RELATIONSHIP BETWEEN CARDIOVASCULAR RISK FACTORS AND SOCIO-ECONOMIC FACTORS: THE EXAMPLE OF SOUTH-EASTERN EUROPEAN COUNTRIES

Author(s):  
Velma Pijalović ◽  
Jasmina Selimović ◽  
Tea Mioković
2020 ◽  
Vol 41 (35) ◽  
pp. 3325-3333 ◽  
Author(s):  
Taavi Tillmann ◽  
Kristi Läll ◽  
Oliver Dukes ◽  
Giovanni Veronesi ◽  
Hynek Pikhart ◽  
...  

Abstract Aims Cardiovascular disease (CVD) risk prediction models are used in Western European countries, but less so in Eastern European countries where rates of CVD can be two to four times higher. We recalibrated the SCORE prediction model for three Eastern European countries and evaluated the impact of adding seven behavioural and psychosocial risk factors to the model. Methods and results We developed and validated models using data from the prospective HAPIEE cohort study with 14 598 participants from Russia, Poland, and the Czech Republic (derivation cohort, median follow-up 7.2 years, 338 fatal CVD cases) and Estonian Biobank data with 4632 participants (validation cohort, median follow-up 8.3 years, 91 fatal CVD cases). The first model (recalibrated SCORE) used the same risk factors as in the SCORE model. The second model (HAPIEE SCORE) added education, employment, marital status, depression, body mass index, physical inactivity, and antihypertensive use. Discrimination of the original SCORE model (C-statistic 0.78 in the derivation and 0.83 in the validation cohorts) was improved in recalibrated SCORE (0.82 and 0.85) and HAPIEE SCORE (0.84 and 0.87) models. After dichotomizing risk at the clinically meaningful threshold of 5%, and when comparing the final HAPIEE SCORE model against the original SCORE model, the net reclassification improvement was 0.07 [95% confidence interval (CI) 0.02–0.11] in the derivation cohort and 0.14 (95% CI 0.04–0.25) in the validation cohort. Conclusion Our recalibrated SCORE may be more appropriate than the conventional SCORE for some Eastern European populations. The addition of seven quick, non-invasive, and cheap predictors further improved prediction accuracy.


Author(s):  
Ali Sabri Taylan ◽  
Hüseyin Tatlidil

Credit risk pricing is perhaps an understudied topic in comparisons to its profound impact on the world’s financial markets and economies. This study uses established price discovery techniques to develop a method of price discovery for credit risk in three financial markets: equity, debt, and credit derivative. This chapter is motivated by the development of credit-related instruments and signals of stock price movements of South-Eastern European countries—Bulgaria, Croatia, Greece, Hungary, Romania, Slovenia, Slovakia, and Turkey—during the recent financial crisis. In this study, the authors evaluate the dynamics of fiscal risk or country risk measured by sovereign Credit Default Swap (CDS), liquidity risk measured bond markets, and stock markets for the monthly based September 2008 – February 2011 period. The study examines monthly data observing 38 months and 8 countries. A panel vector autoregression model is proposed for changes in Long-Term Interest Rate (LTIR), changes in CDS spreads (CDS), and changes in stock index. In conclusion, CDS markets and stock markets are more significant than bond markets in explaining the post-crisis relationship among developing South-Eastern European countries. The analysis displays that long-term monetary policy did not affect CDS premium and stock index level. A strong relationship is found between the CDS spread and stock market. During financial crisis and after the crisis, the correlations among CDS, stock, and bond markets are collapsed by panicked investors’ rapid movement and wild speculators. This risk perception can explain the difference between the finance theory and practices in the market.


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