Introduction: The study presents associations between prevalence of chronic diseases and selected socio-economic (SES) attributes in adult population of Slovakia and analyses the prevalence of chronic diseases in regions of Slovakia.
Methods: In total, 735 respondents (146 men and 589 women) with a mean age of 37.79 ± 13.6 participated in this cross-sectional study. The main observed characteristics were chronic diseases and their associations with SES attributes, namely household income, education, age and lifestyle represented by frequency in engaging in recondition-relaxation activities. In order to obtain data, a self-administrated online questionnaire was used. Data were analysed by calculation of odds ratio and chi-square test. The significance level was set at 0.05.
Results: Apart from lung disease which are least suffered in central Slovakia (χ^2 = 9.850, df = 1, p = 0.043), the prevalence of chronic diseases is equally represented in all 8 administrative regions of Slovakia. Prevalence of chronic diseases is significantly influenced by age. The age of 40 is critical for the occurrence of chronic diseases. Respondents with higher education level have a lower prevalence of chronic diseases and vice versa (OR = 1.127; RR = 1.079). A better lifestyle represented by higher frequency of engaging in recondition relaxation activities was found in healthy respondents (OR = 0.700549 and RR = 0.936958; χ^2 test p = 0.000798). Household income did not show a significant association with the prevalence of chronic diseases (OR = 1.06; RR = 1.025; χ^2 test, p = 0.778).
Conclusion: The study did not confirm a higher prevalence of chronic diseases in regions with weaker SES in Slovakia. Out of the 4 monitored SES attributes, 3 of them (age, education and lifestyle) had a significant impact on the prevalence of chronic diseases. Household income showed only a minimal association with the prevalence of chronic diseases, but this interdependence was not significant (Tab. 6, Ref. 41). Text in PDF www.elis.sk Keywords: socio-economic status, chronic diseases, age, household income, education.