Migration and depression: A comparative analysis between european countries

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Master

Reference

Migration and depression: A comparative analysis between european countries

ANDREATOU, Adamantia

Abstract

Migration is a risk factor for depression, however little is known on how the different migrant integration policies followed by the host countries may influence migrants' depression risk.

Using the data from the European Social Survey carried out the period of 2014-2015 and the overall score of the Migrant Integration Policy Index (MIPEX 2015), a selected sample of countries is divided in two group of countries based on whether they follow more or less inclusive integration policies. Natives' attitudes towards migrants and migrants' social and socioeconomic characteristics are tested in relationship with migrants' depression risk for the two groups of countries. Country-level analysis shows that countries with higher depression risk do not necessarily have more negative attitudes towards immigrants. Multivariate logistic regression analysis indicates that for both groups of countries the most prominent predictor for depression is permanent medical conditions and disability, followed by low socioeconomic conditions and low social support. On the other hand, discrimination is a predictor only for the countries following [...]

ANDREATOU, Adamantia. Migration and depression: A comparative analysis between european countries. Master : Univ. Genève, 2019

Available at:

http://archive-ouverte.unige.ch/unige:114225

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A master thesis in Socioeconomics, orientation Demography

Student: Adamantia Andreatou

Professor: Philippe Wanner

Migration and depression :

A comparative analysis between European countries

January 2019

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Acknowledgments

First and foremost, I would like to express my gratitude to my thesis advisor Philippe Wanner for his precious guidance and comments that have been a constant source of encouragement in shaping this master thesis. He has been of great support and understanding and I sincerely thank him for that.

I would like to extend my thanks to all my professors in the Socioeconomics and Demography Master’s Degree Program who taught me valuable skills and knowledge for my future career and broadened my horizons.

I would also like to express my heartiest thanks to my parents for all their support. And last but not least, a special thanks to my husband, Andreas, for giving me the opportunity to start this master, for believing in me and for supporting me to reach the goal of completing this task.

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1 Introduction

Migration and its associated processes can influence migrants’ mental wellbeing. Although there is no conclusive evidence for a large increase in the risk of mood disorders associated with migration (Swinnen and Selten, 2007), migration process remains a risk factor for depression.

Migrants constitute an increasing part of the European population and labour markets rely more and more on them. As population ageing in Europe increases, there is a high demand for migrants to make up shortfalls in the workforce (OECD, 2014). Therefore, it is crucial for the receiving countries to maximize the benefits from migration.

However, mental illnesses have considerable implications on employment and productivity.It is a fact that having a mental health problem considerably increases the chances of both unemployment and economic inactivity. The unemployment rate for people with a common mental health condition is double than that found among the general population (Steadman and Taskila, 2015). Therefore, migrant mental health related knowledge is of great public interest.

While there are many studies that examine the relationship between migration and depression, little is known on how the different national integration policies and contexts influence this relationship. The main purpose of this thesis is to analyse the association between depression and migration depending on different integration policies, but also on social and personal factors. To do so, I use the data from the 2014 European Social Survey (ESS7) which was administered in several European countries (see chapter 3). Furthermore, I divide a selected number of countries in more and less integrative countries based on their Migrant Integration Policy Index (MIPEX 2015) score (see chapter 6).

2 Depression

2.1 Choice of Depression

While it would be very interesting to explore the relationship between mental health and migration process and, consequently cover a wide range of mental disorders, I chose to focus on the case of depression for several reasons. First of all, this choice complies with the type of the available data. In this study I use data from the European Social Survey 2014-2015 (ESS7¹) and not from hospital registers. Despite the fact that data from hospital registers would be reliable on the diagnosis of patients’ mental disorder, there would be a lack of vital information needed for my analysis, such as the social context of the host countries. Another important

1 Data derived from the 7^th round of the European Social Survey 2014 (ESS7).

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6 reason for not using data from hospital registers is that the occurrence of depressive symptoms doesn’t necessarily lead to hospitalisation. The ESS7 was realised on the general population, containing variables from which depression risk can be deducted, while also including several information on migrant’s socioeconomic status and natives’ opinion on migration.

Another reason for choosing the case of depression among other mental disorders is the fact that questions on mental disorders are considered sensitive. It is probable that a person who suffers from a serious mental disorder will not reply to the survey. Consequently, persons who suffer from the rather common depression have less probabilities of being underestimated in the sample than persons who suffer from more serious mental disorders.

Last but not least, I chose depression for reasons of simplicity. The range of mental disorders is vast and would necessitate additional data and a complex analysis, while the case of depression is more precise and suitable for the analysis needed in the context of a master thesis.

2.2 Measurement of depression

To measure depression, I use the Center for Epidemiologic Studies Depression Scale, known as the CES-D scale, (see Table 2-1) created by Radloff in 1977. CES-D is a 20- item scale designed to identify the current²risk of developing depressive disorders in the general population. The CES-D is a short, structured self-report measure, acceptable to the respondent, and not substantially influenced by the normal range of conditions during a household interview. This scale was designed for studying the relationships between depression and other variables across population subgroups, so it matches perfectly the needs of this study.

An 8-item version of the original CES-D scale is used in the ESS7 questionnaire which enables us to measure depression with the available data. The ESS7 questionnaire includes the following 8 variables³ :

(1) felt depressed (2) felt lonely (3) felt sad (4) were happy (5) enjoyed life

(6) felt everything was an effort (7) restless sleep

(8) could not get going

The variables were happy and enjoyed life were recoded to weren’t happy and didn’t enjoy life respectively, in order to match the formulation of the 6 other variables. The response

2 Current period means the period of one week before the interview

3 These 8 variables correspond to the questions E20 - E27 of the ESS7 questionnaire

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7 categories for the 8 variables are none or almost none of the time (score 1), some of the time (score 2), most of the time (score 3) and all or almost all of the time (score 4). A sum for all the 8 variables was calculated to indicate a total score which can range from 8 (for a person who replies none or almost none of the time to all 8 questions) to 32 (for a person who replies all or almost all of the time to all 8 questions). The higher the total score the higher the risk of developing depressive symptomatology. The persons who didn’t reply to more than 4 questions out of 8 were excluded from the study population. In case of no answer in a question, an average substitution was used as a score for this question (Leveque and Va Rossem, 2015).

For the original CES-D scale, the total score could range from 0 to 60. That included 20 questions with scores varying from 0 for “None or almost none of the time”, to 3 for “All or almost all of the time”. A cut-off score of 16 has been found to have sensitivity and specificity rates of 86.7 and 76.6 respectively for identifying depressed individuals, whereas a cut-off score of 21 has a sensitivity and specificity rate of 73.0 and 96.1 (Shean and Baldwin, 2008;

Siddaway et al., 2017). After adjustment to our 8-item version with total scores ranging from 8 to 32, a cut-off score of 16.53 was estimated accordingly.

Table 2-1: Original CES-D scale for depression measurement in the general polulation⁴

Source: Radloff 1977, The CES-D Scale: A Self-Report Depression Scale for Research in the General Population, Center for Epidemiologic Studies National Institute of Mental Health, Digital Conservancy at the University of Minnesota, United State,

4 The underlined parts in black indicate the variables that exist in the data of ESS7

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3 Data

For the needs of this study I use data from the 7th round of the European Social Survey (ESS7) which was administered in 22 European countries. This survey aims firstly to monitor and interpret change in public attitudes and values within Europe and to investigate how they interact with Europe's changing institutions. Secondly to advance and consolidate improved methods of cross-national survey measurement in Europe and beyond, and thirdly to develop a series of European social indicators, including attitudinal indicators (ESS documentation).

ESS includes variables that allow measuring the risk of developing depressive symptomatology in the general population, which is the dependant variable of this study. It also includes variables that take into account many aspects of migrants’ individual sociodemographic variables, as well as variables on public perceptions towards immigrants. In addition, because of the ESS survey design methodology, within ESS data there is a significant sample of migrant population. Another reason is that there are comparable data for several countries, which provides the possibility of doing a comparative analysis between countries or group of countries.

The ESS is representative for the general population older than 15 years, living in a private household irrespective of language or nationality. The survey involves strict random probability sampling, a minimum target response rate of 70% and rigorous translation protocols (ESS documentation).

All the analysis of the data is implemented using the software for statistics and data science STATA.

4 Literature linkages and hypotheses

4.1 Risk factors for depression

Depression is one of the most common psychiatric disorders, however it has not been clearly understood. Depression is considered a syndrome caused by various factors rather than by a single aetiology. Although many biological factors have been suggested to be risk factors for depression, there are also psychosocial factors that may lead to it (Jeon et al, 2017).

Depression is a gendered phenomenon, since the risk for depression for women is twice as high than for men. The exact reasons for that are not clear, however it is suggested that women experience more psychosocial stress and hormonal changes. In terms of age, in adolescents and adults the incidence of depression is approximately twice as high in women and is the

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9 highest in the 22 to 44-year-old age group. Concerning the marital status, depression occurs more frequently in persons who are divorced, separated or do not have a close interpersonal relationship (Jeon et al, 2017).

Not all researchers agree if there is a relationship between socioeconomic status and depression. Some argue that people with lower socioeconomic status report more depressions, while others argue that there is no association between these two variables (Lorant et al, 2003; Leveque et Van Rossem, 2015; Jeon et al, 2017).

In case of comorbidity with other disorders, the risk for depression increases. Such disorders are alcohol abuse or dependence, panic disorder, obsessive compulsive disorder and social anxiety disorder. Chronic medical conditions are important risk factors for depression. In addition, results of genetic studies, such as family, adoption and twin studies, have shown direct and accurate risk factors (Jeon et al, 2017).

Depression can develop in all types of personalities. However, persons who judge themselves strictly or have high expectations and who suffer from the loss of self-esteem or self- confidence are more likely to develop depression. It is worth noting that stress that damage self-esteem may be very subjective depending on the person (Jeon et al, 2017).

Life events and environmental stress are also associated with depression. The psychosocial stress with the greatest influence is loss, such as the death of a close family member, loss of a job, economic loss, and health problems. However, depression may also develop without preceding stressors (Jeon et al, 2017).

In order to assess quantitatively life events and environmental stress, Holmes and Rahes developed the Social Readjustment Rating Scale for 43 life events. At the Table 4-1 are figured the 15 most important life events that influence the depression risk. It is known that the incidence of psychosomatic disorders, including depression, increases when life change units exceed 200 points per year on the social scale. However, this scale cannot be applied with the same way to all individuals, since there are persons who are less vulnerable to stress (Holmes and Rahe, 1967; Jeon et al, 2017).

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Table 4-1: Social readjustment rating scale

Source: Holmes T and R. Rahe (1967) and Jeon et al (2017)

4.2 Migration and depression

Although there is much literature that links migration and depression, the exact mechanisms that may lead to migrants’ depression have not been clearly understood since there is no direct causal relationship between migration and the occurrence of depressive symptoms. Research has shown that not all migrants develop depression and that not all depressives have history of migration (Bhugra, 2003).

However, migrants are considered as a group with increased risk for mental health problems.

There are many theories that link depression and migration, the most prevalent being the migration stress model and the acculturation thesis (Leveque and Va Rossen, 2015; Berry, 1997; Missine and Bracke 2012). According to the migration stress model, migration involves a period of increased stress which might lead to emotional distress and to higher levels of depression among the first-generation migrants (Leveque and Va Rossen, 2015; Missine and Bracke, 2012).

However, it is not the migration process itself that provokes stressful feelings, but also living in a different culture than the culture of the country of origin. The acculturation process, the phenomenon by which the minority culture assimilates the values of the majority culture, inevitably involves social and psychological problems that, however, are expected to dissipate

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11 over the time (Bhugra, 2003; Leveque and Va Rossen, 2015; Berry, 1997; Escobar et al. 2010;

Jibeen 2011).

Another factor that influences the stress levels is social support. A socially excluding environment at the host country can be a chronic stress factor potentially leading to depressive symptoms. It is in this context that more inclusive national policies for migrant integration or a supporting social environment can buffer the genesis of depression (Leveque and Va Rossen, 2015). However, protective factors towards depression do not depend exclusively on social support but also on methods unique to each individual (Bhugra, 2003).

Another branch of literature identified eight theoretical considerations for adjustment such as loss, fatalism, expectations, negative life events, social support and clash of values (Bhugra, 2003; Furnham and Bochner, 1986). More specifically, migration is linked with the loss of objects or relationships, such as residence and belongings or family, friends, reputation and occupational status, which, in consequence can lead to a period of mourning. Unresolved, prolonged or unexpressed mourning can lead to depression. However, psychologically and physically healthy migrants are less likely to become depressed due to stress (Bhugra, 2003).

In addition, high expectations that cannot, or don’t become fulfilled may lead to harsh adjustment to reality and depression. People who migrate for economic reasons may have high expectations that cannot always fulfilled. In this case, lower expectations may be beneficial for migrants’ mental health. From another point of view, low expectations could lead to poor social mobility that in turn leads to different problems (Bhugra, 2003).

However, another part of the theory suggests that people who become depressed after migration were about to become depressed anyway, due to biological or social factors and that individuals may be vulnerable to depression prior to migration or independently of migration (Bhugra, 2003).

From the above it is evident that individual, group, but also societal factors or in combination can play a role in the genesis of depressive symptoms.

4.3 Research questions and hypotheses

As stated previously, the objective of the present analysis is to examine if the relationship between depression and migration is dependent on different levels of national integration contexts.

Through this analysis I try to reply to several research questions:

(1) Are migrants at higher risk for depression compared to natives?

(2) How does migrant depression risk evolve over time?

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12 (3) Which are the main difficulties that the immigrants face at their host societies and that have the strongest impact on the depression risk?

For all the above questions I examine if there is a difference or a distinct pattern between the two genders and between the countries that follow more and less favourable integration policies.

The corresponding hypotheses are:

(1) Migrants have higher risk for depression compared to natives, because of the aforementioned factors that link migration and depression.

The difference between the depression risk of migrants and natives is expected to be bigger at the countries following less supportive integration policies.

(2) The depression development in relation with time is linked with either chronic problems / problematic situations that persist and are not resolved over time, or with sudden (within a short period) and massive changes in a person’s life that he/she cannot handle them.

The immigrants leaving in more integrative countries, given that they will be more supported in their host societies, will have lower depression risk across time compared to immigrants leaving in countries that follow unfavourable integration policies and vice versa.

(3) Individual (based on immigrants’ characteristics) and collective (based on host society’s perceptions towards immigration) variables that describe difficulties that the immigrants face at their host societies are examined based on the literature.

It is expected that the countries with unfavourable integration policies for migrants will have more negative outcomes concerning the examined variables and stronger association between depression risk and the studied variables compared to inclusive countries and vice versa.

4.4 Limitations

This study has several limitations, the most important being that the ESS dataset does not include data on pre-migratory conditions and motivation for migration. Numerous studies have reported that forcibly displaced immigrants are at a dramatically increased risk of suffering from somatic, psychosomatic, and psychiatric disorders, including depression, anxiety, and post-traumatic stress disorder (Jamil, 2010). Therefore, not having information on the pre- migratory conditions and motivation for migration there is not the possibility of identifying if immigrants’ depression risk is linked to prior, peri or after migration processes.

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13 In addition, without having any information on respondents’ life before migrating to their host countries, it is not possible to verify if some persons were predisposed to develop depressive symptoms anyway and independently to the migration process.

Furthermore, this study uses a self-report depression inventory which does not allow the identification of persons with clinical depression. Although the ESS data allow the quantification of a depression risk score, persons with such a risk are not necessarily depressed.

In addition, the complexity of the studied phenomenon itself is a limitation. Depression is a disorder caused by various factors, such as life events, biological and socioeconomic factors.

Based on the literature (chapter 4.1), it is mostly the accumulation of life events or life changes that has an influence on the development of depression rather than a single event.

Consequently, survey questionnaires not primarily designed to study depression fail to collect all the necessary information.

Lastly, the chosen sample includes countries that, according to the MIPEX 2015 classification, follow favourable, slightly favourable and halfway favourable integration policies. Countries with slightly unfavourable or unfavourable policies are not represented, consequently the comparison between extreme cases (favourable and unfavourable policies), that would be more informative, cannot be studied.

4.5 Integration and national integration policies

Integration is an integral part of immigrant’s life in the host country. From the moment that immigrants arrive in the host community, they try to find their place in the society. This is an inevitable reality they face, not only in terms of more immediate or physical needs, such as housing, but also in the social or political sense (www.migrationpolicy.org).

Using the definition of the International Organization for Migration (IOM, 2011), integration is

“The process by which migrants become accepted into society, both as individuals and as groups…[Integration] refers to a two-way process of adaptation by migrants and host societies…[and implies] consideration of the rights and obligations of migrants and host societies, of access to different kinds of services and the labour market, and of identification and respect for a core set of values that bind migrants and host communities in a common purpose”.

The “acceptance” mentioned in the above definition is an abstract concept, meaning that there is not a strict interpretation, since the particular requirements for acceptance by a receiving society vary greatly from country to country. Another important aspect of this definition is that the responsibility of integration does not depend only on one group, but on many factors, such

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14 as immigrants themselves, the host government and society, institutions and communities (www.migrationpolicy.org).

In general, we could say that there are two parties or levels involved in the integration process:

in an individual level are the immigrants, with their characteristics, personal profiles and efforts towards adaptation to their new life and environment, and in a collective level the host society with its interactions with the newcomers and their institutions. It is finally the interaction between these two parties that determines the direction and the outcome of integration (www.migrationpolicy.org).

National policies can largely influence immigrants’ integration process, since they determine the opportunities given to immigrants and subsequently their prospects for integration into the host society. Laws and regulations have the power to give access or exclude migrants from the host society and influence several aspects of immigrants’ lives, such as the educational system, institutional arrangements in the labour marker or access to citizenship (www.migrationpolicy.org). However, national policies on integration vary significantly not only from country to country, but also within the same country depending on the group of people they are referring to.

5 Retained variables

For the selection of the variables, I am based on the three main perspectives as proposed by Maxwell that I further enrich with other brunches of the literature.

These perspectives are:

(1) the prospects for successful integration over time

(2) the barriers that prevent migrants from achieving successful integration

(3) the host society environment (Leveque and Van Rossem, 2015; Maxwell, 2010).

The two first perspectives are focused on individual-level variables, while the third on collective-level variables.

5.1 Individual-level variables

The first theory sees migrant integration as a process that develops over time and across generations (Leveque et Van Rossem, 2015; Maxwell, 2010). Two measures that have been used extensively in the literature to measure interaction with the host society, also used in this study, are migrant generation and length of stay (Greenman and Xie, 2011). For this purpose, I created two variables. The first one distinguishes migrants according to their generation and

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15 natives (natives=0, 1^st generation migrants=1, 2^nd generation migrants=2). The second one divides further the 1^st generation migrants according to their length of stay (more or less than 5 years of stay for 1^st generation migrants), to test if newcomers (length of stay <5 years) are at higher or lower depression risk compared to settled immigrants.

Table 5-1: Individual variables for migration status and region of origin

Variable label Categories Migration status 0=Natives

1=1^stgeneration migrants 2=2^nd generation migrants Migration status per

length of stay

0=Natives

1=1^st generation migrants with length of stay < 5 years 2=1^st generation migrants with length of stay >= 5 years 3=2^nd generation migrants

European born or not 1=EU born 2=Non-EU born

In this study, first-generation immigrants are considered people born in a country other than their country of residence. Second-generation immigrants are native-born persons with at least one foreign-born parent. Natives are people born in the country of residence with both parents born also in the country of residence.

To test whether legal constraints in the host countries between European born⁵ and non- European born migrants is a predictor of depressive symptomatology, I further divide migrants according to their place of birth.

The second perspective focuses on the barriers that may prevent migrants from achieving integration (Levecque and Van Rossem 2015; Maxwell 2010). Robust findings show that ethnic minorities face integration problems (Constant at el, 2008). Being part of an ethnic minority or non - dominant group places persons in a more vulnerable position, in terms of numerical, economic or political power, in comparison with the “mainstream” or dominant group (Berry,

5 European born migrants are considered migrants who were born in the EU-28 countries and the countries of the Schengen area.

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16 1997). Although there is the assumption that minorities are becoming part or should be in the process of becoming part of the “mainstream” culture, that does not always happen (Berry 1997). In some cases, this process is resisted by either or both the dominant and non-dominant cultural group (Berry, 1997; Kymlicka, 1995; UNESCO, 1985).

In addition, discrimination is acknowledged as the single most important integration barrier (Constant et al, 2008). Self-reported discrimination due to colour or race, nationality, religion, language and ethnicity is most probably linked to the public opinion (or to natives’ opinions since natives constitute the great majority of the host countries), and mostly to negative attitudes and perceptions. However, the collective perspective (natives’ perceptions towards immigrants) is further investigated in the following chapter, while in this chapter the focus is on the individual characteristics.

Blocked social mobility is also considered to be another significant barrier to integration (Maxwell, 2010). Much of the literature on how integration outcomes improve over time assumes that migrants can access greater economic opportunities as they become part of the host society (Maxwell, 2010). Not only migrants of the same generation, but each subsequent generation of immigrants is also expected to achieve higher social and economic status as it becomes more culturally and linguistically similar to native middle class (Greenman, Xie 2011;

Greenman, Xie 2008; Rumbaut 1997; Zhou 1997). This would also represent a successful migration project, relative to having stayed in the country of origin (Pratt, 2015).

However, this is not always the case. Recent scholarship argues that economic changes such as de-industrialization and growing supply of highly skilled jobs have reduced the opportunities for low-skilled migrants to access upward social mobility. Consequently, in such a demanding environment, migrants without high-level qualifications may face difficulties while trying to integrate in the host society (Maxwell, 2010; Gans, 2007; Portes and Zhou, 1993; Portes and Rumbaut, 2001).

Highly skilled workers are normally defined as having a university degree or extensive/equivalent experience in a given field (Iredale 2008). While this definition also includes immigrants with extensive professional experience, due to data limitation and for reasons of simplicity this study takes into account only the educational level. Based on the above definition, low skilled persons are considered persons without university education and highly skilled, persons with university education.

In addition, the link between migration, discrimination, poverty and social exclusion has been repeatedly stressed on the literature (socialplatform.org/migration). Considering the barriers that would prevent migrants to integrate successfully in the host society as a form of social exclusion, it would be an omittance not to include additional variables that measure the migrants’ socioeconomic position. For this reason, I also include variables on poverty and employment. In addition, it is expected that the financially most disadvantaged immigrants will

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17 have less opportunities for education and training, which in consequence will keep them trapped in lower social strata.

Finally, another key mechanism, linked to individual efforts, that facilitates the integration process are the gradual adoption of local language (Maxwell, 2010; Park et al., 1925; Gordon, 1964). Inversely, not speaking the local language and not participating in language courses in host country would also be a barrier to integration.

Concerning the selected indicators, I include the self-perceived membership of an ethnic minority group and of group which is discriminated against (Table 5-2). These variables answer to the following questions “Do you belong to a minority ethnic group in [country]?”and “Would you describe yourself as being a member of a group that is discriminated against in this country?”(Leveque and Van Rossem, 2015).

Table 5-2:Individual variables for self-perceived discrimination and membership in minority group

Variable label Categories

Belong to a minority ethnic group 1=No 2=Yes Belong to discriminated group 1=No

2=Yes

To take into account the immigrants’ socioeconomic position, I include three variables. For education, I use the highest level of education completed. Low education is considered other than university education. I also include the variable “Feeling about household's income nowadays” to measure subjective perception on household’s income and financial difficulties.

For the classification of the employment status I use the variable “Main activity” which I recode in the categories “employed”, “unemployed”, “permanently or disabled” and “retired”. The

“employed” category includes persons in paid work and the “unemployed” persons who are unemployed and are looking / not looking for a job, in education, in community or military service or in housework. Retired individuals constitute a separate category. Lastly, chronic medical conditions are important risk factors for depression. For this reason, I kept permanently sick or disabled persons in a single category.

Table 5-3: Individual variables for socioeconomic position

Original variable

Recoded variable

Original categories Recoded categories

Level of qualifications

1=ES-ISCED I, less than lower secondary

2=Low

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18 Highest level

of education, ES – ISCED

2=ES-ISCED II, lower secondary

3=ES-ISCED IIIb, lower tier upper secondary 4=ES-ISCED IIIa, upper tier upper secondary 5=ES-ISCED IV, advanced vocational, sub-d

6=ES-ISCED V1, lower tertiary education

1=High

7=ES-ISCED V2, higher tertiary education “Main activity” “Employment

status”

Paid work 1=Employed

Retired 4=Retired

Permanently sick or disabled

3=Permanently sick or disabled

Unemployed, not looking for job

2=Unemployed

Unemployed, looking for job

Education

Community or military service

Housework, looking after children, others

“Feeling about household's income nowadays”

“Financial difficulties”

1= Living comfortably on present income

1=No

2= Coping on present income

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19 3= Difficult on present

income

=Yes

4= Very difficult on present income

To assess if immigrants speak or not the host country’s language⁶, the ESS database includes two variables: first mentioned most spoken language at home and second mentioned most spoken language at home. If none of these languages is the host country language, then I assume that the person doesn’t speak the country’s language. However, not speaking the local language at home doesn’t necessarily mean that a person doesn’t speak the local language. In addition, there is no variable in the dataset that measures actual training and effort to learn the local language thus making it impossible to include such an effort into consideration. In conclusion, the available data on language are not very reliable on rating the actual capability of speaking the local language or the actual effort for its adoption⁷.

I also included an additional variable in the group of individual-level variables that is found to be associated with depression renamed “social support” (Leveque and Van Rossem, 2015).

According to research, life event losses and perceived strain are positively related to depressive symptomatology, while close relationships and perceived support are negatively related to these symptoms. It is also found that social support not only protects individuals against the negative effects of stress, but it is also possible that it contributes to the amelioration of depressive symptoms (Aneshensel and Stone, 1982).

Table 5-4: Individual variable social support

Original variable name

New variable name and label

Original categories Recoded categories

Number of people with whom you can discuss intimate and personal matters

Social support 0=None 1=More than 7 per.

1=1 person 2=2-6 persons 2=2 persons 3=0-1 person 3=3

4=4-6

6 By host country`s language is meant the official languages spoken in each host country.

7 The “language” variable didn’t give statistically significant results at the trials for the creation of the logistic regression models and, consequently, it is not included in the analysis part. However, this insignificance is, most probably, due to inappropriate data for the creation of a reliable language indicator, rather than non- association between depression risk and speaking/not speaking host’s country language.

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20 5=7-9

6=More than 10

5.2 Collective level variables

Variables on the environment of the host society, including natives ‘perceptions and attitudes towards immigrants are also included. Negative attitudes or sentiments towards immigrants, such as xenophobia, can constitute integration process more challenging since they can be used to justify discrimination or support for political parties that follow anti-immigrant policies (Fetzer 2000; Joppke 2005; Maxwell 2010; Paskeviciute and Anderson 2008). Natives’

attitudes, along with country’s historical tradition on diversity influence the level of immigrants’ acceptance in the host society (Banting and Kymlicka 2006; Koopmans et al. 2005;

Maxwell 2010).

Since absence or inefficient social support may lead to depression, it is expected than an unfriendly host environment, such as negative attitudes and perceptions towards immigrants and not acceptance of diversity from the part of the host society, would lead to increased prevalence of depression. Therefore, negative public opinion on immigrants, would be a risk factor for depression.

To test attitudes towards immigrants, I create a new variable which will measure the acceptance to diversity. In the dataset there are four questions that examine to what extent the host country should allow immigrants to come from:

(1) same race/ethnic group as majority (2) different race/ethnic group from majority (3) poorer countries in Europe

(4) poorer countries outside Europe

All these four questions use the same categorisation of answers, which permits to create a single total score and measure acceptance to diversity. These answers are:

(1) allow many (2) allow some (3) allow a few (4) allow none

The two first answers are recoded as positive and the two last as negative. I recoded the “don’t know” answers as negatives since they are not enough to constitute a distinct category (for example neutral attitude). I prefer not to recode them as missing data and I consider that the

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21 persons who did not answer to these questions had stronger tendency towards negative perception than positive.

The methodology of creation of this variable is the following: I created a counter that adds 1 if an answer is positive or deducts 1 if an answer is negative. This process is repeated for all four questions. Consequently, final scores range from -4 for a person who gave negative answer to all four questions to +4 for a person who gave a positive answer to all questions.

Table 5-5: Collective variables

Original questions used for creation of new variable

New variable Categories of original variable

Scores of new variables

(1) same race/ethnic group as majority (2) different race/ethnic group from majority (3) poorer countries in Europe

(4) poorer countries outside Europe

Acceptance to diversity

1= allow many 2= allow some 3= allow a few 4= allow none

-4 Low acceptance -3

-2 -1 0 +1 +2 +3

+4 High acceptance (1) Immigration is bad

or good for host country’s economy (2) Immigration

undermines or enriches host country’s cultural life

Perception towards immigration

0=Bad for the economy 1

2 3 4 5 6 7 8 9

10=Good for the economy

-2 Negative perceptions -1

0 +1

+2 Positive perceptions

Some races/ethic group are born:

(1) Less intelligent (2) Harder working

Level of prejudice

1=Yes 2=No

-2 High prejudice -1

0 +1

+2 Low prejudice

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22 To measure perception towards immigration in the host country I created a single variable from the following two variables:

(1) “Would you say it is generally bad or good for host country’s economy that people come to live here from other countries?”

(2) “Would you say that the host country's cultural life is generally undermined or enriched by people coming to live here from other countries?”

Both questions use a 11 scale answers from 0 being the most negative perception towards immigration to 10 being the most positive. For both questions there is an attraction towards score 5 since there is a great majority of the sample that has neutral perception. I followed the same methodology as before: I created a counter that adds 1 if an answer is positive (answer score above 5) or deducts 1 if an answer is negative (answer score below 5). This process is repeated for both questions. Consequently, final scores range from -2 for a person who gave negative answer to both questions to +2 for a person who gave a positive answer to both questions.

To control for potential existence of prejudices in the host society, I also created a new variable which compiles the following binary variables:

(1) “Do you think some races or ethnic groups are born less intelligent than others? “ (2) “Do you think some races or ethnic groups are born harder working than others?”

For the construction of the new variable I followed once more the same methodology.

Consequently, the final scores range from – 2 (for persons who agreed to both statements) to +2 (for persons who disagreed to both statements).

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23

6 Comparative analysis between countries

One of the purposes of this thesis is to study whether the depression risk among immigrants is dependent on the integration policies followed by the host countries. For this reason, I divided countries that have a more and less favourable integration context for immigrants based on the Migrant Integration Policy Index score (MIPEX 2015).

As mentioned in the chapter 5, MIPEX is a useful tool for the evaluation and comparison on what governments are doing to promote the integration of migrants. MIPEX data cover the following eight policy areas: labour market mobility, education, political participation, family reunion, health, long-term residence, access to nationality and anti-discrimination policies.

MIPEX indicators are on a 0–100 scale for each policy area, where 100 is the top score for each country.

Table 6-1: Division of countries in integrative + & integrative -

Country MIPEX score &

level of integration

Recoded level of integration

Portugal 80 Favorable Integrative +

Sweden 80

Belgium 70 Slightly favorable

Norway 69

Germany 63

Netherlands 61

Spain 61

Denmark 59 Halfway favorable Integrative -

United Kingdom 56

France 54

Ireland 51

Estonia 49

Austria 48

Slovenia 48

Switzerland 46

I first sorted the countries in descending order according to their final MIPEX score (Table 6-1).

After, I grouped the countries that follow favourable (with a range of scores from 80 to 100) and slightly favourable (60-79 score) integrative policies and recoded them as integrative +. In addition, I recoded the countries having halfway favourable (41-59 score) policies as integrative -. With this method I have an almost equal number of countries in each group based on their MIPEX score (seven countries in the integrative + group and eight in the integrative – group).

In the ESS7 sample there are no countries having slightly unfavourable (21-40 score) or unfavourable (1-20 score) integration policies, apart from Lithuania (38 score). However, I excluded Lithuania, as well as four other countries, because of the very small relative frequency

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24 of foreign-born population in their sample (less than 5%). These countries and their respective foreign-born percentage are: Czech Republic (2.09%), Finland (4.79%), Hungary (1.59%), Lithuania (3.33%) and Poland (0.99%). I also excluded Israel for which there is not a MIPEX score.

7 Analysis

7.1 Univariate & bivariate analysis

7.1.1 Individual level variables

The depression variable

As mentioned in the chapter “Measurement of depression” the depression scores range from 8 to 32, with higher scores translating in higher risk for development of depressive symptomatology. The Figure 7-1 describes the distribution of the depression score variable only for the immigrant population. It is a right-skewed distribution as a large part of the depression scores occur on the left side of the figure. The calculated cut-off score 16.53 divides the population in persons not being (for depression risk scores ranging from 8 to less than 16.53) and being in risk for depression (for scores ranging from 16.53 to 32). Based on the above cut- off score, the 16.68% of the immigrant population is in risk for depression. The mean value of the depression score variable is 13.55 which is below the depression risk threshold.

Figure 7-1: Description of dependent variable

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25 Depression risk for natives and migrants⁸

The first goal of the analysis is to identify whether migrants in the selected European countries are at higher risk for depression compared to the native population. The second one is to study if the relationship between depression risk and migration is depended on different levels of migrant integration. The depression risk is also examined per gender, migrant generation and length of stay for first generation migrants.

The Figure 7-2 indicates the percentage of respondents with depression risk scores superior or equal to 16.53 (percentage of persons with depression risk) per migrant status and gender.

Overall, females are at much higher depression risk compared to males. This result was expected since, as seen at the risk factors for depression (chapter 4.1), females are more vulnerable to depression symptomatology compared to males. Furthermore, migrants reported relatively higher depression risk percentages compared to natives. However, this difference is bigger for the male population than the female. Migrant females are in the most disadvantaged position in terms of depression, while native men in the least.

Figure 7-2: Depression risk per migration status & gender

The following bar plot describes the difference of the depression risk per integrative category and for each country of the sample. The countries are divided in integrative + and integrative – and they appear in descending order (from the left part of the figure to the right) based on their final MIPEX score.

8 Natives are people born in the country of residence with both parents born also in the country of residence.

Migrants are first and second-generation migrants which are grouped in a single category. In this study first- generation immigrants are considered people born in a country other than their country of residence. Second- generation immigrants are native-born persons with at least one foreign-born parent.

0 5 10 15 20 25

Natives Migrants Natives Migrants

Males Females

Depression risk (%)

Depression risk per migration status & gender

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26 The Figure 7-3 indicates that in almost all countries, the only exceptions being Great Britain and Slovenia, the depression rates for the migrant population are bigger compared to that of the native polulation.

Figure 7-3: Depression risk difference between migrants and natives per country

The countries with the biggest difference in depression risk between the two population categories (>8%) are Norway, Netherlands and Estonia. The countries with the smallest difference (<2% in absolute values) are Great Britain and Spain. From the figure I conclude that the difference between migrants and natives is not dependent on whether a country follows supportive or excluding integration policies and that there is no distinct pattern in the difference of depression levels between the integrative + and integrative - countries.

Depression risk per migration status, generation and length of stay

For the comparison of migrants’ depression risk per migration status, I further divided migrants according to their generation (first and second-generation). Analyzing depression risk for such categorization shows that conclusions cannot be drawn.

As displayed at the Figure 7-4 , for the integrative + countries I observe that in Portugal more second-generation migrants are at risk for depression compared to first^-generation, while in Norway and the Netherlands the opposite is observed, with a difference of depression risk between first and second-generation migrants bigger than 6%. For the integrative – countries, in Austria more second-generation migrants are at risk for depression than first-generation migrants, while in Switzerland and Denmark the risk levels between the two categories are equivalent. In Ireland, Estonia and Slovenia the difference is more than 6%.

-4 -2 0 2 4 6 8 10

PT SE BE NO DE NL ES DK GB FR IE EE AT SI CH

Integrative + Integrative -

Depression risk difference between

migrants and natives per country (%)

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27

Figure 7-4: Depression risk difference between first and second- generation migrants

The additional information derived from the two following plots (Figure 7-5 & Figure 7-6) is the distinction of the first-generation migrants based on their length of stay, in immigrants staying less and more than 5 years in the host society. With only exception being Denmark and for both categories of countries (integrative + and integrative -), immigrants staying more than 5 years in the host society are at higher risk of depression compared to newcomers (<5 years of stay). The countries with the sharpest increase at the depression risk are Portugal, the Netherlands and Estonia.

Figure 7-5: Depression risk per generation & length of stay in host country, integrative + -10

-8 -6 -4 -2 0 2 4 6 8 10

PT SE BE NO DE NL ES DK GB FR IE EE AT SI CH

Integrative + Integrative -

Depression risk difference between 1st and 2nd generation migrants (%)

0 10 20 30 40 50

1st gen<5 years 1st gen>=5 years 2nd gen

Depression risk per generation & length of stay, Integrative + (%)

PT SE BE NO DE NL ES

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28

Figure 7-6: Depression risk per generation & length of stay in host country, integrative –

The Table 7-1 indicates the depression risk per gender, migration status and generation for the integrative + and integrative – countries. It seems that overall immigrants in integrative + countries are more vulnerable to depression compared to immigrants in integrative -, with females being in the most vulnerable position. Female natives and female first-generation immigrants have very close depression risks, while the risk for the next generation increases.

Concerning the males, male first-generation immigrants have higher depression risk compared to the other male population categories. Male natives and especially male natives in integrative – countries have the lowest levels. In conclusion, the depression risk to the next generation for females increases, while for males decreases.

Table 7-1: Depression risk per integrative category, gender & migration status

Males (%) Females (%)

Natives 1st gen. 2nd gen. Natives 1st gen. 2nd gen.

Integrative + 14.16 17.45 15.93 23.76 24.72 27.42

Integrative - 12.02 16.62 13.13 18.77 18.48 21.50

Depression risk per length of stay and gender for first generation migrants

I further analyze immigrant depression risk per length of stay in the host country and gender for first-generation migrants. Length of stay is divided in classes of 10 years, apart from the last class in which all first-generation immigrants with length of stay more than 50 years are grouped in a single category. The grouping of the last class is due to the small number of observations for immigrants staying more than 50 years in the host country.

0 10 20 30 40 50

1st gen<5 years 1st gen>=5 years 2nd gen

Depression risk per generation & length of stay, Integrative - (%)

DK FR GB IE EE AT SI CH

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29 From the Figure 7-7 I observe that for the integrative + countries the higher percentages of relative risk for depression risk occur after fewer years of length of stay compared to the integrative – countries. In particular, for males in integrative + countries the pick of depression risk occurs at the [10-20) class of length of stay and for females at the [20-30) class (22.51% of the male population of the [10-20) class and 29.40% of the female population of the [20-30) class is in depression risk). For integrative – countries, the highest level of depression risk occurs at the [30-40) and [40-50) classes of length of stay for males and females respectively (similarly 18.47% of the male population of the [30-40) class and 38.82% of the female population for the [40-50) class are at depression risk). After these picks, depression risk becomes progressively lower for both group of countries and genders.

These findings suggest that migrants in integrative + countries, leaving in a more supporting environment compared to immigrants in integrative – countries, and after a shorter period of distress linked to the migration process, manage to lower the depression risk levels in a shorter period after their arrival to the host country. On the contrary, a socially excluding environment or less integrative policies can be a chronic stress factor that leads to an increasing depression risk for a longer period. Consequently, migrants in integrative – countries, and in particular females, have for a much longer period an increasing depression risk and they reach much higher depression risk levels.

Figure 7-7: Depression risk per length of stay & gender

In addition, females have higher levels of depression risk compared to males, with the only exception being the first two classes for the integrative – countries where males are in relatively higher risk for depression. This result was expected since, as seen on the risk factors for depression (chapter 4.1), women are twice as high in depression risk compared to men. In addition, the difference between female and male depression risk for the integrative + countries is kept constant for all classes, while for the integrative – countries there are many fluctuations.

0 5 10 15 20 25 30 35 40 45

[0-10) [10-20) [20-30) [30-40) [40-50) [50-100) (in years)

Depression risk per length of stay & gender (%)

Male Integrative + Female Integrative + Male Integrative - Female Integrative -

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30 It seems that women in less integrative countries are in the most disadvantaged position in terms of depression in comparison with the other population categories. The relative depression risk for women in integrative – countries increases constantly from the moment they arrive in the host country up to 50 years of stay and they reach the highest levels of depression risk (nearly 40% of women in the [40-50) class are in depression risk).

A common trend for all the four categories of population displayed at the same figure is that the depression risk for the class [10-20) is higher compared to the [0-10) class. This finding suggests that established immigrants (>=10 years of stay) are at higher risk for depression than newcomers (<10 years of stay).

An explanation could be based on the theory of the environmental stress and life events, as analyzed in the chapter “migration and depression”. Newcomers face many changes in a short period of their life. Changes that an average person is expected to have during a larger period of his life or even a lifetime, such as change of house, language, friends, colleagues, habits etc., an immigrant undergoes during a few years. Therefore, stress starts to accumulate and, most probably in combination with other factors, eventually leads to an increased depression risk.

The above-mentioned changes could be also translated in loss, such as loss of friends and family members, loss of previous place of residence, loss of previous social status etc.

Another explanation could be based on the theory for migrants’ expectations. It is probable that newcomers (especially economic migrants) have high levels of expectations when arriving to a new country and as the years go by, some of them realize that they cannot meet their initial expectations, resulting in an increasing depression risk. Eventually in some cases, after some years of stay expectations are adjusted to reality, resulting in a decreasing level of depression risk. Also, it is possible that accumulated disadvantages, such as unrealized expectations in combination with stress and various life events, increases further the depression risk.

Self-perceived discrimination and membership in minority ethnic group

As indicated at the Figure 7-8, migrants experience more discrimination than natives. Overall, first generation migrants experience more discrimination compared to the second generation, consequently across generations immigrants feel⁹ more accepted by their host societies.

Overall, females in integrative – countries are more discriminated compared to all the other population categories (females in integrative +, males in integrative + and males in integrative – countries). This is true not only for the female immigrant population, but also for natives.

Indeed, approximately the double percentage of the native females in integrative - countries experience discrimination compared to the other native populations (approximately 10% of

9 The measurement of discrimination is based on self-perceived attitudes.

Migration and depression: A comparative analysis between european countries

Master

Reference

Migration and depression: A comparative analysis between european countries

A master thesis in Socioeconomics, orientation Demography

Student: Adamantia Andreatou

Professor: Philippe Wanner

Migration and depression :

A comparative analysis between European countries

Acknowledgments

Table of Contents

List of figures

List of tables

1 Introduction

2 Depression

3 Data

4 Literature linkages and hypotheses

5 Retained variables

6 Comparative analysis between countries

7 Analysis

Depression risk per migration status & gender

Depression risk difference between

migrants and natives per country (%)

Depression risk difference between 1st and 2nd generation migrants (%)

Depression risk per generation & length of stay, Integrative + (%)

Depression risk per generation & length of stay, Integrative - (%)

Depression risk per length of stay & gender (%)