Journal of Public Health

, Volume 27, Issue 1, pp 21–28 | Cite as

The role of individual characteristics and municipalities in social inequalities in perceived health (Italy, 2010–2012): a multilevel study

  • Simone SartiEmail author
  • F. Biolcati-Rinaldi
  • A. Vitalini
Original Article



The empirical evidence shows discordant results regarding the role of local contexts on individual health. This article considers the role of the municipal socio-economic contexts on self-rated health in Italy, taking into account some individual variables.


Multilevel model software (MlwiN) is used to fit multilevel linear regression models of perceived health. Individual data are from the Italian surveys on “Aspects of Daily Life” 2010, 2011 and 2012, collected by the Italian National Institute of Statistics (Istat). In addition, municipality-level social, demographic and economic characteristics are from the 2011 Census and the database “Atlas of Italian Municipalities” (Istat).


The main findings of this study confirm that, controlling for age and gender at the individual level, poor health is influenced by socio-economic positions: lower education, not working or looking for employment and disadvantaged family social class predict higher perceived health. The individual level explains the 70.1% heterogeneity in self-assessed health, the family level 25.6% and the municipality level only 4.3%. The additional influence of the socio-economic context is, conversely, of little substantive importance.


Finally, by showing that variability in health relates mainly to individual characteristics, this study suggests that intervention to mitigate social inequalities in health should focus on structural factors, such as education and the labour market.


Italy Municipalities Perceived health Socio-economic context Ecological models Inequalities in health 


Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

Italian data were collected by ISTAT-National Institute of Statistics (Italy) according to the international standards and the Italian legislation (art. 9 del d.lgs. n. 322/89; d.lgs. n. 196/03). More information at:

Specific information on interviewees’ municipalities in “Multiscopo” surveys was used under a particular agreement between the University of Milan and ISTAT (Sede Regionale per la Lombardia).

Informed consent

Informed consent was obtained from all individual participants included in the study before taking part.


  1. Bell ML, Zanobetti A, Dominici F (2013) Evidence on vulnerability and susceptibility to health risks associated with short-term exposure to particulate matter: a systematic review and meta-analysis. Am J Epidemiol 178(6):865–876 first published online July 25, 2013. CrossRefGoogle Scholar
  2. Cummins S, Stafford M, Macintyre S, Marmot M, Ellaway A (2005) Neighbourhood environment and its association with self-rated health: evidence from Scotland and England. J Epidemiol Community Health 59(3):207–213CrossRefGoogle Scholar
  3. Diez Rouz AV (2001) Investigating neighborhood and area effects on health. Am J Public Health 91(11):1783–1789CrossRefGoogle Scholar
  4. Egidi V, Spizzichino D (2006) Perceived health and mortality: a multidimensional analysis of ECHP Italian data, Genus LXII, n. 3–4Google Scholar
  5. Erikson R, Goldthorpe JH (1992) The constant flux. Clarendon Press, Oxford, p 1992Google Scholar
  6. Fayers PM, Sprangers MAG (2002) Understanding self-rated health. Lancet 359:9302Google Scholar
  7. Goldstein H (2011) Multilevel statistical models (Vol. 922), WileyGoogle Scholar
  8. Goldthorpe JH (2009) Analysing social inequality: a critique of two recent contributions from economics and epidemiology. Eur Sociol Rev.
  9. Haslam SA, Jette J, Postmes T, Haslam C (2009) Social identity, health and well-being: an emerging agenda for applied psychology, Appl Psychol-Int Rev 58, (1), 1–23. doi:
  10. Hox JJ (2010) Multilevel analysis: Techniques and applications, Taylor & FrancisGoogle Scholar
  11. Istat (2006) Il sistema di indagini sociali multiscopo, RomaGoogle Scholar
  12. Jylhä M (2009) What is self-rated health and why does it predict mortality? Towards a unified conceptual model. Soc Sci Med 69:307–316CrossRefGoogle Scholar
  13. Lucchini M, Sarti S, Tognetti M (2009) I welfare regionali e le differenze territoriali nelle disuguaglianze di salute, Dimensioni della disuguaglianza in Italia: povertà, salute, abitazione, (edit by) A.Brandolini, C.Saraceno and A.Schizzerotto, Bologna, Il Mulino, 165–189Google Scholar
  14. Macintyre S, Ellaway A, Cummins S (2002) Place effects on health: how can we conceptualise, operationalise and measure them? Soc Sci Med 55:125–139CrossRefGoogle Scholar
  15. Mackenbach JP, Stirbu I, Roskam AJR, Schaap MM, Menvielle G, Leinsalu M, Kunst AE (2008) Socioeconomic inequalities in health in 22 European countries. N Engl J Med 358(23):2468–2481CrossRefGoogle Scholar
  16. Marinacci C, Spadea T, Biggeri A, Demaria M, Caiazzo A, Costa G (2004) The role of individual and contextual socioeconomic circumstances on mortality: analysis of time variations in a city of north-West Italy. J Epidemiol Community Health 58:199–207CrossRefGoogle Scholar
  17. Marinacci C, Ferracin E, Landriscina T, Cislaghi C, Gargiulo L, Costa G (2010) Differenze geografiche o differenze sociali, Rapporto OsservaSalute 473–484Google Scholar
  18. Marmot M (2005) Social determinants of health inequalities. Lancet 365(9464):1099–1104CrossRefGoogle Scholar
  19. Marmot M (2015). The health gap: the challenge of an unequal world. Bloomsbury PublishingGoogle Scholar
  20. Phelan J, Link BG, Tehranifar P (2010) Social conditions as fundamentalcauses of health inequalities: theory, evidence, and policy implica-tions. J Health Soc Behav 51:S28–S40CrossRefGoogle Scholar
  21. Pickett K, Pearl M (2001) Multilevel analyses of neighbourhood socio-economic context and health outcomes: a critical review. J Epidemiol Community Health 55:111–122CrossRefGoogle Scholar
  22. Piombo S (2013) Multilevel analysis in household surveys: an application to health condition data, PhD Dissertation Thesis, University of BolognaGoogle Scholar
  23. Ross CE, Wu C (1996) Education, age, and the cumulative advantage in health. J Health Soc Behav 37:104–120CrossRefGoogle Scholar
  24. Sarti S, Zella S (2016) Changes in the labour market and health inequalities during the years of the recent economic downturn in Italy. Int J Soc Sci Res 57:116–132Google Scholar
  25. Schaefer-McDaniel N, O’Brien Caughy M, O’Campo P, Gearey W (2010) Examining methodological details of neighbourhood observations and the relationship to health: a literature review. Soc Sci Med 70(2):277–292CrossRefGoogle Scholar
  26. Subramian SV, Kawachi I, Kennedy BP (2001) Does the state you live in make a difference?Multilevel analysis of self-rated health in the US. Soc Sci Med 53:9–19. CrossRefGoogle Scholar
  27. Tremblay S, Ross NA, Berthelot JM (2002) Regional socio-economic context and health. Public Health Rep 13:1–12Google Scholar
  28. Wilkinson RG, Pickett KE (2009) Income inequality and social dysfunction. Annu Rev Sociol 35:493–511CrossRefGoogle Scholar
  29. Willson AE, Shuey KM, Elder GH Jr (2007) Cumulative advantage processes as mechanisms of inequality in life course health. AJS 112(6):1886–1924Google Scholar
  30. World Bank (2017) World Bank Open Data. Available at:

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Social and Political SciencesUniversity of MilanMilanItaly
  2. 2.ISTAT Sede territoriale per la LombardiaISTAT–National Institute of StatisticsRomeItaly

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