Risks of alimentary dependent diseases: Assessment, prognosis and management
D.A. Kiryanov, M.A. Zemlyanova, D.R. Khismatullin
Federal Scientific Center for Medical and Preventive Health Risk Management Technologies, 82 Monastyrskaya Str., Perm, 614045, Russian Federation
In the Russian Federation, just as everywhere in the world, prevalence of alimentary dependent diseases, with predominant overweight and obesity in adults and children, poses a serious threat to population health and life expectancy. This necessitates methodological support for a comprehensive study of risk factors responsible for development of these pathological states at various levels of aggregation under influence exerted by a range of factors associated with unhealthy diets.
The aim of the study is to improve methodological approaches to analyzing the risk of alimentary dependent health issues and loss of years of life expectancy.
A methodology for assessing, predicting, and managing health risks associated with alimentary factors has been developed and implemented in two scales, population and individual. The following methods were used: medical and sociological surveys; systemic, multiple regression, and spatial-dynamic analysis; health risk assessment; neural network and evolutionary modeling; constructing a system of random scenarios; and life expectancy calculation.
The population-level loss of life expectancy due to the risk of developing diseases potentially caused by chemical and microbiological contamination of food products averages 1.08 years in the Russian Federation. The projected loss of life years due to diseases caused by an unbalanced diet is 2 years. The reduction in life expectancy at the individual level for schoolchildren under the worst-case nutrition scenarios is likely to be up to 4.7 years. The resulting parameters are manageable at the government level, taking regional specifics into account.
The developed methodology and analytical tools allowed us to quantify the impact of food quality and safety on health at the population and individual levels, reflecting current trends and regional characteristics, making it possible to predict the loss of life expectancy. As predicted, the effectiveness of implementing a set of management decisions could average 3 years in terms of life expectancy increase.
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