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The European Journal of Public Health 2000 10(2):101-104; doi:10.1093/eurpub/10.2.101
© 2000 by European Journal of Public Health
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PATTERNS OF MORTALITY

Regional life expectancy patterns in Lithuania

RAMUNE KALEDIENE1, and JADVYGA PETRAUSKIENE1

1Department of Social Medicine, Kaunas Medical University Kaunas, Lithuania

Correspondence: Ramune Kalediene, Associate Professor, Department of Social Medicine, Kaunas Medical University, Mickeviclus Str. 9, 3000 Kaunas, Lithuania, tel.+370 7 732535, fax+370 7 330157, e.mail. kaleda{at}kaunas.omnitel.net

Background: The objective of this study was to investigate levels and trends of inequalities in life expectancy in administrative regions of Llthuania during 1988–1996 and to analyse possible reasons for reglonal inequalities. Methods: Information about the population and the deceased was obtained from the Lithuanian Department of Statistics. Life tables of 55 administrative regions of Lithuania were compiled in 3 year intervals: 1988–1990, 1991–1993 and 1994–1996. The contribution of major causes of death to regional inequalities in life expectancy was assessed. Associations of the regional inequalities in life expectancy with the level of urbanisation, health care resources, level of education, marital status, and unemployment along with certain indicators of well-being were evaluated. Results: The life expectancy of males varied by 7.4–10.8 years and that of females by 5.6–7.2 years in different regions. The more favourable regions for both males and females were the major towns and the resort town of Druskininkai. Differences in mortality from external causes of death in males and cardiovascular diseases in females contributed most significantly to the regional inequalities in life expectancy. Inequalities correlated with the regional differences in the level of urbanisation, education and marital status. There were no associations observed with either the distribution of health care resources, level of unemployment or certain other economic aspects of well-being. Conclusions: Large-scale, individual-based data would need to be studied to explain the considerable regional inequalities in life expectancy and for equity-oriented policy and strategy application.

Keywords: evaluation, life expectancy, regional inequalities


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