BMC Public Health
Volume 19, Issue 1, 2019

Bias in cohort-based comparisons of immigrants' health outcomes between countries: A simulation study (Article) (Open Access)

Sauzet O.* , Razum O.
  • a Department of Epidemiology and International Public Health, Bielefeld School of Public Health (BiSPH), Bielefeld University, P.O. Box 10 01 31, Bielefeld, 33501, Germany, Center for Statistics, Bielefeld University, P.O. Box 10 01 31, Bielefeld, 33501, Germany
  • b Department of Epidemiology and International Public Health, Bielefeld School of Public Health (BiSPH), Bielefeld University, P.O. Box 10 01 31, Bielefeld, 33501, Germany

Abstract

Background: Cohort-type data are increasingly used to compare health outcomes of immigrants between countries, e.g. to assess the effects of different national integration policies. In such international comparisons, small differences in cardiovascular diseases risk or mortality rates have been interpreted as showing effects of different policies. We conjecture that cohort-type data sets available for such comparisons might not provide unbiased relative risk estimates between countries because of differentials in migration patterns occurring before the cohorts are being observed. Method: Two simulation studies were performed to assess whether comparisons are biased if there are differences in 1. the way migrants arrived in the host countries, i.e. in a wave or continuously; 2. the effects on health of exposure to the host country; or 3., patterns of return-migration before a cohort is recruited. In the first simulation cardiovascular disease was the outcome and immortality in the second. Bias was evaluated using a Cox regression model adjusted for age and other dependant variables. Results: Comparing populations from wave vs. continuous migration may lead to bias only if the duration of stay has a dose-response effect (increase in simulated cardiovascular disease risk by 5% every 5 years vs. no risk: hazard-ratio 1.20(0.15); by 10% every 5 years: 1.47(0.14)). Differentials in return-migration patterns lead to bias in mortality rate ratios (MRR). The direction (under- or overestimation) and size of the bias depends on the model (MRR from 0.92(0.01) to 1.09(0.01)). Conclusion: The order of magnitude of the effects interpreted as due to integration policies in the literature is the same as the bias in our simulations. Future studies need to take into account duration and relevance of exposure and return-migration to make valid inferences about the effects of integration policies on the health of immigrants. © 2019 The Author(s).

Author Keywords

Return-migration Immigrant health Integration policies Left truncation

Index Keywords

Internationality Emigrants and Immigrants Computer simulation Bias health status statistical bias cohort analysis international cooperation Emigration and Immigration Cohort Studies Cardiovascular Diseases mortality human Humans migrant migration cardiovascular disease

Link
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068858320&doi=10.1186%2fs12889-019-7267-2&partnerID=40&md5=16d7764729f784567700abc8eeef45d8

DOI: 10.1186/s12889-019-7267-2
ISSN: 14712458
Original Language: English