Background
The number of migrants in Europe has increased rapidly over the last few decades, nearly two thirds of all migrants worldwide live in Europe or Asia [
1]. With a total number of 12 million people Germany and the Russian Federation host the second largest migrant populations in the world [
1,
2]. Equalling almost 3 million people, individuals with Turkish migration backgrounds constitute the largest migrant group in Germany and are defined as all Turks who immigrated to Germany after 1949 as well as all Turks born in Germany and all individuals born in Germany as Germans with at least one Turkish parent [
2]. In response to labour shortages in the 1960s, Western Germany invited a large number of migrants from Turkey and other Mediterranean countries, who were often followed by their families later on [
3].
Migration and mental health
Research studies in US and Canada have provided evidence that the ‘healthy migrant effect’ not only holds for physical health but also for mental health [
4,
5]. In line with these findings, American and Canadian studies concerning mood disorders in particular reported that migrants soon after immigration typically showed lower rates of mood disorders compared to the host population [
6‐
8]. In contrast, European studies, found higher prevalence rates of depression in a substantial part of migrant groups compared to the host populations [
9,
10]. A meta-analysis found combined prevalence rates of depression to be 20% (95% CI = 14–26) among labour migrants in Europe [
11]. Elderly European migrants in particular showed a higher risk of depression relative to the host population [
12,
13].
A possible consequence of migration is the long lasting and multi-dimensional process of acculturation defined as any change that occurs when individuals or groups from different cultures continuously stay in contact with each other [
14‐
16]. One of the most widely studied acculturation concepts is Berry’s model of four different acculturation strategies (integration, assimilation, separation and marginalisation), based on two main components: maintenance of culture of origin and participation in the host culture [
16,
17]. Other frequently used measures of acculturation were nativity, length of residency in the host country and language proficiency [
18,
19]. An orientation towards both cultures, showed the most favourable effect on mental health and was negatively associated with depression [
20,
21]. A lower risk of depression in foreign-born migrants relative to their native-born descendants was observed across different American migrant groups illustrating the difference between migrant generations [
5,
7,
8,
22‐
24]. Early age at immigration as well as longer residency in the host country correlated with high risks of mood disorders among migrants [
6,
8,
22,
25], whereas a study among Asian Americans found varying associations between depression and immigration-related variables, emphasising the need to differentiate between gender [
23].
Depressive disorders among individuals with Turkish migration backgrounds
Several large population-based studies in the Netherlands, Belgium and Germany demonstrated higher prevalence rates of depression in Turkish migrants of the first and second migration generation compared to the host population and other migrant groups [
26‐
31]. Results of clinical research showed that depression is one of the most frequently diagnosed conditions in patients with Turkish origins in Germany, occurring more frequently and with a significantly higher severity relative to patients of the host-society [
32,
33]. Other health care and clinical studies reported increased psychological distress among patients with Turkish migration backgrounds in Germany, particularly in female ones [
34‐
36]. The probability of receiving treatment for unipolar depression was higher in Turkish migrants and their native-born descendants than in any other migrant group or the host population in the Netherlands [
37].
Common risk factors related to elevated rates of depressive disorders among first and second generation migrants with Turkish origins were: being female [
28,
29,
38], older age [
29], and low socioeconomic status [
26,
27,
29]. Regarding acculturation, integration was found to be the most beneficial acculturation strategy associated with low rates of depression in Turkish migrants of the first and second migration generation, whilst marginalisation and separation were associated with increased depression rates [
38,
39]. When it comes to migration status, a higher risk and more severe symptoms of depression in foreign-born Turkish migrants of the first generation relative to their descendants born in the host country were reported [
27,
31,
38].
Aim of the study
To our knowledge epidemiological data of mental disorders among individuals with migration backgrounds is scarce in Germany, in particular regarding specific migrant groups and the use of standardised diagnostic instruments [
40,
41]. The aim of this paper was to provide epidemiological data of depressive disorders among individuals with Turkish migration backgrounds in Germany. We focused on the 12-months prevalence of any depressive disorder, respectively MDD and dysthymia, as well as symptom severity of MDD. We also examine the following previously identified risk factors for depression: gender, age and socioeconomic status and explore the relationship with acculturation and migration status using the following constructs: cultural identity, mother tongue, language proficiency, nativity, migration generation, length of residency in Germany, age at immigration and citizenship.
Methods
The study was part of an international research project‚ ‘Orientation of the health care system towards the needs of migrants with mental disorders‘, a co-operation between the University Medical Centre Hamburg-Eppendorf and the Charité-Universitätsmedizin Berlin. The study was approved by the Ethics committees of the Hamburg Chamber of Psychotherapists and the Ethics Commission and Data Commissioner of the Charité-Universitätsmedizin Berlin. An extensive description of the study design and sampling methods can be found in the study protocol [
42] and is briefly summarised as follows.
Sample
A total number of 662 standardized clinical interviews were completed in Hamburg (n = 376) and Berlin (n = 286). Participants met the following criteria: individuals with Turkish migration backgrounds, living in Berlin or Hamburg, aged from 18 to 65 years, consented to a face-to-face interview and had sufficient mobility to visit one of the interview offices in central locations.
Recruitment procedure and interview setting
The data collection of the present study took place in Hamburg and Berlin from August 2011 to July 2012. In order to increase the willingness of participation, focus groups, which aimed to identify potential recruitment barriers and resources, were conducted in a pre-study [
43]. Study participants were recruited via a random sampling of the regional population register in districts of Hamburg which had a high percentage and density of individuals with Turkish migration backgrounds. The recruiting phase was accompanied by a public media campaign. In Hamburg, 10,873 individuals with Turkish citizenship or German citizenship and Turkish origin (i.e. due to a naturalisation) were identified through their citizenship status or by the onomastic procedure, which was based on a proven name-algorithm [
44]. Potential participants were initially contacted via mail. Due to low response rates (on average 2.5%), snowball sampling was additionally applied in the last phase of data collection. In Berlin, a random sampling of individuals with Turkish migration background was not possible due to privacy protection laws. Participants were recruited directly by on-site collection at public locations, which had a high percentage and density of individuals with Turkish migration backgrounds and snowball sampling. During the snowball sampling in Hamburg and the data collection in Berlin, a quota scheme was applied originating from population-based micro census data of 2009, which contained the variables: sex (male/female), age (18–29/30–49/50–65) and education level (high/middle/low) to approximate a representative sample. Information and survey materials were available in both languages, Turkish and German. All interviews were conducted face-to-face by trained bilingual interviewers in one of the interview offices. Based on the participant’s language preference 458 of the completed interviews were conducted in Turkish language and 204 in German language.
The participants received an incentive of 10 Euro per 60 min of interviewing, as a gift card in Hamburg and cash in Berlin. The average length of an interview was 117 min.
Measures
Depressive disorders
Depressive disorders were assessed by Section E of the CIDI DIA-X Version 2.8, a computer-assisted version of the ‘Diagnostic Expert system for disorders/Munich Composite International Diagnostic Interview’ (DIA-X/M-CIDI; Wittchen and Pfister, 1997). The CIDI DIA-X is a fully standardised, clinical face-to-face interview which assesses diagnoses of mental disorders along with symptom severity according to the international classification systems DSM-IV-TR with ICD-10 compatible codes [
45]. It includes 109 questions to assess mood disorders. The CIDI DIA-X Version 2.8 was translated into Turkish according to Harkness [
46] and was tested in a pre-trial. Quantitative and qualitative analyses support a comparable quality and feasibility level of the Turkish version of the instrument in contrast to the German version [
47]. For a detailed description of the translation and editing process as well as the feasibility analysis of the translated CIDI DIA-X Version 2.8 review Dingoyan et al. [
47]. The reliability of the M-CIDI for mood disorders was good with kappa values of 0.65 or above [
48].
Sociodemographic data
The instrument contained 50 core questions on the basis of the sociodemographic module questions of the German Health Interview and Examination Survey for Adults [
49] as well as the micro census 2010. Relevant sociodemographic measures for the present paper were gender, age and socioeconomic status measured by educational level and equivalent disposable household income. The equivalent disposable household income was calculated according to the modified Organisation for Economic Cooperation and Development (OECD) equivalence scale, taking into account the size of the household and age of its members [
50]. A 1.0 weight was assigned to the head of the household, every additional household member received a weight of 0.5 and children up to 15 years of age received a weight of 0.3. The total monthly disposable income was divided by the sum of the household members’ weights to obtain the equivalent disposable household income [
50].
Acculturation and migration status
Measures of acculturation status were added to the instrument for sociodemographic data. Language proficiency was used as a proxy measure of acculturation (maintenance of culture of origin and/or participation in the host culture), which was measured by the migrants’ self-determined ability to speak German and/or Turkish and the mother tongue. Another indicator was perceived cultural identity, with participants being asked which term they would use to label themselves regarding their cultural identity. Migration status was assessed by nativity, migration generation, length of residency in Germany, age at immigration and citizenship.
Statistical analysis
Data analysis was conducted by SPSS Statistics version 22. Cross-tabulations were performed to calculate 12-month prevalence rates for each risk factor. Values were rounded to one decimal place. The total number of cases differs by variable considered caused by missing values.
A series of stepwise bivariate logistic regressions was conducted in order to assess the association between risk factors and prevalence rates of depressive disorders. Odds ratio (OR) and 95% confidence intervals (CI) were also computed. The significance of individual risk factors was assessed by the Wald-test. Likelihood ratio tests were conducted for the overall fit of the different models and the values of Nagelkerke R
2 were reported [
51]. Cross tables were calculated and Fisher’s exact test was performed to explore the relationship between symptom severity and risk factors. Due to a lack of variability in the data, categories of citizenship, cultural identity, mother tongue and language proficiency were partly merged together in order to perform stepwise bivariate logistic regression analyses. Additionally, the variables nativity, migration generation and age at immigration had to be excluded from the analyses because of redundancies in the data pattern. They were indirectly represented by length of residency. In view of the fact that gender is one of the most common risk factors for depressive disorders, results were presented separately for male and female participants. A differentiation of the two migration generations had to be forwent given the large differences in numbers of participants belonging to the first and second generation.
Results
The characteristics of the study sample and the 12-month prevalence rates of any depressive disorder (MDD or dysthymia), MDD and dysthymia by risk factors are presented in Table
1. Group sizes were relatively balanced for sociodemographic data due to the sampling procedure. The majority of the sample described themselves as Turkish or German-Turkish. Only1.4% of participants described themselves as having a German cultural identity, even though 28.4% of participants held German citizenship. Over 80% declared Turkish to be their mother tongue, however almost all participants claimed to speak German and Turkish. Over three quarters of the sample were migrants of the first generation, originating from Turkey.
Table 1
Study sample characteristics and 12-month prevalence rates of depressive disorders by risk factors
Total | 662 | 100 | 29.0 | 14.4 | 14.7 |
Gender |
Male | 276 | 41.7 | 23.2 | 10.5 | 12.7 |
Female | 386 | 58.3 | 33.2 | 17.1 | 16.1 |
Age, y |
18–29 | 139 | 21.0 | 22.3 | 11.5 | 10.8 |
30–49 | 385 | 58.2 | 27.3 | 14.3 | 13.0 |
50–65 | 138 | 20.8 | 40.6 | 17.4 | 23.2 |
Education |
Low | 257 | 38.8 | 35.4 | 14.8 | 20.6 |
Moderate | 161 | 24.3 | 30.4 | 17.4 | 13.0 |
High | 244 | 36.9 | 21.3 | 11.9 | 9.4 |
Income, € |
≤ 921 | 360 | 65.2 | 33.1 | 15.0 | 18.1 |
922–1417 | 117 | 21.2 | 25.6 | 11.1 | 14.5 |
> 1418 | 75 | 13.6 | 21.3 | 14.7 | 6.7 |
Cultural identity |
Turkish | 295 | 45.7 | 28.1 | 12.5 | 15.6 |
German | 9 | 1.4 | 33.3 | 22.2 | 11.1 |
German-Turka
| 188 | 29.1 | 30.9 | 17.0 | 13.8 |
Other identity | 153 | 23.7 | 28.8 | 14.4 | 14.4 |
Mother tongue |
Turkish | 534 | 81.8 | 30.1 | 15.5 | 14.6 |
German | 17 | 2.6 | 23.5 | 5.9 | 17.6 |
Both | 63 | 9.6 | 23.8 | 11.1 | 12.7 |
Other language | 39 | 6.0 | 25.6 | 10.3 | 15.4 |
Language proficiency |
Turkish | 61 | 9.3 | 34.4 | 14.8 | 21.3 |
German | 4 | 0.6 | 25.0 | 25.0 | 0.0 |
Both | 590 | 90.1 | 28.5 | 14.4 | 14.1 |
Nativity |
Turkey | 502 | 76.9 | 30.7 | 15.3 | 15.3 |
Germany | 151 | 23.1 | 24.5 | 11.9 | 12.6 |
Migration generation | | | | | |
1st generation | 502 | 76.9 | 30.7 | 15.3 | 15.3 |
2nd generation | 151 | 23.1 | 24.5 | 11.9 | 12.6 |
Length of residency, y |
German-born | 151 | 23.7 | 24.5 | 11.9 | 12.6 |
≤ 10 | 59 | 9.2 | 27.1 | 10.2 | 16.9 |
10–20 | 124 | 19.4 | 27.4 | 17.6 | 15.3 |
21–30 | 102 | 16.0 | 31.4 | 18.3 | 13.7 |
> 30 | 202 | 31.7 | 34.2 | 11.9 | 15.8 |
Age at immigration, y |
German-born | 151 | 23.7 | 24.5 | 11.9 | 12.6 |
≤ 13 | 118 | 18.5 | 34.7 | 17.8 | 11.9 |
13–18 | 118 | 18.5 | 29.8 | 19.5 | 15.3 |
18–25 | 148 | 23.2 | 27.0 | 24.2 | 16.9 |
> 25 | 103 | 16.1 | 29.8 | 10.7 | 17.5 |
Citizenship |
Turkish | 415 | 63.5 | 28.4 | 13.7 | 14.7 |
German | 184 | 28.4 | 32.8 | 18.3 | 14.5 |
Both | 53 | 8.1 | 22.6 | 7.5 | 15.1 |
Women, older people and people with low socioeconomic status in particular were affected by higher prevalence rates of depressive disorders. Concerning acculturation factors subjects with a German cultural identity suffered more frequently form depressive disorders, while individuals who reported Turkish as their single mother tongue and who only spoke Turkish showed elevated prevalence rates of depressive disorders. Migrants of the first generation were more at risk of suffering from depressive disorders compared to the native-born descendants, in particular those who immigrated under the age of 13 and those who had stayed over 30 years in Germany.
In order to assess the association of sociodemographic-related (Model 1), acculturation-related (Model 2) and migration-related (Model 3) risk factors with any depressive disorder, MDD and dysthymia ORs are represented in Tables
2,
3 and
4. Table
2 shows that older age represented the strongest independent risk factor for any depressive disorder. Male (
p < .05) and female participants (
p < .05) of older age were at a significantly higher risk to suffer from any depressive disorder than young individuals, even when adjusted for acculturation status and migration status. A low income showed a significant relationship with increased prevalence of any depressive disorder in male individuals, when controlled for acculturation and migration status (
p < .05).
Table 2
Risk factors of 12-month prevalence rates of any depressive disorder – OR and 95% CI
Age, y |
18–29 | referent | referent | referent | referent | referent | referent |
30–49 | 1.37 (0.53–3.79) | 1.78 (0.91–3.49) | 1.78 (0.66–4.83) | 1.79 (0.91–3.53) | 2.51 (0.81–7.74) | 2.08 (0.97–4.49) |
50–65 | 2.64 (0.95–7.33) | 2.61* (1.18–5.81) | 3.02* (1.01–9.00) | 2.55* (1.14–5.72) | 6.35* (1.48–27.23) | 2.77* (1.03–7.49) |
Education |
High | referent | referent | referent | referent | referent | referent |
Moderate | 1.26 (0.55–2.90) | 0.1.60 (0.82–3.12) | 1.09 (0.46–2.56) | 1.55 (0.79–3.05) | 1.32 (0.53–3.24) | 1.58 (0.78–3.19) |
Low | 1.09 (0.50–2.38) | 0.1.75 (0.96–3.19) | 1.16 (0.52–2.60) | 1.73 (0.93–3.21) | 1.52 (0.64–3.62) | 1.86 (0.96–3.60) |
Income, € |
> 1418 | referent | referent | referent | referent | referent | referent |
922–1417 | 1.53 (0.46–5.07) | 0.70 (0.27–1.80) | 1.59 (0.46–5.45) | 0.67 (0.26–1.76) | 1.51 (0.42–5.38) | 0.68 (0.26–1.79) |
≤ 921 | 2.73 (0.95–7.81) | 0.83 (0.37–1.89) | 2.87 (0.98–8.42) | 0.80 (0.35–1.84) | 3.36* (1.10–10.27) | 0.91 (0.38–2.17) |
Cultural identity |
Turkish | | | referent | referent | referent | referent |
German, German-Turka
| | | 1.40 (0.62–3.19) | 1.23 (0.71–2.13) | 1.57 (0.66–3.73) | 1.09 (0.61–1.94) |
Other identity | | | 1.57 (0.67–3.69) | 1.03 (0.52–2.03) | 1.72 (0.70–4.23) | 0.99 (0.49–2.00) |
Mother tongue |
Turkish | | | referent | referent | referent | referent |
German, both | | | 1.47 (0.58–3.73) | 0.80 (0.33–1.96) | 1.44 (0.53–3.89) | 0.75 (0.30–1.87) |
Other language | | | 0.22 (0.03–1.79) | 0.84 (0.29–2.44) | 0.19 (0.02–1.62) | 0.84 (0.28–2.52) |
Language proficency |
Turkish | | | referent | referent | referent | referent |
German, both | | | 1.65 (0.17–2.48) | 0.86 (0.41–1.81) | 1.94 (0.23–3.92) | 0.80 (0.37–1.75) |
Length of residency, y |
German-born | | | | | referent | referent |
≤ 10 | | | | | 2.46 (0.666–9.13) | 1.03 (0.18–5.78) |
10–20 | | | | | 0.62 (0.18–2.16) | 1.85 (0.60–5.75) |
21–30 | | | | | 0.85 (0.24–2.94) | 1.65 (0.54–5.06) |
> 30 | | | | | 0.36 (0.11–1.16) | 2.04 (0.69–6.02) |
Citizenship |
Turkish | | | | | referent | referent |
German, both | | | | | 1.41 (0.62–3.19) | 1.61 (0.90–2.90) |
Table 3
Risk factors of 12-month prevalence rates of MDD – OR and 95% CI
Age, y |
18–29 | referent | referent | referent | referent | referent | referent |
30–49 | 1.13 (0.33–3.93) | 2.25 (0.92–5.54) | 0.83 (0.23–3.03) | 2.49 (1.00–6.22) | 0.68 (0.15–3.18) | 2.34 (0.83–6.57) |
50–65 | 1.40 (0.35–5.60) | 2.61 (0.92–7.45) | 0.98 (0.23–4.17) | 2.78 (0.95–8.17) | 0.64 (0.8–4.77) | 2.26 (0.62–8.29) |
Education |
High | referent | referent | referent | referent | referent | referent |
Moderate | 2.80 (0.82–9.65) | 1.24 (0.57–2.68) | 2.85 (0.77–10.52) | 1.16 (0.52–2.60) | 3.27 (0.87–12.34) | 1.16 (0.51–2.60) |
Low | 1.71 (0.51–5.74) | 0.88 (0.42–1.88) | 1.61 (0.47–5.53) | 0.85 (0.39–1.88) | 1.87 (0.52–6.78) | 0.89 (0.39–2.06) |
Income, € |
> 1418 | referent | referent | referent | referent | referent | referent |
922- 1417 | 0.51 (0.15–1.71) | 0.82 (0.37–1.84) | 0.56 (0.16–1.92) | 0.78 (0.34–1.76) | 0.53 (0.15–1.86) | 0.70 (0.30–1.63) |
≤ 921 | 0.32 (0.07–1.52) | 2.18 (0.89–5.34) | 0.32 (0.07–1.54) | 2.25 (0.89–5.67) | 0.28 (0.06–1.42) | 1.95 (0.74–5.14) |
Cultural identity |
Turkish | | | referent | referent | referent | referent |
German, German-Turka
| | | 0.73 (0.21–2.51) | 2.24* (1.15–4.38) | 0.94 (0.26–3.41) | 2.02* (1.01–4.07) |
Other identity | | | 1.26 (0.40–3.98) | 1.16 (0.48–2.84) | 1.65 (0.49–5.55) | 1.12 (0.45–2.79) |
Mother tongue |
Turkish | | | referent | referent | referent | referent |
German, both | | | 0.22 (0.03–1.80) | 0.87 (0.30–2.55) | 0.21 (0.02–1.81) | 0.86 (0.29–2.55) |
Other language | | | 0.69 (0.08–6.00) | 0.81 (0.21–3.20) | 0.71 (0.08–6.65) | .87 (0.21–3.59) |
Language proficency |
Turkish | | | referent | referent | referent | referent |
German, both | | | 1.59 (0.18–14.22) | 1.25 (0.45–3.53) | 1.79 (0.18–18.28) | 1.12 (0.39–3.28) |
Length of residency, y |
German-born | | | | | referent | referent |
≤ 10 | | | | | 2.52 (0.41–15.56) | 1.03 (0.18–5.78) |
10–20 | | | | | 0.61 (0.09–4.12) | 1.85 (0.60–5.75) |
21–30 | | | | | 1.54 (0.25–9.48) | 1.65 (0.54–5.06) |
> 30 | | | | | 1.42 (0.27–7-51) | 1.41 (0.70–2.83) |
Citizenship |
Turkish | | | | | referent | referent |
German, both | | | | | 0.53 (0.16–1.70) | 1.32 (0.66–2.67) |
Table 4
Risk factors of 12-month prevalence rates of dysthymia – OR and 95% CI
Age, y |
18–29 | referent | referent | referent | referent | referent | referent |
30–49 | 1.82 (0.49–6.75) | 1.15 (0.48–2.75) | 3.40 (0.79–14.56) | 1.08 (0.45–2.59) | 6.60* (1.30–33.49) | 1.46 (0.56–3.83) |
50–65 | 3.50 (0.90–13.63) | 1.75 (0.65–4.70) | 6.48* (1.39–30.23) | 1.66 (0.61–4.49) | 29.42**(3.74–231.17) | 2.41 (0.71–8.26) |
Education |
High | referent | referent | referent | referent | referent | referent |
Moderate | 0.91 (0.30–2.74) | 1.62 (0.64–4.07) | 0.64 (0.20–2.06) | 1.59 (0.62–4.04) | 0.88 (0.25–3.14) | 1.71 (0.65–4.53) |
Low | 1.54 (0.61–3.88) | 2.23 (0.99–4.99) | 1.59 (0.60–4.25) | 2.12 (0.93–4.83) | 2.94 (0.96–8.95) | 2.56* (1.05–6.20) |
Income, € |
> 1418 | referent | referent | referent | referent | referent | referent |
922–1417 | 1.39 (0.31–6.26) | 2.47 (0.49–12.41) | 1.73 (0.34–8.18) | 2.59 (0.51–13.27) | 1.55 (0.28–8.61) | 2.55 (0.49–13.23) |
≤ 921 | 2.01 (0.53–7.55) | 2.67 (0.60–11.98) | 2.74 (0.65–11.58) | 02.59 (0.57–11.87) | 3.25 (0.71–14.86) | 2.71 (0.58–12.76) |
Cultural identity |
Turkish | | | referent | referent | referent | referent |
German, German-Turka
| | | 2.06 (0.75–5.66) | 0.56 (0.27–1.17) | 2.18 (0.72–6.58) | 0.50 (0.23–1.09) |
Other identity | | | 1.72 (0.57–5.19) | 0.91 (0.40–2.11) | 1.75 (0.54–5.72) | 0.90 (0.38–2.14) |
Mother tongue |
Turkish | | | referent | referent | referent | referent |
German, both | | | 3.68* (1.24–10.29) | 0.83 (0.23–3.01) | 3.26 (0.97–11.00) | 0.76 (0.20–2.83) |
Other language | | | dropped | 0.94 (0.24–3.69) | dropped | 0.88 (0.22–3.61) |
Language proficency |
Turkish | | | referent | referent | referent | referent |
German, both | | | 0.41 (0.09–1.91) | 0.69 (0.30–1.59) | 0.69 (0.13–3.67) | 0.69 (0.28–1.67) |
Length of residency, y |
German-born | | | | | referent | referent |
≤ 10 | | | | | 1.92 (0.36–10.32) | 1.08 (0.29–4.05) |
10–20 | | | | | 0.63 (0.12–3.18) | 0.77(0.27–2.20) |
21–30 | | | | | 0.61 (0.13–2.87) | 0.43 (0.14–1.35) |
> 30 | | | | | 0.18 (0.04–0.81) | 0.66 (0.23–1.86) |
Citizenship |
Turkish | | | | | referent | referent |
German, both | | | | | 2.69 (0.91–7.99) | 1.60 (0.75–3.40) |
According to Table
3, only cultural identity was a significant predictor of the prevalence of MDD among female participants. In Model 3, when adjusted for the confounding factor of migration status, female individuals who described their cultural identity as German, German-Turk, person of Turkish migration background or other cultural identity showed a risk about double as high for MDD relative to individuals with a Turkish cultural identity (
p < 0.05).
In Table
4, it can be observed that higher rates of dysthymia were related to older age among male participants, in particular (
p < .05) when controlled for acculturation status. Additionally, when adjusted for migration status, older male subjects were almost 30 times more likely to suffer from dysthymia than their counterparts in the young age group (
p < .001). Compared to male participants who stated Turkish as their single mother tongue male participants claiming German and Turkish as their mother tongue showed a higher risk of dysthymia (
p < .05). Significance was lost however when controlled for migration status. When controlled for the confounding variables of acculturation and migration status, female participants with a low education level were more likely to suffer from dysthymia (
p < .05).
Symptom severity (mild, moderate or severe) of MDD was significantly associated with gender, χ2 (N = 662) =8.53, p < .05. Moderate symptom severity was observed in 70.3% of the women suffering from MDD compared to 29.7% among men. Similarly, 74.5% of women with MDD showed severe symptoms in comparison to 25.5% among men. Other risk factors did not show any significant association with the symptom severity of MDD.
Conclusion
Individuals of Turkish migration backgrounds show high prevalence rates of depressive disorders, which are associated with older age and partly with low socioeconomic status. Symptom severity of MDD correlates with gender, with severe symptoms of this appearing mainly in female participants. Acculturation in the sense of an orientation towards culture of origin and host culture is related to higher prevalence of subtypes of depression. The need for more representative studies of individuals with Turkish migration backgrounds is emphasised along with further exploration of risk factors. Despite the findings that individuals with Turkish migration backgrounds in Germany are at a high risk of suffering from depressive disorders, migrants are underrepresented in the German outpatient mental health care system [
57]. It exists a need for an extended focus on protective factors and barriers within the mental health care system in order to develop policies for prevention and intervention programs for individuals with Turkish migration backgrounds in order to facilitate equal access to health information and mental health service.
Acknowledgements
The authors gratefully thank the Volkswagen Foundation for funding this study, all participants and interviewers of our study, as well as all supporters and the advisory board.
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