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Changing effect of the numerator–denominator bias in unlinked data on mortality differentials by education: evidence from Estonia, 2000–2015
  1. Domantas Jasilionis1,2,
  2. Mall Leinsalu3,4
  1. 1Laboratory of Demographic Data, Max Planck Institute for Demographic Research, Rostock, Germany
  2. 2Demographic Research Centre, Vytautas Magnus University, Kaunas, Lithuania
  3. 3Stockholm Centre for Health and Social Change, Södertörn University, Huddinge, Sweden
  4. 4Department of Epidemiology and Biostatistics, National Institute for Health Development, Tallinn, Estonia
  1. Correspondence to Domantas Jasilionis, Max Planck Institute for Demographic Research, Konrad Zuse Str. 1 18057, Rostock, Germany; jasilionis{at}


Background This study highlights changing disagreement between census and death record information in the reporting of the education of the deceased and shows how these reporting differences influence a range of mortality inequality estimates.

Methods This study uses a census-linked mortality data set for Estonia for the periods 2000–2003 and 2012–2015. The information on the education of the deceased was drawn from both the censuses and death records. Range-type, Gini-type and regression-based measures were applied to measure absolute and relative mortality inequality according to the two types of data on the education of the deceased.

Results The study found a small effect of the numerator–denominator bias on unlinked mortality estimates for the period 2000–2003. The effect of this bias became sizeable in the period 2012–2015: in high education group, mortality was overestimated by 23–28%, whereas the middle education group showed notable underestimation of mortality. The same effect was small for the lowest education group. These biases led to substantial distortions in range-type inequality measures, whereas unlinked and linked Gini-type measures showed somewhat closer agreement.

Conclusions The changing distortions in the unlinked estimates reported in this study warn that this type of evidence cannot be readily used for monitoring changes in mortality inequalities.

  • Mortality
  • Inequalities
  • Education
  • Measurement
  • Eastern Europe

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  • Contributors DJ and ML conceived the research question and designed the study. ML compiled census-linked mortality data. DJ conducted the statistical analysis, interpreted the results and wrote the draft of manuscript. ML contributed to the interpretation of the data and to revisions of the manuscript. Both authors approved the final version of the submitted manuscript.

  • Funding This study was funded by Riksbankens Jubileumsfond—The Swedish Foundation for Humanities and Social Sciences (grant P15-0520:1). The work by ML was partially supported by the Estonian Research Council (grant PRG722). The work by DJ has been partially supported by the Max Planck Society within the framework of the project ‘On the edge of societies: New vulnerable populations, emerging challenges for social policies and future demands for social innovation. The experience of the Baltic Sea States’ (2016–2021).

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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