scholarly journals Childhood asthma prevalence and risk factors in three Eastern European countries - the Belarus, Ukraine, Poland Asthma Study (BUPAS): an international prevalence study

2016 ◽  
Vol 16 (1) ◽  
Author(s):  
Grzegorz Brozek ◽  
Joshua Lawson ◽  
Andrei Shpakou ◽  
Olga Fedortsiv ◽  
Leonid Hryshchuk ◽  
...  
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.


2014 ◽  
Vol 155 (21) ◽  
pp. 833-837 ◽  
Author(s):  
József Marton ◽  
Attila Pandúr ◽  
Emese Pék ◽  
Krisztina Deutsch ◽  
Bálint Bánfai ◽  
...  

Introduction: Better knowledge and skills of basic life support can save millions of lives each year in Europe. Aim: The aim of this study was to measure the knowledge about basic life support in European students. Method: From 13 European countries 1527 volunteer participated in the survey. The questionnaire consisted of socio-demographic questions and knowledge regarding basic life support. The maximum possible score was 18. Results: Those participants who had basic life support training earned 11.91 points, while those who had not participated in lifesaving education had 9.6 points (p<0.001). Participants from former socialist Eastern European countries reached 10.13 points, while Western Europeans had average 10.85 points (p<0.001). The best results were detected among the Swedish students, and the worst among the Belgians. Conclusions: Based on the results, there are significant differences in the knowledge about basic life support between students from different European countries. Western European youth, and those who were trained had better performance. Orv. Hetil., 2014, 155(21), 833–837.


2017 ◽  
pp. 38-60 ◽  
Author(s):  
Ewa Cieślik

The paper evaluates Central and Eastern European countries’ (CEEs) location in global vertical specialization (global value chains, GVCs). To locate each country in global value chains (upstream or downstream segment/market) and to compare them with the selected countries, a very selective methodology was adopted. We concluded that (a) CEE countries differ in the levels of their participation in production linkages. Countries that have stronger links with Western European countries, especially with Germany, are more integrated; (b) a large share of the CEE countries’ gross exports passes through Western European GVCs; (c) most exporters in Central and Eastern Europe are positioned in the downstream segments of production rather than in the upstream markets. JEL classification: F14, F15.


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