Home
Issues
Aim and Scope
Open Access
Editorial Board
Indexing
Why publish with us
Contact Us
Instructions to Authors (PDF)
Manuscript Types
Manuscript Formatting
How to submit
Preprints
Special publications & Reprints
Authorship & COI
Principles of Transparency Checklist
Data Policies
Publication Ethics and Publication Malpractice Statement
Premature mortality and levels of inequality in years of life lost across 296 regions of 31 european countries in 2019: A burden of disease study
1
Department of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen Department of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen Hungary
2
Public Health Unit, Primary Healthcare Cluster Baixo Mondego NOVA National School of Public Health, Public Health Research Centre, Universidade NOVA de Lisboa Portugal
3
Department of Public Health, Erasmus MC University Medical Center, Rotterdam Netherlands
4
Norwegian Institute of Public Health Norway
5
Department of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen Hungary
6
Department of Public Health, FSPAC, Babeș-Bolyai, Cluj-Napoca Romania
7
Örebro University, Swedish National Research School of Ageing and Health Sweden
8
Department of Healthcare, Faculty of Health, University of Vlora Albania
9
Department of Non-Communicable Diseases and Injuries, Santé Publique France France
10
Robert Koch Institute, Berlin Germany
11
School of Health and Wellbeing, University of Glasgow United Kingdom
Publication date: 2023-04-26
Popul. Med. 2023;5(Supplement):A825
ABSTRACT
Background and Objectives:
Inequalities in life expectancy and years of life lost (YLL) are key measures of disease burden within a population. Although European countries aim for convergence in health status, few comparative studies have addressed health inequalities at the sub-national level. This study aimed to examine all-cause YLL by sub-national NUTS2 regions in the European Economic Area (EEA) and assess level of regional inequality in YLL rates through the Gini Coefficient (GC), between males and females in 2019.
Methods:
To quantify existing inequalities, we extracted from Eurostat (2019) socio-economic data, age-standardised population, and deaths by all causes for 296 NUTS2 regions across the EEA. Residual life expectancy was retrieved from the Global Burden of Disease study (2019). Age-standardised YLL (expressed as rate/100,000 inhabitants) and GC of sub-national inequalities in YLL rates were calculated with 95% Confidence Intervals (CI) using STATA.
Results:
The highest YLL in 2019 for females were observed in Bulgaria (Severozapaden), with 24,102 (CI 20,769–27,434), followed by Hungary (Észak-Magyarország) with 22,532 (CI 20,100–24,963). For males, the highest YLL values were again in Bulgaria (Severozapaden) with 43,523 (CI 38,854–48,192), followed by Romania (Southeast region), with 42,390 (CI 39,717–45,062). Overall, there were higher GC for sub-national YLL rates across countries in males (0,15; CI 0,14–0,16) compared to females (0,12; CI 0,11–0,13). France (0,08; CI 0,02–0,14) and Portugal (0,08; CI 0,04–0,11) had the highest GC for females, whereas the highest GC for males were estimated for Belgium (0,08; CI 0,06–0,11) and Portugal (0,08 CI 0,05–0,11).
Conclusion:
Our comparative analyses showed that regions located in Eastern and Central European countries had the highest YLL, while Western European countries had the highest GC values, indicating larger inequalities in premature mortality within these countries. Public health strategies need to take into account these regional health inequalities for future policies and interventions.
Inequalities in life expectancy and years of life lost (YLL) are key measures of disease burden within a population. Although European countries aim for convergence in health status, few comparative studies have addressed health inequalities at the sub-national level. This study aimed to examine all-cause YLL by sub-national NUTS2 regions in the European Economic Area (EEA) and assess level of regional inequality in YLL rates through the Gini Coefficient (GC), between males and females in 2019.
Methods:
To quantify existing inequalities, we extracted from Eurostat (2019) socio-economic data, age-standardised population, and deaths by all causes for 296 NUTS2 regions across the EEA. Residual life expectancy was retrieved from the Global Burden of Disease study (2019). Age-standardised YLL (expressed as rate/100,000 inhabitants) and GC of sub-national inequalities in YLL rates were calculated with 95% Confidence Intervals (CI) using STATA.
Results:
The highest YLL in 2019 for females were observed in Bulgaria (Severozapaden), with 24,102 (CI 20,769–27,434), followed by Hungary (Észak-Magyarország) with 22,532 (CI 20,100–24,963). For males, the highest YLL values were again in Bulgaria (Severozapaden) with 43,523 (CI 38,854–48,192), followed by Romania (Southeast region), with 42,390 (CI 39,717–45,062). Overall, there were higher GC for sub-national YLL rates across countries in males (0,15; CI 0,14–0,16) compared to females (0,12; CI 0,11–0,13). France (0,08; CI 0,02–0,14) and Portugal (0,08; CI 0,04–0,11) had the highest GC for females, whereas the highest GC for males were estimated for Belgium (0,08; CI 0,06–0,11) and Portugal (0,08 CI 0,05–0,11).
Conclusion:
Our comparative analyses showed that regions located in Eastern and Central European countries had the highest YLL, while Western European countries had the highest GC values, indicating larger inequalities in premature mortality within these countries. Public health strategies need to take into account these regional health inequalities for future policies and interventions.
| ISSN: | 2654-1459 |
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
