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Original article

Vol. 153 No. 1 (2023)

The Swiss neighbourhood index of socioeconomic position: update and re-validation

  • Radoslaw Panczak
  • Claudia Berlin
  • Marieke Voorpostel
  • Marcel Zwahlen
  • Matthias Egger
Cite this as:
Swiss Med Wkly. 2023;153:40028


BACKGROUND: The widely used Swiss neighbourhood index of socioeconomic position (Swiss-SEP 1) was based on data from the 2000 national census on rent, household head education and occupation, and crowding. It may now be out of date.

METHODS: We created a new index (Swiss-SEP 2) based on the 2012–2015 yearly micro censuses that have replaced the decennial house-to-house census in Switzerland since 2010. We used principal component analysis on neighbourhood-aggregated variables and standardised the index. We also created a hybrid version (Swiss-SEP 3), with updated values for neighbourhoods centred on buildings constructed after the year 2000 and original values for the remaining neighbourhoods.

RESULTS: A total of 1.54 million neighbourhoods were included. With all three indices, the mean yearly equivalised household income increased from around 52,000 to 90,000 CHF from the lowest to the highest index decile. Analyses of mortality were based on 33.6 million person-years of follow-up. The age- and sex-adjusted hazard ratios of all-cause mortality comparing areas in the lowest Swiss-SEP decile with areas of the highest decile were 1.39 (95% confidence interval [CI] 1.36–1.41), 1.31 (1.29–1.33) and 1.34 (1.32–1.37) using the old, new and hybrid indices, respectively.

DISCUSSION: The Swiss-SEP indices capture area-based SEP at a high resolution and allow the study of SEP when individual-level SEP data are missing or area-level effects are of interest. The hybrid version (Swiss-SEP 3) maintains high spatial resolution while adding information on new neighbourhoods. The index will continue to be useful for Switzerland’s epidemiological and public health research.


  1. Chadwick E. Report on the Sanitary Condition of the Labouring Population of Great Britain, 1842. Edinburgh: Edinburgh University Press; 1965.
  2. Smith GD, Egger M. Socioeconomic differences in mortality in Britain and the United States. Am J Public Health. 1992 Aug;82(8):1079–81. DOI:
  3. Panczak R, Galobardes B, Voorpostel M, Spoerri A, Zwahlen M, Egger M; Swiss National Cohort and Swiss Household Panel. A Swiss neighbourhood index of socioeconomic position: development and association with mortality. J Epidemiol Community Health. 2012 Dec;66(12):1129–36. DOI:
  4. Moser A, Panczak R, Zwahlen M, Clough-Gorr KMK, Spoerri A, Stuck AEAE, et al. What does your neighbourhood say about you? A study of life expectancy in 1.3 million Swiss neighbourhoods. Journal of Epidemiology & Community Health 2014;68:1125-32. doi: DOI:
  5. Galobardes B, Shaw M. Lawlor D a, Lynch JW, Davey SG, Davey Smith G. Indicators of socioeconomic position (part 1). J Epidemiol Community Health. 2006;60:95–101.
  6. Basten C, von Ehrlich M, Lassmann A. Income Taxes, Sorting and the Costs of Housing: Evidence from Municipal Boundaries in Switzerland*. Econ J (Lond). 2017;127(601):653–87. DOI:
  7. Bowen EA, Mitchell CG. Housing as a Social Determinant of Health: Exploring the Relationship between Rent Burden and Risk Behaviors for Single Room Occupancy Building Residents. Soc Work Public Health. 2016;31(5):387–97. DOI:
  8. Galobardes B, Shaw M, Lawlor DA, Lynch JW, Davey Smith G. Indicators of socioeconomic position (part 2). J Epidemiol Community Health. 2006 Feb;60(2):95–101. DOI:
  9. Jeong A, Eze IC, Vienneau D, de Hoogh K, Keidel D, Rothe T, et al. Residential greenness-related DNA methylation changes. Environ Int. 2022 Jan;158:106945. DOI:
  10. Matthes KL, Zuberbuehler CA, Rohrmann S, Hartmann C, Siegrist M, Burnier M, et al. Selling, buying and eating - a synthesis study on dietary patterns across language regions in Switzerland. Br Food J. 2022 Mar;124(5):1502–18. DOI:
  11. Mozun R, Kuehni CE, Pedersen ES, Goutaki M, Kurz JM, de Hoogh K, et al.; On Behalf Of The Luis Study Group. LuftiBus in the school (LUIS): a population-based study on respiratory health in schoolchildren. Swiss Med Wkly. 2021 Aug;151:w20544. DOI:
  12. Statistik B für. Bevölkerungsdaten im Zeitvergleich, 1950-2020 - 1950-2020 | Tabelle. Bundesamt für Statistik 2021. ().
  13. ISCO - International Standard Classification of Occupations. n.d. ().
  14. Tillmann R, Voorpostel M, Antal E, Kuhn U, Lebert F, Ryser VA, et al. The Swiss Household Panel Study: observing social change since 1999. Longit Life Course Stud. 2016;7(1):64–78. DOI:
  15. Tele Atlas Schweiz AG. Strassennetz und Adressdaten von Tele Atlas gehören in jedes Geo-lnformationssystem. Geomatik Schweiz 2003:294–5.
  16. OECD. Compare your income - Methodology and conceptual issues. Paris: 2020.
  17. Lipps O. Income imputation in the Swiss Household Panel 1999-2007. Lausanne: FORS; 2010.
  18. Bopp M, Spoerri A, Zwahlen M, Gutzwiller F, Paccaud F, Braun-Fahrländer C, et al. Cohort Profile: the Swiss National Cohort—a longitudinal study of 6.8 million people. Int J Epidemiol. 2009 Apr;38(2):379–84. DOI:
  19. Spoerri A, Zwahlen M, Egger M, Bopp M, Spoerri A, Zwahlen M, et al. The Swiss National Cohort: a unique database for national and international researchers. Int J Public Health. 2010 Aug;55(4):239–42. DOI:
  20. Office FS. Swiss National Cohort (SNC) n.d.
  21. Stensrud MJ, Hernán MA. Why Test for Proportional Hazards? JAMA. 2020 Apr;323(14):1401–2. DOI:
  22. ISKO. Stata module to recode 4 digit ISCO-88 occupational codes n.d.
  23. Wickham H, Averick M, Bryan J, Chang W, McGowan LD, François R, et al. Welcome to the Tidyverse. J Open Source Softw. 2019;4(43):1686. DOI:
  24. Pebesma E. Simple Features for R: Standardized Support for Spatial Vector Data. R J. 2018;10(1):439. DOI:
  25. Valente P. Innovative Approaches to Census-Taking: Overview of the 2011 Census Round in Europe. In: Crescenzi F, Mignani S, editors. Statistical Methods and Applications from a Historical Perspective: Selected Issues. Cham: Springer International Publishing; 2014. pp. 187–200. DOI:
  26. Darin-Mattsson A, Fors S, Kåreholt I. Different indicators of socioeconomic status and their relative importance as determinants of health in old age. Int J Equity Health. 2017 Sep;16(1):173. DOI:
  27. Spycher J, Morisod K, Eggli Y, Moschetti K, Le Pogam MA, Peytremann-Bridevaux I, et al. Indicators on Healthcare Equity in Switzerland. New Evidence and Challenges. Report commissioned by the Federal Office of Public Health. Bern: FOPH; 2021.
  28. Vallarta-Robledo JR, Marques-Vidal P, Sandoval JL, De Ridder D, Schaffner E, Humair JP, et al. The neighborhood environment and its association with the spatio-temporal footprint of tobacco consumption and changes in smoking-related behaviors in a Swiss urban area. Health Place. 2022 Jul;76:102845. DOI:
  29. Mongin D, Cullati S, Kelly-Irving M, Rosselet M, Regard S, Courvoisier DS; Covid-SMC Study Group. Neighbourhood socio-economic vulnerability and access to COVID-19 healthcare during the first two waves of the pandemic in Geneva, Switzerland: A gender perspective. EClinicalMedicine. 2022 Mar;46:101352. DOI:
  30. Riou J, Panczak R, Althaus CL, Junker C, Perisa D, Schneider K, et al. Socioeconomic position and the COVID-19 care cascade from testing to mortality in Switzerland: a population-based analysis. Lancet Public Health. 2021 Sep;6(9):e683–91. DOI:
  31. Growth for Knowledge. GfK releases 2019 purchasing power for Austria and Switzerland n.d.
  32. Lansley G. Cars and socio-economics: understanding neighbourhood variations in car characteristics from administrative data. Reg Stud Reg Sci. 2016;3(1):264–85. DOI:
  33. Blumenstock J, Cadamuro G, On R. Predicting poverty and wealth from mobile phone metadata. Science. 2015 Nov;350(6264):1073–6. DOI:
  34. Quercia D, Saez D. Mining Urban Deprivation from Foursquare: Implicit Crowdsourcing of City Land Use. IEEE Pervasive Comput. 2014;13(2):30–6. DOI:
  35. Kloog I, Koutrakis P, Coull BA, Lee HJ, Schwartz J. Assessing temporally and spatially resolved PM2.5 exposures for epidemiological studies using satellite aerosol optical depth measurements. Atmos Environ. 2011;45(35):6267–75. DOI:
  36. Ward AD, Trowland H, Bracewell P. The Dynamic Deprivation Index: measuring relative socio-economic deprivation in NZ on a monthly basis. Kotuitui. 2019;14(1):157–76. DOI:
  37. Allik M, Leyland A, Travassos Ichihara MY, Dundas R. Creating small-area deprivation indices: a guide for stages and options. J Epidemiol Community Health. 2020 Jan;74(1):20–5. DOI:

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