Understanding age variations in the migrant mortality advantage: An international comparative perspective

Abstract

This paper investigates age variations in foreign-born vs. native-born mortality ratios in an international comparative perspective, with the purpose of gaining insight into the mechanisms underlying the so-called migrant mortality advantage. We examine the four main explanations that have been proposed in the literature for the migrant mortality advantage (i.e., in-migration selection effects, out-migration selection effects, cultural effects, and data artifacts), and formulate expectations as to whether they should generate an increase, a decrease, or no change in relative mortality over the life course. Using data from France, the US and the UK for periods around 2010, we then examine typical age patterns of foreign-born vs. native-born mortality ratios in light of this theoretical framework. We find that these mortality ratios vary greatly by age, with important similarities across migrant groups and host countries. The most systematic age pattern we find is a U-shape pattern: at the aggregate level, migrants often experience excess mortality at young ages, then exhibit a large advantage at adult ages (with the largest advantage around age 45), and finally experience mortality convergence with natives at older ages. The explanation most consistent with this pattern is the “in-migration selection effects” explanation. By contrast, the “out-migration selection effects” explanation is poorly supported by the observed patterns. Our age disaggregation also shows that migrants at mid-adult ages experience mortality advantages that are often far greater than typically documented in this literature. Overall, these results reinforce the notion that migrants are a highly-selected population exhibiting mortality patterns that poorly reflect their living conditions in host countries.

Healthy migrant effect in the Swedish context: a register-based, longitudinal cohort study.

“…Some explanatory views attributed to migrants’ positive health status at arrival are present in the literature. One claims that migrants often constitute a selection of strong and healthy individuals who can handle the physiological, social and mental hardships of uprooting, travel and resettlement 18 34. This could be a reason for the positive health outcomes of Western migrants in our study.…”

“…The cultural effects explanation points at health-promoting lifestyle factors with regard to, for example, food, alcohol and drugs. Finally, data artefacts refer to register fallacies, such as over-registration, and that primarily elderly migrants return permanently to their geographical origin without notice and still remain in the registers (salmon bias) 7 15 17 18…”

“…Many studies have observed a ‘healthy migrant effect’ (HME), that is, that migrants often have a better health status than the remaining population in the native country, but also compared with the majority in the host country, especially during the first 5–10 years after immigration. The HME has been documented in studies worldwide and explained in different lines 6–18. Most studies on the HME are undertaken in North America, but there are also enlightening studies from Europe, for example, Denmark,13 Germany,14 Spain16 and Norway 19.…”

Mortality Paradox of Older Italian-Born Men in Australia: The Concord Health and Ageing in Men Project

“…Another study examining how the migrant mortality advantage differs with age in France, the UK and the US, found a U-shaped relationship in most migrant groups and settings, with lower comparative mortality observed during middle age and higher mortality at younger and older ages [11].…”

Adult mortality among second-generation immigrants in France: Results from a nationally representative record linkage study

“…Deaths and exposure terms were then combined to calculate age-specific mortality rates, which were then converted into probabilities of dying between age 18 and 65 using standard life table methodologies. (For more information about these sources, see Guillot et al 2018. ) Table A-10 compares these probabilities of dying calculated on the basis of these two different data sources.…”