Assessment of correlation between heterogeneous risk factors and morbidity among working population in Russian regions with different background of health formation
N.A. Lebedeva-Nesevrya1, A.O. Barg1, M.Yu. Tsinker2, V.G. Kostarev3
1Perm State University, 15 Bukireva Str., Perm, 614990, Russian Federation
2Federal Scientific Center for Medical and Preventive Health Risk Management Technologies, 82 Monastyrskaya Str., Perm, 614045, Russian Federation
3Federal Service for Surveillance over Consumer Rights protection and Human Well-being, Perm regional office, 50 Kuibyisheva Str., Perm, 614016, Russian Federation
The research focuses on classifying Russian regions as per their sanitary-hygienic and social-economic welfare, as well as on assessing (for certain nosologies) correlations between heterogeneous risk factors and morbidity with temporary disability among working population. The RF regions were classified (with k-average cluster analysis) as per their sanitary-hygienic and social-economic welfare in order to spot out territories with similar "background" for formation of working population health.We used data provided by the Federal Statistic Service (as per the RF regions) collected in 2016 as our empiric base. As per cluster analysis results, we assigned the RF regions into four specific categories, namely "ill-being", "moderately ill-being", "moderately well-being", and "well-being" (the obtained data are visualized on the map of the country).The performed correlation-regression analysis allowed us to obtain more than twenty authentic models that described correlations between various factors and morbidity with temporary disability among working population.We calculated determination coefficient R2 for each model that characterized a share of explained variation in a health parameter caused by a factor that was considered in a model.We paid special attention to the 1st cluster that had the least favorable background for health formation (here we detected most apparent influence exerted by social and economic factors on analyzed health parameters of working population). The 2nd clyster was also examined thoroughly as it was characterized with the highest morbidity among working population (we revealed that social-hygienic welfare on territories belonging to this cluster had greater influence on health parameters than social and economic one).Our data can be appliedto create federal and regional programs aimed at preserving and improving working population health.
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