# Impact of Environmental Conditions on the Health of the Far Eastern Region Population
## 2 Materials and Methods  
The studies were conducted over four years (2014-2017). For the analysis, the State reports \"On the sanitary-epidemiological situation in the Russian Federation\" and statistical data from the Federal Statistics Service of the Russian Federation were used [13]. To assess the impact of environmental pollution on health, basic medical and demographic indicators along with information on the incidence and prevalence of diseases among the population using medical care were used [14; 15; 16; 17]. The sources of information were medical records, annual reports from medical institutions, information on the number of diseases registered in patients living in the area of service of the medical institution, as well as information on the annual number of contingents served [18; 19; 20; 21].  
To ensure the uniformity of information from the data set, cases were excluded where there was no information on the incidence in the population or concentrations and emissions of pollutants for some years, for any reason [22; 23; 24; 25].  
Diabetes mellitus, hypertension, and malignant neoplasms are designated as socially significant diseases. For the analysis, the State reports \"On the sanitary-epidemiological situation in the Russian Federation\" and statistical data from the Federal Statistics Service of the Russian Federation were used [13].  
In the study of the dynamics of morbidity in the population of the Far Eastern region, extrapolation methods were used from the data of State reports on various classes of diseases and certain types of pathologies [26; 27; 28; 29; 30; 31; 32; 33; 34]. These methods were based on the study of the existing patterns and the development patterns of the studied phenomenon and their spread to future forecasts, i.e., beyond the base period.  
For the purpose of a long-term forecast, a detailed study of the variability of morbidity and the effects of emissions and concentrations of pollutants on the health of the population was conducted using correlation and regression analysis based on an array of data for the analyzed period.  
Methods of statistical analysis of time series, construction of regression models of processes, and factor analysis allowed the main trends of development to be analyzed based on a set of data on the object of observation, to study the dependencies of some parameters on others. Statistical models are built on the assumption that the simulated process is random and investigated using statistical techniques. To estimate the combined effect of the incidence of diabetes mellitus, hypertension, malignant neoplasms in the population, the stepwise multiple regression equation was used. The Statistica 8.0 automated processing program was used to build the regression equations. The significance of the equation was determined by the coefficient of determination R\({}^{2}\) and the distribution of residuals.  
In order to determine the impact of water and air pollution on life expectancy and the emergence of diseases in the Far Eastern Federal district, a statistical analysis was carried out. The data were sourced from the publications of the Federal State Statistics Service, posted on the website of the service, as well as statistical materials from the Ministry of Health of the Russian Federation. The indicators taken in the district for 2014-2017 were the maximum available. Calculations were carried out by means of Microsoft Excel and the econometric package Statistica 8.0.  
The criteria for assessing the state of atmospheric air in the region were indicators such as emissions of pollutants, and those for assessing the state of water resources included the amount of discharged polluted water. The following data were used as control variables that characterize the economic condition of the region and additional factors affecting health: the use of fresh water, population density, and the proportion of employed in heavy work and in conditions that did not meet health requirements.