Morbidity with Temporary Work Incapacity in Russian Regions: Do Macrosocial Determinants Explain the Difference?

Monday, 16 July 2018
Distributed Paper
Natalia LEBEDEVA-NESEVRIA, Federal Scientific Center for Medical and Preventive Health Risk Management Technologies, Russian Federation, Perm State University, Russian Federation
Mihail TSINKER, Federal Scientific Center for Medical and Preventive Health Risk Management Technologies, Russia
Morbidity with temporary work incapacity has a wide use in Russia and other East Europe countries for characterization of health of working population. The indicators of morbidity (number of cases, days and the length of one case) have a steady downward trend from 2005 to 2015 in all 85 Russian regions. But the significant difference between regions still exists. Average number of days of morbidity with temporary work incapacity (2005–2015) was 884.2 days per 100 workers in Ural Federal district, 805.6 days – in North-West Federal district and 618.2 days – in North Caucasus Federal district. Average length of one case of morbidity (2014) was 1.2–1.3 times higher than on average in Russia in 5 regions of Far East Federal district, 3 regions of Siberia Federal district and 3 – of North Caucasus Federal district. To explain the difference we used 3 indicators of environmental determinants of health, 9 macrosocial indicators (gross regional product, fixed capital investment per capita, average income of households, average wage and several others) and the percentage of workplaces with harmful working conditions (2005–2015). The correlation and regression analysis were used. None of chosen indicators have a significant effect on level of morbidity with temporary work incapacity. For example, the average income of households effects on number of cases of morbidity (r=(–)0.18; R2=0.03, p<0.05) as well as an average wage does (r=(–)0.15; R2=0.02, p<0.05). The level of unemployment correlates with the number of days of morbidity (r=(–)0.28; R2=0.03, p<0.05). The same correlation was found for the percentage of high qualified workers (r=(–)0.25; R2=0.06, p=0.000). The explanation of the difference between regions may be connected with 1) lifestyle factors (that can be proved by the data of national survey in all regions) and/or 2) presenteeism (that requires using another indicators of health of working population).