
Econometric Modeling and Forecasting of Regional Environmental Conditions and Public Health Issues in Uzbekistan: A Case Study of Navoi Region
DOI:
https://doi.org/10.30564/jees.v7i4.8421Abstract
In this research work, the problems of connection between various harmful substances emitted into the atmosphere and population morbidity indicators were analyzed in the Navoi region, located in the industrialized and arid climate region of the Republic of Uzbekistan, in the Central Asian region. In today’s globalization process, due to the rapid development of the industry, several problems related to the health of the population are also appearing, so it is more important than ever to pay serious attention to solving these problems. Item 11 of the UN Sustainable Development Goals is also dedicated to the sustainable development of cities, and it is especially emphasized that the people living in the cities of the Asian continent have a very low chance of breathing clean air. Issues such as a very thorough analysis of this situation, improving the environmental situation as much as possible, transitioning to a green economy as soon as possible, and strengthening the health of the population are more important. In the implementation of this study, using methods such as statistical data analysis, sociological survey, and econometric modeling with the help of R Studio software, an attempt was made to determine the correlation between various harmful substances released into the atmosphere and disease groups of the population. This study’s conclusions show a direct relationship between the harmful substances released into the atmosphere and some types of population diseases in the industrialized region of Uzbekistan in Navoi, and their reduction by 2028 forecasts is presented. Decision-making organizations can use these results to prevent this situation from exacerbating.
Keywords:
SDGs; Sustainable Cities and Communities; Econometric Modeling; Air Pollution; Navoi Region; ARIMAReferences
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Copyright © 2025 Subkhan Abbasov, Nilufar Komilova, Normurod Latipov, Nazokat Mukhammedova, Iroda Khudoyvberdiyeva, Suhrob Chulliyev, Sirojiddin Do'sbekov

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