More Related Content

Slideshows for you(20)

Similar to Do different immigrant integration policies impact on migrants’ health? A test with a European general population survey(20)


More from sophieproject(20)


Do different immigrant integration policies impact on migrants’ health? A test with a European general population survey

  1. Do different immigrant integration policies impact on migrants’ health? A test with a European general population survey Davide Malmusi, Aitor Domínguez-Aguayo, Laia Palència, Carme Borrell
  2. Background Immigrants from disadvantaged areas: • poorer socio-economic conditions • “healthy immigrant effect” vanishing over time1 Little knowledge on the impact of immigration control and integration policies on immigrants’ health (mostly US, undocumented, single policy cases)2 Emerging cross-country analyses3 not yet linked to immigration policy context 1 De Maio, Int J Equity Health 2010 2 Martinez et al, J Immigr Minor Health 2013 3 Rafnsson et al, Eur J Public Health 2013
  3. Objective To analyse the differences across European countries with different integration policies: • in immigrants’ self-rated health • in self-rated health inequalities between natives and immigrants, and the contribution of socio-economic conditions to such differences.
  4. Conceptual framework: Immigration policy and migrants’ health
  5. Integration policy typologies Three models are describedbased on legal and cultural rights:4,5 - Multicultural: facility to acquire citizenship (ius soli), tolerance of cultural difference. UK, Netherlands, Sweden - Differential exclusionist: migrants as “guest workers”, low tolerance, citizenship based on ancestry. Germany - Assimilationist: facility to acquire citizenship, but cultural manifestations should be private. France Increasing policy convergence of EU countries with historically different approaches.6,7 4 Castles, J Ethn Migr Stud 1995 5 Weldon, Am J Pol Sci 2006 6 Mahnig and Wimmer, J Int Migr Integr 2000 7 Heckmann and Schnapper, 2003
  6. MIPEX overall score not associated with depression after controlling for individual variables. Levecque et al, Ethn Health 2014
  7. Methods. Design and data Design: Cross-sectional Data source: European Union Survey on Income and Living Conditions (EU-SILC) 2011 cross-sectional database Study population: individuals aged 16 or over Countries excluded: No 2011 data released, not classified in the typology, not separating EU and non-EU foreign-born, <0.5% immigrants, Lithuania (most “foreign-born” from USSR) Countries included: United Kingdom, the Netherlands, Belgium, Sweden, Norway, Finland, Italy, Spain, Portugal, Switzerland, France, Luxembourg, Austria and Denmark Valid sample: 184,388 subjects (7,088 immigrants)
  8. Methods. Variables Dependent variables: • Self-rated health (very good, good / fair, bad, very bad) • Limiting longstanding illness • Activity limitation because of health problems Independent variables: • Immigrant status: born in country of residence, or born outside the EU and having resided ten or more years in the country • Country typology of integration policies (Meuleman-Reeskens) Explanatory variables: EU citizenship, Year of immigration, Educational level, Occupational social class, Economic situation (household income, material deprivation, ability to make ends meet, overcrowding) Adjustment by age, stratification by sex
  9. Country policy typology MIPEX 2007 Latent Class Analysis. Meuleman and Reeskens 2008
  10. Country policy typology MIPEX 2007 Latent Class Analysis. Meuleman and Reeskens 2008 Multicultural Differential exclusionist Assimilationist
  11. Methods. Analysis Description of explanatory variables by country typology, sex and immigrant status Description of the sample size and age-adjusted prevalence* of poor health by country, sex and immigrant status Using robust Poisson regression models, estimation of prevalence ratios (PR) of poor self-rated health: • between migrants living in each country group • for migrants versus natives within each country group sequentially adjusting for age and explanatory variables * Predicted probability post-estimation function of Poisson regression
  12. Results Tertiary education (%) Men Women
  13. Results Managerial, professional or technical occupation (%) Men Women
  14. Results Household in the lowest income quintile (%) Men Women
  15. Results Poor self-rated health. Country by country Predicted prevalence at age 50 via regression (%) Men Women Numbers indicate immigrants’ weighted sample size
  16. Results Poor self-rated health Predicted prevalence at age 50 via regression (%) Men Women
  17. Results Immigrants between country types (ref. multicultural) Poor self-rated health. Prevalence ratio with 95%CI
  18. Results Immigrants versus natives Poor self-rated health. Prevalence ratio with 95%CI
  19. Results Limiting longstanding illness Predicted prevalence at age 50 via regression (%) Men Women
  20. Results Immigrants between country types (ref. multicultural) Limiting longstanding illness. Prevalence ratio with 95%CI
  21. Results Immigrants versus natives Limiting longstanding illness. Prevalence ratio with 95%CI
  22. Discussion. Main results First cross-country comparative study that tests the influence of integration policy models on migrants’ health Immigrants in all typologies experience poorer health than natives, fully or partly explained by socioeconomic conditions Immigrants in countries with an “exclusionist” model experience worse health and more health inequality than in other countries, beyond what expected for their poorer socioeconomic conditions Less conclusive* tendency to better migrants’ health in multicultural compared to assimilationist countries * Differences reduced when adjusting for education, when omitting recent immigration countries, with other health indicators
  23. Discussion. Limitations
  24. Discussion. Limitations EU-SILC: Country-level heterogeneities in sampling, data collection and response rates Mixing together all non-EU migrants (or all foreign-born) Limited participation/representativeness of immigrants Comparability of self-rated health across countries and origins Typology analysis: single big countries driving results Use of a ‘history-blind’ empirical typology based on MIPEX 2007
  25. Conclusions and recommendations Integration policy models appear to make a difference on migrants’ health across Europe. The “exclusionist” model results in larger socioeconomic segregation for migrants and takes a toll on their health. Inclusive social policies and reduced barriers to full citizenship may have health benefits. Future studies Adequate cross-country samples of migrants with similar origins Other health indicators (including mortality) Multilevel (MIPEX dimensions scores, GDP, welfare policy…) Qualitative studies to uncover how policy gets under the skin
  26. @sophieproject Thank you! Gracias! Gràcies! Grazie! Photos: Roberto Brancolini, Roberto Malaguti

Editor's Notes

  1. These countries are characterised by a consideration of migrants as temporary guest workers, with little perspectives for attaining citizenship and political rights, strict rules on long-term residence or family reunification, and little initiatives to combat discrimination [19]. This approach is mirrored in the results of this study: the access of migrants with the lowest education level, segregating in the least qualified occupational classes and experiencing the poorest living conditions. Health outcomes are also the poorest, and inequalities persist even after controlling for socioeconomic disadvantage. Previous studies have shown lower tolerance towards migrants in exclusionist countries [13] and that MIPEX scores are inversely related with perceived group threat from immigrants [41]: this may rebound in migrants’ ill-health through discrimination and lack of support