Medico-Geographical Assessment of the Prevalence of Respiratory Diseases in Northern and Southern Areas of the Russian Far East: Comparison of Kamchatka and Primorsky Regions

Тип публикацииJournal Article
Дата публикации2023-04-01
Включен в RSCI
scimago Q4
БС4
SJR0.169
CiteScore0.7
Impact factor
ISSN22195238, 26190788
Pharmaceutical Science
Complementary and alternative medicine
Pharmacology (medical)
Краткое описание

Introduction: Diseases of the respiratory system make a significant contribution to the incidence of the Russian population. Consideration of regional differences in the distribution of respiratory diseases contributes to a better understanding of the true extent of this problem. The Primorsky and Kamchatka Regions require stabilization of the demographic situation, which is affected, inter alia, by respiratory diseases. Objective: To study spatial differences and risk factors for diseases of the respiratory system in the Primorsky and Kamchatka Regions. Materials and methods: The assessment was conducted for 2010–2020 based on official statistics on respiratory disease rates in adults and children. To study spatial differences, the epidemiological risk value was estimated for intraregional territories at the first stage of work. The second stage included identification of risk factors for the spread of respiratory diseases using methods of correlation and information entropy analysis. Results: The territories of the regions differing in the level of epidemiological risk (high, increased, moderate and low) were determined. In the Primorsky Region, a high risk of respiratory diseases for adults and children was identified on 9 and 15 territories, respectively, while in the Kamchatka Region, the numbers were found to be much lower (5 and 8). At the regional level, environmental and territorial factors had the greatest impact on respiratory disease rates in the Primorsky Region while in Kamchatka healthcare, weather and climate factors were found to be of major importance. Conclusion: The results of the assessment of long-term respiratory disease rates in the Kamchatka and Primorsky Regions show that the local situation remains difficult and tense. It is of concern since the main part of the population resides within the territories of high and elevated risk. As a rule, these are northern, distant districts both in Kamchatka and Primorye. The risk factors analyzed have regional differences.

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FARMAKOEKONOMIKA Modern Pharmacoeconomics and Pharmacoepidemiology
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Pogorelov A. R. Medico-Geographical Assessment of the Prevalence of Respiratory Diseases in Northern and Southern Areas of the Russian Far East: Comparison of Kamchatka and Primorsky Regions // ЗДОРОВЬЕ НАСЕЛЕНИЯ И СРЕДА ОБИТАНИЯ - ЗНиСО / PUBLIC HEALTH AND LIFE ENVIRONMENT. 2023. pp. 30-39.
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Pogorelov A. R. Medico-Geographical Assessment of the Prevalence of Respiratory Diseases in Northern and Southern Areas of the Russian Far East: Comparison of Kamchatka and Primorsky Regions // ЗДОРОВЬЕ НАСЕЛЕНИЯ И СРЕДА ОБИТАНИЯ - ЗНиСО / PUBLIC HEALTH AND LIFE ENVIRONMENT. 2023. pp. 30-39.
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TY - JOUR
DO - 10.35627/2219-5238/2023-31-4-30-39
UR - https://doi.org/10.35627/2219-5238/2023-31-4-30-39
TI - Medico-Geographical Assessment of the Prevalence of Respiratory Diseases in Northern and Southern Areas of the Russian Far East: Comparison of Kamchatka and Primorsky Regions
T2 - ЗДОРОВЬЕ НАСЕЛЕНИЯ И СРЕДА ОБИТАНИЯ - ЗНиСО / PUBLIC HEALTH AND LIFE ENVIRONMENT
AU - Pogorelov, A R
PY - 2023
DA - 2023/04/01
PB - Federal Center for Hygiene and Epidemiology
SP - 30-39
SN - 2219-5238
SN - 2619-0788
ER -
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@article{2023_Pogorelov,
author = {A R Pogorelov},
title = {Medico-Geographical Assessment of the Prevalence of Respiratory Diseases in Northern and Southern Areas of the Russian Far East: Comparison of Kamchatka and Primorsky Regions},
journal = {ЗДОРОВЬЕ НАСЕЛЕНИЯ И СРЕДА ОБИТАНИЯ - ЗНиСО / PUBLIC HEALTH AND LIFE ENVIRONMENT},
year = {2023},
publisher = {Federal Center for Hygiene and Epidemiology},
month = {apr},
url = {https://doi.org/10.35627/2219-5238/2023-31-4-30-39},
pages = {30--39},
doi = {10.35627/2219-5238/2023-31-4-30-39}
}