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Main arrow Archive of previous Issues arrow ╣1 2014 (35) arrow Multi-dimensional model of risk factors of rheumatic diseases
Multi-dimensional model of risk factors of rheumatic diseases Print
Monday, 17 March 2014

D.N. Begun
Orenburg State Medical Academy, Orenburgá

Abstract. The work is substantiated by the fact that rheumatic diseases are a recognized medical and social problem due to their high prevalence, chronic nature, reduced quality of life, disability, and heavy financial burden.

The aim of the study was to develop a multi-dimensional model of risk factors of rheumatic diseases based on their detection rates and quantitative assessment.

The study subject was adult population of the Orenburg region.

Methods and dataľ sociological survey, sample size - 2960 respondents. To evaluate statistical significance of relationship between risk factors and arthral syndrome Pearson's X2 (for qualitative factors) and criterion Mann's ľ Whitney (for quantitative factors) were used. Contribution of each statistically significant factor to the development of rheumatic diseases was estimated through calculating relative risk, additive risk, additive population risk, and additive share of population risk. Three models of arthral syndrome development were built up using the classification trees method: including all risk factors, including only social factors and including only professional risk factors. Analysis of all established risk factors identified the following leading factors: work experience over 20 years, genetic predisposition, affiliation to the social group "employees", occupation is associated with frequent weight lifting.

The model including only social factors showed a special contribution of the age group over 40 years, affiliation to the group "employees", poor living conditions, and unbalanced diet. The model including only professional factors identified the following leading factors: work experience over 20 years, occupation is associated with frequent static loads, monotonous movements, and weight lifting. Results of the study can serve as algorithms for selecting population while planning preventive activities.

Keywords: rheumatic diseases, prevalence, risk factors, modeling.


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