title: Assessing the effect of regional deprivation on mortality avoiding compositional bias: a natural experiment.
abstract: OBJECTIVE
  We assessed the effect of regional deprivation on individual mortality by making use of a natural experiment: we followed up ethnic German resettlers from Former Soviet Union countries who were quasi-randomly distributed across the socioeconomically heterogeneous counties of Germany's federal state North Rhine-Westphalia (NRW).
  
  
  METHODS
  We used data from the retrospective cohort study 'AMOR' on the mortality of resettlers in NRW (n=34 393). Based on the postcode of the last known residence we linked study participants to the 54 counties of NRW, which were aggregated in six deprivation clusters. Mortality rates and standardised mortality ratios (SMRs) were calculated for each cluster. After a mean follow-up of 10 years, 2580 resettlers were deceased.
  
  
  RESULTS
  For male and female cohort members, mortality rates and SMRs were highest in the cluster 'poverty poles' (SMR men: 1.21, 95% CI 1.04 to 1.41; SMR women: 1.17, 95% CI 0.99 to 1.37), whereas they were lowest in the cluster 'prospering regions and suburban counties' (SMR women: 0.86, 95% CI 0.70 to 1.05) as well as in the cluster 'heterogeneous counties' (SMR men: 0.73, 95% CI 0.61 to 0.88).
  
  
  CONCLUSIONS
  The population which was quasi-randomly distributed to counties of differing socioeconomic status experienced different levels of mortality. It was highest in regions with the highest level of regional deprivation. Previous studies describing this positive relationship between mortality and regional deprivation could not differentiate between compositional and contextual effects. Thus, our findings indicate that in terms of mortality, regional deprivation does matter.
authors.affiliation: Department of Epidemiology & International Public Health, Bielefeld School of Public Health (BiSPH), Bielefeld University, Bielefeld, Germany.
authors.forename: Katharina
authors.initials: K
authors.lastname: Reiss
authors.forename: Ursula
authors.initials: U
authors.lastname: Berger
authors.forename: Volker
authors.initials: V
authors.lastname: Winkler
authors.forename: Sven
authors.initials: S
authors.lastname: Voigtländer
authors.forename: Heiko
authors.initials: H
authors.lastname: Becher
authors.forename: Oliver
authors.initials: O
authors.lastname: Razum
mesh_terms: D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000368:Aged; D015982:Bias; D016000:Cluster Analysis; D003467:Cultural Deprivation; D005260:Female; D005858:Germany / Q000453:epidemiology; D054625:Healthcare Disparities / Q000208:ethnology* / Q000592:standards / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D008875:Middle Aged; D009026:Mortality / Q000639:trends*; D011204:Poverty Areas; D016016:Proportional Hazards Models; D012111:Residence Characteristics / Q000706:statistics & numerical data; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D017678:Sex Distribution; D012959:Socioeconomic Factors; D013383:Suburban Population; D014171:Transients and Migrants / Q000706:statistics & numerical data*; D055815:Young Adult