Statistical Analysis of Environmental Pollution Impact on Population Morbidity in the Republic of Mari El

The article considers an econometric approach to the analysis of relation between the population morbidity rate depending on ecology and the environmental pollution index. Panel data are used in this approach. The purpose is to find quantitative relations between the state of the environment and public health under the differentiated man-caused load threatening public health in the Republic of Mari El. Materials and methods. The research methods are based on the approaches to correlation and regression analysis of the panel data. In order to identify the environmental pollution index statistically related to the morbidity rate, Pearson and Spearman's correlation coefficients were calculated. Then the regression models for the panel data were developed: a fixed-effect model and a random-effect model. The sources of the panel data are the following: Regional Statistics Office in the Mari El Republic (Maristat), Office of the Federal Service for Surveillance on Consumer Rights Protection and Human Wellbeing in the Mari El Republic (Rospotrebnadzor) and Ministry of Healthcare of the Mari El Republic. The data include six air and water pollution indexes and seven priority indicators of the population morbidity rate in 15 municipal districts of the Mari El Republic in the period of 2009–2017. Results. The analysis of the Pearson and Spearman's correlation coefficients helped to identify environmental pollution indexes closely related to the population morbidity rate. These indicators were used as input data of the panel regression model. Three statistically significant panel regression models were identified. They describe the impact of pollution of drinking water from the distributed network on bronchial asthma morbidity among 0–14-aged children diagnosed for the first time in their life; and the impact of emission into the atmosphere of pollutants from the point emission sources on gastritis and duodenitis morbidity among 15–17 aged teenagers diagnosed for the first time in their life. Conclusion. The identified models have biological plausibility. The ethiopathogenetic analysis confirms the possibility of existence of the identified relations. The statistically significant relations between environmental pollution and public health do not prove existence of cause-and-effect links between them. It is statistical demonstration of the hypothesis of their possible existence. This demonstration is an essential work stage to make the hypothesis a hard fact. In the future, it is proposed to use additional, more objective and integral evaluation of environmental quality, for example, the fluctuating asymmetry of bilateral features of biological objects.