Medical-Environmental Assessment and Forecasting of Socially Significant Pathology of the Population of the Republic of Dagestan

Гасангаджиева, А. Г.; Габибова, П. И.; Даудова, М. Г.; Галкина, И. В.; Гираев, К. М.; Магомедова, З. Я.

doi:10.18470/1992-1098-2019-4-147-164

Cited by 3 publications

(1 citation statement)

References 14 publications

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“…: «Показатели состояния здоровья населения Республики Дагестан». Статистическая обработка результатов исследования проводилась с использованием пакета прикладных программ STATISTICA и Excel [4].…”

Section: материал и методы исследованияunclassified

Influence of the quality of drinking water supply sources on the formation of the ecologically-dependent pathology of the population of the Republic of Dagestan

Даудова

Багомедова

Бекшоков³

et al. 2021

Ûg Ross.: èkol. razvit.

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Aim. Study of the influence of drinking water quality on the ecologically-dependent morbidity of the population of the Republic of Dagestan.Material and Methods. Methods of current and retrospective analysis of regional health indicators and methods of mathematical-statistical and medical-geographical analysis were used. Statistical processing of the results was carried out using the STATISTICA and Excel software packages. When carrying out laboratory studies on the quality of drinking water, we used a Lumex atomic absorption spectrometer "MGA-915MD".Results. Numerous hygiene studies indicate the direct impact of unsatisfactory drinking water quality on the health of a population. The relationship between sanitary and chemical indicators and the incidence rate for a number of nosological forms has been proven. It is generally accepted that human health is influenced by lifestyle factors (working, living and relaxation conditions), heredity and the ecological condition of the area of residence, including the quality of drinking water. Although it is not possible to differentiate the share of the negative effect caused by the consumption of poor quality drinking water but the incidence of certain nosological forms (cancer of the esophagus, gastrointestinal tract and kidney diseases) in the those regions of the Republic of Dagestan under consideration correlates with the characteristics of drinking water.Conclusion. The problem of pollution of water supply sources for the population in the dynamics of the long-term remains a priority concern. The quality and safety of drinking water are decreasing, which cannot but have a negative impact on public health. Correlation linkages between indicators of drinking water quality and oncological morbidity of the population were also established in indicators below the maximum permissible concentrations, which corresponds to a typical logistic model of causal relationships and serves as evidence of the high dependence of health disorders on chemical contamination of water supply sources.

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Section: материал и методы исследованияunclassified

Influence of the quality of drinking water supply sources on the formation of the ecologically-dependent pathology of the population of the Republic of Dagestan

Даудова

Багомедова

Бекшоков³

et al. 2021

Ûg Ross.: èkol. razvit.

Self Cite

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A Machine Learning Approach to Exploring Ecological Determinacy of Socially Significant Diseases in Moscow

Marunko,

Zolotova

2023

2023 16th International Conference Management of Large-Scale System Development (MLSD)

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Intelligent Data Processing Methods for Studying the Influence of the Environment on the Morbidity of the Population in Moscow

Zolotova,

Marunko

2024

Statistika i ekonominka

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Purpose of the study. The purpose of the study is to confirm or refute the environmental determinism of the occurrence of socially significant diseases among the population of Moscow based on the analysis of data on environmental and health indexes in the context of municipal units of the city.Materials and methods. The article analyzes Russian and foreign bibliography on the research problem. Based on collected and processed open data on environmental indexes and population morbidity in various districts of Moscow, various types of analysis were carried out to identify the relationship between these data. To classify socially significant diseases based on environmental indexes of the place of residence, machine learning models were designed. The mathematical basis of machine learning methods is the k-nearest neighbors’ method, multilayer perceptron, and gradient boosting. To create the models, the Jupyter Notebook software tool, which supports the Python programming language, was used.Results. Correlation and regression analysis showed that there is a statistically significant correlation between some selected environmental indexes and the occurrence of socially significant diseases. This result indicates a possible relationship, which is one of the main conclusions of this paper. A web interface has been developed to automate the analysis of new data using constructed machine learning models used to conduct regression analysis to create a binary logistic model (prediction based on collected data of people with socially significant diseases) and a multiclass classification models (prediction based on collected data, which it is the disease that can be detected in a person). The machine learning models used were analyzed and the best model for classifying socially significant diseases was determined.Conclusion. As a result of the study, it was possible to collect comprehensive information about various environmental indexes and the presence or absence of various objects that have an impact on the environment. These data were used not only in machine learning models, but also to form an objective assessment of the environmental situation of municipal units of Moscow city. Since automatic updating of the rating for dynamic data was implemented, this result can be used by ordinary users who do not have sufficient qualifications in ecology and medicine for independent analysis of the ecological state of areas. We believe that such research will certainly lead to effective practical solutions in this area.

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Medical-Environmental Assessment and Forecasting of Socially Significant Pathology of the Population of the Republic of Dagestan

Cited by 3 publications

References 14 publications

Influence of the quality of drinking water supply sources on the formation of the ecologically-dependent pathology of the population of the Republic of Dagestan

Influence of the quality of drinking water supply sources on the formation of the ecologically-dependent pathology of the population of the Republic of Dagestan

A Machine Learning Approach to Exploring Ecological Determinacy of Socially Significant Diseases in Moscow

Intelligent Data Processing Methods for Studying the Influence of the Environment on the Morbidity of the Population in Moscow

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