄ΠΈΡΠ΅Π»ΡΡΠΊΠΎΠ³ΠΎ ΡΡΡΠ΄Π° ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΎΠ΄Π½ΠΎΠΉ ΠΈΠ· ΠΏΠ΅ΡΡΠΏΠ΅ΠΊΡΠΈΠ² ΡΠ°Π·Π²ΠΈΡΠΈΡ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΈ ΡΠΎΠ΄ΠΈΡΠ΅Π»ΡΡΠΊΠΎΠ³ΠΎ ΡΡΡΠ΄Π° - Π½Π°ΡΡΠ½ΠΎΠ³ΠΎ Π½Π°ΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ, Π°ΠΊΡΠΈΠ²Π½ΠΎ ΡΠ°Π·Π²ΠΈΠ²Π°Π΅ΠΌΠΎΠ³ΠΎ Π·Π°ΡΡΠ±Π΅ΠΆΠ½ΡΠΌΠΈ, Π° Ρ Π½Π°ΡΠ°Π»Π° 2000-Ρ
Π³Π³. - ΠΈ ΡΠΎΡΡΠΈΠΉΡΠΊΠΈΠΌΠΈ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°ΡΠ΅Π»ΡΠΌΠΈ. ΠΡΡΠΎΠΊΠΈΠΉ ΡΡΠΎΠ²Π΅Π½Ρ ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎ-ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ Π΄ΠΈΡΡΠ΅ΡΠ΅Π½ΡΠΈΠ°ΡΠΈΠΈ ΡΠΎΡΡΠΈΠΉΡΠΊΠΈΡ
ΡΠ΅ΡΡΠΈΡΠΎΡΠΈΠΉ, Π° ΡΠ°ΠΊΠΆΠ΅ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎΡΡΡ ΡΠ΅ΡΠ΅Π½ΠΈΡ Π²Π°ΠΆΠ½ΡΡ
ΡΡΡΠ°ΡΠ΅Π³ΠΈΡΠ΅ΡΠΊΠΈΡ
Π·Π°Π΄Π°Ρ, ΡΡΠΎΡΠΌΡΠ»ΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
Π² Π½Π°ΡΠΈΠΎΠ½Π°Π»ΡΠ½ΠΎΠΌ ΠΏΡΠΎΠ΅ΠΊΡΠ΅ Β«ΠΠ΅ΠΌΠΎΠ³ΡΠ°ΡΠΈΡΒ» ΠΈ Π‘ΡΡΠ°ΡΠ΅Π³ΠΈΠΈ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ ΡΠ°Π·Π²ΠΈΡΠΈΡ Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ Π½Π° ΠΏΠ΅ΡΠΈΠΎΠ΄ Π΄ΠΎ 2025 Π³ΠΎΠ΄Π°, Π°ΠΊΡΡΠ°Π»ΠΈΠ·ΠΈΡΡΡΡ ΠΈΠ·ΡΡΠ΅Π½ΠΈΠ΅ ΠΏΡΠ°ΡΠΎΠ΄ΠΈΡΠ΅Π»ΡΡΠΊΠΎΠ³ΠΎ ΡΡΡΠ΄Π°. Π¦Π΅Π»Ρ Π½Π°ΡΡΠΎΡΡΠ΅Π³ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠΎΡΡΠΎΠΈΡ Π² Π²ΡΡΠ²Π»Π΅Π½ΠΈΠΈ ΡΠΏΠ΅ΡΠΈΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ΅Π³ΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
ΡΠΈΡΡΠ°ΡΠΈΠΉ - ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ ΠΏΡΠ°ΡΠΎΠ΄ΠΈΡΠ΅Π»ΡΡΠΊΠΎΠ³ΠΎ ΡΡΡΠ΄Π° Π² ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎ-ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠΌ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅ ΡΡΡΠ°Π½Ρ. ΠΠΌΠΏΠΈΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΎΡΠ½ΠΎΠ²ΠΎΠΉ Π°Π½Π°Π»ΠΈΠ·Π° ΠΏΠΎΡΠ»ΡΠΆΠΈΠ»ΠΈ Π΄Π°Π½Π½ΡΠ΅ ΠΎΠ±ΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π ΠΎΡΡΡΠ°ΡΠ° Β«ΠΠΎΠΌΠΏΠ»Π΅ΠΊΡΠ½ΠΎΠ΅ Π½Π°Π±Π»ΡΠ΄Π΅Π½ΠΈΠ΅ ΡΡΠ»ΠΎΠ²ΠΈΠΉ ΠΆΠΈΠ·Π½ΠΈ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡΒ», ΠΎΡΠ΄Π΅Π»ΡΠ½ΡΠ΅ Π²ΠΎΠΏΡΠΎΡΡ ΠΊΠΎΡΠΎΡΠΎΠ³ΠΎ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡΡ Π² ΠΏΠ΅ΡΠ²ΠΎΠΌ ΠΏΡΠΈΠ±Π»ΠΈΠΆΠ΅Π½ΠΈΠΈ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°ΡΡ ΠΏΡΠ°ΡΠΎΠ΄ΠΈΡΠ΅Π»ΡΡΠΊΠΈΠΉ ΡΡΡΠ΄. Π ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅ ΠΎΡΠ½ΠΎΠ²Π½ΠΎΠ³ΠΎ ΠΌΠ΅ΡΠΎΠ΄Π° ΠΏΡΠΈΠΌΠ΅Π½ΡΠ»ΠΈΡΡ ΠΈΠ΅ΡΠ°ΡΡ
ΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΊΠ»Π°ΡΡΠ΅ΡΠ½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· (Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΌΠ΅ΡΠΎΠ΄Π° ΠΠ°ΡΠ΄Π°, ΠΊΠ²Π°Π΄ΡΠ°ΡΠ° Π΅Π²ΠΊΠ»ΠΈΠ΄ΠΎΠ²Π° ΡΠ°ΡΡΡΠΎΡΠ½ΠΈΡ ΠΈ Π΄ΡΡΠ³ΠΈΡ
ΠΌΠ΅Ρ) ΠΈ Π½Π΅ΠΈΠ΅ΡΠ°ΡΡ
ΠΈΡΠ΅ΡΠΊΠΈΠΉ ΠΊΠ»Π°ΡΡΠ΅ΡΠ½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· (ΠΌΠ΅ΡΠΎΠ΄ k-ΡΡΠ΅Π΄Π½ΠΈΡ
). Π ΠΏΡΠΎΡΠ΅ΡΡΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΏΠΎΠ»ΡΡΠ΅Π½Ρ ΡΠ΅ΠΎΡΠ΅ΡΠΈΠΊΠΎ-ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΈ ΠΏΡΠΈΠΊΠ»Π°Π΄Π½ΡΠ΅ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ. ΠΡΠ»Π° ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Π° ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠ°Ρ ΠΎΡΠ½ΠΎΠ²Π° ΠΈΠ·ΡΡΠ΅Π½ΠΈΡ ΠΏΡΠ°ΡΠΎΠ΄ΠΈΡΠ΅Π»ΡΡΠΊΠΎΠ³ΠΎ ΡΡΡΠ΄Π°, ΡΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½Π½Π°Ρ Π½Π° Π±Π°Π·Π΅ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ² ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ ΡΠΎΠ΄ΠΈΡΠ΅Π»ΡΡΠΊΠΎΠ³ΠΎ ΡΡΡΠ΄Π° ΠΈ Π·Π°ΡΡΠ±Π΅ΠΆΠ½ΡΡ
Π΄Π΅ΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ ΠΏΡΠ°ΡΠΎΠ΄ΠΈΡΠ΅Π»ΡΡΡΠ²Π°. ΠΠΌΠΏΠΈΡΠΈΡΠ΅ΡΠΊΠΈΠΉ Π°Π½Π°Π»ΠΈΠ· ΠΏΠΎΠ·Π²ΠΎΠ»ΠΈΠ» Π²ΡΡΠ²ΠΈΡΡ ΠΈ ΠΎΡ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΠΎΠ²Π°ΡΡ 6 ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ ΠΏΡΠ°ΡΠΎΠ΄ΠΈΡΠ΅Π»ΡΡΠΊΠΎΠ³ΠΎ ΡΡΡΠ΄Π° Π±Π°Π±ΡΡΠ΅ΠΊ, ΡΠ»ΠΎΠΆΠΈΠ²ΡΠΈΡ
ΡΡ Π² ΡΠΎΡΡΠΈΠΉΡΠΊΠΎΠΌ ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎ-ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠΌ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅. ΠΡΡΠ²Π»Π΅Π½Π½ΡΠ΅ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΡΠ°Π·Π»ΠΈΡΠ°ΡΡΡΡ ΠΏΠΎ ΡΡΠΎΠ²Π½Ρ ΠΈ ΠΈΠ½ΡΠ΅Π½ΡΠΈΠ²Π½ΠΎΡΡΠΈ Π²ΠΊΠ»ΡΡΠ΅Π½Π½ΠΎΡΡΠΈ ΠΆΠ΅Π½ΡΠΈΠ½ ΡΡΠ°ΡΡΠ΅Π³ΠΎ Π²ΠΎΠ·ΡΠ°ΡΡΠ° Π² ΡΡΠ΅ΡΡ ΠΏΡΠ°ΡΠΎΠ΄ΠΈΡΠ΅Π»ΡΡΠΊΠΎΠ³ΠΎ ΡΡΡΠ΄Π°, Π° ΡΠ°ΠΊΠΆΠ΅ ΠΈΡ
ΠΏΠΎΡΠ΅Π½ΡΠΈΠ°Π»Ρ Π² ΡΡΠΎΠΉ ΡΡΠ΅ΡΠ΅. ΠΡΠ» ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½ ΡΠ΅Π³ΠΈΠΎΠ½Π°Π»ΡΠ½ΡΠΉ ΡΠΎΡΡΠ°Π² ΠΊΠ°ΠΆΠ΄ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΏΡΠ°ΡΠΎΠ΄ΠΈΡΠ΅Π»ΡΡΠΊΠΎΠ³ΠΎ ΡΡΡΠ΄Π° - Π²ΡΠ΄Π΅Π»Π΅Π½Ρ ΡΠ΅Π³ΠΈΠΎΠ½Ρ-ΡΠ΄ΡΠ°, ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»ΡΡΡΠΈΠ΅ ΡΠΎΠ±ΠΎΠΉ Π³ΡΡΠΏΠΏΡ ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ², ΡΡΡΠΎΠΉΡΠΈΠ²ΠΎ ΡΠ²ΡΠ·Π°Π½Π½ΡΡ
Π² ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
Π²Π°ΡΠΈΠ°Π½ΡΠ°Ρ
ΠΊΠ»Π°ΡΡΠ΅ΡΠΈΠ·Π°ΡΠΈΠΈ. ΠΠΎΠΊΠ°Π·Π°Π½Ρ ΠΏΡΠ΅ΠΈΠΌΡΡΠ΅ΡΡΠ²Π° Π°ΠΊΡΠΈΠ²ΠΈΠ·Π°ΡΠΈΠΈ ΠΈ ΡΡΠΈΠΌΡΠ»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠΎ ΡΡΠΎΡΠΎΠ½Ρ Π³ΠΎΡΡΠ΄Π°ΡΡΡΠ²Π° ΠΏΡΠ°ΡΠΎΠ΄ΠΈΡΠ΅Π»ΡΡΠΊΠΎΠ³ΠΎ ΡΡΡΠ΄Π° Π² ΡΠ΅Π³ΠΈΠΎΠ½Π°Ρ
ΡΡΡΠ°Π½Ρ. ΠΠ΅ΡΡΠΏΠ΅ΠΊΡΠΈΠ²Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ - ΠΈΠ·ΡΡΠ΅Π½ΠΈΠ΅ ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠ΅ΠΉ ΠΏΡΠ°ΡΠΎΠ΄ΠΈΡΠ΅Π»ΡΡΠΊΠΎΠ³ΠΎ ΡΡΡΠ΄Π° Π΄Π»Ρ ΡΠ°Π·Π½ΡΡ
ΠΊΠ°ΡΠ΅Π³ΠΎΡΠΈΠΉ Π΅Π³ΠΎ ΡΡΠ±ΡΠ΅ΠΊΡΠΎΠ² - ΠΌΡΠΆΡΠΈΠ½, ΠΏΡΠ°ΡΠΎΠ΄ΠΈΡΠ΅Π»Π΅ΠΉ, ΠΏΡΠΎΠΆΠΈΠ²Π°ΡΡΠΈΡ
Π²ΠΌΠ΅ΡΡΠ΅ Ρ Π²Π½ΡΠΊΠ°ΠΌΠΈ ΠΈ ΠΎΡΠ΄Π΅Π»ΡΠ½ΠΎ ΠΎΡ Π½ΠΈΡ
, ΠΏΡΠΎΠΆΠΈΠ²Π°ΡΡΠΈΡ
Π² ΠΎΠ΄Π½ΠΎΠΌ Π³ΠΎΡΠΎΠ΄Π΅, ΡΠ΅Π³ΠΈΠΎΠ½Π΅ ΠΈΠ»ΠΈ ΡΠ°Π·Π½ΡΡ
ΡΠΎΡΡΠΈΠΉΡΠΊΠΈΡ
ΡΠ΅Π³ΠΈΠΎΠ½Π°Ρ
.Foreign researchers consider the phenomenon of grandparentsβ labour in the framework of the economy of parental labour. Since the early 2000s, Russian scientists have been actively studying this problem due to high socio-economic disparity of Russian regions, and important strategic objectives stated in the Demography National Project and the Strategy of Spatial Development of the Russian Federation for the period until 2025. We identified and described specific regional situations, namely, models of grandparentsβ labour in the socio-economic space of the country. To analyse grandparentsβ labour, we examined individual questions of the βComprehensive monitoring of living conditionsβ survey published by the Federal State Statistics Service (Rosstat). The research methodology includes both hierarchical (based on Wardβs method, the square of the Euclidean distance, and other measures) and non-hierarchical cluster analysis (the k-means method). We proposed a method for studying grandparentsβ labour based on research of parental labour and international demographic studies on grandparenthood. The empirical analysis revealed 6 models of grandparentsβ labour in the socio-economic space of Russia. These models differ in the level and intensity of involvement of older women in the sphere of grandparentsβ labour and their potential in this area. For each model of grandparentsβ labour, we identified the core regions (groups of regions) involved in the clustering. We explained why the government should be interested in the activation and stimulation of grandparentsβ labour in Russian regions. Further research should focus on examining the particularities of grandparentsβ labour depending on the actors: men, grandparents living with their grandchildren and apart from them, living in the same city, in the same or different regions of Russia.ΠΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ Π²ΡΠΏΠΎΠ»Π½Π΅Π½ΠΎ ΠΏΡΠΈ ΡΠΈΠ½Π°Π½ΡΠΎΠ²ΠΎΠΉ ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΠ΅ Π Π€Π€Π Π² ΡΠ°ΠΌΠΊΠ°Ρ
Π½Π°ΡΡΠ½ΠΎΠ³ΠΎ ΠΏΡΠΎΠ΅ΠΊΡΠ° β20β011β00280.The article has been prepared with the support of Russian Foundation for Basic Research, the project No. 20β011β00280
Manifestations and diagnosis of reactive arthritis
Objective: Studying of peculiarities of etiology and clinical process of Reactive Arthritis. Materials and Methodology: the research studied 56 patients where 18 were males and 38 were females (with average age range spanning from 35+10,2 years old). All examinees undergone physical, laboratory, x-ray, ultrasound, immunological, and microbiological check-up. The criteria for diagnosis of Reactive Arthritis were based on those accepted during the III International Meeting on Reactive Arthritis in Berlin in 1996. Results: The results of the study showed the prevailing of Urological Reactive Arthritis (87,5%) with the tendency towards the age increase (45-46 years old), towards Chlamydia aetiology (Ch. thrachomatis, Ch. pneumonia and Ch. Psitaki and their combination). Chlamidia were found in 20% of studied patients with Reactive Arthritis, whereas 50% of cases showed the combination of Micoplasma, Ureaplasma and Intestinal Infection. The trigger factors for Reactive Arthritis development of 57,1% of the studied patients were combined infection. In more frequently occurred cases the clinical picture was blurred. The study showed that Monoarthritis was encountered with more often than Polyarthritis. A quarter of the studied patients had 3-4 affected joints. The inflammation process involved legs joints, that is, those of ankle and knee. 98,2% of the patients with Reactive Arthritis had Enthesitis. 100% of the patients had the signs of Sinovitis which went along with Periarthritis in the form of Bursitis or Tendinitis. All of the patients had their ureal channel affected. All of the patients had the affection of eyes in anamnesis. No changes were found in 21,43% of the cases throughout the study. The affection of skin was seen as Keratoderma of soles, Onychodystrophy, Dermatitis, Pink Papulosis Rashes, and Nodular Erythema. The I-II degree of activity process was shown as prevalent. Conclusion: At Reactive Arthritis development was found to be mixed infection where Chlamydia prevailed. Monoarthritis with the affection of mainly lower extremities joints turned to appear with the frequency. In comparison with x-ray examination, Arthrosonography Method stays as more precise (p<0,001) and more informative in diagnosis of Arthritis. It is necessary to prescribe antibiotics during the treatment process as well as to use active anti-inflammation therapy.Π¦Π΅Π»Ρ. ΠΠ·ΡΡΠΈΡΡ ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠΈ ΡΡΠΈΠΎΠ»ΠΎΠ³ΠΈΠΈ ΠΈ ΠΊΠ»ΠΈΠ½ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠ΅ΡΠ΅Π½ΠΈΡ Π Π΅Π. ΠΠ°ΡΠ΅ΡΠΈΠ°Π» ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ. ΠΠ±ΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΎ 56 Π±ΠΎΠ»ΡΠ½ΡΡ
, ΠΈΠ· Π½ΠΈΡ
18 ΠΌΡΠΆΡΠΈΠ½ ΠΈ 38 ΠΆΠ΅Π½ΡΠΈΠ½ (ΡΡΠ΅Π΄Π½ΠΈΠΉ Π²ΠΎΠ·ΡΠ°ΡΡ 35+10,2 Π»Π΅Ρ). ΠΡΠ΅ΠΌ Π±ΡΠ»ΠΎ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΎ ΡΠΈΠ·ΠΈΠΊΠ°Π»ΡΠ½ΠΎΠ΅, Π»Π°Π±ΠΎΡΠ°ΡΠΎΡΠ½ΠΎΠ΅, ΡΠ΅Π½ΡΠ³Π΅Π½ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ΅ ΠΈ ΡΠ»ΡΡΡΠ°Π·Π²ΡΠΊΠΎΠ²ΠΎΠ΅, ΠΈΠΌΠΌΡΠ½ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ΅ ΠΈ ΠΌΠΈΠΊΡΠΎΠ±ΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ΅ ΠΎΠ±ΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅. ΠΠΈΠ°Π³Π½ΠΎΠ· Π Π΅Π ΡΡΠ°Π²ΠΈΠ»ΡΡ Π½Π° ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΠΈ ΠΊΡΠΈΡΠ΅ΡΠΈΠ΅Π², ΠΏΡΠΈΠ½ΡΡΡΡ
Π½Π° III ΠΠ΅ΠΆΠ΄ΡΠ½Π°ΡΠΎΠ΄Π½ΠΎΠΌ ΡΠΎΠ²Π΅ΡΠ°Π½ΠΈΠΈ ΠΏΠΎ Π Π΅Π Π² ΠΠ΅ΡΠ»ΠΈΠ½Π΅ Π² 1996 Π³. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. ΠΡΠ΅ΠΎΠ±Π»Π°Π΄Π°Π» ΡΡΠΎΠ³Π΅Π½Π½ΡΠΉ Π Π΅Π (87,5%) Ρ ΡΠ΅Π½Π΄Π΅Π½ΡΠΈΠ΅ΠΉ ΠΊ ΡΠ²Π΅Π»ΠΈΡΠ΅Π½ΠΈΡ Π²ΠΎΠ·ΡΠ°ΡΡΠ° Π±ΠΎΠ»ΡΠ½ΡΡ
(45-46 Π»Π΅Ρ), Ρ
Π»Π°ΠΌΠΈΠ΄ΠΈΠΉΠ½ΠΎΠΉ ΡΡΠΈΠΎΠ»ΠΎΠ³ΠΈΠΈ (Chlamidia thrachomatis, Chlamidia pneumonia ΠΈ Chlamidia psitaki ΠΈ ΠΈΡ
ΡΠΎΡΠ΅ΡΠ°Π½ΠΈΠ΅). Π₯Π»Π°ΠΌΠΈΠ΄ΠΈΠΈ Π±ΡΠ»ΠΈ Ρ 70% Π±ΠΎΠ»ΡΠ½ΡΡ
Π Π΅Π, Π° Π² 50% ΡΠΎΡΠ΅ΡΠ°Π»ΠΈΡΡ Ρ ΠΌΠΈΠΊΠΎΠΏΠ»Π°Π·ΠΌΠ΅Π½Π½ΠΎΠΉ, ΡΡΠ΅Π°ΠΏΠ»Π°Π·ΠΌΠ΅Π½Π½ΠΎΠΉ ΠΈ ΠΊΠΈΡΠ΅ΡΠ½ΠΎΠΉ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΡΠΌΠΈ. Π£ 57,1 % Π±ΠΎΠ»ΡΠ½ΡΡ
ΡΡΠΈΠ³Π³Π΅ΡΠ½ΡΠΌ ΡΠ°ΠΊΡΠΎΡΠΎΠΌ ΡΠ°Π·Π²ΠΈΡΠΈΡ Π Π΅Π ΡΠ²ΠΈΠ»Π°ΡΡ ΡΠΌΠ΅ΡΠ°Π½Π½Π°Ρ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΡ. ΠΡΠ΅ΠΎΠ±Π»Π°Π΄Π°Π»Π° ΡΡΠ΅ΡΡΠ°Ρ ΠΊΠ»ΠΈΠ½ΠΈΡΠ΅ΡΠΊΠ°Ρ ΠΊΠ°ΡΡΠΈΠ½Π°. ΠΠΎΠ½ΠΎΠ°ΡΡΡΠΈΡ Π²ΡΡΡΠ΅ΡΠ°Π»ΡΡ ΡΠ°ΡΠ΅, ΡΠ΅ΠΌ ΠΏΠΎΠ»ΠΈΠ°ΡΡΡΠΈΡ. Π£ ΡΠ΅ΡΠ²Π΅ΡΡΠΈ Π±ΠΎΠ»ΡΠ½ΡΡ
ΠΏΠΎΡΠ°ΠΆΠ°Π»ΠΈΡΡ 3-4 ΡΡΡΡΠ°Π²Π°. Π Π²ΠΎΡΠΏΠ°Π»ΠΈΡΠ΅Π»ΡΠ½ΡΠΉ ΠΏΡΠΎΡΠ΅ΡΡ ΠΏΡΠ΅ΠΈΠΌΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎ Π²ΠΎΠ²Π»Π΅ΠΊΠ°Π»ΠΈΡΡ ΡΡΡΡΠ°Π²Ρ Π½ΠΎΠ³: Π³ΠΎΠ»Π΅Π½ΠΎΡΡΠΎΠΏΠ½ΡΠΉ ΠΈ ΠΊΠΎΠ»Π΅Π½Π½ΡΠΉ. Π£ 98,2% Π±ΠΎΠ»ΡΠ½ΡΡ
Π Π΅Π ΠΈΠΌΠ΅Π»ΡΡ ΡΠ½ΡΠ΅Π·ΠΈΡ, Ρ 100% Π±ΠΎΠ»ΡΠ½ΡΡ
- ΡΠΈΠ½ΠΎΠ²ΠΈΡΠ°, ΠΊΠΎΡΠΎΡΡΠΉ ΡΠΎΡΠ΅ΡΠ°Π»ΡΡ Ρ ΠΏΠ΅ΡΠΈΠ°ΡΡΡΠΈΡΠΎΠΌ Π² Π²ΠΈΠ΄Π΅ Π±ΡΡΡΠΈΡΠ° ΠΈΠ»ΠΈ ΡΠ΅Π½Π΄ΠΈΠ½ΠΈΡΠ°. Π£ Π²ΡΠ΅Ρ
Π±ΠΎΠ»ΡΠ½ΡΡ
ΠΎΡΠΌΠ΅ΡΠ°Π»ΠΎΡΡ ΠΏΠΎΡΠ°ΠΆΠ΅Π½ΠΈΠ΅ ΡΡΠΎΠ³Π΅Π½ΠΈΡΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΡΠ°ΠΊΡΠ°. ΠΠΎΡΠ°ΠΆΠ΅Π½ΠΈΠ΅ Π³Π»Π°Π· Π² Π°Π½Π°ΠΌΠ½Π΅Π·Π΅ ΠΈΠΌΠ΅Π»ΠΈ Π²ΡΠ΅ ΠΏΠ°ΡΠΈΠ΅Π½ΡΡ, Π½ΠΎ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡ Π½Π° ΠΌΠΎΠΌΠ΅Π½Ρ ΠΎΠ±ΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΎΡΡΡΡΡΡΠ²ΠΎΠ²Π°Π»ΠΈ Ρ 21,43%. ΠΠΎΡΠ°ΠΆΠ΅Π½ΠΈΡ ΠΊΠΎΠΆΠΈ Π±ΡΠ»ΠΈ Π² Π²ΠΈΠ΄Π΅ ΠΊΠ΅ΡΠ°ΡΠΎΠ΄Π΅ΡΠΌΠΈΠΈ ΠΏΠΎΠ΄ΠΎΡΠ², ΠΎΠ½ΠΈΡ
ΠΎΠ΄ΠΈΡΡΡΠΎΡΠΈΠΈ, Π΄Π΅ΡΠΌΠ°ΡΠΈΡΠ°, ΡΠΎΠ·ΠΎΠ²ΠΎΠΉ ΠΏΠ°ΠΏΡΠ»Π΅Π·Π½ΠΎΠΉ ΡΡΠΏΠΈ, ΡΠ·Π»ΠΎΠ²Π°ΡΠΎΠΉ ΡΡΠΈΡΠ΅ΠΌΡ. ΠΡΠ΅ΠΎΠ±Π»Π°Π΄Π°Π»Π° I-II ΡΡΠ΅ΠΏΠ΅Π½Ρ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ ΠΏΡΠΎΡΠ΅ΡΡΠ°. ΠΡΠ²ΠΎΠ΄Ρ. ΠΡΠΈ Π Π΅Π ΡΠ°ΡΠ΅ Π²ΡΡΠ²Π»ΡΠ»Π°ΡΡ ΡΠΌΠ΅ΡΠ°Π½Π½Π°Ρ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΡ, ΡΡΠ΅Π΄ΠΈ ΠΊΠΎΡΠΎΡΠΎΠΉ ΠΏΡΠ΅ΠΎΠ±Π»Π°Π΄Π°Π»ΠΈ Ρ
Π»Π°ΠΌΠΈΠ΄ΠΈΠΈ. Π§Π°ΡΠ΅ ΠΈΠΌΠ΅Π»ΡΡ ΠΌΠΎΠ½ΠΎΠ°ΡΡΡΠΈΡ Ρ ΠΏΡΠ΅ΠΈΠΌΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠΌ ΠΏΠΎΡΠ°ΠΆΠ΅Π½ΠΈΠ΅ΠΌ ΡΡΡΡΠ°Π²ΠΎΠ² Π½ΠΈΠΆΠ½ΠΈΡ
ΠΊΠΎΠ½Π΅ΡΠ½ΠΎΡΡΠ΅ΠΉ. Π Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠ΅ Π°ΡΡΡΠΈΡΠ° ΠΌΠ΅ΡΠΎΠ΄ Π°ΡΡΡΠΎΡΠΎΠ½ΠΎΠ³ΡΠ°ΡΠΈΠΈ ΡΠ²Π»ΡΠ΅ΡΡΡ Π΄ΠΎΡΡΠΎΠ²Π΅ΡΠ½ΠΎ (Ρ<0,001) Π±ΠΎΠ»Π΅Π΅ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠ²Π½ΡΠΌ ΠΏΠΎ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ Ρ ΡΠ΅Π½ΡΠ³Π΅Π½ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ. Π Π»Π΅ΡΠ΅Π½ΠΈΠΈ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎ Π½Π°Π·Π½Π°ΡΠ΅Π½ΠΈΠ΅ Π°Π½ΡΠΈΠ±ΠΈΠΎΡΠΈΠΊΠΎΠ², Π° ΡΠ°ΠΊΠΆΠ΅ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΠ΅ Π°ΠΊΡΠΈΠ²Π½ΠΎΠΉ ΠΏΡΠΎΡΠΈΠ²ΠΎΠ²ΠΎΡΠΏΠ°Π»ΠΈΡΠ΅Π»ΡΠ½ΠΎΠΉ ΡΠ΅ΡΠ°ΠΏΠΈΠΈ
Corporate Family-Friendly Policies: The Possibility of Implementation in Russian Regions
Π ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΡ Π³ΠΎΡΡΠ΄Π°ΡΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΠΏΡΠΎΠ½Π°ΡΠ°Π»ΠΈΡΡΡΠΊΠΎΠΉ ΠΏΠΎΠ»ΠΈΡΠΈΠΊΠΈ ΠΌΠΎΠΆΠ΅Ρ Π²ΠΊΠ»ΡΡΠΈΡΡΡΡ ΡΠ΅Π»ΡΠΉ ΡΡΠ΄ ΡΠΎΡΠΈΠ°Π»ΡΠ½ΡΡ
ΠΈΠ½ΡΡΠΈΡΡΡΠΎΠ². ΠΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΡΠ΅Π΄ΠΏΡΠΈΡΡΠΈΡΠΌΠΈ ΠΊΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½ΠΎΠΉ ΠΏΠΎΠ»ΠΈΡΠΈΠΊΠΈ, ΠΎΡΠΈΠ΅Π½ΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ Π½Π° ΡΠ΅ΠΌΡΠΈ ΡΠ°Π±ΠΎΡΠ½ΠΈΠΊΠΎΠ², ΠΏΡΠΈ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½Π½ΠΎΡΡΠΈ Π² ΡΠ΅Π»ΠΎΠΌ ΡΡΠ΄Π΅ Π΄ΡΡΠ³ΠΈΡ
ΡΡΡΠ°Π½ Π² Π ΠΎΡΡΠΈΠΈ Π²ΡΡΡΠ΅ΡΠ°Π΅ΡΡΡ Π΄ΠΎΡΡΠ°ΡΠΎΡΠ½ΠΎ ΡΠ΅Π΄ΠΊΠΎ. ΠΡΠΈ ΡΡΠΎΠΌ Π² Π ΠΎΡΡΠΈΠΈ Π½Π°Π±Π»ΡΠ΄Π°Π΅ΡΡΡ Π²ΡΡΠΎΠΊΠΈΠΉ ΡΡΠΎΠ²Π΅Π½Ρ Π΄ΠΈΡΡΠ΅ΡΠ΅Π½ΡΠΈΠ°ΡΠΈΠΈ ΡΠΎΡΡΠΈΠΉΡΠΊΠΈΡ
ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ² ΠΏΠΎ ΠΌΠ½ΠΎΠ³ΠΈΠΌ ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎ-ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΡΠΌ. Π¦Π΅Π»Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠΎΡΡΠΎΠΈΡ Π² ΡΠΎΠΌ, ΡΡΠΎΠ±Ρ, Π²ΠΎ-ΠΏΠ΅ΡΠ²ΡΡ
, Π²ΡΡΠ²ΠΈΡΡ ΡΠ΅Π³ΠΈΠΎΠ½Π°Π»ΡΠ½ΡΠ΅ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΡΠΎΡΡΠΈΠΉΡΠΊΠΎΠ³ΠΎ ΠΊΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½ΠΎΠ³ΠΎ ΡΠ΅ΠΊΡΠΎΡΠ° ΠΈ, Π²ΠΎ-Π²ΡΠΎΡΡΡ
, ΠΎΠΏΡΠ΅Π΄Π΅Π»ΠΈΡΡ ΡΠ΅ ΠΈΠ· Π½ΠΈΡ
, ΠΊΠΎΡΠΎΡΡΠ΅ ΠΎΠ±Π»Π°Π΄Π°ΡΡ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ Π²ΡΡΠΎΠΊΠΈΠΌ ΠΏΠΎΡΠ΅Π½ΡΠΈΠ°Π»ΠΎΠΌ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½ΠΈΡ ΠΊΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½ΠΎΠΉ ΠΏΠΎΠ»ΠΈΡΠΈΠΊΠΈ, ΠΎΡΠΈΠ΅Π½ΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ Π½Π° ΡΠ΅ΠΌΡΠΈ ΡΠ°Π±ΠΎΡΠ½ΠΈΠΊΠΎΠ² ΠΈ Π½Π°ΠΏΡΠ°Π²Π»Π΅Π½Π½ΠΎΠΉ Π½Π° ΡΠΎΡΡ ΡΠΎΠΆΠ΄Π°Π΅ΠΌΠΎΡΡΠΈ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ ΡΡΠΈΡ
ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ². ΠΠΈΠΏΠΎΡΠ΅Π·Π° ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠΎΡΡΠΎΠΈΡ Π² Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠΈ Π²ΡΡΠ²Π»Π΅Π½ΠΈΡ ΡΠ°ΠΊΠΈΡ
ΡΠΎΡΡΠΈΠΉΡΠΊΠΈΡ
ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ² Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΌΠ½ΠΎΠ³ΠΎΠΌΠ΅ΡΠ½ΠΎΠΉ ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎ-ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ. ΠΠ»Ρ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠΎΡΡΠΈΠΉΡΠΊΠΎΠ³ΠΎ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π° ΠΏΡΠΈΠΌΠ΅Π½ΡΠ»ΡΡ ΠΈΠ΅ΡΠ°ΡΡ
ΠΈΡΠ΅ΡΠΊΠΈΠΉ ΠΊΠ»Π°ΡΡΠ΅ΡΠ½ΡΠΉ Π°Π½Π°Π»ΠΈΠ·, Π·Π°ΡΠ΅ΠΌ ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΎΡΡ ΠΏΡΠΎΡΠΈΠ»ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΠΊΠ»Π°ΡΡΠ΅ΡΠΎΠ² ΠΏΠΎ Π΄ΠΎΠΏΠΎΠ»Π½ΠΈΡΠ΅Π»ΡΠ½ΡΠΌ ΠΏΠ΅ΡΠ΅ΠΌΠ΅Π½Π½ΡΠΌ. ΠΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π»ΠΈΡΡ Π΄Π°Π½Π½ΡΠ΅ ΠΎΡΠΈΡΠΈΠ°Π»ΡΠ½ΠΎΠΉ ΡΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ ΠΏΠΎ ΡΡΠ±ΡΠ΅ΠΊΡΠ°ΠΌ Π Π€, Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΡΡΡΠΈΠ΅ ΡΠ°Π·Π²ΠΈΡΠΈΠ΅ ΠΊΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½ΠΎΠ³ΠΎ ΡΠ΅ΠΊΡΠΎΡΠ°. ΠΡΠ΄Π΅Π»Π΅Π½Ρ ΠΏΡΡΡ ΠΊΠ»Π°ΡΡΠ΅ΡΠΎΠ² ΡΠΎΡΡΠΈΠΉΡΠΊΠΈΡ
ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ². ΠΠ±ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΎ, ΡΡΠΎ Π΄Π²Π° ΠΈΠ· Π½ΠΈΡ
ΠΌΠΎΠ³ΡΡ ΡΡΠ°ΡΡ ΠΏΠΈΠ»ΠΎΡΠ½ΡΠΌΠΈ Π΄Π»Ρ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½ΠΈΡ ΠΏΡΠ°ΠΊΡΠΈΠΊ ΠΏΠΎΠ»ΠΈΡΠΈΠΊΠΈ, ΠΎΡΠΈΠ΅Π½ΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ Π½Π° ΡΠ΅ΠΌΡΠΈ ΡΠ°Π±ΠΎΡΠ½ΠΈΠΊΠΎΠ², Π·Π°Π½ΡΡΡΡ
Π½Π° ΡΡΠΈΡ
ΠΏΡΠ΅Π΄ΠΏΡΠΈΡΡΠΈΡΡ
. Π Π΄Π°Π½Π½ΡΡ
ΠΊΠ»Π°ΡΡΠ΅ΡΠ°Ρ
Π½Π°Π±Π»ΡΠ΄Π°ΡΡΡΡ ΡΠΏΠ΅ΡΠΈΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ Π΄Π΅ΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ (ΠΎΡΠΎΠ±ΠΎ Π½ΠΈΠ·ΠΊΠΈΠ΅ ΡΠΎΠΆΠ΄Π°Π΅ΠΌΠΎΡΡΡ ΠΈ ΠΏΠΎΡΠ΅Π½ΡΠΈΠ°Π» Π΅Π΅ ΡΠΎΡΡΠ°) ΠΈ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΠ΅ (Π²ΡΡΠΎΠΊΠ°Ρ ΠΈΠ½Π½ΠΎΠ²Π°ΡΠΈΠΎΠ½Π½Π°Ρ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ ΠΈ Π½ΠΈΠ·ΠΊΠ°Ρ Π΄ΠΎΠ»Ρ ΡΠ±ΡΡΠΎΡΠ½ΡΡ
ΠΏΡΠ΅Π΄ΠΏΡΠΈΡΡΠΈΠΉ, ΡΠ°ΠΌΡΠ΅ Π²ΡΡΠΎΠΊΠΈΠ΅ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΠΈ Π΄Π΅ΠΌΠΎΠ³ΡΠ°ΡΠΈΠΈ ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΠΉ ΠΈ ΡΡΠ΅Π΄Π½ΠΈΠΉ ΡΡΠΎΠ²Π΅Π½Ρ ΠΊΠΎΠ½Π΅ΡΠ½ΠΎΠ³ΠΎ ΠΏΠΎΡΡΠ΅Π±Π»Π΅Π½ΠΈΡ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ) ΡΡΠ»ΠΎΠ²ΠΈΡ. Π‘Π΄Π΅Π»Π°Π½ Π²ΡΠ²ΠΎΠ΄, ΡΡΠΎ Π² ΠΊΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½ΠΎΠΌ ΡΠ΅ΠΊΡΠΎΡΠ΅ ΡΡΠΈΡ
ΡΠΎΡΡΠΈΠΉΡΠΊΠΈΡ
ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ² ΠΏΠΎΠ»ΠΈΡΠΈΠΊΠ°, ΠΎΡΠΈΠ΅Π½ΡΠΈΡΠΎΠ²Π°Π½Π½Π°Ρ Π½Π° ΡΠ΅ΠΌΡΠΈ ΡΠ°Π±ΠΎΡΠ½ΠΈΠΊΠΎΠ², ΠΌΠΎΠΆΠ΅Ρ ΡΡΠ°ΡΡ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ Π²ΠΎΡΡΡΠ΅Π±ΠΎΠ²Π°Π½Π½ΠΎΠΉ Π΄Π»Ρ ΠΏΠ΅ΡΡΠΎΠ½Π°Π»Π° ΠΎΡΠ³Π°Π½ΠΈΠ·Π°ΡΠΈΠΉ, Π²ΠΏΠΎΠ»Π½Π΅ Π΄ΠΎΡΡΡΠΏΠ½ΠΎΠΉ Π΄Π»Ρ ΠΏΡΠ΅Π΄ΠΏΡΠΈΡΡΠΈΠΉ ΠΈ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΠΉ Π² ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅ Π½ΠΎΠ²ΠΎΠ³ΠΎ ΠΈΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠ° Π΄Π΅ΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΏΠΎΠ»ΠΈΡΠΈΠΊΠΈ. ΠΠ°Π»ΡΠ½Π΅ΠΉΡΠΈΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΌΠΎΠ³ΡΡ Π±ΡΡΡ ΡΠ²ΡΠ·Π°Π½Ρ Ρ Π°Π½Π°Π»ΠΈΠ·ΠΎΠΌ ΠΊΠ΅ΠΉΡΠΎΠ² ΡΠΎΡΡΠΈΠΉΡΠΊΠΈΡ
ΠΏΡΠ΅Π΄ΠΏΡΠΈΡΡΠΈΠΉ, ΡΠ΅Π°Π»ΠΈΠ·ΡΡΡΠΈΡ
ΠΏΠΎΠ΄ΠΎΠ±Π½ΡΡ ΠΏΠΎΠ»ΠΈΡΠΈΠΊΡ, Π²ΡΡΠ²Π»Π΅Π½ΠΈΠ΅ΠΌ Π±Π΅Π½ΡΠΌΠ°ΡΠΊΠΎΠ², ΠΎΡΠ΅Π½ΠΊΠΎΠΉ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠ΅ΠΉ ΠΌΠ°ΡΡΡΠ°Π±ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠ°ΠΊΠΎΠ³ΠΎ ΠΎΠΏΡΡΠ° ΠΈ ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ Π΅Π³ΠΎ Π΄Π΅ΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ².Various social institutions may be involved in the implementation of the stateβs pro-natalist policy. Family-friendly corporate policies, common in many countries, are still quite rare in Russia. At the same time, many socio-economic indicators significantly differ across Russian regions. The study aims to identify regional development models of the Russian corporate sector and determine those models that have the highest potential for dissemination of family-friendly corporate policies aimed at increasing the birth rate of the population in these regions. It is hypothesised that such Russian regions can be identified based on a multidimensional classification of socio-economic indicators. The hierarchical cluster analysis was used to model the Russian economic space. Then, the clusters were further grouped according to additional variables. The article analysed official regional statistics characterising the development of the corporate sector. Five clusters of Russian regions were identified. It is proved that corporate family-friendly policies can be disseminated in two regions in particular. Specific demographic (in particular, low birth rate and growth potential) and economic (high innovative activity, small number of loss-making enterprises, the highest demographic indicators among organisations and the average level of priveate consumption) conditions are observed in these clusters. It is concluded that in the corporate sector of these Russian regions, family-friendly policy may gain popularity among staff. This approach, accessible to enterprises, can act as an effective tool of demographic policy. Further research should focus on the analysis of cases of Russian enterprises implementing family-friendly policies, identification of benchmarks, assessment of the possibilities of scaling such experience and forecasting its demographic results.Π Π°Π±ΠΎΡΠ° Π½Π°Π΄ ΡΡΠ°ΡΡΠ΅ΠΉ Π.Π. Π¨ΡΠ±Π°Ρ ΠΈ Π.Π. ΠΠ°Π³ΠΈΡΠΎΠ²ΠΎΠΉ Π² ΡΠ°ΡΡΠΈ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠΈ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ, ΠΊΠ»Π°ΡΡΠ΅ΡΠΈΠ·Π°ΡΠΈΠΈ ΡΠΎΡΡΠΈΠΉΡΠΊΠΈΡ
ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ² ΠΈ ΠΈΠ½ΡΠ΅ΡΠΏΡΠ΅ΡΠ°ΡΠΈΠΈ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ² ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠ°Π½Π° Π‘ΠΎΠ²Π΅ΡΠΎΠΌ ΠΏΠΎ Π³ΡΠ°Π½ΡΠ°ΠΌ ΠΡΠ΅Π·ΠΈΠ΄Π΅Π½ΡΠ° Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ Π½Π° Π³ΠΎΡΡΠ΄Π°ΡΡΡΠ²Π΅Π½Π½ΡΡ ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΡ Π²Π΅Π΄ΡΡΠΈΡ
Π½Π°ΡΡΠ½ΡΡ
ΡΠΊΠΎΠ» Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ (ΠΠ¨-1327.2022.2). Π’Π΅ΠΎΡΠ΅ΡΠΈΡΠ΅ΡΠΊΠΎΠ΅ ΠΎΠ±ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΡΠΎΠ±Π»Π΅ΠΌΡ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ, Π²ΡΠΏΠΎΠ»Π½Π΅Π½Π½ΠΎΠ΅ Π. Π―Π½Ρ, ΡΠ΅Π°Π»ΠΈΠ·ΠΎΠ²Π°Π½ΠΎ ΠΏΡΠΈ ΡΠΈΠ½Π°Π½ΡΠΎΠ²ΠΎΠΉ ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΠ΅ ΠΠΈΠ½ΠΈΡΡΠ΅ΡΡΡΠ²Π° Π½Π°ΡΠΊΠΈ ΠΈ Π²ΡΡΡΠ΅Π³ΠΎ ΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΡ Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ Π² ΡΠ°ΠΌΠΊΠ°Ρ
ΠΡΠΎΠ³ΡΠ°ΠΌΠΌΡ ΡΠ°Π·Π²ΠΈΡΠΈΡ Π£ΡΠ°Π»ΡΡΠΊΠΎΠ³ΠΎ ΡΠ΅Π΄Π΅ΡΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΠ½ΠΈΠ²Π΅ΡΡΠΈΡΠ΅ΡΠ° ΠΈΠΌΠ΅Π½ΠΈ ΠΏΠ΅ΡΠ²ΠΎΠ³ΠΎ ΠΡΠ΅Π·ΠΈΠ΄Π΅Π½ΡΠ° Π ΠΎΡΡΠΈΠΈ Π.Π. ΠΠ»ΡΡΠΈΠ½Π° Π² ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΠΈΠΈ Ρ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠΎΠΉ ΡΡΡΠ°ΡΠ΅Π³ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π°ΠΊΠ°Π΄Π΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π»ΠΈΠ΄Π΅ΡΡΡΠ²Π° Β«ΠΡΠΈΠΎΡΠΈΡΠ΅Ρ-2030Β».The work of Oksana Shubat and Anna Bagirova in terms of developing a research methodology, clustering Russian regions and interpreting the results was supported by the Council for Grants of the President of the Russian Federation for state support of leading scientific schools of the Russian Federation (NSh-1327.2022.2). Theoretical substantiation of the research by Yan Doudou was supported by the Ministry of Science and Higher Education of the Russian Federation within the framework of the development program of the Ural Federal University as part of the strategic academic leadership program Β«Priority 2030Β»
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