The article addresses development of methodical approaches to calculating levels of health disorders caused by short-term exposure to ambient air pollution. We have established and parameterized relationships relevant for quantification of probable health outcomes as responses to elevated levels of chemicals in ambient air higher than their reference ones. These relationships were modeled using system analysis techniques and were based on dynamic data series on ambient air quality at the control points and the number of applications for medical aid in settlements with their overall population being more than 5 million people. We have formalized relationships that describe how intensively acute health disorders develop under short-term exposure to chemical levels in ambient air being higher than the reference ones that are identified at the control points. The resulting models rely on official data and can be used to predict and assess public health risks in any area where ambient air quality is monitored. The formalized relationships were tested within identifying levels of incidence associated with acute short-term exposure to ambient air pollution in a large industrial center. It was established that, according to data collected in 2020, the highest associated incidence was caused by exposure to benzene (on average 0.364 mg/m3 higher than the reference level) in ambient air and was detected as per such nosologies as ‘Allergic rhinitis unspecified’ and ‘Predominantly allergic asthma’. We are planning to use the results obtained at this stage in the research in further development of methodical approaches to assessing and predicting chemical health risks in areas influenced by hazardous chemical objects under short-term exposure to high levels of pollutants.
The article discusses the effect of micro-macroelements coming from food on human health in different age groups. The consumption of micro- and micronutrients was established by direct questionnaire. Two categories of the population of the Perm Territory acted as questionnaires: students of educational institu-tions of Perm and Kungur and workers of the oil and gas industry. The questionnaire contained infor-mation about the daily consumption of food products, their volume and cooking features. The survey was conducted by direct questionnaire, as a result of which information was obtained on the consumption of various food products. Based on available literature, the amount of food consumed was converted to the amount of biologically significant elements consumed. Excessive intake of proteins, fats and cholesterol and insufficient intake of iodine and manganese are common among the children surveyed. The inter-viewed adults are characterized by an excess of protein, fat and cholesterol intake and a lack of dietary fi-ber, potassium, magnesium, iodine, vitamins B1 and B2, and manganese. As a result of mathematical modeling, reliable relationships were established between the occurrence of various diseases and the con-sumption of elements. The largest number of associated bonds with biologically significant elements was shown by the nervous system and skin and subcutaneous tissue. The largest number of associated bonds among micro and macro elements was found in selenium and iron, with 6 patterns for each element.
The article addresses development of methodical approaches to calculating levels of health disorders caused by short-term exposure to ambient air pollution. We have established and parameterized relationships relevant for quantification of probable health outcomes as responses to elevated levels of chemicals in ambient air higher than their reference ones. These relationships were modeled using system analysis techniques and were based on dynamic data series on ambient air quality at the control points and the number of applications for medical aid in settlements with their overall population being more than 5 million people. We have formalized relationships that describe how intensively acute health disorders develop under short-term exposure to chemical levels in ambient air being higher than the reference ones that are identified at the control points. The resulting models rely on official data and can be used to predict and assess public health risks in any area where ambient air quality is monitored. The formalized relationships were tested within identifying levels of incidence associated with acute short-term exposure to ambient air pollution in a large industrial center. It was established that, according to data collected in 2020, the highest associated incidence was caused by exposure to benzene (on average 0.364 mg/m3 higher than the reference level) in ambient air and was detected as per such nosologies as ‘Allergic rhinitis unspecified’ and ‘Predominantly allergic asthma’. We are planning to use the results obtained at this stage in the research in further development of methodical approaches to assessing and predicting chemical health risks in areas influenced by hazardous chemical objects under short-term exposure to high levels of pollutants.
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