Healthy ageing in a comparative perspective
Reus Pons, Matias
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Reus Pons, M. (2018). Healthy ageing in a comparative perspective: A study of the health of older migrants and non-migrants across Europe. University of Groningen.
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Healthy ageing
in a comparative
perspective
A study of the health of older migrants and
non-migrants across Europe
ISBN: 978-94-034-0586-5
ISBN (E-publication): 978-94-034-0585-8 Cover design: Remco Wetzels
Lay-out and print by: ProefschriftMaken | www.proefschriftmaken.nl English language editing: Miriam Hils
A study of the health of older migrants and non-migrants across Europe
PhD thesis
to obtain the degree of PhD at the
University of Groningen and the Vrije Universiteit Brussel on the authority of the
Rector Magnificus of the University of Groningen Prof. E. Sterken,
Rector of the Vrije Universiteit Brussel Prof. C. Pauwels,
and in accordance with
the decision by the College of Deans of the University of Groningen. This thesis will be defended in public on
Monday 30 April 2018 at 16.15 hours
by
Prof. F. Janssen Prof. H. Vandenheede Co-supervisor Dr. E.U.B. Kibele Assessment Committee Prof. M. Reineveld Prof. P. Deboosere Prof. P. Bracke Prof. A. Solé Auró
Chapter 1 Introduction 7 Chapter 2 Differences in mortality between groups of older
migrants and older non-migrants in Belgium, 2001 to 2009
29
Chapter 3 Differences in healthy life expectancy between older migrants and non-migrants in three European coun-tries over time
59
Chapter 4 Differences in the health transition patterns of older
migrants and non-migrants in Europe (2004–2015) 79
Chapter 5 Health differences between migrants and non-mi-grants aged 50 to 79 in Europe: the role of integration policies and public attitudes towards migration and migrants (2004–2015)
115
Chapter 6 Conclusion and discussion 153
English summary 175
Nederlandse samenvatting 181
chapter 1
Chapter 1
1.1 InTroducTIon And rEsEArcH quEsTIons
Healthy ageing is being promoted by the European Commission in response to changes in the European population structure, and to the associated changes in health care demand (European Commission, 2015). Healthy ageing strategies are aimed at helping people remain healthy as they grow older. The specific goals of such strategies range from supporting people in maintaining the ability to work at younger older ages, which is itself a protective health factor; to improving the quality of life of older people, and their abilities to live independently at advanced ages (Kristiansen et al., 2016).
However, in addition to growing older, European societies are becoming more multicultural as a result of international migration (Lanzieri, 2011). Compared to non-migrants, migrants face additional health threats due to the challenges they encounter before, during, and after the migration process (International Organi-zation for Migration, 2013). As a result, there are serious concerns about whether healthy ageing is as prevalent among migrants as among non-migrants in Europe (Kristiansen et al., 2016). This question becomes especially relevant in a context in which other forms of health inequality, such as health gaps between countries or between socio-economic groups, are widening (Fouweather et al., 2015; Hu et al., 2016; Mackenbach et al., 2016; Azzopardi-Muscat et al., 2017).
While the issues of migration, ageing, and health are on the political agenda in all European countries, relatively little attention has been paid to the health of older migrants in Europe (Rechel et al., 2011). Under international human rights law, every person has an intrinsic right to ‘the highest attainable standard of health’ (United Nations, 2000), irrespective of nationality or migrant status (International Organization for Migration, 2013). Furthermore, European health care systems and policies are based on a principle of equity (Nørredam & Krasnik, 2011). In addition to these human rights and equality arguments, there are economic arguments for migration: contrary to popular belief, migrants help sustain the European welfare state models (Trummer & Krasnik, 2017). Knowledge about the health of older migrants and non-migrants (International Organization for Migration, 2009), and about the specific health needs of migrants (Diaz et al., 2017), will prove crucial when assessing future health care demand in a culturally diverse Europe, and when seeking to tailor related policies and interventions. Previous research on health inequalities between migrants and non-migrants has
and has rarely focused on the older population. To provide a better understanding of how healthy ageing differs between migrants and non-migrants, there is a need for studies that go beyond the national level by comparing the health of migrants in different countries; studies that take the country-of-residence contex-tual effects into account; and studies that go beyond the typical cross-sectional approach (Kristiansen et al., 2016; Agyemang et al., 2017). Moreover, to gain a better understanding of the health risks and benefits involved with migration, a multidisciplinary approach is needed (Agyemang et al., 2017; Hanefeld et al., 2017).
This study aims to provide crucial new knowledge on the health of older migrants in Europe. The overall objective is to assess differences in health between older migrants and non-migrants across Europe, and to explain these differences using a range of individual and contextual factors.
The study was guided by the following two general research questions:
How does the health of older migrants and non-migrants differ across European countries, and how do these differences evolve over time and with age?
To what extent are the health differences between older migrants and non-migrants in Europe explained via individual and contextual factors?
This study is innovative in a number of ways. First, the study focuses specifically on the older population. Second, a cross-country comparative perspective is taken. Third, the health situations of older migrants and non-migrants are analysed from both cross-sectional (including time trends) and longitudinal perspectives. Fourth, the study considers a range of health indicators, including mortality and measures of both physical and mental health, as well as a combined measure of general health and mortality. Finally, in addition to individual determinants of health, the contextual effect of the country of residence in explaining health differences between older migrants and non-migrants is considered.
This study focuses on older migrants from the first generation living in western and southern European countries. Older migrants were defined as individuals aged 50 and older who were born in a country other than their current country of residence.
Chapter 1
1.2 oldEr mIgrAnTs In EuropE
The term ‘migrant’ is defined differently in the literature and by various organisa-tions. Generally, an international migrant is defined as someone who moved to a country he/she was not born in, and has made that country his/her usual place of residence (UNESCO, 2017). However, any population movement across an international border, regardless of the length, composition, and causes of the move, may also be defined as international migration (International Organization for Migration, 2017). Therefore, it seems reasonable to assume that migrants are a highly heterogeneous group. Indeed, migrants differ in their origins, socio-economic status, cultures, and reasons for migration (Diaz et al., 2017).
From 2000 onwards, the migrant population has been growing faster than the total population in the world (United Nations, 2016). Worldwide, 244 million people – including 76 million people living in Europe – are currently classified as international migrants (United Nations, 2016). The combination of current and past migration trends, together with the general ageing of the population, have led to increasing population shares of older migrants in European countries (Lanzieri, 2011).
Most of the older migrants currently living in western Europe immigrated after World War II. Three main periods of post-war migration can be distinguished. Between the 1950s and the 1973 oil crisis, countries in western Europe received migrants from neighbouring countries and former colonies, as well as labour migrants (guest workers), mainly from southern Europe, Turkey, and north Africa (Jennissen et al., 2006; van Mol & de Valk, 2016). The second period, which lasted until the end of the 1980s, was characterised by a sudden end to labour migration. While some migrants (mainly southern Europeans) returned to their countries of origin, the majority settled in the receiving countries, and migration continued in the form of family migration (van Mol & de Valk, 2016). A third period, which started in the 1990s after the fall of the Iron Curtain, was characterised by an increase in intra-European mobility, and by an increasing influx of asylum seekers (Salt, 2011; van Mol & de Valk, 2016).
The history of migration outlined above generally applies to all north-western Eu-ropean countries. Most of the older migrants currently living in western Europe are first-generation migrants who arrived in one of the three periods described above (de Valk & Schans, 2008), and thus entered the destination countries from
It is, however, important to note that the immigration patterns of European countries are not identical. First, the specific origins of migrants may differ based on the geographical position and the former colonial ties of each country. Fur-thermore, whereas most labour migrants to continental European countries came from the Mediterranean area (Lanzieri, 2011), most labour migrants to the United Kingdom came from New Commonwealth countries (Landman & Cruickshank, 2001). In addition, in certain countries substantial numbers of labour migrants also came from neighbouring countries: e.g., there was an influx of Irish to the United Kingdom, and of Finns to Sweden (Castles et al., 2014). Second, large numbers of ethnic Germans (‘aussiedler’) migrated to Germany from the 1950s onwards, first from central Europe, and later (after 1989) from the former Soviet Union (Jennissen et al., 2006; van Mol & de Valk, 2016). The ‘aussiedler’ have never been officially considered migrants, and were granted immediate citizenship (Castles et al., 2014). However, they can be considered de facto migrants given that their backgrounds are diverse, their socio-economic status tends to be low, and their German language skills are often limited (Münz & Ohliger, 1998). The history of migration to southern European countries such as Italy and Spain is somewhat different. These countries, which had traditionally been countries of emigration, have started to receive immigrants in recent decades. Initially, economic development and the establishment of democratic regimes in many southern European countries facilitated the return of many nationals during the late 1970s and the 1980s (Domingo Valls, 2002). Later, from the late 1990s on-wards, immigration to southern Europe diversified, and included migrants from Latin America, Africa, and elsewhere in Europe (Salt, 2011; Castles et al., 2014). Thus, most of the older migrants currently living in southern European countries have been in these countries for shorter periods of time than their counterparts in western European countries. Moreover, some migrants to southern Europe are wealthy north-western Europeans who have chosen to retire there (Warnes & Williams, 2006).
1.3 dIffErEncEs In HEAlTH bETwEEn mIgrAnTs And non-mIgrAnTs
Most previous migrant health research has focused on the total population or the younger adult population. The results of these studies vary depending on whether the outcome measure used was mortality, cause-specific mortality, self-perceived health, disability, mental disorders, or certain chronic diseases.
Chapter 1
A number of these studies have found that overall mortality was lower for adult migrants than for adult non-migrants in several European countries, including Belgium (Deboosere & Gadeyne, 2005), Finland (Lehti et al., 2017), France (Boulogne et al., 2012), Germany (Razum et al., 1998), Norway (Syse et al., 2016), and the United Kingdom (Wallace & Kulu, 2015; Hayes et al., 2017). Given the relatively low socio-economic status of migrants, this migrant mortality advantage has often been called the ‘migrant mortality paradox’. A less restrictive version of the paradox postulates that in cases in which an overall migrant mortality advantage is not observed, migrants may still have a mortality advantage when compared with non-migrants with a similar socio-economic status (Riosmena et al., 2013).
Regardless of the potential existence of an overall mortality advantage, adult migrants still face certain cause-specific mortality disadvantages. Migrants, and especially those of non-western origin, tend to have higher mortality from infec-tious diseases, diabetes, and stomach and liver cancers (Landman & Cruickshank, 2001; Bos et al., 2004; Deboosere & Gadeyne, 2005; Boulogne et al., 2012; Rechel et al., 2013; Kristiansen et al., 2016). The patterns of cardiovascular mortality differences appear to be more complex among migrant populations. For example, cardiovascular mortality is especially high among migrants from south Asia, and is lower among migrants from certain other countries, such as Turkey and Morocco (Landman & Cruickshank, 2001; Deboosere & Gadeyne, 2005; Kristiansen et al., 2016). Moreover, Muslim migrants tend to have relatively low mortality from alcohol-related causes and from certain external causes of death, such as suicide (Deboosere & Gadeyne, 2005; Lehti et al., 2017).
In terms of general health, migrants generally have better health outcomes than non-migrants at the time of arrival, but experience steeper rates of health decline with age and increasing length of residence (Newbold, 2005; de Maio & Kemp, 2010; So & Quan, 2012; Kim et al., 2013). Thus, migrants progressively lose their initial health advantage with increasing duration of residence (Norredam et al., 2014; Vandenheede et al., 2015; Syse et al., 2016). Accordingly, most previous studies have shown that compared to non-migrants, older migrants living in Europe – and especially those of non-western origin – are more likely to be in poor health, to suffer from health complaints and chronic conditions, and to have disabilities or mental disorders (Solé-Auró & Crimmins, 2008; Aichberger et al., 2010; Lanari & Bussini, 2012; Carnein et al., 2014).
Previous migrant health research has also clearly shown that migrants are not a homogeneous group. Variations in the individual characteristics of migrants, especially in terms of age and duration of stay (see previous paragraph), country of origin (see paragraph on cause-specific mortality), and country of residence largely explain the varying results found in studies on migrant health (e.g., Diaz et al., 2017).
The conditions in the country of residence play a role in shaping the health of both migrants and non-migrants. Agyemang et al. (2017) showed that in various European countries, the prevalence of obesity and diabetes was higher among migrants than non-migrants, but that the patterns of obesity and diabetes preva-lence among the migrants living in each of these countries resembled the patterns of prevalence among the non-migrants in each respective country. Moreover, there are indications that the context of reception affects the rates of health deterioration with age. While migrants in the United States were found to have better general health outcomes than non-migrants at ages 50–60 (Gubernskaya, 2014; Garcia & Reyes, 2017), the opposite was shown to be the case in Europe (Solé-Auró & Crimmins, 2008; Aichberger et al., 2010; Lanari & Bussini, 2012; Carnein et al., 2014). These results suggest that the patterns of healthy ageing among migrants vary across countries. It should be emphasised that the migrant groups studied in the United States, mainly Black and Hispanic migrants (e.g., Markides & Eschbach, 2005), differ from the migrant groups distinguished in Europe, i.e. migrants with a western (European) or non-western background (e.g., Vandenheede et al., 2015).
Most previous migrant health research focused on the total or the younger adult population. In addition, most studies in Europe examined a single outcome health measure, country of settlement, and/or origin group. In light of the findings de-scribed above, and given that mortality and morbidity at older ages contribute the most to the total burden of disease, and therefore represent major public health issues, a separate focus on the older population is clearly needed. Moreover, cross-country comparisons will enable to formulate generalised conclusions, and may al-low to relate potential differences between countries to specific contextual effects. Furthermore, longitudinal, preferably life course approaches can be used to assess how health inequalities between migrants and non-migrants are shaped through the lives of individuals, and how these health inequalities can lead to distinct forms of inequality at different stages in the life course. Finally, it may be relevant to consider a range of health indicators, including mortality and measures of both physical and mental health, as well as a combined measure of mortality and morbidity.
Chapter 1
Accordingly, this study aims to address the research gaps described above by analysing health differences between migrants and non-migrants in Europe with a specific focus on the older population, while taking a cross-country comparative perspective, incorporating both cross-sectional and longitudinal approaches, and including different dimensions of health. More specifically, this thesis compares the health situations of older migrants with those of older non-migrants across Europe based on their levels of overall and cause-specific mortality, general health, and prevalence of diabetes and depression. A combined measure of mor-tality and general health – i.e., healthy life expectancy – is used to bring together the knowledge gained from both mortality and morbidity patterns and trends over time. Examining changes in health with age will also allow to provide more nuanced answers to the question of whether healthy ageing is as prevalent among migrants as among non-migrants.
1.4 ExplAInIng HEAlTH dIffErEncEs bETwEEn mIgrAnTs And non-mIgrAnTs
Socio-economic status, which can be regarded as a measure of an individual’s position in society, is often based on education, job status, and income; and is in-versely associated with health (Adler et al., 1994). Thus, the lower socio-economic status (e.g., Gushulak et al., 2010) of migrants is one of the main factors that explain their health disadvantages relative to non-migrants. In the section below (1.4.1), how low socio-economic status could result in poor health outcomes is discussed. Although the ‘social determinants of health’ framework is rather general, the section pays special attention to the question of how this framework could be applied to explain the differences in the health outcomes of migrants and non-migrants. The subsequent section (1.4.2) delves into how this framework combines with specific risks migrants face before, during, and after migration to explain migrant health outcomes, effectively taking a life course perspective. In addition, this section presents the main theories that seek to explain the health differences between (older) migrants and non-migrants.
1.4.1 The social determinants of health framework
The WHO model on the social determinants of health (Solar & Irwin, 2010) postulates that the association between socio-economic status and health is medi-ated via three intermediate determinants or pathways: material, psychosocial, and behavioural and biological factors. The association of material factors, such as
in-and the association between behavioural factors in-and health (e.g., Abraído-Lanza et al., 2005), are rather straightforward. Stress is one of the main psychosocial fac-tors that could cause physiological changes, which, if prolonged, could result in a dysregulation of inflammatory responses of the body leading to a wide range of physical and mental diseases (Cohen et al., 2007; Iwata et al., 2013). Furthermore, these three intermediate pathways are not independent, but are interrelated. For instance, both poor living conditions and stress are likely to have a negative influ-ence on health-related practices, such as diet and exercise.
Other similar frameworks exist. For instance, the model developed by Myers (2009) distinguishes psychosocial adversities (stresses) from psychosocial capaci-ties (coping resources). Indeed, migrants also have a wide range of socio-cultural coping strategies, including social networks and spiritual resources (Kristiansen et al., 2016). In addition, Myers’ (2009) model separates behavioural from biological factors.
These material, psychosocial, and behavioural pathways are embodied within a broader policy and societal context (Solar & Irwin, 2010). When looking at health inequalities between migrants and non-migrants, it is important to distinguish specific aspects of the policy and societal contexts that may affect migrants in particular. The existing studies that have explored these issues mainly focused on racism or discrimination (e.g., Ikram et al., 2015b). Integration policies and public attitudes towards migration and migrants have been identified as potentially im-portant contextual effects that could explain migrants’ health outcomes in various destination countries (Agyemang et al., 2010; Castañeda et al., 2015). However, these effects have received little attention in the existing scientific research (Huijts & Kraaykamp, 2012; Ikram et al., 2015; Malmusi, 2015a), and are not yet well understood.
Finally, the ‘social determinants of health’ framework also includes the role of the health care system (Solar & Irwin, 2010). While the health care system is clearly integrated into the policy and societal contexts, it also cuts across the three intermediate determinants of health. Policy and societal values and attitudes determine access to health care via legal and actual entitlements by minimising formal (legal entitlement) and informal barriers (e.g., culturally adapted services), (Nørredam & Krasnik, 2011). However, informal barriers also operate via mate-rial, behavioural, and psychosocial factors. For instance, an individual’s health literacy (psychosocial) and financial situation (material) may condition his/her actual care-seeking behaviour. This might explain why migrants tend to make
Chapter 1
less use of preventive services and more use of emergency services than non-migrants (Nørredam & Krasnik, 2011).
1.4.2 Explaining migrant health inequalities over the life course
While it has often been shown that migrants have a health advantage at the time of arrival, this finding is unexpected given migrants’ relatively low socio-economic status. This advantage has largely been explained by selection effects, since most of the people who migrate are healthy. This effect is also known as ‘positive health selection’ or as the ‘healthy migrant effect’ (Razum et al., 1998; Abraído-Lanza et al., 1999; Palloni & Arias, 2004; Rechel et al., 2013; Norredam et al., 2014; Vandenheede et al., 2015). ‘Negative health selection’, which is also known as the ‘salmon bias effect’, occurs when migrants return to their home country later in life when their health declines, leaving a healthier migrant population in the destination country (Razum et al., 1998; Palloni & Arias, 2004). Previ-ous studies have shown that negative health selection does not play a major role in Europe (Razum et al., 1998; Vandenheede et al., 2015). Another explanation that is often given for migrants’ health advantage at the time of arrival is that migrants tend to engage in better health behaviours than non-migrants, including having healthier diets and lower levels of smoking and drinking (Abraído-Lanza et al., 2005). Furthermore, among migrants from less developed countries, the improved socio-economic, sanitary, and health care conditions in the destination country might be associated with a decline in the prevalence of and the mortality due to infectious diseases, and maternal and childhood conditions. It is also likely that, even if these migrants adopt risky behaviours from the host society, the effects of these behavioural change would not have a manifest impact on chronic diseases for many years (Law & Wald, 1999; Razum & Twardella, 2002).
This initial migrant health advantage tends to wear off with increasing length of residence in the host country (Vandenheede et al., 2015). The steeper rates of health decline among migrants with age and length of residence have often been explained using the ‘cumulative disadvantage’ theory (Angel et al., 2001; Dannefer, 2003). Migrants generally experience a range of hardships, including material deprivation, poor working conditions, social isolation, psychosocial stress, and limited access to services (Gushulak et al., 2010). ‘Acculturation’ hypotheses (Abraído-Lanza et al., 2005) imply that migrants adopt some of the cultural patterns of the host society, progressively diminishing the cultural and social distance between groups. In principle, however, acculturation does not always imply the assimilation of minority groups to the main culture, as cultural
seems to suggest that migrants tend to abandon their relatively healthy lifestyles and adopt health-damaging behaviours from the host society (Abraído-Lanza et al., 2005; Kunst et al., 2011). However, most chronic conditions have long latency periods from the adoption of a risky behaviour to the clinical manifestation of a disease (Law & Wald, 1999; Razum & Twardella, 2002). Therefore, the cumulative effects of having a low socio-economic status over a migrant’s lifetime and/or having adopted unhealthy lifestyles may not be visible until older ages, many years after migration. This process effectively transforms the initial migrant health advantage into a health disadvantage vis-à-vis older non-migrants. Studies using longitudinal data enable to draw conclusions about causality, and therefore allow to test whether individual factors such as socio-economic status or health-related behaviours explain health outcomes later in life. So far, there has been no study that has analysed the health differences between older migrants and non-migrants in Europe from a longitudinal point of view. This aspect seems especially relevant given that socio-economic and lifestyle changes in midlife have been shown to be associated with health outcomes later in life (Hessel & Avendano, 2016; Berstad et al., 2017).
Life course perspectives enable to better understand how all these factors and processes take place over the life courses of individuals, and thus shape health inequalities between (older) migrants and non-migrants. The health of migrants results from a complex interplay of exposures (legal, social, economic, cultural, behavioural) during the life course, in addition to specific health challenges related to migration itself (International Organization for Migration, 2006). These expo-sures take place during the four phases of migration: namely, before migration, during migration, after settlement, and (eventually) upon return (Gushulak et al., 2010). An alternative, yet similar model would classify these exposures according to whether they take place in the country of origin, during the process of migra-tion, or in the country of destination; while also considering the effects derived from the motives for migration (Spallek et al., 2011).
The different pathways (material, behavioural, and psychosocial) in the ‘social determinants of health’ framework, as well as the overarching policy and societal contexts, influence the different stages of migrants’ lives. The context of origin affects migrants’ baseline health status through the physical, socio-economic, and political environment, and by shaping health-related behaviours and practices (Razum & Twardella, 2002; Abraido-Lanza et al., 2005; Deboosere & Gadeyne, 2005). Most of the existing studies that looked at health differences between older migrants and non-migrants (cross-sectional or longitudinal) did not
distin-Chapter 1
guish migrants by country of origin. During the movement phase, travel condi-tions – which may be characterised by perilous physical environments, abuse and violence, and a lack of health services – may have negative effects on the health of migrants (Gushulak et al., 2010). After their arrival, the migrants’ working and living conditions, changes in health-related behaviours, degree of social isola-tion, and access to (adapted) health services are the major health determinants (Gushulak et al., 2010). A country with inclusive policies and a tolerant and open society is especially likely to achieve a favourable context for migrants and their health (International Organization for Migration, 2013). Since migrants often return to their country of origin to visit relatives and friends, it is also impor-tant to consider the risk of acquiring certain diseases, especially in tropical and low-income areas, which might later be imported into the country of residence (Gushulak et al., 2010). In addition to the hazards migrants face during the four phases of migration, there are a series of cross-cutting factors that are important to consider throughout the lives of migrants, including age, gender, and genetics (International Organization for Migration, 2013).
This study aims to address some of the research gaps specified above by taking a longitudinal perspective, which may allow to draw more nuanced conclusions about causality; and by investigating the effect of the context in the country of residence (in addition to the effect of individual characteristics). More specifically, this thesis explores the extent to which socio-economic status (highest level of education, job status, and housing status); health-related behaviours (body mass index, smoking, and physical activity); integration policies; and public attitudes towards migration and migrants explain migrant health inequalities.
1.5 THIs sTudy
1.5.1 Approach
To answer the research questions above, this study employs a novel and multidis-ciplinary approach. The study combines theory and methods from demography, sociology, and epidemiology. This thesis explores the health situations (and their trends over time) of migrants and non-migrants, with a focus on the older population, using both cross-sectional and longitudinal approaches. The relative importance of individual and contextual factors in explaining inequalities in health between older migrants and non-migrants is also explored. At the same time, a European cross-country comparative perspective is used to describe and
that different health indicators capture different aspects of health or different stages in the disablement process (Jagger et al., 2011), a range of health indica-tors are considered, including various measures of mortality, subjective overall health (self-rated health), physical health (diabetes prevalence), and mental health (depression).
1.5.2 Setting
This study focuses on older individuals (aged 50 and older) living in western and southern Europe. A distinction is made between non-migrants and migrants from the first generation. The latter group is defined as those who were born abroad and who migrated to their current country of residence at some point during their life course. Although this definition of migrant might not be the most accurate in theoretical terms, it has the advantage that it is easily measurable and ensures the comparability of data for different countries. The migrants are further subdivided into those of western and non-western origin, according to the definition used by Statistics Netherlands (CBS, 2017). While this is a rather broad distinction, it provides important insights into the effects of the context of origin of migrants, and thus goes beyond a simple classification of migrants into a single generic group.
1.5.3 Data and methods
A variety of data and methods are used, including both macro (population-level) and micro (individual-level) approaches. The data and methods are tailored to the specific requirements of each research question, as detailed below.
The data used to analyse cross-sectional health differences between older mi-grants and non-mimi-grants derive from national registers, censuses, and health surveys in Belgium, the Netherlands, and England and Wales (2001–2011). Data from the 2001 Belgian census were linked with the population and mortality registers, allowing a mortality follow-up until 2009. Standardised mortality rates and mortality rate ratios (Poisson regression) were applied to assess all-cause and cause-specific mortality differences between older migrants and non-migrants in Belgium (2001–2009). Mortality data from the death registers of Belgium, the Netherlands, and England and Wales were combined with general health data. These data were derived from the census in the cases of Belgium and England and Wales, and from the Health Survey (previously under the Permanent Research on the Living Situation survey) in the case of the Netherlands. Life table calculations (life expectancy, healthy life expectancy) allowed to analyse differences in both mortality and health between older migrants and non-migrants, and to compare
Chapter 1
the inequalities between these three countries, and over time (2001–2011). Fur-thermore, decomposition techniques were used to illustrate that inequalities in mortality and in general health do not necessarily follow a similar pattern, which highlights the added value of using a combined measure of health and mortality. Data to analyse the differences in health transitions between older migrants and non-migrants, and to assess the extent to which individual and contextual factors explain migrant inequalities in health and in health transitions, were derived from the Survey of Health, Ageing and Retirement in Europe (SHARE, 2004–2015). SHARE collects data on health, socio-economic status, and the social networks of people aged 50 and older in various European countries (Börsch-Supan, 2013). Additionally, to analyse the role of the context in the country of residence, data on country-level integration policies (Niessen et al., 2007) and public attitudes towards migration and migrants (ESS, 2014) were combined with SHARE data. A micro approach was applied, and logistic regression models were performed to assess the influence of individual determinants of health (cross-sectional, and longitudinal approaches), and the influence of the context in the country of residence (cross-sectional approach only), in explaining migrant inequalities in health. Furthermore, the longitudinal approach provided additional insights into how migrant health inequalities at older ages are shaped over the life courses of individuals.
Data derived from registers and census have the advantage of including the whole population within a country or region. While this has substantial benefits in terms of sample size, the available information in these data sources is somewhat limited, and certain comparability problems can arise across countries and over time. In contrast, surveys may provide more detailed data, and in the case of European-wide surveys such as SHARE, more comparable data across countries. Nevertheless, such surveys are rarely designed to adequately sample the migrant population. Thus, the use of survey data can result in small migrant sample sizes and problems with the generalisability of findings.
1.6 ouTlInE of THE THEsIs
This thesis consists of six chapters. After this first introductory chapter, chapters two to five address specific sub-questions that will help answer the overarching research questions outlined above. In the last chapter, the findings are discussed
All of the chapters aim to provide an answer to the question: How does the health of older migrants and non-migrants differ across European countries, and how do these differences evolve over time and with age? Chapters 4 and 5 addition-ally aim to provide an answer to the question: How can the health differences between older migrants and non-migrants in Europe be explained via individual and contextual factors?
More specifically, chapter 2 investigates whether migrants in Belgium maintain an overall mortality advantage at older ages, and how this advantage is reflected in cause-specific mortality. Specific causes of mortality are in turn associated with specific exposures and health-related behaviours, which allows to offer some pre-liminary conclusions about the genesis of mortality differences between migrants and non-migrants.
Chapter 3 investigates the issue further by considering other health domains beyond mortality, and assesses the differences in healthy life expectancy between older migrants and non-migrants in Europe. Furthermore, chapter 3 takes a cross-country comparative perspective by studying this issue in three different European countries: Belgium, the Netherlands, and England and Wales. These countries were chosen because they have similar life expectancies at birth, similar migration histories, and reliable data.
Chapter 4 takes a rather novel longitudinal perspective, and analyses how health transitions differ between older migrants and non-migrants in Europe. The longitudinal view allows to assess how migrant health inequalities at older ages in Europe are generated over time at the individual level. In addition, a range of individual health-related factors, including socio-economic and demographic characteristics and health-related behaviours, are included to assess their role in explaining the differences in health transitions between older migrants and non-migrants in Europe.
Chapter 5 investigates the extent to which integration policies and public at-titudes towards migration and migrants explain the health differences between older migrants and non-migrants in 10 European countries: Austria, Belgium, Denmark, France, Germany, Italy, the Netherlands, Spain, Sweden, and Switzer-land. Additionally, various individual-level factors are included to help explain the health differences between older migrants and non-migrants. Furthermore, this chapter incorporates several dimensions of health, including measures of overall (self-rated health), physical (diabetes prevalence), and mental health (depression),
Chapter 1
which allow to explore how the health differences between migrants and non-migrants vary according to the health indicator considered.
Finally, in chapter 6, the main findings of the PhD thesis as a whole are sum-marised and discussed, along with their implications for future research and policy.
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chapter 2
Differences in mortality between groups of older migrants
and older non-migrants in belgium, 2001 to 2009
This chapter is based on: Reus-Pons M, Vandenheede H, Janssen F, Kibele EUB (2016). Differences in mortality between groups of older migrants and older non-migrants in Belgium, 2001–09. European Journal of Public Health 26(6):992-1000.
Abstract: European societies are rapidly ageing and becoming multicultural. We studied differences in overall and cause-specific mortality between migrants and non-migrants in Belgium specifically focusing on the older population. We performed a mortality follow-up until 2009 of the population aged 50 and over living in Flanders and the Brussels-Capital Region by linking the 2001 census data with the population and mortality registers. Overall mortality differences were analysed via directly age-standardised mortality rates. Cause-specific mortality differences between non-migrants and various western and non-western migrant groups were analysed using Poisson regression models, controlling for age (model 1) and additionally controlling for socio-economic status and urban typology (model 2). At older ages, most migrants had an overall mortality advantage relative to non-migrants, regardless of a lower socio-economic status. Specific migrant groups (e.g. Turkish migrants, French and eastern European male migrants, and German female migrants) had an overall mortality disadvantage, which was, at least partially, attributable to a lower socio-economic status. Despite the general overall mortality advantage, migrants experienced higher mortality from infec-tious diseases, diabetes-related causes, respiratory diseases (western migrants), cardiovascular diseases (non-western female migrants), and lung cancer (western female migrants). Mortality differences between older migrants and non-migrants depend on cause of death, age, sex, migrant origin, and socio-economic status. These differences can be related to lifestyle, social networks, and health care use. Policies aimed at reducing mortality inequalities between older migrants and non-migrants should address the specific health needs of the various migrant groups, as well as socio-economic disparities.
Chapter 2
2.1 InTroducTIon
The study of mortality differences between older migrants and non-migrants in Europe is important for a number of reasons. Health is a universal human right, irrespective of nationality or migrant status (International Organization for Migration, 2013). Accordingly, the European Parliament encourages EU member states to tackle health inequalities, including those between migrants and non-migrants (European Union, 2012). This becomes even more relevant in a context where European societies are becoming older and more multicultural (Lanzieri, 2011).
Previous studies on all-cause mortality differences between migrants and non-migrants mainly focused on the total or younger adult population. These studies found that migrants in Europe often have an overall mortality advantage relative to non-migrants, despite generally having a lower socio-economic status, which is known as the ‘migrant mortality paradox’ (Razum et al., 1998; Abraído-Lanza et al., 1999; Palloni & Arias, 2004).
However, relative mortality differences between migrants and non-migrants vary by country of residence, migrant origin, sex, and age (Agyemang et al., 2012). Since non-migrants’ mortality differs across countries (Bhopal et al., 2012), rela-tive mortality inequalities cannot be strictly compared. However, similar relarela-tive positioning may indicate ‘country of origin’ effects. While in France most migrant groups had a mortality advantage over non-migrants (Boulogne et al., 2012), in England and Wales most migrant groups experienced higher mortality than non-migrants (Landman & Cruickshank, 2001). In the Netherlands, mortality was higher among most male migrant groups compared with non-migrants, while differences were not statistically significant among females (Bos et al., 2004). In Belgium, adults from southern Europe, Morocco, and Turkey had lower mortality risks than non-migrants, while French males and sub-Saharan females experienced higher risks (Deboosere & Gadeyne, 2005). Compared to the non-migrant popu-lation, most migrant groups in France and the Netherlands were reported to have higher mortality at younger ages, but lower mortality at older ages (Uitenbroek & Verhoeff, 2002; Bos et al., 2004; Boulogne et al., 2012).
Previous studies showed that the overall mortality advantage of migrants could only be partially explained by positive health selection—i.e., the fact that predomi-nantly young and healthy people migrate (Razum et al., 1998; Abraído-Lanza et
off with length of stay (Vandenheede et al., 2015). Negative health selection— i.e., the return of unhealthy migrants to their country of origin—appears to be an unlikely explanation in Europe (Razum et al., 1998; Abraído-Lanza et al., 1999; Vandenheede et al., 2015). Therefore, mortality differences between older migrants and non-migrants must be attributable to other mechanisms, such as health-related lifestyles (Abraído-Lanza et al., 2005), social and migrant networks (de Valk et al., 2011), and health care use (Nørredam & Krasnik, 2011), which often change in a migration context (Marmot et al., 1984). The analysis of cause-specific mortality differences enables to disentangle some of these mechanisms via specific risk profiles related to specific causes of death.
Previous studies on relative cause-specific mortality differences showed that most migrants, especially those of non-western origin, had excess mortality from infec-tious diseases, diabetes, and homicide; and low mortality from all cancers com-bined (Landman & Cruickshank, 2001; Singh & Siahpush, 2001; Bos et al., 2004; Deboosere & Gadeyne, 2005; Boulogne et al., 2012; Vandenheede et al., 2015). Cardiovascular and cerebrovascular disease mortality tends to be high among mi-grants from eastern Europe, South Asia, the Caribbean, and sub-Saharan Africa; and low among migrants from Morocco and Turkey (Landman & Cruickshank, 2001; Bos et al., 2004; Deboosere & Gadeyne, 2005; Boulogne et al., 2012). To our knowledge, no study so far analysed relative cause-specific mortality dif-ferences between migrants and non-migrants specifically focusing on the older population. Our aim is therefore to analyse overall and cause-specific mortality differences between different groups of older migrants and non-migrants. We performed our analysis in Belgium, one of the forerunners in Europe in the transition to an older and more multicultural society. Furthermore, Belgium currently has a larger proportion of older migrants than other traditional Eu-ropean immigration countries, such as Germany, the United Kingdom, and the Netherlands (de Valk et al., 2011).
2.2 mETHods
We studied first-generation migrants and non-migrants aged 50 years and older living in Flanders and the Brussels-Capital Region at the time of the 2001 census. We performed a mortality follow-up of these individuals until 2009. The final
Chapter 2
population included in the analyses was 2,356,122, of whom 92.3 % were non-migrants and 7.7 % were non-migrants.
We defined migrants as individuals born outside Belgium and with a foreign nationality at birth. We classified migrants according to their nationality at birth into two main groups: western and non-western (Vandenheede et al., 2015). We additionally distinguished more specific migrant groups, including the main nationalities of older migrants in Belgium: Dutch, French, German, Moroccan, and Turkish migrants; southern European migrants, grouped together since most of them had arrived as ‘guest workers’ (de Valk et al., 2011); and eastern Euro-pean migrants, grouped together since most of them were political refugees or belonged to ethnic minorities (Jennissen et al., 2006). Second-generation migrants (N = 20,936) were excluded, since their mortality outcomes likely differ from both those of non-migrants and those of first-generation migrants.
Data on age, sex, nationality at birth, education, housing status, and urban typol-ogy were derived from the 2001 census. Census data were linked with the popula-tion and mortality register data in two steps. First, the census was linked with population register data on emigration and all-cause mortality via a personal ID number (100 % linkage). Censored cases consisted of people who left Flanders and the Brussels-Capital Region during the follow-up period. Information on the cause of death was then obtained by linking these data with the mortality register using an identification key (98 % of the cases linked).
The classification of the underlying causes of death and the respective ICD-10 codes included in each category are shown in Table 2.1. This classification takes into account the most important causes of death at older ages, the potential risk factors, and ensures comparability with classifications from previous studies (Deboosere & Gadeyne, 2005; Vandenheede et al., 2015).
All of the analyses were performed separately by sex.
We analysed overall mortality differences via direct age-standardised mortality rates (ASMR) over the period 2001–2009 for the different groups of older mi-grants and non-mimi-grants, considering the total older population in Flanders and the Brussels-Capital Region in 2001 as the standard. We calculated 95 % confi-dence intervals (CI) for the ASMR as detailed by Curtin & Klein (1995).
Table 2.1. Selected cause of death groups with International classification of diseases (Icd) codes
Cause of death ICD-10
Infectious diseases A00-B99
Neoplasms (all) C00-D48
Lung cancer C33-C34
Breast cancer C50
Prostate cancer C61
Cardiovascular diseases (all) I00-I99
Ischaemic heart disease I20-I25
Heart failure I50
Cerebrovascular disease I60-I69
Respiratory diseases J00-J99
Diabetes mellitus E10-E14
Alcohol-related mortality F10, G31.2, G62.1, I42.6, K29.2, K70, K73, K74.0-K74.2,
K74.6, K86.0, X45, X65, Y15
External causes (all) V00-Y84
Suicide X60-X84, Y87
Symptoms and ill-defined conditions
R00-R99
The analysis of cause-specific mortality differences required us to weight our data. While it was possible to link the census and register data with the mortality register data for 98 % of the population, the proportion of unlinked cases was considerably higher for some migrant groups (Table 2.2). We calculated simple ra-tio weights (Fawcett et al., 2002) based on sex, age, nara-tionality at birth, educara-tion, and urban typology for those who died during the interval. We calculated ASMR for the different causes of death to assess the contribution of each cause of death to the overall ASMR of the different groups of older migrants and non-migrants. Relative mortality differences over the study period were analysed using weighted Poisson regression models for each cause of death. From these models, we derived mortality rate ratios (MRR) and their 95 % CI, for the different groups of older migrants relative to older non-migrants. The natural logarithm of the person-years at risk was included in the models as the offset variable. Model 1 controls for age, whereas model 2 additionally controls for socio-economic status (education and housing status) and urban typology. For this purpose only, we additionally considered the associated and intermediate causes of death for alcohol- and diabetes-attributable mortality, since the effects of alcohol on health
Chapter 2
are often underestimated at older ages (Hoeck & van Hal, 2012) and diabetes is often associated with mortality without being the underlying cause (Vandenheede et al., 2013).
Table 2.2. Unlinked deaths by sex and origin group
Origin group Males Females Deaths % Deaths % Total population 5,163 2.12 4,888 1.88 Non-migrants 3,704 1.61 3,873 1.58 Migrants 1,459 10.25 1,015 7.06 Western migrants 834 7.54 624 4.98 German migrants 34 5.36 41 2.44 French migrants 107 6.5 118 4.88 Dutch migrants 162 5.28 86 2.84
Southern European migrants 350 11.38 211 9.85
Eastern European migrants 113 7.23 121 5.67
Other western migrants 68 6.34 47 4.18
Non-western migrants 625 19.72 391 21.16
Turkish migrants 199 24.39 128 23.4
Moroccan migrants 340 21.79 200 25.51
Other non-western migrants 86 10.84 63 12.19
Data source: Belgian 2001 census linked to National Register (2001-2009)
Age was defined as a categorical variable in five-year age groups up to 85+. Education consisted of four categories (up to primary, lower secondary, upper secondary, and tertiary education). Housing status was defined as a compound variable including both housing quality and tenure (Vandenheede et al., 2013). Urban typology distinguished between central cities, suburbs, and non-urban municipalities (Luyten & van Hecke, 2007). The unweighted regression results are available in a supplement at the end of this chapter (Tables 2.S.1 and 2.S.2). 2.3 rEsulTs
The ASMR of older non-migrants were 31.4 deaths per 1,000 (95 % CI 31.3–31.6) for males and 27.7 deaths per 1,000 (27.6–27.8) for females (Table 2.3). Migrants, especially those of western origin, tended to have lower mortality than non-migrants. Mortality was particularly low among Moroccan males (ASMR 23.0,
