International migrant populations are some of the most mobile populations in the world, making it difficult to accurately determine their numbers in host countries and their outcomes relative to the locally-born population. This is because many host country systems are not equipped to capture the moves of migrants into and, particularly, out of their countries. If migrants leave a host country and an exit is not recorded, they continue to exist in host country databases even after they have migrated elsewhere. This issue is known as ‘over-coverage’. It can lead to downward bias in the denominators of any rates that we might calculate, as we think that there are more migrants in a host country than there truly are. For outcomes like mortality, over-coverage can also impact the numerator of our rates as not only have migrants exited –while potentially remaining as ‘residents’ in host country data systems – they might well have died elsewhere. This often leads to concerns about whether mortality estimates of migrants can be trusted.

In a recent article investigating the impact of over-coverage on the mortality of migrant populations in Sweden between 2010 and 2015, we built upon the intersection of two recent findings (Wallace and Wilson 2021): first, over-coverage is highest at peak migration ages (ages 15-39), and second, migrant mortality is lowest at these same ages. This led us to wonder whether higher levels of over-coverage at young adult ages are actually driving the lower mortality of migrants at these ages. To answer this question, we used a survival analysis of Sweden’s population registers.

The case of Sweden (consistent with others: U.S., U.K. and France)

As shown in Figure 1, we found a distinct ‘U-shape’ of migrant mortality over age among Sweden’s migrant population. A similar pattern has recently been documented for the migrant populations of the US, the UK, and France (Guillot et al2018), with mortality among migrants relative to the locally-born populations forming a U-shape of lowest-low mortality around peak migration ages. This advantage then disappears, or is reversed, for older migrants, most notably in Sweden. Examining the impact of over-coverage on this ‘U-shape’ of advantage, we found that levels of over-coverage were indeed highest at peak migration ages. We also found that, at some ages, over-coverage may account for a sizeable share of the migrant mortality advantage. Crucially, however, over-coverage in isolation does not explain this lower relative mortality.

For specific origins, both the age-specific pattern of mortality and the impact of over-coverage vary. For example, we found the characteristic U-shape of mortality in some groups (such as Asia, the Middle East, and Central & Eastern Europe) but not in others (such as Finland and the other Nordic countries). Additionally, the impact of adjusting for over-coverage is larger in some groups (such as other Western and other Nordic countries) and much smaller in others (such as the Middle East and for Central & Southern America). Again, however, over-coverage alone does not explain the age variation we observed in the origin-specific mortality analysis.

The lower mortality of international migrants is genuine

Ultimately, we concluded that the unique mortality patterns of international migrants, and in particular their characteristic age profile of mortality, could not be explained by over-coverage, an important potential source of bias in studies that involve migrants. We pointed to migrants born in the Middle East, an origin group that combines the characteristic U-shaped mortality advantage with lower levels of over-coverage, as providing the most reliable evidence to date that the lower mortality of international migrants is genuine.

Given the marked age variation in migrant mortality patterns, we also highlighted the need, where possible, to adopt an age-specific perspective in studies of migrant mortality. Migrants from Central & Eastern Europe exemplify this call, as while young adult migrants in this group have a mortality advantage over the native-born population of Sweden, older migrants have a large disadvantage. We also highlighted migrants from Finland to show that not all migrant groups have an advantage over the native-born population of Sweden. Finnish migrants have a near systematic disadvantage in their mortality levels over age, which are actually underestimated because of population over-coverage.

Research on migrant mortality should refocus attention away from data-related explanations of the advantage and toward understanding the substantive processes that might explain its existence, and the combinations of mechanisms that may result in the absence, reversal, or tapering of these relative advantages with age (see also Ichou and Wallace 2019, Wallace 2019, Wallace and Wilson 2020). Some combination of selection and adaptation is probably at work here, but this is a subject that requires separate investigation.

References

Guillot, M., M. Khlat, I. Elo, M. Solignac, M. Wallace. 2018. Understanding age variations in the migrant mortality advantage: An international comparative perspective, PLoS One13(6): e0199669. doi:10.1371/journal.pone.0199669

Ichou M., Wallace M. 2019. The ‘Healthy Immigrant Effect’: the role of educational selectivity. N-IUSSP, March 10, .

Wallace M. 2019. Low migrant death rates: actual or artefactual? N-IUSSP, April 23.

Wallace M., B. Wilson. 2020. Migrant mortality advantage and the selection hypothesis, N-IUSSP, February 17,

Wallace M., B. Wilson. 2021. Age variations and population over-coverage: Is low mortality among migrants merely a data artefact?Population Studies, online first.

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When we study the social outcomes of international migrants – such as fertility, health or education – we typically compare them with three reference groups: (i) non-migrants in the destination country, (ii) non-migrants in the origin country (iii) and immigrants from the same origin country living in different destinations. Although there is more than one potential comparison group, migration scholars almost always compare immigrants with non-migrants in the countries they move to. This focus on destination comparisons is understandable; they are easier because they only require a single data source. Comparisons with origin, on the other hand, require at least two harmonized data sources containing similar information and of requisite quality; one source for immigrant outcomes in the destination country and another for non-migrant outcomes in the origin country.

Destination comparisons also reflect a greater interest in where immigrants are living now, how their lives change after arrival, and the links between migration, integration and inequality. Nevertheless, comparisons with non-migrants in the destination only tell us part of the story about immigrants’ lives. If we additionally make comparisons with non-migrants in origin countries, then this can help us to understand why the outcomes of immigrants differ from non-migrants in the destination country. Often, immigrants are said to be “selected” from their origin populations. This might mean that those who leave a country are, for example, more highly educated or healthier than those who stay behind. These two factors are not independent. If some people are more highly educated than others, then they are probably healthier too, and vice versa. Although destination comparisons can tell us a lot about the experiences of immigrants in their new country, they say little about selection unless we compare them with the population they are selected from.

Comparing immigrants with their origin country: mortality…

In a recent study (Wallace and Wilson 2019), we compared the mortality of immigrants in the United Kingdom (UK) with non-migrants in their origin countries. Our analysis is framed around the migrant mortality advantage – a term used to describe the frequently observed situation in which immigrants have lower overall mortality than non-migrant populations at destination. It is considered advantageous because immigrants, on average, will live longer than non-migrants. Researchers often suspect that selection plays a big role in the advantage. For example, if we find that immigrants from India – a country that ranks around 130^th in the world life expectancy rankings – have lower mortality than non-migrants in the UK – a country that ranks around 30^th in the world – then it’s likely that the immigrants have, on average, lower mortality than non-migrants in India.

In our study, we estimated relative mortality, versus origin, of immigrants from the 35 countries with the largest immigrant populations in the United Kingdom, by age and sex. We analysed data on deaths and population sizes from the Office for National Statistics (in the UK) alongside equivalent data for origin countries from the Human Mortality Database and the United Nations World Population Prospects. We also analysed equivalent data on the educational attainment – of immigrants versus their country of birth – as a more widely accepted measure of selection (Feliciano and Lanuza 2017) and a characteristic that remains quite stable with time (unlike mortality, which is directly affected by people’s experiences in the destination country (Ichou and Wallace 2018).

Figure 1 shows the age-specific mortality of immigrants relative to the population in their countries of birth. The far-left panel shows the “average” for all immigrants living in the UK plotted in black, with individual immigrant groups plotted in light grey. The red line indicates mortality in origin countries at a given age. Values below the red line indicate a mortality advantage, whereas those above the red line indicate excess mortality among immigrants. The other panels show four examples of immigrant groups from countries with different levels of the Human Development Index (HDI), ranging from low (Nigeria) to very high (the United States). These examples are fairly typical of the averages for each HDI category that we show in the full paper, and they illustrate three key findings. First of all, there is a common shape across panels, in which the advantage is largest at young adult ages and decreases with age. Second, the advantage at young adult ages is largest among immigrants from poorer countries and diminishes as we move up HDI categories. Third, we find that substantial mortality advantages exist at older ages (65+) for countries in the low and medium HDI categories, but not for groups in the high and very high categories.

… and education

Figure 2 shows an almost identical analysis, but with a focus on education. Here, the far-left panel shows that immigrants almost always have higher rates of tertiary education than average members of the population in their country of birth. There are only a few exceptions (i.e. the light grey line is below the red line), with the clearest case being Lithuania (not singled out here). Generally, the size of the differentials falls as we move up HDI categories. For example, Nigerian immigrants are much more highly educated than their Nigerian origin population, whereas immigrants from the US are only somewhat more highly educated than the US average. Variation over age is likely to reflect cohort differences in migration, as well as cohort trends in the origin countries, including factors such as educational expansion.

Conclusions: selective selection at work (but weakening over time)

So, what do these findings tell us? We think that the patterns provide evidence consistent with selection. Immigrants have lower mortality than the population in their country of origin, on average. The lower the level of development in the origin country, the larger this advantage tends to be. This suggests that immigrants from poor countries need to be more strongly selected than immigrants from rich countries in order to generate a similar mortality advantage vs. the same destination population. Next, the advantage is largest at young adult ages and diminishes with age. Since the majority of immigrants arrive at young adult ages, this finding is consistent with the idea that selection effects are strongest shortly after immigrants arrive and weaken over time. In absence of data on duration of residence, it is at young adult ages that we come closest to capturing the extent of selection effects among immigrants, as these are the ages where the selection has just taken place (and exposure to life at destination is minimised). With time and a growing influence of destination-specific risk factors that affect mortality, the role of selection diminishes. Last, immigrants are also more highly educated, on average, than their origin populations. Given that education is a more stable measure of selection (because it is unlikely to change from young adulthood onwards), this result adds further support for our conclusions on mortality.

Overall, our findings represent an important reference point in the re-conceptualization of immigrant outcomes relative to origin country populations. We are not the first to make such comparisons (Marmot, Adelstein, and Bulusu 1984; Gadd et al. 2006), but our study is the first to do so for such a diverse array of countries and in such detail (i.e. by age, sex and origin country), even considering comparisons to destination. Given that selection seems to be an important explanation of the migrant mortality advantage, we should consider how the flows of selected people between countries – often from poor to rich countries – impacts positively on national mortality metrics in rich countries, negatively on national mortality in poor countries and potentially inflates the size of health inequalities between them.

Bibliography

Feliciano, C., and Y. R. Lanuza. 2017. “An immigrant paradox? Contextual attainment and intergenerational educational mobility.” Am Sociol Rev 82 (1):211-241.

Gadd, M., S. E. Johansson, J. Sundquist, and P. Wandell. 2006. “Are there differences in all-cause and coronary heart disease mortality between immigrants in Sweden and in their country of birth? A follow-up study of total populations.” BMC Public Health 6:102. doi: 10.1186/1471-2458-6-102.

Ichou, M., and M. Wallace. 2018. “The Healthy Migrant Effect: The role of educational selectivity in the good health of migrants.” Demographic Research 40 (4):61-94. doi: 10.4054/DemRes.2019.40.4.

Marmot, M.G., A.M. Adelstein, and L. Bulusu. 1984. “Lessons from the study of immigrant mortality.” The Lancet 323 (8392):1455-1457. doi: 10.1016/S0140-6736(84)91943-3.

Wallace, M., and B. Wilson. 2019. “Migrant Mortality Advantage Versus Origin and the Selection Hypothesis.” Population and Development Review 45 (4):767-+. doi: 10.1111/padr.12298.

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The migrant mortality advantage is the name given to the observation that international migrants tend to have lower death rates than the native population in the receiving country (Ichou and Wallace, 2019). While this phenomenon is regularly observed in high-income countries, researchers are unable to reach a consensus regarding its origins; some argue that the advantage is real, while others see it as artefactual.

Migrant mortality advantage: two contrasting explanations

For the former, lower migrant mortality is considered genuine and generated by processes such as selection – the idea that people who move are healthier and more highly educated than those they leave behind – and cultural factors – the idea that migrants tend to practice less-risky, health-promoting behaviors. For the latter, lower migrant mortality is considered artificial and borne out of the inability of national data systems and surveys to adequately capture the mobility of migrant populations. The resulting errors lead to migrant death rates that appear to be lower than they actually are.

At the individual-level, capturing emigration poses the greatest challenge. There is little incentive to register an exit from a country and there is rarely a legal requirement to do so. Consequently, we do not always know when – or if – migrants have left the host country. This contrasts with immigration, for which registration is required so that new arrivals can receive ID numbers, granting them access to the job market, social security, and healthcare.

The two main problems arising from missing emigration data are censoring bias and salmon bias. Censoring bias refers to the inability to identify and remove emigrants from risk populations upon which death rates (or other demographic outcomes) are based. If someone makes an unregistered exit from the host country and there are no markers to identify this event, they are still considered to be ‘at risk’ of death in the host country even though they have left and may have died elsewhere. This artificially depresses death rates because the numerators (number of deaths) are deflated and the denominators (number of people or person-years) are inflated. Salmon bias suggests that those who leave are negatively selected in their health i.e. they are frailer and more likely to die than the migrants who remain in the host country. This leads to depressed death rates because average death rates of the migrants would be higher if both stayers and leavers were fully accounted for.

Censoring

Wallace and Kulu (2014) have previously investigated censoring bias among migrant populations living in England and Wales. In the absence of complete information on emigration from these two countries, the authors ‘filled in the blanks’ using information from censuses, National Health Service records and civil registers to identify unregistered emigration from England and Wales. Having identified possible emigrants, they then conducted a series of sensitivity analyses around the date of emigration (imputing dates based upon dates of those who registered their exits) to show that censoring bias contributed to, but could not fully explain, the migrant mortality advantage. However, because migrant death rates can remain depressed even after correcting for censoring bias (i.e. if emigrants are negatively selected by their health status), it was also necessary to identify and correct for a potential salmon bias effect.

The salmon bias effect

Using the same data, Wallace and Kulu (2018) studied the probability of migrants leaving England and Wales in bad health. Figure 1 shows results from separate discrete-time survival models examining the migrant mortality advantage (top) and salmon bias effect (bottom) among migrant females (left) and males (right). From the top two panels, we can see that nearly all migrant groups experience a migrant mortality advantage, i.e. they have lower relative mortality than the England and Wales-born. From the bottom two panels we can see that migrants in three groups (India, Pakistan and Bangladesh, and Caribbean) show evidence for a salmon bias i.e. were more likely to leave England and Wales in poor health. Given that emigration in the other groups was not selective and all but those from the ”Anglo-Saxon group” (US, Canada, Australia and New Zealand) experienced a migrant mortality advantage, we can conclude that the advantage of these groups is real and not caused by biases.

However, the mortality advantage of migrants from India, Pakistan and Bangladesh and Caribbean could be explained by selective emigration. The authors therefore indirectly corrected the mortality rates of these groups for the salmon bias effect at the aggregate level to see if it could explain away their advantage. They found that the death rates of emigrants would have to be unrealistically high to account for their lower death rates relative to the England and Wales-born. Therefore, as with censoring bias, they concluded that a salmon bias effect contributed to, but could not explain, the migrant mortality advantage.

Migrants live longer than natives (but no so much as data suggest)

Our findings demonstrate that migrants really do have lower death rates than the England and Wales-born. This allows us to focus on more substantive explanations of the advantage to try to understand why migrants often have lower risks of death than those of natives in host countries. Such findings fly in the face of public perceptions of migrants, who are often considered to adversely affect health and health care in host countries. However, while biases could not fully explain the migrant mortality advantage, they did explain a part of it. This is important, because it shows that the inability to capture movement in and out of host countries generates some degree of bias in our rates. This is relevant not only for migrant-specific rates, but for all rates in which migrants form a sizeable proportion of the population of interest. Such biases will only increase as the relative proportions of migrants continue to increase in host countries. This suggests a need to reform registration systems to better capture the increased mobility of international migrants. This is important to ensure greater confidence in our findings and in those provided to policy makers.

References

Ichou M. and Wallace M. 2019. The ‘Healthy Immigrant Effect’: the role of educational selectivity. N-IUSSP.

Wallace M. and Kulu, H. 2014. Low immigrant mortality in England and Wales: a data artefact? Soc Sci Med, 120, 100-9.

Wallace M. and Kulu H. 2018. Can the salmon bias effect explain the migrant mortality advantage in England and Wales? Population, Space and Place, e2146.

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The Healthy Immigrant Effect (HIE) refers to the recurring finding that people who have just moved to a new country have better health and lower death rates than the native population there. Over time, however, the health and mortality of these migrant populations become more like those of natives. Such a finding is often considered ‘paradoxical’, as migrants in the host country occupy lower socioeconomic positions (e.g. they have lower educational levels, lower incomes and lower-skilled jobs), on average, than natives. This conflicts with the long-held belief that lower socioeconomic positions are associated with poorer health and higher risks of death. Central to explaining this paradox is migrant selection, i.e. the notion that those who move are not simply ‘average’ members of their origin population; they are better educated, wealthier and more highly skilled than the ‘typical’ members of the population that they leave behind.

The problem of measuring selection in the countries of origin

However, this selection process is difficult to capture as it requires detailed and comparable information on migrants’ experiences in both the host and origin countries. As a result, most studies only compare the characteristics of migrants with those of natives in the host country. This tells us little about the level and effects of migrant selection. Crucially, this comparison ignores two facts: first, that migrants’ health is a combination of their previous life experiences in the origin country and current life experiences in the host country; and second, that a given socioeconomic position in one country as determined by a certain level of, say, education is unlikely to equate to the same position in another. If we only consider socioeconomic position as measured in the host country, we ignore the formative part of migrants’ lives that determined their health just before they migrated and risk underestimating migrants’ previous social standing in their origin country. Consequently, we are liable to overestimate migrant-native health differences.

In a recent study (Ichou and Wallace 2019), we directly tested migrant selection as an explanation of the HIE among migrants in France. Using data from the French Trajectories and Origins survey (a large-scale survey of migrants and their children in France) and the Barro-Lee dataset (which contains educational attainment data for 146 countries in 5-year intervals from 1950 to 2010), we reconstructed a direct measure of immigrants’ educational selectivity, as previously developed by Ichou (2014). In short, this measure of ‘relative educational attainment’ re-positioned immigrants in the distribution of educational attainment of the population of the same cohort and gender in the origin country. Placing immigrants’ education in the context in which it was attained enabled us to capture broader dimensions of education and SES that are crucial in determining the health of migrants prior to their arrival.

Migrants are indeed positively selected

First, for all migrants combined, we showed that migrants are very positively selected in terms of their education level (largely originating from above the 80^th percentile in the education distributions of their origin country). Figure 1 shows that migrants from North Africa to France were, on average, positively selected in terms of education from the origin country, with some selection from the middle-lower end of the distribution. On the other hand, migrants from South Europe were, on average, neither positively nor negatively selected. Such variation shows the considerable diversity within immigrant populations in France.

We then tested the effect of this educational selectivity on the size of health disparities between immigrants and natives using three health measures: self-rated health, health limitations and chronic illnesses. For all migrants, those with shorter durations (0-4, 5-9 years) were clearly advantaged in terms of chronic illness (both sexes) and self-rated health (males only). Patterns in the longest duration group (10+ years), on the other hand, were similar to those of natives. As Figure 2 shows, while North African migrants (especially males and recent arrivals) had a health advantage relative to natives born in France, this was not the case for South European migrants in any of the three outcomes. Importantly, although educational level as measured in the host country could not explain these health differences, adjusting for their level of educational selectivity helped explain the Healthy Immigrant Effect in France.

Overall, the study showed that immigrants in France were positively selected in terms of educational attainment in their country of origin, which translated into better health (relative to natives) in the country of destination. In accordance with the UCL-Lancet report (Abubakar et al. 2018), this suggests that rather than damaging health, migrants likely add some value to overall population health.

The better health of migrants does not last

Of course, certain subgroups may require specific health policies. A concerning and common finding was a weakening or loss of the health advantage in groups who have stayed longer in the host country. Among North African males, for example, although the long duration group was at least as positively selected as the short duration group, they had no health advantage. Indirectly, this tells us that time spent in the host country can have a detrimental impact upon immigrants’ health. This may simply reflect an inevitable attenuation of initial selection effects over their duration of stay in France. Or it could be indicative of the adverse effects of exposure in the host country to discrimination or less favourable social conditions than natives.

article also published on www.ined.fr

References

Ichou, Mathieu (2014), “Who they were there: immigrants’ educational selectivity and their children’s educational attainment”, European Sociological Review, 30(6), p. 750-765. x

Ichou Mathieu & Wallace Matthew (2019) “The healthy immigrant effect: the role of educational selectivity in the good health of migrants”, Demographic Research, 40(4), p. 61-94.

Abubakar, Ibrahim, et al. (2018) “The UCL–Lancet Commission on Migration and Health: the health of a world on the move.” The Lancet 392(10164), p. 2606-2654.

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