European Spatial Research and Policy

Author ORCID Identifier Hübelová Dana


The purpose of the study is to compare the differentiation of the demographic and socio-economic indicators and the structure of mortality of the population in EU countries in the period 2011–2014. The composite indicator of mortality structure revealed the most favourable situation in Finland (134.4%), while the worst situation was found in Hungary (63.8%). The best demographic and socio-economic situation was found in Luxembourg (165.4%) and the worst in Hungary (64.9%), Greece (65.9%) or Lithuania (67.3%). The regression model equation shows that the mortality structure is strongly affected by the variables of life expectancy at birth and education. It is evident that there was a differentiation in the demographic and socio-economic indicators in EU countries in the period 2011–2014, while there was no unambiguous trend of the convergence of the mortality structure among EU countries.


demographic and socio-economic indicators, cause-specific mortality, composite indicator, European population comparison




AKTAŞ, M.T. (2017), ‘Comparing EU Countries, Turkey and Macedonia via Clustering Analysis for Quality of Life Indicators’, [in:] KOÇ S., ÖRUÇ E. and ANLAR A. (eds.), Economic Issues: Crises, Finance and Agriculture. London IJOPEC Publication, pp. 76–104.

ALBERT, C. and DAVIA, M.A. (2011), ‘Education is a key determinant of health in Europe: a comparative analysis of 11 countries’, Health Promotion International, 26 (2), pp. 163–170.

BÖRSCH-SUPAN, A., BRANDT, M., HUNKLER, Ch., KNEIP T., KORBMACHER J., MALTER, F., SCHAAN, B., STUCK, S. and ZUBER, S. (2013), ‘Data Resource Profile: The Survey of Health, Ageing and Retirement in Europe (SHARE)’, International Journal of Epi-demiology, 42 (4), pp. 992–1001.

BRANDT, M., DEINDL, Ch. and HANK, K. (2012), ‘Tracing the origins of successful aging: The role of childhood conditions and social inequal-ity in explaining later life health’, Social Science and Medicine, 74 (9), pp. 1418–1425.

CASELLI, G., VALLIN, J. and WUNSCH, G. (2006), Demography: analysis and synthesis. London, Elsevier.

DAVEY SMITH, G., HART, C., HOLE, D., MACKINNON, P., GILLIS, Ch., WATT, G., BLANE, D. and HAWTHORNE, V. (1998), ‘Educa-tion and Occupational Social Class. Which Is the More Important Indicator of Mortality Risk?’, Journal of Epidemiology and Community Health, 52 (3), pp. 153–160.

DUPRE, E.M., GEORGE, K.L., LIU, G. and PETERSON, D.E. (2012), ‘The Cumulative Effect of Unemployment on Risks for Acute Myocardial Infarction’, Archives of Internal Medicine, 172 (22), pp. 1731–1736.

EUROSTAT’S REPORT FOR THE EUROPEAN COMMISSION (2017), Global Europe 2050. Brussels: European Commission.

FRASER, S.D.S. and GEORGE, S. (2015), ‘Perspectives on differing health outcomes by city: Accounting for Glasgow´s excess mortality’, Risk Management and Healthcare Policy, 8, pp. 99–110.

GALOBARDES, B., LYNCH, W.J. and DAVEY SMITH, G. (2004), ‘Childhood socioeconomic circumstances and cause-specific mortality in adulthood: Systematic review and interpretation’, Epidemiologic Reviews, 26, pp. 7–21.

HEBÁK, P. (2013), Statistické myšlení a nástroje analýzy dat. Prague: Informatorium.

HENDL, J. (2012), Přehled statistických metod: analýza a metaanalýza dat. Prague: Portál.

HUDRLÍKOVÁ, L. (2014), Kompozitní indikátory: konstrukce, využití, interpretace. Disertační práce. Prague: Vysoká škola ekonomická v Praze.

HÜBELOVÁ, D. KOZUMPLÍKOVÁ, A., JADCZAKOVÁ, V. and ROUSOVÁ, G. (2018), ‘Spatial differentiation of selected health factors of the South Moravian Region population’, Geographia Cassoviensis, 12 (1), pp. 34–52.

KHANG, Y.H., YANG, S., CHO, H.J., JUNG-CHOI, K. and YUN, S.Ch. (2010), ‘Decomposition of socio-economic differences in life expec-tancy at birth by age and cause of death among 4 million South Korean public servants and their dependents’, International Journal of Epidemi-ology, 9 (6), pp. 1656–1666.

KINO, S., BERNABÉ, E. and SABBAH, W. (2017), ‘Socioeconomic inequality in clusters of health-related behaviours in Europe: latent class analysis of a cross-sectional European survey’, BMC Public Health, (17) 1, pp. 1–8.

KRAUT, A., WALLD, R. and MUSTARD, C. (2001), ‘Impact of diabetes on employment and income in Manitoba, Canada’, Diabetes Care, 24 (1), pp. 64–68.

LEMSTRA, M., ROGERS, M. and MORAROS, J. (2015), ‘Income and heart disease Neglected risk factor’, Canadian Family Physician, 61 (8), pp. 698–704.

LIMM, H., HEINMÜLLER, M., LIEL, K., SEEGER, K., GÜNDEL, H., KIMIL, A. and ANGERER, P. (2012), ‘Factors associated with differ-ences in perceived health among German long-term unemployed’, BMC Public Health, 12 (1), pp. 485–494.

LUNDBERG, O., YNGWE, M.Å., STJÄRNE, M.K., BJÖRK, L. and FRITZELL, J. (2008), The Nordic experience: Welfare states and public health. Stockholm: Centre for Health Equity Studies (CHESS), University/Karolinska Institutet, p. 217.

MACINTYRE, K., STEWART, S., CHALMERS, J., PELL, J., FINLAYSON, A., BOYD, J., REDPATH, A., McMURRAY, J. and CAPE-WELL, S. (2001), ‘Relation between socioeconomic deprivation and death from a first myocardial infarction in Scotland: population based analysis’, British Medical Journal, 322 (7295), pp. 1152–1153.

MARMOT, M. (2017), ‘Social justice, epidemiology and health inequalities’, European Journal of Epidemiology, 32 (7), pp. 537–546.

MARMOT, M., FRIEL, S., BELL, R. and HOUWELING, A.J.T. (2008), ‘Public Health: Closing the gap in a generation: health equity through action on the social determinants of health’, The Lancet, 372 (9650), pp. 1661–1669.

MAYNOU, P.L. (2013), ‘Health convergence analysis of the EU regions: 1995 and 2009’, 53rd Congress of the European Regional Science Association: Regional Integration: Europe, the Mediterranean and the World Economy, Palermo, Italy, pp. 2–55.

McNAMARA, C., BALAJ, M., THOMSON, H.K., EIKEMO, T.A., SOLHEIM, F.E. and BAMBRA, C. (2017), ‘The socioeconomic distribu-tion of non-communicable diseases in Europe: Findings from the European Social Survey (2014) special module on the social determinants of health’, European Journal of Public Health, 27 (1), pp. 22–26.

MESLÉ, F. and VALLIN, J. (2002), ‘Mortality in Europe: The Divergence between East and West’, Population, 57 (1), pp. 171–212.

MINICUCI, N., NAIDOO, N., CHATTERJI, S. and KOWAL, P. (2016), ‘Data Resource Profile: Cross-national and cross-study sociodemo-graphic and health-related harmonized domains from SAGE plus ELSA, HRS and SHARE (SAGE+, Wave 1)’, International Journal of Epi-demiology, (45) 5, pp. 1403–1403j.

OECD (2016), Health at a Glance: Europe 2016 – State of Health in the EU Cycle. Paris: OECD Publishing.

ROTHENBACHER, F. (2013), The Central and East European Population since 1850, Springer, Palgrave Macmillan UK.

SHKOLNIKOV, M.V., ANDREEV, M.E., JASILIONIS, D., LEINSALU, M., ANTONOVA, O. and McKEE, M. (2006), ‘The changing rela-tion between education and life expectancy in central and eastern Europe in the 1990s’, Journal of Epidemiology and Community Health, 60, pp. 875–881.

SHKOLNIKOV, V.M., ANDREEV, E.M., LEON, D.A., McKEE, M., MESLÉ, F. and VALLIN, J. (2004), ‘Mortality Reversal in Russia: the story so far’, Hygiea Internationalis an Interdisciplinary Journal for the History of Public Health, 4 (1), pp. 29–80.

SPIJKER, J. (2004), Socioeconomic determinants of regional mortality differences in Europe, Groningen: Purdue University Press.

SPIJKER, J. (2014), ‘Socioeconomic Determinants of Mortality in Europe: Validation of Recent Models Using the Latest Available Data and Short-Term Forecasts’, [in:] ANSON, J., LUY, M. (eds.), Mortality in an International Perspective, Springer International Publishing, Swit-zerland, pp. 35–78.

SPIJKER, J. and WISSEN, A. (2010), ‘Socioeconomic determinants of male mortality in Europe: The absolute and relative income hypotheses revisited’, Genus, 6 (1), pp. 37–61.

ŠPROCHA, B., ŠÍDLO, L. and BURCIN, B. (2015), ‘Úroveň úmrtnosti na Slovensku a v Česku v európskom pohľade’, Geografický časopis, 67 (1), pp. 25–43.

TOBIASZ-ADAMCZYK, B., BRZYSKI, P., GALAS, A., BRZYSKA, M. and FLOREK, M. (2011), ‘Relationship between characteristics of social network, health-related quality of life and mortality patterns in older age. Krakow study’, Journal of Epidemiology & Community Health, 65, pp. 215–215.

VANDENHEEDE, H., DEBOOSERE, P., ESPELT, A., BOPP, M., BORRELL, C., COSTA, G.E., TERJE, A., GNAVI, R., HOFFMANN, R., KULHANOVA, I., KULIK, M., LEINSALU, M., MARTIKAINEN, P., MENVIELLE, G., RODRIGUEZ-SANZ, M., RYCHTARIKOVA, J. and MACKENBACH, J.P. (2015), ‘Educational inequalities in diabetes mortality across Europe in the 2000s: the interaction with gender’, International Journal of Public Health, 60 (4), pp. 401–410.

VILINOVA, K., REPASKA, G., VOJTEK, M. and DUBCOVÁ, A. (2017), ‘Spatio-temporal Differentiation of Cancer Incidence in Slovakia’, European Spatial Research and Policy, 24 (2), pp. 167–190.

WHO (2016), International statistical classification of diseases and related health problems, ICD-10, 1, 4th edition.

WHO (2017), ICD-10 Version: 2016. Copenhagen (WHO Division of Information, Evidence, Research and Innovation) [11.10.2019]. Retrieved from:

WILKINSON, R. and MARMOT, M. (2003), The solid facts: social determinants of health, Copenhagen, Centre for Urban Health, World Health Organization, 31 p.

WINKLEBY, M. and CUBBIN, C. (2003), ‘Influence of individual and neighbourhood socioeconomic status on mortality among black, Mexican-American, and white women and men in the United States’, Journal of Epidemiology and Community Health, 57 (6), pp. 444–452.

First Page


Last Page