Cascade Model-Based Study of Potential Regional Health Losses Prevented through Rospotrebnadzor Control and Supervisory Activities

Introduction: Exposure to adverse environmental factors has been proven to induce additional cases of disease and death in the population. In the absence of effective measures taken to improve environmental quality, the levels of these factors rise, thus causing a potential increase in related human health outcomes. The concept of "prevented" morbidity and mortality cases is used to describe contribution of such measures to improving health of the population.

Objective: Theoretical computational study of prevented regional health losses resulting from control and supervisory activities of the Russian Federal Service for Surveillance on Consumer Rights Protection and Human Wellbeing (Rospotrebnadzor).

Materials and methods: The previously developed cascade model is theoretically presented in the triple system of links between control and supervisory activities of Rospotrebnadzor, environmental quality indicators, and public health using methods of neural network modeling, factor analysis, and multiple linear regression. Morbidity, mortality, and years of potential life lost were taken as responses to changes in environmental quality. Specific planned and unscheduled activities of Rospotrebnadzor, including liability imposed on business entities polluting the environment were considered as affecting the quality of the latter.

Results: We established pronounced regional differences in prevented morbidity cases. The largest number of prevented cases ranging from 4,574 to 19,047 per 100,000 population was observed in the Republic of Dagestan, Kaliningrad and Saratov Regions, the city of Sevastopol, the Murmansk Region, the Altai Republic, the Belgorod Region, and the Karachay-Cherkess Republic. The smallest number of incident cases prevented through Rospotrebnadzor control and supervisory activities (1,976 to 2,528 per 100,000 population) was noted in the Sverdlovsk, Altai, Krasnoyarsk, and Tambov Regions, Republics of Tyva and Karelia, the Ryazan Region, and the Republic of North Ossetia–Alania. The highest number of prevented deaths in the general population (55.6 to 101.7 per 100,000 population) was observed in the city of Sevastopol, the Kaliningrad Region, the Republic of Dagestan, Saratov, Tula, Belgorod, and Krasnodar Regions, and the Chechen Republic. The lowest number of prevented deaths (17.8 to 26.6 per 100,000 population) was estimated in the Sverdlovsk, Tyumen, Murmansk, Chelyabinsk, Krasnoyarsk, Transbaikal, and Altai Regions, the Republic of North Ossetia–Alania, and the Nizhny Novgorod Region. The largest number of prevented years (1.61 to 3.73) of potential life lost was established in the Republic of Dagestan, the Kaliningrad Region, the city of Sevastopol, Saratov, Belgorod, Bryansk, and Lipetsk Regions, and the Karachay-Cherkess Republic. Many of these regions were also among the leaders in terms of prevented morbidity and mortality. The smallest number of prevented years of life lost was observed in the regions of the Central, Ural, and Siberian Federal Districts, while the highest were noted in the Southern and North Caucasus Federal Districts.

Conclusions: We conducted the theoretical computational study of potential regional health losses prevented by means of control and supervisory activities of Rospotrebnadzor, structured and differentiated the losses by constituents of the Russian Federation, as well as by age groups, causes of morbidity and mortality, and environmental quality indicators.

1. Shepelev II, Zhukov EI, Pilyaeva OV. Disposal of fine dust during complex processing of nepheline raw materials. Еkologiya i Promyshlennost' Rossii. 2023;27(2):4–9. (In Russ.) doi: 10.18412/1816-0395-2023-2-4-9

2. Shumakher MYu, Sorokina AS, Konovalov VV, Gilaev GG. Evaluation of the potential of carbon dioxide utilization at oil fields of the Samara region. Oborudovanie i Tekhnologii dlya Neftegazovogo Kompleksa. 2023;(1(133)):36–41. (In Russ.) doi: 10.33285/1999-6934-2023-1(133)-36-41

3. Zhuravleva MV, Bagautdinova AR, Klimentova GYu, Garafeev RR. Catalytic technologies for low-carbon development of petroleum and gas chemical complex. Yuzhno-Sibirskiy Nauchnyy Vestnik. 2023;(1(47)):67–75. (In Russ.) doi: 10.25699/sssb.2023.47.1.002

4. Zaitseva NV. Hygiene in resolving actual problems of developing the health potential and life expectancy of the population in the Russian Federation. Gigiena i Sanitariya. 2022;101(10):1138–1144. (In Russ.) doi: 10.47470/0016-9900-2022-101-10-1138-1144

5. Nikiforova NV, Zaitseva NV, Kleyn SV. On assessing the morbidity of the population associated with the atmospheric air quality on the example of a Russian constituent entity. Siberian Journal of Life Sciences and Agriculture. 2022;14(4):73–88. doi: 10.12731/2658-6649-2022-14-4-73-88

6. Gritsenko TD, Prosviryakova IA, Sokolov SM, Pshegroda AE. Analysis of population morbidity, associated with multicomponent air pollution in public places. Zdorov'e i Okruzhayushchaya Sreda. 2022;(32):16–21. (In Russ.)

7. Atiskova NG, Shur PZ, Romanenko KV, Shlyapnikov DM, Sharaeva AA. Forming a list of priority hygenic standards of ambient air ingredients for harmonization. Zdorov'e Naseleniya i Sreda Obitaniya. 2013;(11(248)):7–9. (In Russ.)

8. Kovshov AA, Novikova YuA, Fedorov VN, Tikhonova NA. Diseases risk assessment associated with the quality of drinking water in the urban districts of Russian Arctic. Vestnik Ural'skoy Meditsinskoy Akademicheskoi Nauki. 2019;16(2):215–222. (In Russ.) doi: 10.22138/2500-0918-2019-16-2-215-222

9. Alekseev VB, Kleyn SV, Vekovshinina SA, Andrishunas AM, Glukhikh MV. Associated with the drinking water from centralized drinking water supply systems priority factors for deterioration of health of the population in the Russian Federation. Zdravookhranenie Rossiyskoy Federatsii. 2022;66(5):366–374. (In Russ.) doi: 10.47470/0044-197X-2022-66-5-366-374

10. Dorokhin SA, Bakutina YuYu, Vasilieva MV, Melikhova EP, Skrebneva AV. [Structure of population morbidity associated with the water factor.] Molodezhnyy Innovatsionnyy Vestnik. 2018;7(S3):22. (In Russ.)

11. Deryabin AN, Unguryanu TN, Buzinov RV. Population health risk caused by exposure to chemicals in soils. Health Risk Analysis. 2019;(3):18–25. doi: 10.21668/ health.risk/2019.3.02.eng

12. Maksimova AM, Nesterov DA, Finarov DP. Contamination of soil of Krasnogvardeiskii district of St. Petersburg with heavy metals. Izvestiya Rossiyskogo Gosudarstvennogo Pedagogicheskogo Universiteta im. A.I. Gertsena. 2012;(153-2):104–109. (In Russ.)

13. Gutor EM, Zhidkova EA, Gurevich KG, et al. Some approaches and criteria for assessing the risk of developing occupational diseases. Meditsina Truda i Promyshlennaya Ekologiya. 2023;63(2):94–101. (In Russ.) doi: 10.31089/1026-9428-2023-63-2-94-101

14. Yashnikova MV. Evaluation of neurological deficiency in patients with insult working in the conditions of exposure to harmful production factors. Sibirskiy Nauchnyy Meditsinskiy Zhurnal. 2018;38(3):86–91. (In Russ.) doi: 10.15372/SSMJ201803013

15. Davydova EA, Belskaia EN, Postnikova US, Taseiko OV. Assessing the risks of circulatory diseases due to noise exposure in urban areas. Control Sciences. 2023;(1):29–35. doi: 10.25728/cs.2023.1.4

16. Petrov SB, Sennikov IS, Petrov BA. Influence of ecological factors of the urban environment on the population morbidity of blood circulatory systems. Fundamental'nye Issledovaniya. 2015;(1-5):1025–1028. (In Russ.)

17. Sabirova ZF, Budarina OV, Shipulina ZV. Ranking of air pollution, socio-economic, and medical factors in the formation of mortality (for example, the centre of petrochemistry and chemistry). Mezhdunarodnyy Zhurnal Prikladnykh i Fundamental'nykh Issledovaniy. 2019;(10):98–102. (In Russ.)

18. Novikov SM, Shashina TA, Dodina NS, et al. The experience of empirical research on comparative assessment of radiation and chemical health risks due to exposure to environmental factors. Gigiena i Sanitariya. 2019;98(12):1425–1431. (In Russ.) doi: 10.47470/0016-9900-2019-98-12-1425-1431

19. Kiku PF, Yarygina MC, Gorborukova TC, Beniowa SN. Associations between sociohygienic factors on health of children and adolescents in Primorsky Krai. Еkologiya Cheloveka (Human Ecology). 2016;(4):9–13. (In Russ.) doi: 10.33396/1728-0869-2016-4-9-13

20. Rakhmanin YuA, Zaitseva NV, Shur PZ, et al. Scientific and economic aspects of the solution of regional problems in environmental medicine Gigiena i Sanitariya. 2005;(6):6. (In Russ.)

21. Martynova AA. Territorial zoning of the Murmansk region according to the most important environmental diseases in the population of the Murmansk region. Rossiyskaya Arktika. 2023;5(3):26–39. (In Russ.) doi: 10.24412/2658-4255-2023-3-26-39

22. Andreeva EE, Onishсhenko GG, Kleyn SV. Hygienic assessment of priority risk factors of environment and health condition of the population of Moscow. Health Risk Analysis. 2016;(3):23–34. doi: 10.21668/health.risk/2016.3.03.eng

23. Zaitseva NV, Shur PZ, Kiryanov DA, Kamaltdinov M, Cinker MYu. Methodical approaches for health population risk estimation based evolution models. Zdorov'e Naseleniya i Sreda Obitaniya. 2013;(1(238)):4–6. (In Russ.)

24. Kiryanov DA, Tsinker MYu, Istorik OA, Stepanov EG, Davletnurov NKh, Efremov VM. On assessment of Rospotrebnadzor surveillance and control activities efficiency in regions: Assessment criteria being prevented economic losses caused by population morbidity and mortality and associated with negative impcats exerted by environmental factors. Health Risk Analysis. 2017;(3):12–20. doi: 10.21668/health.risk/2017.3.02.eng

25. Popova AYu, Bragina IV, Zaitseva NV, et al. On the scientific and methodological support of the assessment of the performance and effectiveness of the control and supervision activity of the Federal Service for Surveillance on Consumer Rights Protection and Human Wellbeing. Gigiena i Sanitariya. 2017;96(1):5–9. (In Russ.) doi: 10.18821/0016-9900-2017-96-1-5-9

26. Kiryanov DA, Kamaltdinov MR, Tsinker MYu, Chigvintsev VM, Babina SV, Kuchukov AI. Cascade model for assessing and predicting health losses prevented through control and supervisory activities of Rospotrebnadzor. Zdorov'e Naseleniya i Sreda Obitaniya. 2023;31(12):27–36. (In Russ.) doi: 10.35627/2219-5238/2023-31-11-27-36