Infertility and Seeking Medical Help to Have a Child Vary Across Migrant Origin Groups in Germany

Milewski, Nadja; Passet-Wittig, Jasmin; Bujard, Martin Article — Published Version Infertility and Seeking Medical Help to Have a Child Vary Across Migrant Origin Groups in Germany Population Research and Policy Review Provided in Cooperation with: Springer Nature Suggested Citation: Milewski, Nadja; Passet-Wittig, Jasmin; Bujard, Martin (2025) : Infertility and Seeking Medical Help to Have a Child Vary Across Migrant Origin Groups in Germany, Population Research and Policy Review, ISSN 1573-7829, Springer Netherlands, Dordrecht, Vol. 44, Iss. 2, https://doi.org/10.1007/s11113-024-09921-3 This Version is available at: https://hdl.handle.net/10419/323556 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. http://creativecommons.org/licenses/by/4.0/ Vol.:(0123456789) Population Research and Policy Review (2025) 44:25 https://doi.org/10.1007/s11113-024-09921-3 ORIGINAL RESEARCH Infertility andSeeking Medical Help toHave aChild Vary Across Migrant Origin Groups inGermany NadjaMilewski1 · JasminPasset‑Wittig1 · MartinBujard1 Received: 4 March 2024 / Accepted: 12 November 2024 / Published online: 29 March 2025 © The Author(s) 2025 Abstract This study investigates the extent to which immigrants in Germany are faced with infertility, and it examines their use of reproductive health-care services. Previous research on migrant fertility centered mostly on the higher fertility rates of immigrants and their adaptation processes, but has largely neglected infertility. At the same time, research on infertility in the European low-fertility context has focused almost exclusively on non-migrant populations. Our results indicate higher infertility and lower seeking of medical help among migrants as compared with non-migrants. However, there is substantial heterogeneity between different migrant groups: Firstgeneration migrants show higher risks of infertility and lower use of medical help to get pregnant. The study also shows differences according to (parents’) regions of origin: Persons from Russia, Central Asia, and the Middle East (including Turkey) have a higher risk of perceiving infertility or uncertainty about it than other European origin groups. Those from Russia and Central Asia have the lowest use of medical help-seeking. These group differences cannot be explained by socioeconomic factors. Our results suggest that certain immigrant groups—despite having on average a higher number of children—face notable reproductive disadvantages, which deserve further attention in research on migrant fertility and assisted reproduction in general. Keywords Infertility· Subfecundity· Migration· Medically assisted reproduction (MAR)· Assisted reproductive technology (ART)· Reproductive health· Stratified reproduction· Germany * Nadja Milewski nadja.milew[email protected] Jasmin Passet-Wittig [email protected] Martin Bujard Mar[email protected] 1 Federal Institute forPopulation Research (BiB), Friedrich-Ebert-Allee 4, 65185Wiesbaden, Germany N.Milewski et al. 25 Page 2 of 38 Introduction This study investigates heterogeneity in infertility perceptions and help-seeking behavior by comparing immigrants with the native non-migrant population in Germany. In current demographic research there is growing interest in infertility (Carson & Kallen, 2021; Lazzari etal., 2022; McQuillan etal., 2022), seeking medical help to get pregnant (Domar etal., 2012; Greil etal., 2010; Passet-Wittig & Greil, 2021), and the rapidly growing sector of reproductive medicine (Adamson etal., 2018; Aleixandre-Benavent etal., 2015; Crawford & Ledger, 2019) in the Global North. This is because regions like Europe are characterized by fertility postponement, and older age is one of the most important non-modifiable risk factors for infertility (Dunson etal., 2002; Evers, 2002). However, previous quantitative studies have rarely included immigrant or ethnic minorities in Europe, which is noteworthy, as the proportion of migrants and their birth numbers is significant and increasing across Europe (Bagavos, 2019; Passet-Wittig & Greil, 2021; Sobotka, 2008). We argue that infertility is an important aspect to consider in research on migrant populations, because it has implications for their life course and family structure, but also for different demographic developments of social groups. In addition, knowledge of how infertility varies across different migrant groups can also provide important insights into the processes of adaptation within migrant populations, for example by looking at migrant generation or groups of origin countries (Wilson, 2019). Previous quantitative studies on migrant fertility in Europe mostly investigated the fertility adaptation processes of immigrants from high(er)-fertility contexts. They generally found that fertility levels of immigrant groups are on average higher than those of natives and that they decline in subsequent generations (Kulu etal., 2019; Milewski, 2010). The perceived “hyperfertility” of at least some immigrant groups may have contributed to migration researchers neglecting fertility barriers in immigrant groups (Atkin, 2009; Haug & Milewski, 2018; Inhorn & van Balen, 2002). However, the composition of migrant groups in Europe is changing, i.e. migrants are more often coming from countries with low and late fertility in Eastern Europe and Latin America (González-Ferrer et al., 2017), or from countries with rapidly changing fertility patterns, e.g. Turkey (Baykara-Krumme & Milewski, 2017). More recently, migrant groups, such as refugees, have attracted scholarly attention (Saarela & Wilson, 2022). These papers point to declining fertility in particularly vulnerable groups—however, the role of infertility still is an open question. Our study therefore complements research on migrant fertility by looking at infertility and the seeking of medical help to have a child. A better understanding of infertility among migrant populations also provides important information about the well-being, health status, and access to reproductive health care of these populations. Previous empirical results on various aspects of migrant health produced mixed results, suggesting that selection processes accompanying emigration, i.e. the healthy migrant effect, and selection Infertility andSeeking Medical Help toHave aChild Vary Across… Page 3 of 38 25 associated with remigration, i.e. the salmon bias effect, play a role (Razum etal., 2000). Comparatively few demographic studies have looked into perinatal health or birth outcomes in migrant populations (Juarez etal., 2019; Milewski & Peters, 2014; Väisänen et al., 2022). Only recently, attempts have been made to consider the role of women’s health in studies of migrant fertility (Alderotti & Trappolini, 2022), or to include migrant status in analyses of infertility perceptions (Passet-Wittig etal., 2020) and of medical help-seeking for infertility (Köppen etal., 2021). Despite these few exceptions, research on migrant infertility care in Europe is scarce. It comprises qualitative studies, mostly patient samples drawn from clients using reproductive health-care services (Culley etal., 2006)—yet, it is not clear whether the prevalence of infertility and medical help-seeking to have a child is similar to that of the majority population, and how much variation there is between different migrant groups in Europe. In the US, Colen (1986) coined the termstratified reproductionto describe how reproduction is structured across social and cultural boundaries. The implication is that policies and structures empower privileged—White, non-migrant women belonging to the majority group—and disempower less privileged—migrant— women throughout their life courses. The field of medically assisted reproduction (MAR) is stratified, as barriers based on class and race/ethnicity persist (Inhorn, 2018). Recent systematic literature reviews on reproductive endocrinology and infertility have only analyzed studies from the US (Christ etal., 2022; Jackson-Bey et al., 2021; Merkison et al., 2023); they predominantly indicate that ethnic and racial minority groups are disadvantaged in reproductive care and access to infertility treatment. It is unclear whether such findings can be generalized to the European context, given the differences in immigrant and ethnic minority populations and health-care systems (Calhaz-Jorge etal., 2020; Passet-Wittig & Bujard, 2021; Präg & Mills, 2017). Against this background, we pose the following research questions: First, what are the patterns and determinants of infertility among migrant groups in Germany? Second, what are the patterns and correlates of their use of medically assisted reproduction? For both questions, we compare migrants with the non-migrant majority population and examine differences among various migrant groups. For the latter, we pay particular attention to the role of the migrant generation and the migrants’ region of origin. Our study pools data from 12 waves of the German family panel study pairfam (Huinink etal., 2011) to investigate self-perceived infertility of individuals (if single) or couples. Importantly, we include uncertainty in the response behavior, i.e. the answer category of “I don’t know” to account for the sensitivity of the infertility question and cultural differences in response behavior. We go beyond existing research by studying self-perceived infertility and help-seeking behavior in the same sample. Therefore, we can relate the potential need to the usage of MAR. This allows us to draw conclusions about the extent to which differences in medical helpseeking between migrants and non-migrants may be related to different needs and/or to, e.g. institutional barriers (Jackson-Bey etal., 2021). N.Milewski et al. 25 Page 4 of 38 Background Country Context Germany makes an interesting case for this study of infertility and medical helpseeking due to the increasing multi-ethnicity of its population. Germany has been one of the main destinations for migrants in Western Europe for several decades. Therefore, the proportion of immigrants, including their descendants, has been rising steadily and accounted for about 30% of the population in 2023. Among the younger cohorts, the age group of 20 to 45years, who are of reproductive age and potential users of MAR, about 37% are immigrants, including their descendants (this group is made up of about 15% of persons with German citizenship and about 22% of persons with (exclusively) foreign citizenship) (Destatis, 2024). Since the end of World War II in 1945, immigrants came to Germany for various reasons and from a variety of regions of origin. Immigrant groups include, among others, labor migrants from southern European countries and Turkey since the 1960s, and since the 1990s, increasingly from Eastern and South-eastern European countries. In addition, immigrant groups include ethnic Germans mainly from Eastern Europe (e.g., from former Soviet countries) and refugees from the Balkan countries (following the wars in the former Yugoslavia), Iraq or Syria. In 2023, the countries of origin of migrants and their descendants in Germany were divided into 28% Near and Middle East (including Turkey), about 5% Kazakhstan, about 5% Russia, about 15% Balkan countries, about 29% North, West, Central, South, South-East Europe, and about 17% others. Socioeconomic differences, such as sex ratio, education, and household income, vary widely between these migrant groups, e.g. the share of low education is higher than among natives in Kazakhstan and the Balkan countries and highest in the Near and Middle East (Destatis, 2024). Another reason why Germany is a good case study is its long-standing low fertility rate and the sharp rise in the mean age of childbearing. Although there has been a slight increase in the total fertility rate (TFR) in recent years until 2021 (Bujard & Andersson, 2024), it still remains well below the population replacement level of 2.1 births per woman. In addition, at over 20%, Germany has a high rate of childlessness, and similar to other countries in the Global North, the causes for this are far from being fully understood. One of the reasons lies in the increasing age at which women and men are having children, which is a crucial risk factor for infertility (Dunson etal., 2002; Evers, 2002). According to the medical definition, people are considered infertile after one year or more of regular unprotected intercourse without getting pregnant (Zegers-Hochschild et al., 2017). Overall, the prevalence of self-perceived infertility in Germany is currently estimated at around 5–6% for both men and women (Passet-Wittig etal., 2020). Infertility increases with age, reflecting the age-related increase in various biological fertility problems (ESHRE, 2005). In parallel with the ongoing demographic trend of fertility postponement, the use of MAR is increasing in Europe. MAR Infertility andSeeking Medical Help toHave aChild Vary Across… Page 5 of 38 25 is a growing health-care sector in Germany and widely available (DIR, 2021), but treatment rates are relatively low compared to other European countries (De Geyter etal., 2020; Präg & Mills, 2017). One reason for this may be that access to treatment in Germany is rather restrictive and not very inclusive. Currently, public health-care insurance only reimburses married heterosexual couples and typically covers 50% of treatment costs for a maximum of three IVF (in-vitro fertilization) cycles. As a result, the use and timing of MAR is highly dependent on the economic situation of the person or couple (Köppen etal., 2021; PassetWittig, 2017). Migrants, Ethnic Diversity, andInfertility In Germany, as in other European countries, the heterogeneity of the population has increased as a result of continuing and changing immigration and different demographic behavior of immigrant and majority populations. For some time now, scholars have acknowledged that migrants are highly heterogeneous—what has been termed as “super diversity” (Vertovec, 2007). The notion of within-migrant heterogeneity is receiving increasing attention in research on the demographic behavior of migrants, such as research on fertility (Erman, 2022; Milewski & Adserà, 2023; Wilson, 2019) and research on reproductive health (Väisänen et al., 2022). Acknowledging this heterogeneity helps to move beyond a binary, simplistic distinction between immigrants and non-migrants, or natives. Key characteristics that account for migrant heterogeneity are migrant generation and region of origin. So far, gender differences and dyadic approaches that consider both partners in a couple have received only little attention (Lazzari etal., 2022). Studies on migrant fertility in Europe look almost exclusively at women and have mainly focused on how migration impacts the subsequent life course of migrants and their descendants, i.e. birth transitions, and how fertility varies among migrants according to their origin and destination contexts (Adserà & Ferrer, 2015; Kulu etal., 2019; Milewski & Adserà, 2023). Empirical studies on the fertility of immigrants in Europe provide support for the hypothesis of migrant selection, e.g. in the case of marriage migrants, which refers to first-generation migrants who move to marry a spouse abroad, and who are often subject to special immigration regulations. At the same time, the influence of socialization in high(er) fertility contexts, which persists long after migration, proves to be significant. Immigrants often have earlier childbearing schedules, overall have higher fertility than their non-migrant counterparts at destination, and childlessness is rather low among immigrants. Migrant fertility levels typically decline with increasing length of stay and in the subsequent migrant generation; while age at childbearing rises—which is usually interpreted as a result of adaptation processes and migrant children’s adjustment to the low(er) fertility contexts at destination (overview Kulu etal., 2019; for Germany: Milewski, 2007, 2010; Krapf & Wolf, 2015; Wolf, 2016). At the same time, culturally differing attitudes regarding the relevance of marriage for childbearing (Liu & Kulu, 2023), differences in gender-role attitudes, in particular towards motherhood (Haug & Milewski, 2018), persist over generations between minority and majority N.Milewski et al. 25 Page 6 of 38 groups. These cultural characteristics, along with socioeconomic factors, are conducive to (relatively) earlier and higher fertility schedules (Milewski, 2010). In addition to selection, adaptation,and socialization, another mechanism linking migration and fertility is disruption. Based on the assumptions that international migration is a stressful process (Sluzki, 1979) and that migrants may experience processes of marginalization, the disruption hypothesis predicts lower fertility among migrants compared to non-migrants. However, there is little evidence to support the disruption hypothesis. On the one hand, this may be related to the fact that most empirical studies to date have examined labor or family migrants (Mussino & Strozza, 2012). Recently, a few studies have looked at groups, which may experience more negative impacts of migration on marriage and partnership. Refugees in Finland (in the 1940s) were found to have lower fertility (Saarela & Wilson, 2022). On the other hand, most empirical studies focus on immigrants in countries with fertility below or close-to-replacement level. If majority populations have lowest-low fertility, it is virtually impossible for migrants to fall below that level. We noticed that the empirical studies on migrant fertility (including our own ones) interpret declining fertility levels as evidence of adaptation processes in migrant populations. This interpretation is based on the implicit assumption that the differences between the groups or their changes over time are the result of voluntary decisions to have fewer children. However, previous research has not systematically compared the individual fertility intentions of migrants with their fertility outcomes and the causes of any gap, and whether any gap differs from the corresponding gap among non-migrants. This raises the question of the extent to which any fertility decline and any gap between intentions and fertility are due to deliberate choices, to fertility barriers such as infertility, or to a combination of the two. Infertility is a barrier to reproduction that is also related to health. Recently, poor general and mental health among migrant women and men has been shown to reduce fertility intentions (Alderotti & Trappolini, 2022). However, comparatively few studies have looked at reproductive barriers, including infertility (Johnson etal., 2023) or perinatal health (Väisänen etal., 2022). This is particularly important for migrants, as health is unequally distributed. There is considerable evidence to suggest that international migrants, particularly those moving for work or education, tend to be positively selected for health—this is generally referred to as the healthy migrant effect (HME). Any initial health benefits for first-generation immigrants are assumed to diminish when immigrants stay longer in the host country. Such advantages also decrease over migrant generations. The cause for this process is attributed to increasing similarities between migrants and the respective host population in terms of socioeconomic factors as well as life style and structural conditions (Loi etal., 2021). The initial health benefit of migrants may disappear and their health may deteriorate to a point where it is even worse than that of the native population. Some authors link the levelling off of the HME to the experience of cumulative disadvantages and discrimination in general and the health-care system in particular, which in turn may increase the vulnerability of migrants. Such disadvantages may persist over generations, i.e. when immigrant groups develop into minoritized groups characterized by ethnicity, race, or religion (Bean & Tienda, 1990; Geronimus etal., 2006; Kulu etal., 2019). At the same time, minority-group status and lower socioeconomics are associated with occupational hazards, Infertility andSeeking Medical Help toHave aChild Vary Across… Page 7 of 38 25 environmental risks and poorer housing conditions, experiences of discrimination, lifestyle risk factors, and poorer health outcomes (Bean & Tienda, 1990; Coleman, 1994; Foner & Alba, 2008), and may contribute to a higher risk of infertility among migrant and ethnic minority groups (Jackson-Bey etal., 2021). Overall, the empirical evidence on reproductive and perinatal health supports the hypothesis of the healthy migrant effect, suggesting advantages for first-generation migrants in particular. At the same time, the evidence on reproductive health highlights the importance of region of origin as a potential marker of differences. For instance, with respect to pre-term birth (PTB)—a risk factor for poor health and development outcomes of the child—the evidence is mixed. Higher PTB risks were found in Finland, but mainly for women who immigrated from low-income countries and not for those from high-income countries (Bastola etal., 2020; Väisänen etal., 2022). In Sweden, results varied between different groups of origin (Juárez etal., 2019; Li et al., 2013) while in the UK, PTB risks were lower among immigrants (Opondo etal., 2020). In this paper, we will use the terms “fertility advantage” to refer to lower infertility and “fertility disadvantage” to refer to higher infertility. The following main working hypotheses guide our empirical study on perceived infertility. We expect to find variation in perceived infertility across migrant generations, with a migrant fertility advantage mainly in the first generation as compared to non-migrants; the fertility advantage may be smaller in the second generation (H1A on generational differences). Our second hypothesis addresses the variation by migrants’ origin-groups: We expect a greater fertility advantage for migrants in origin groups that show greater difference in fertility patterns when compared to German natives. Migrants from countries with lower ages at birth and higher fertility levels, e.g. from the Middle East, may have lower infertility compared to Germans and compared to migrants from countries with ageing fertility patterns, e.g. from other European countries (H1B on origin-group differences). A third working hypothesis refers to the role of moderators. We consider two main correlates of infertility; i.e. age and general health. The migrant generations and origin groups exhibit differences in patterns of childbearing age and health. On average, as stated above, the lower socioeconomic positions that migrants often occupy in the host country may correlate with a lower age of childbearing, higher average fertility and lower rates of childlessness. An earlier age of childbearing may imply that migrants are less affected by the postponement pattern, which increases the risk of age-related infertility. Infertility is also related to other dimensions of health and lifestyle. In our data set, we can use the information on self-rated health and assume that better health is associated with lower infertility. We expect that controlling for health, age and parenthood may reduce infertility differences between migrants and non-migrants (H1C). Migrants, Ethnic Diversity, andSeeking Medical Help toGet Pregnant Medical infertility, or the perception of it, often prompts individuals to seek help from reproductive health-care services. This is the second focus of our study. Systematic literature reviews on reproductive endocrinology and infertility (Christ etal., 2022; Jackson-Bey etal., 2021; Merkison et al., 2023) indicate that ethnic and racial minority groups in the US face disadvantages in both reproductive care N.Milewski et al. 25 Page 8 of 38 and access to infertility treatment. In the European context, however, there is limited research (Culley etal., 2006). Existing European studies suggest broad similarities between migrant groups in Europe and Black and Latino ethnic groups in the US in their experiences of prejudice and discrimination in obstetric practice (in London (Gürtin-Broadbent, 2009), for Germany and England (Johnson & Borde, 2009), in The Netherlands (van Rooij & Korfker, 2009), for Germany (Vanderlinden, 2011)). Inhorn etal. (2009) also highlighted immigrants from predominantly Muslim Arab countries in the US, whose experiences of discrimination and stigmatized perceptions of high fertility mirror those of Muslim immigrants in Europe, especially after 9/11. Barriers to accessing reproductive health care and technologies encompass a wide range of factors. These include provider-related issues such as overt discrimination, low cultural competence, and delayed referral to fertility clinics. Financial constraints and language barriers also pose significant problems (Geiger, 2003; Seifer etal., 2022). Certain aspects may be a direct result of the disadvantaged socioeconomic conditions faced by migrant or ethnic minority groups, such as lower income and difficulties in affording treatment. Indirectly, life-style andhealth factors such as a higher risk of obesity, which may be cited by providers as a reason for refusing care, contribute to lower utilization of medical expertise, lower satisfaction with treatment, and potentially lower success rates (Butts, 2021; Galic etal., 2021; Gürtin-Broadbent, 2009). Some research suggests that migrants may be more likely than non-migrants to seek medical help to get pregnant if they perceive themselves to be facing infertility. Factors related to the migrant community, such as the intergenerational transmission of culture and fertility knowledge, may influence clients’ medical help-seeking behavior (Culley & Hudson, 2009). For many migrant groups, biological parenthood remains of utmost importance, particularly in communities where childlessness is uncommon, and the societal repercussions of infertility are potentially significant (Christ etal., 2022). In Germany, immigrant women were found to have lower fertility awareness than non-migrant women, particularly in terms of knowledge regarding the age-related fertility decline (Milewski & Haug, 2022). However, they also expressed a greater willingness to use MAR when faced with conception difficulties and showed more openness towards methods such as egg donation and surrogacy which are not allowed in Germany. Furthermore, differences between migrant groups have been identified: First-generation migrants showed significantly different attitudes towards MAR use compared to non-migrants, while responses of secondgeneration migrants were more in line with those of non-migrants, indicating ongoing socioeconomic and cultural assimilation across migrant generations (Haug & Milewski, 2018). Notably, more permissive attitudes and stronger intentions to use MAR were observed, not only among women from countries with Muslim traditions, such as Turkey, but also among women from Eastern European nations such as Poland, as well as those with Christian religiosity (Milewski & Haug, 2020). Quantitative evidence on the actual behavior of seeking help to conceive among migrant and ethnic minority groups in European countries is both scarce and inconclusive. A non-patient study in Germany focused on immigrant groups, their attitudes towards MAR and their use of treatment. This study revealed no significant Infertility andSeeking Medical Help toHave aChild Vary Across… Page 15 of 38 25 Results Perception ofInfertility Table1 shows the proportions of the total sample, and of women and men, who perceived infertility by migrant generation and by country group of origin. Overall, the mean prevalence of perceived infertility is about 7.7%, with little difference between the sexes (8.0% for women and 7.5% for men). A total of 4.8% of respondents say they are unsure. With 5.4%, men are slightly more likely to state “don’t know” than women (4.2%). When we test our working hypothesis 1A, differentiating by migrant generation, we find significant differences: In the total sample and among women and men, the share of those perceiving infertility is higher among first-generation migrants compared to non-migrants and second-generation migrants. In the total sample, perceived infertility is about 5 percentage points higher among first-generation migrants than among the other two groupings. A similar pattern is found for the answer “don’t know”. 7% of the first-generation migrants answered “don’t know”, compared to 5.3% of second-generation migrants and 4.3% of non-migrants. Testing our working hypothesis H1B, differentiating by migrants’ region of origin also reveals significant differences between migrant groupings. In total, individuals from the Balkan countries are—at around 6%—by far the least likely to perceive infertility. The Balkan country grouping also remains the least likely to perceive Table 1 Perceived infertility by sex, migrant generation and region of origin (%) Calculations based on pairfam waves 1–12 (weighted data). Ntotal = 12,777 persons with n = 58,802 observations Dk Don’t know, NWCSSE North, West, Central, South, South-East Europe *indicates significant variation between the migrant status group variables regarding perceived infertility on 5% level, based on Pearson chi-squared tests, test statistics calculated for full sample only Total sample Women Men Fertile Infertile Dk Fertile Infertile Dk Fertile Infertile Dk Migrant generation* Non-migrant 88.8 6.9 4.3 89.2 7.1 3.7 88.5 6.6 4.9 Gen. 1 migrant 80.7 12.3 7.0 82.3 11.8 5.9 78.8 12.8 8.4 Gen. 2 migrant 87.1 7.7 5.3 87.4 7.8 4.8 86.7 7.5 5.8 Region of origin* Non-migrant 88.8 6.9 4.3 89.2 7.1 3.7 88.5 6.6 4.9 NWCSSE Europe 84.7 10.0 5.4 84.8 10.6 4.6 84.5 9.1 6.4 Balkan 89.1 6.0 4.9 89.9 4.4 5.7 88.1 8.1 3.8 Russia 77.9 13.7 8.4 77.1 16.0 6.9 79.2 10.1 10.7 Kazakhstan 81.9 10.6 7.6 83.8 10.0 6.2 79.9 11.2 9.0 Middle East 83.4 9.9 6.7 85.7 7.5 6.8 81.5 11.9 6.6 Other 84.0 9.9 6.1 87.3 8.8 3.9 80.5 11.1 8.4 Overall share 87.5 7.7 4.8 87.9 8.0 4.2 87.1 7.5 5.4 n 52,581 3779 2442 27,540 2131 1107 25,041 1648 1335 N.Milewski et al. 25 Page 16 of 38 infertility when differentiating by sex. In contrast, individuals from Russia are—at around 14%—the most likely to perceive infertility in the whole sample, but there are some differences between the sexes. Women from Russia have—at around 16%—the highest prevalence of perceived infertility. Among men, those from Kazakhstan and from the Middle East have the highest proportions of perceived infertility (11 to 12%), and their proportions are significantly higher than those of women from the same region. Among men from Russia, the share of those perceiving infertility is also quite high (about 10%), but much lower than that of women. Additionally, we used the combined indicator of migrant generation and region of origin for the whole sample (not shown). This indicator sheds light on the regions of origin that contribute most to the increased risk of perceived infertility among first-generation migrants. All regions of origin except the Balkans have higher perceived infertility than non-migrants, with migrants from Russia having by far the highest share at almost 15%. Overall, second-generation migrants from most regions of origin have rates of perceived infertility that are not so different from those of non-migrants (range: 3 to 9%). Migrants from Europe have the highest proportion of perceived infertility (9%). For the multivariable analyses, we proceed in two steps to test our working hypotheses, first using migrant generation as the main independent variable, and second using the combined indicator of migrant generation and region of origin. Figure1 shows the results of the multivariable analysis for migrant generation using AME (the full table of results can be found in Table7 in the Appendix). The first row in each category shows results from the baseline model (Models M1). Moderators and control variables were added in two steps (Models M2 to M3). The analyses show that first-generation migrants are 5.4 percentage points more likely to perceive infertility than non-migrants in the baseline model. First-generation migrants are also 2.7 percentage points more likely to report being unsure than non-migrants. In contrast, second-generation migrants do not differ from non-migrants in their probability of perceiving infertility. The migrant disadvantage for first-generation migrants persists when sex, parenthood, health, and age are introduced to the model (Model M2). Their introduction rather results in a slight increase in the probability of perceived infertility and a larger increase in the probability of “don’t know”-answers. Additionally, the inclusion of marital status/partnership and education in Model M3 does not change the association between migrant generation and perceived infertility. Figure2 complements the picture by highlighting differences in region of origin within migrant generations (the full table of results table can be found in Table8 in the Appendix). In the baseline model, first-generation migrants from Russia are 8 percentage points more likely to perceive infertility than non-migrants. Migrants from the Balkan countries are the group with the smallest increase in the probability of perceived infertility compared to non-migrants. Overall, these results remain stable when moderators and controls are added to the model—thus, not supporting our working hypothesis H1C on the role of the groupings’ sociodemographics. By and large, themoderators and controls showed the effects known from the literature: Persons, who were older, childless and rated their health as poor were more likely to perceive infertility (Tables7 and 8 in the Appendix). Infertility andSeeking Medical Help toHave aChild Vary Across… Page 17 of 38 25 Hence, the results do not support our working hypothesis 1A; contrary to our assumption, first-generation migrants have a fertility disadvantage compared to non-migrants. However, no such disadvantages were found for the second migrant generation. Our results also contradict our working hypothesis 1B by showing that migrants from countries where fertility patterns are characterized by a rather young fertility schedule have not lower, but higher rates of infertility and uncertainty—and thus a fertility disadvantage—compared to non-migrants. Seeking Medical Help toHave aChild In our second analysis, we look at seeking help to have a child in the sample of those who said that they were trying to have a child. Table2 shows the proportion of persons who indicated any medical help-seeking. Testing our working hypothesis H2A, i.e. comparing migrant generations, we found the lowest proportion of help-seekers among second-generation migrants and the highest among nonmigrants, while first-generation migrants were in-between. This pattern does not align with hypothesis H2A where we assumed that second-generation migrants would be closer to non-migrants than first-generation migrants. Non−migrant Gen. 1 migrant Gen. 2 migrant −.1 −.05 0 .05 .1 .15 −.1 −.05 0 .05 .1 .15 Perceived infertility Don’t know M1 M2 M3 Fig. 1 Perceived infertility, by sex and migrant generation (AME). Calculations based on pairfam waves 1–12 (weighted data), Ntotal = 12,777 persons with n = 58,802 observations. AME average marginal effects, NWCSSE North, West, Central, South, South-East Europe. Multinomial logit model; full models are available in Table7 (Appendix). Model M2 controls for sex, age, parenthood, and health. Model M3 additionally controls for marital status/partnership, education,and wave N.Milewski et al. 25 Page 18 of 38 By region of origin—testing our hypothesis H2B—variation among migrants was less pronounced, except for the very heterogeneous group of “other” regions. The lowest shares of help-seeking were found among respondents from the Middle East, Russia, and Kazakhstan. These patterns are not entirely consistent with what would be expected from our findings on perceived infertility, where nonmigrants would have lower needs than first-generation migrants, and people from the Middle East, Russia and Kazakhstan would have a higher need as opposed to other groupings. In fact, we found the opposite pattern of use: the groupings with the highest infertility—i.e. potential need—have lower treatment rates than those with lower need. Thus, our results do not support our working hypotheses H2A and H2B, but rather indicate a more heterogeneous pattern. Due to the relatively small sample size, we focus on the comparison between migrants and non-migrants in the following analyses, testing the role of moderators and controls (working hypothesis 2C). For the same reason, a simple indicator of seeking medical help vs. not seeking medical help is applied in most descriptive and multivariable analyses. Table 3 relates the need for treatment—to the extent that this need can be expressed in terms of perceived infertility—to medical help-seeking. We compare Non−migrant Gen. 1, NWCSSE Europe Gen. 1, Balkan Gen. 1, Russia Gen. 1, Kazakhstan Gen. 1, Middle East Gen. 2, NWCSSE Europe Gen. 2, Balkan Gen. 2, Russia Gen. 2, Kazakhstan Gen. 2, Middle East −.1 −.05 0 .05 .1 .15 −.1 −.05 0 .05 .1 .15 Perceived infertility Don’t know M1 M2 M3 Fig. 2 Perceived infertility, by migrant generation and migrants’ region of origin (AME). Calculations based on pairfam waves 1–12 (weighted data), Ntotal = 12,777 persons with n = 58,802 observations. AME average marginal effects, NWCSSE North, West, Central, South, South-East Europe. Multinomial logit model; full models are available in Table8 (Appendix). Model M2 controls for sex, age, parenthood, and health. Model M3 additionally controls for marital status/partnership, education,and wave. Residual categories “Gen. 1, other” and “Gen. 2, other” not shown in figure Infertility andSeeking Medical Help toHave aChild Vary Across… Page 19 of 38 25 help-seeking rates between migrants and non-migrants by perceived infertility status. Generally, those who perceive infertility are about twice as likely to have sought medical help as those who do not perceive infertility. However, the helpseeking rate among the latter is still significant, suggesting that self-perceived infertility does not capture all the reasons for seeking medical help. Help-seeking rates are higher among non-migrants, whether they perceive infertility or not. However, the difference is much more pronounced when no fertility problems are perceived. In a next step, we compare the share of help-seekers for two different types of treatment between migrants and non-migrants. As Table 2 shows, 33% of nonmigrants sought help to have a child, compared to about 28% among first-generation migrants and 21% among second-generation migrants. When assessing the type of treatment (not shown), migrants are less likely than non-migrants to mention the family doctor/gynecologist as the highest level of treatment (about 14% vs. about 23%), but migrants and non-migrants are similarly likely to say that they received treatment typically provided in fertility clinics (9.7% vs. 9.6%). Importantly, if we look only at those who sought medical help to get pregnant, migrants are more likely to have received treatment at a fertility clinic (migrants: about 40%; non-migrants: about 29%). Figure 3 shows the results of the multivariable analysis, which are consistent with the descriptive findings (see Tables2 and 3). There is a stable disadvantage for migrants in seeking medical help to have a child: Their probability of seeking help is about 8 percentage points lower than that of non-migrants. The negative association Table 2 Any medical helpseeking, by migrant generation and region of origin (%) Calculations based on pairfam waves 7–12 (weighted data). Ntotal = 1500 persons with n = 2,345 observations NWCSSE North, West, Central, South, South-East Europe *indicates significant variation between the migrant status group variables regarding medical help-seeking on 5% level, based on Pearson’s chi-squared test Any medical help-seeking No Yes Migrant generation* Non-migrant 67.0 33.0 Gen. 1 migrant 72.3 27.7 Gen. 2 migrant 79.5 20.5 Region of origin* Non-migrant 67.0 33.0 Europe + Balkan 77.0 23.0 Russia/Kazakhstan 82.4 17.6 Middle East 82.8 17.2 Other 58.4 41.6 Overall share 69.8 30.3 n 1642 703 N.Milewski et al. 25 Page 20 of 38 between migrant status and help-seeking remains relatively stable in magnitude and significance when moderators andcontrol variables are added—thus not supporting our working hypothesis H2C on the role of the sociodemographic composition. Of the covariates, parenthood and perception of infertility are the strongest predictors—each reducing the probability of help-seeking by about 20 percentage points. As parenthood is an important predictor and migrants are more likely to have children, also in our sample, we also tested whether having children moderates the association between migrant status with medical help-seeking, but found no such effect (not shown). Overall, the effects of the explanatory variables are in the directions as known from the literature. Respondents in our sample are more likely to have sought medical help to get pregnant if they are older, childless, married, have higher education, have a household income of 3500€ or more, and perceive their health status as poor. Robustness andData Quality Our estimated prevalence of perceived infertility of 8.0% among women and 7.5% among men is within the range of other European studies of self-reported 12-month infertility, but at the lower end of this range (Cox etal., 2022). They also compare well with another pairfam study using the same indicator, which estimated slightly lower mean prevalence of 5.6% for women and 4.9% for men (Passet-Wittig etal., 2020). The higher average prevalence in the current study could be due to the ageing of the sample, as the other study only used waves 1 to 7. In our sample, 30% of all women and men have sought medical help to have a child. This also compares well with a study on non-migrants and migrants in Germany (Milewski & Haug, 2022), which is based on a different data source. Importantly, our estimates proved rather robust to modifications to the sample. For the main analyses on perceived infertility, observations from respondents who reported a pregnancy for themselves or—where applicable—their partner were excluded because they were not asked about perceived infertility. As a sensitivity analysis (results available on request), we treated these respondents/couples as Table 3 Help-seeking rates, by migrant status and perceived infertility (%) Calculations based on pairfam waves 7–12 (weighted data). Ntotal = 1500 persons with n = 2345 observations Perceived infertility Ratio of help seekers perceiving infertility/help seekers not perceiving infertility Yes No Don’t know Non-migrant 64.4 29.4 25.2 2.2 Migrant 43.0 23.0 16.7 1.9 Total % 57.8 27.4 20.9 2.1 n 137 552 58 Infertility andSeeking Medical Help toHave aChild Vary Across… Page 21 of 38 25 fertile, based on the assumption that most couples who achieve a pregnancy have conceived naturally, and re-ran the analyses. No substantial differences were found when comparing the effect estimates in this analysis with the findings in Tables7 and 8 in Appendix, indicating that the assumption about natural conception was reasonable. However, this may change with increasing use of medically assisted reproduction. It would therefore be preferable to have information on how each pregnancy was conceived. As is sometimes the case in panel surveys, the routing of respondents to the perceived infertility question was subject to change. In waves 2 and 3, preload information on infertility status was used in the filter. Respondents who considered themselves or their partners as definitively infertile were not re-asked the same question, implicitly assuming their sterility. From wave 4 onwards, the question was posed without referencing the preload information. To test whether the conditional filtering in waves 2 and 3 affected the results, we conducted analyses excluding these waves, but found no substantial differences (results available on request). This study looked at medical help-seeking in the whole population of women and men of reproductive age, which gives a broad picture of those seeking help to have child. These analyses showed that migrants were less likely to have sought medical help. However, we would expect to find a similar negative association in a sample of Non−migrant (ref.) Migrant (Both) fertile (ref.) At least 1 person infertile Don’t know if self/couple (in)fertile −.3 −.2 −.1 0 .1 .2 .3 M1 M2 M3 M4 Fig. 3 Help-seeking by migrant status and perceived infertility (AME). Calculations based on pairfam waves 7–12 (weighted data). Ntotal = 1500 persons with n = 2345 observations. AME average marginal effects. Logistic model; full models are available in Table9 (Appendix). Model M2 controls for sex, age, parenthood, and health. Model M3 additionally controls for marital status/partnership, education, and household income. Perceived infertility is added in Model M4 N.Milewski et al. 25 Page 22 of 38 only people perceiving infertility, as migrants are over-represented in this sample. To test this, we re-ran the analyses in a sample of 240 people perceiving infertility (in waves 7 to 10) and also found a negative association. However, we are careful about interpreting this finding because the cell sizes become very small when we differentiate between migrants and non-migrants. More data would be needed to investigate this further. We also wanted to include more life style and health variables—i.e. BMI, smoking, alcohol—in addition to subjective health. Here, we faced some limitations. BMI is updated every year, but only for the main sample and not for the Demodiff sample, thus it contains a lot of missing values. Smoking was only included for the full sample in waves 5, 7, 9, and only for the refreshment sample in wave 11. Alcohol consumption was only included in waves 5, 7, 9, and 11. Including them would have resulted in a large proportion of missing values for these variables. Alternatively, using only selected waves would have been problematic, given that self-perceived infertility among migrants is a rather uncommon event. Finally, we considered random effects panel models as an alternative estimation method (see "Plan of Analysis" Section) as an additional robustness check. We estimated random effects multinomial logit models for the infertility analysis and random effects logit models for the medical help-seeking analysis. We conclude that the findings are robust to the estimation method and that main conclusions of the analyses remain valid (results available upon request). Conclusion This study examines differences in perceived infertility and seeking medical help to get pregnant among migrants compared to non-migrants in Germany, providing insights into a group often overlooked in infertility research, particularly in Europe. Studying migrants and their reproductive health needs is particularly important in countries like Germany and many other European countries, where the migrant population exceeds one quarter of the population. Using representative data from the general population over 12 waves, we compared the perceived infertility of women and men and/or their partners and their use of medical help to conceive with that of non-migrants. Our analysis included firstand second-generation migrants from various regions of origin. Contrary to our expectations of a fertility advantage in the first generation and among migrants from countries at an earlier stage of the second demographic transition, the results did not consistently support these assumptions. Instead, we observed significant variation among migrant groups. In particular, a fertility disadvantage for first-generation migrants emerged, challenging the notion of a healthy-migrant effect on fertility. First-generation migrants faced a higher risk of perceived infertility and were more likely to express uncertainty about their fertility status. To put these effects into context, the prevalence of perceived infertility in our sample was approximately 8%, indicating that it is a relatively uncommon occurrence in the general Infertility andSeeking Medical Help toHave aChild Vary Across… Page 23 of 38 25 population. Consequently, differences between social groups were modest, with an increase of around 5 percentage points among first-generation migrants compared to non-migrants and the second generation (controlling for other factors). However, given the low baseline risk, this increase of 5 percentage points means that more than twice as many first-generation migrants experience infertility compared to nonmigrants—a remarkable scale effect. However, infertility is only one facet of reproductive trajectories and barriers. Another relevant question is whether migrants and non-migrants differ in their medical help-seeking behavior. Our descriptive findings indicated that first-generation migrants not only face higher infertility rates, but also show lower utilization of infertility care. Additionally, we expected that differences between migrants and non-migrants would be less pronounced in the second generation than in the first. However, we found no differences in the risk of self-perceived infertility for secondgeneration migrants compared to non-migrants, but observed even lower treatment rates compared to the first generation. Taken together, these findings point to a pattern of “stratified reproduction” with migrant groups being double-disadvantaged compared to non-migrants. We observed differences in the risk of perceived infertility according to migrants’ regions of origin. We expected lower perceived infertility among migrants from countries where fertility patterns are characterized by young birth ages and low childlessness compared to Germany, which is characterized by late fertility and high childlessness. Instead, we discovered higher rates of infertility and uncertainty—and thus a fertility disadvantage—among groups from Russia, Kazakhstan, and the Middle East, including Turkey. Strikingly, our descriptive analysis suggested that these groups have the lowest use of infertility treatment in our—admittedly—small sample. These findings imply that processes of fertility disruption may be affecting the first generation and certain migrant origin groups in particular. On the one hand, Germany’s general, universal health-care system may, on average, facilitate the integration of migrant health across generations. On the other hand, ethnic marginalization processes may be evident in certain cases. Future research should look more closely at the underlying causes of these differences. Finally, in the realm of migrant fertility research, it is essential not to automatically interpret higher fertility levels among migrants compared to non-migrants as evidence against fertility disruption, or declining fertility levels among subsequent generations as proof of adaptation processes. Instead, future studies should systematically compare fertility ideals and intentions with actual fertility outcomes, and consider reproductive barriers as an explanation for deviations. Such studies can complement existing research and shed light on the extent to which seemingly adaptive processes are due to deliberate choices versus involuntary reproductive barriers. This would ultimately allow direct assessment of the hypothesis of fertility disruption in migrant populations. Furthermore, we examined various stages of help-seeking. Our analysis revealed significant differences among migrants and non-migrants in Germany. Migrants are significantly less likely to receive treatments which are typically provided by a N.Milewski et al. 25 Page 24 of 38 general practitioner or gynecologist (only). Interestingly, there is virtually no difference in the use of treatments typically administered at fertility clinics, such as insemination or IVF. When focusing solely on those seeking any form of medical help, migrants show an even higher tendency to undergo treatment in fertility clinics. This implies that migrants who have decided to seek medical help in conceiving are more likely to seek more advanced and invasive treatments. This finding is consistent with a study showing that first-generation migrants in Germany display greater openness to medically assisted reproduction (MAR) and stronger intentions to use MAR compared with non-migrants (Haug & Milewski, 2018). Taken together, these findings underline, on the one hand, that help-seekers represent a distinct group, demonstrating the importance of using general population samples for a comprehensive understanding of the process of seeking medical help at various stages of treatment. On the other hand, the reasons for this increased openness towards MAR among migrants warrant attention. Previous research suggests that stronger norms regarding having biological children and the significance of motherhood play a crucial role in migrant groups from countries with more familistic social structures. Consequently, infertility is a concern for childless individuals or couples as well as for families wishing to expand beyond one child. As this study shows, this appears to be important to consider in studies of migrants, but should also be considered for non-migrants. Like all empirical research, this study has data-related limitations and offers suggestions for future data collection. We used a social science survey in Germany, which for the first time included questions on the sensitive topic of infertility and help-seeking. Although the pairfam survey covers the general population and includes a representative sample of immigrants, it does not over-represent any particular migrant group. Due to the relatively infrequent, though not rare, occurrence of infertility and help-seeking, the immigrant case numbers were small, limiting the ability to differentiate between migrant groupings as desired. We conducted multivariable analyses for infertility based on migrant generation and region of origin, but were only able to make fairly broad groupings by country of origin. We did not estimate perceived infertility separately for women and men because our research suggests that infertility is a shared experience within a couple, as is potential treatment. However, many causes of infertility may be sex-specific and thus may indicate specific prevention measures and health-care needs for women and men. Therefore, future analyses should also look at patterns of infertility by sex (Trappolini & Giudici, 2021). While the pairfam data provided a solid foundation for studying population heterogeneity in perceived infertility, it was less comprehensive for examining medical help-seeking to get pregnant. Multivariable models controlling for migrant generation or region of origin, let alone for both variables simultaneously, were not feasible. Consequently, the findings indicate a migrant disadvantage, but the variation we found between migrant groupings based on merely descriptive analyses rests on less solid ground. Nevertheless, both variables—migrant generation and (parents’) region of origin—are crucial markers for probing within-migrant diversity Infertility andSeeking Medical Help toHave aChild Vary Across… Page 31 of 38 25 Table 8 (continued) Model 1 Model 2 Model 3 Fertile Infertile Dk Fertile Infertile Dk Fertile Infertile Dk Age in years (ref. < 35) 35 − 39 − 0.077** 0.070** 0.007 − 0.072** 0.065** 0.007 40 + − 0.138** 0.125** 0.013* − 0.130** 0.114** 0.016* Parenthood (ref. no) 0.091** − 0.041** − 0.050** 0.117** − 0.071** − 0.046** Bad health (ref. good health) − 0.032** 0.028** 0.004 − 0.029** 0.028** 0.001 Marital status/partnership (ref. married) No partner 0.052** − 0.068** 0.015** Unmarried 0.028** − 0.040** 0.012** Education (ref. primary/lower secondary) Higher secondary − 0.121** 0.083** 0.039** Tertiary − 0.043** 0.032** 0.011** Missing value − 0.200** 0.205** − 0.005 Calculations based on pairfam waves 1–12 (weighted data). Ntotal = 12,777 persons with n = 58,802 observations AME average marginal effect, Dk Don’t know, NWCSSE North, West, Central, South, South-East Europe * p < 0.05, **p < 0.01 Model 3 includes wave as a control (not shown, available on request) N.Milewski et al. 25 Page 32 of 38 Table 9 Results of the multivariable logistic analysis on the probability of medical help-seeking to have a child, all respondents (AME) Calculations based on pairfam waves 7–12 (weighted data). Ntotal = 1500 persons with n = 2345 observations AME average marginal effect * p < 0.05, **p < 0.01 Model 4 includes wave as a control (not shown, available on request) Model 1 Model 2 Model 3 Model 4 Migrant (ref. non-migrant) − 0.084* − 0.074* − 0.083** − 0.083** Women (ref. men) 0.093** 0.099** 0.092** Age in years (ref. < 35) 35 − 39 0.085** 0.062* 0.049 40 + 0.178** 0.157** 0.114** Parenthood (ref. no) − 0.208** − 0.225** − 0.212** Bad health (ref. good health) 0.081* 0.097** 0.083* Marital status/partnership (ref. married) No partner − 0.168** − 0.164** Unmarried − 0.129** − 0.122** Lower education (ref. higher education) − 0.043 − 0.051 Household income in € (ref. < 1500) 1500–2500 0.091 0.093 2500–3500 0.054 0.047 3500 + 0.114* 0.105* Missing value 0.028 0.034 Perceived infertility (ref. (both) fertile) At least 1 person infertile 0.201** Don’t know if self/couple (in) fertile − 0.073 Infertility andSeeking Medical Help toHave aChild Vary Across… Page 33 of 38 25 Funding Open Access funding enabled and organized by Projekt DEAL. Not applicable. Declarations Conflict of interest The authors declare no conflict of interest. Ethical Approval Not applicable. Patient Consent Statement Not applicable. Permission to Reproduce Material from Other Sources Not applicable. Data Availability The data that support the findings of this study are openly available in GESIS at https:// doi. org/https:// doi. org/ 10. 4232/ pairf am. 5678. 14.1.0. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/ licenses/by/4.0/. References Adamson, G. D., de Mouzon, J., Chambers, G. M., Zegers-Hochschild, F., Mansour, R., Ishihara, O., Banker, M., & Dyer, S. (2018). 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