East/West differences in health in Europe: rates, expectancies and DALYs

Powles, J. and Gouda, H. N. (2010). East/West differences in health in Europe: rates, expectancies and DALYs. In Victor R. Preedy and Ronald R. Watson (Ed.), Handbook of disease burdens and quality of life measures (pp. 505-516) New York, United States: Springer. doi:10.1007/978-0-387-78665-0_30


Author Powles, J.
Gouda, H. N.
Title of chapter East/West differences in health in Europe: rates, expectancies and DALYs
Title of book Handbook of disease burdens and quality of life measures
Place of Publication New York, United States
Publisher Springer
Publication Year 2010
Sub-type Chapter in reference work, encyclopaedia, manual or handbook
DOI 10.1007/978-0-387-78665-0_30
Series Springer reference collection
ISBN 9780387786667
9780387786643
9780387786650
Editor Victor R. Preedy
Ronald R. Watson
Chapter number 30
Start page 505
End page 516
Total pages 12
Total chapters 240
Language eng
Formatted Abstract/Summary
There is a very large health gap between Eastern and Western Europe. We show how different health metrics can be used to characterize this gap. We compare the 15 countries that joined the European Union prior to May 2004 (EU15), the ten who joined since May 2004 – excluding Malta and Cyprus – (EU10) and the three Slavic states of Russia, Ukraine and Belarus (Slavic 3). Rates and risks show that mortality differences are most pronounced amongst adult males, with those in the Slavic 3 being worst off. They also identify the diseases of the circulatory system and injuries as leading contributors to this gap. Life table methods can show how different life stages and different causes of death each contribute to the overall mortality gap. Summary measures – health expectancies and health gaps – combine information on health losses from premature death with information on losses from disease and injury among the living. A particular advantage of health gap metrics (such as the Disability adjusted life years (DALY)) is their capacity to “decompose” health differences into the conditions that produce them. These can, in turn, be attributed to the risk factors that cause them. We illustrate this process with an assessment of the contribution of alcohol to the health gap. Health losses attributable to alcohol are several times higher in males than in females and much higher for males in EU10 and especially Slavic 3 than in EU15.

Metrics for public health assessments should be chosen carefully with the purpose for conducting the assessment clearly in mind.

Q-Index Code BX
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Book Chapter
Collection: School of Public Health Publications
 
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Created: Thu, 14 Nov 2013, 08:35:52 EST by Hebe Gouda on behalf of School of Public Health