Fertility in the port city of (1846‐1920) A detailed analysis of immigrants’ spacing behaviour in an urbanizing context

Sarah Moreels – Mattijs Vandezande – Koen Matthijs

Working paper of the Scientific Research Community Historical Demography

WOG/HD/2010‐14

ISBN 9789067841580

EAN 9789067841580 D/2010/1192/6

© Centre for Sociological Research (CeSO) Parkstraat 45 box 3601 B‐3000 Leuven All rights reserved. Except in those cases expressly determined by law, no part of this publication may be multiplied, saved in an automated datafile or made public in any way whatsoever without the express prior written consent of the author. Alle rechten voorbehouden. Niets uit deze uitgave mag worden verveelvoudigd en/of openbaar gemaakt door middel van druk, fotokopie, microfilm, of op welke andere wijze ook, zonder voorafgaande schriftelijke toestemming van de auteur.

Fertility in the port city of Antwerp (1846‐1920) A detailed analysis of immigrants’ spacing behaviour in an urbanizing context

Sarah Moreels – Mattijs Vandezande – Koen Matthijs

Sarah Moreels Centre for Sociological Research (CeSO) Research domain Family and Population K.U.Leuven Parkstraat 45 – bus 3601 – 3000 Leuven – België Tel: 32 16 323472 Fax: 32 16 323365 [email protected]

Mattijs Vandezande Centre for Sociological Research (CeSO) Research domain Family and Population K.U.Leuven Parkstraat 45 – bus 3601 – 3000 Leuven – België Tel: 32 16 323056 Fax: 32 16 323365 [email protected]

Koen Matthijs Centre for Sociological Research (CeSO) Research domain Family and Population K.U.Leuven Parkstraat 45 – bus 3601 – 3000 Leuven – België Tel: 32 16 323173 Fax: 32 16 323365 [email protected]

1. Introduction During the past decades, various researchers have emphasized the importance of migration for the fertility transition in 19th century Western (Alonso, 2000; Eggerickx, 2001; Lee, 2000; Moch, 2003; Oris, 1996; Perrenoud, 1995; Reher & Iriso‐ Napal, 1989; Sharlin, 1978). However, due to the limited registration of migratory movements in historical sources, research concerning the relationship between migration and fertility is still limited in historical perspective. Moreover, the results of this research often point in opposite directions because migration is a complex process and the term ‘migrant’ contains a diversity of ‘moving people’. Consequently, generalizing the results of this research is hard because the investigated migrants displayed a contextual specificity and were all investigated in different settings (Quaranta, Creighton & Matthys, 2007). Sharlin (1978) argued that immigrants married later than natives and that their fertility is also lower than the indigenous population (Sharlin, 1978). This result was also confirmed by Lee (2000) for the German port city of Bremen. For these migrants, the duration between marriage and first birth, and the length of birth intervals between the first and second child was always longer in comparison to the natives (Lee, 2000, 187). In contrast with these results, Perrenoud (1995) suggested that, in Geneva, immigrant women had a higher fertility (Perrenoud, 1995). Oris (1996) showed that foreign born migrants were pioneers in the fertility decline in Tilleur, while Flemish immigrants restricted their fertility later than the native population (Oris, 1996). Eggerickx (2001) examined migrants in the industrial city of Charleroi and found that they smoothly integrated in the city and soon adopted the reproductive behaviour of the urban (native) population. He also found that fertility control developed with the same intensity among both the natives and immigrants during the 19th century (Eggerickx, 2001). So these results show that, due to their varying socio‐economic and cultural background and the different settings, various groups of migrants wrote a different fertility history in past times. In this paper, an attempt is made to shed (new) light on the interrelations between migration and fertility behaviour in past societies. In this work, the relationship between migration and fertility is specifically investigated in an urbanizing context. The fast urbanisation and demographic expansion in the port city of Antwerp () during the second half of the 19th century influenced the fertility behaviour of the indigenous and foreign inhabitants in a different way. Investigation for the city of Antwerp already showed that migrants were on average two years older than natives when contracting the first marriage and especially rural, semi‐rural and foreign migrants had a higher age at first marriage (Moreels & Matthijs, 2009). Moreover, McDonald’s model of starting, spacing and stopping (1984) demonstrated that the mean length of inter‐birth intervals was larger for migrants and that migrant’s mean age at last birth was lower than that of the natives, which resulted in a lower crude parity for migrants. For this reason, it is interesting to focus in this paper in detail on the spacing behaviour of migrants in the port city of Antwerp. By paying specific attention to the migratory characteristics of the Antwerp immigrants and by comparing their spacing behaviour with the native population, different strategies of birth control can be identified among various groups of migrants.

1 2. Setting: the port city of Antwerp During the 19th century, the port city of Antwerp underwent major socio‐economic and demographic transformations. In the first half of the 19th century, due to a shortage of investments, the textile production which had been one of Antwerp’s main industries, collapsed (Jeuninckx, 1964; Lis, 1986). Antwerp, an industrial city relying on textile industry, transformed itself during the second half of the 19th century to a port city with an international reputation. From 1850 onwards, Antwerp evolved from an inland port to an international port characterized by an intensive import and export of goods. Both external and internal factors were responsible for this expansion. A good business climate and competition from neighbouring ports, along with a continuous industrialization in Belgium, the rapid transformation of the Rhine district (Germany) and the invasion of European markets with cheap foreign grain stimulated the port activities externally. Moreover, local level initiatives were also taken to boost the Antwerp industrial and commercial activities. The expansion of the railway system1 promoted these market opportunities even more. The concentration of economic activity, together with rising employment in the port and a strong population growth created a favourable environment for the establishment of various industrial activities. In 1896, more than 35% of industrial employment in the province of Antwerp was located in the port city itself, and more than two thirds was established in the vicinity of the city of Antwerp (Loyen, 2003; Van Klink, 2003; Veraghtert, 1986). The 19th century expansion of Antwerp as a port and service centre thoroughly changed the labour market. Irregular employment in the port, and the demand for workers with good physical strength and endurance made that unemployed textile workers often could not (because of an inappropriate stature) or would not (because of pride for its own textile industry) work in the Antwerp port. The female work opportunities as cotton spinner or lace maker also became increasingly scarce, so that more and more women practiced a job in the informal service sector, often linked to one of the port activities (e.g. fish seller, hawker, etc.). Because of these new employment possibilities, the port city of Antwerp became a real attraction for (mainly male) migrants during the 19th century (Asaert, 2007b; Lis, 1986; Van Isacker, 1966; Vanfraechem, 2005; Winter, 2009). During the 19th century, the city of Antwerp was also characterized by a demographic expansion. In the first half of the 19th century, the Antwerp population ‐ consisting of around 55,000 inhabitants in 1800 ‐ grew strongly during the subsequent decades. Especially during the years 1846‐1900, the city knew a real population explosion: the port town went from more than 88,000 inhabitants in 1846 to 273,000 people at the end of the 19th century and developed into the biggest city of Belgium (Vrielinck, 2000, 1680‐1681 & 1668‐1669). The strong population growth in Antwerp during the 19th century was achieved through a positive natural and migratory growth. The crude birth rate, which was always higher than the crude death rate, increased dramatically during the second half of the 19th century (with a peak in 1871‐1880). Because the crude mortality rate (with its

1 The first railway traffic between Antwerp and Mechlin took place on the 3rd May 1836. In the following years, the railway system was enlarged to Liege and the German border (Asaert, 2007a).

2 peak in 1861‐1870) declined a decade earlier than the crude birth rate, natural increase was the strongest during the period 1871‐1890 (Kruithof, 1964). Besides the natural growth, the demographic expansion in the city of Antwerp was also strongly affected by migration. From the second half of the 19th century, the large influx of immigrants caused a sharp rise in the migratory increase. At the beginning of the 19th century, approximately 22% of the population was not born in Antwerp and this share rose up till 43.4% in 1900 (Kruithof, 1964; Winter, 2009). All these changes had a strong impact on the social life of the Antwerp population. Fluctuations in rents and the shortage in the local housing market forced poor people into the overcrowded streets and slums and increased the appeals for public charity (Hannes & Lis, 1969; Lis, 1969; Lis, 1986; Vercauteren, 2001; Winter, 2008). The thousands of immigrants who were looking for new employment opportunities in Antwerp were often confronted with housing, hygiene and integration problems (Asaert, 2007b; Lampo, 2002; Van Houtven, 2008). During the last decades of the 19th century, these problems were even strengthened by the arrival of more than one million European migrants who emigrated with the Red Star Line from Antwerp to the ʹNew Worldʹ (Asaert, 2007c; Veraghtert, 1986; Vervoort, 2005). As a result of these economic and social changes, the city of Antwerp faced a chronic lack of space for the port and urban development during the 19th century. The expansion of the port (with the construction of new docks), and the demolition of the old and construction of new walls offered a solution to the increasing population pressure in Antwerp (Asaert, 2007b; Blomme, 2003; De Caigny, 2000; De Kesel, 1964; Devos, 2003; Veraghtert, 1986). As a result of this urban expansion, the public infrastructure such as transport, water, electricity and gas supplies, as well as schools, hospitals, police stations and fire stations were developed thoroughly from the mid 19th century (Bertels, 2008).

3. The Antwerp COR*‐database This research uses the historical demographic database which has been built since 2003 by the Leuven Research Group of the Family and Population (CeSO, K.U.LEUVEN). The database, called the Antwerp COR*‐database, contains longitudinal and intergenerational data at the individual level and offers a unique combination of features. It spans nearly eight decades of time (1846 to 1920) and covers three successive generations (cohorts 1820‐1870), and this for the whole district of Antwerp (an area of 62 municipalities, see figure 1) (Matthijs & Moreels, 2010). After ample evaluation of the pros and cons of different data gathering strategies, a letter sample has been chosen. All persons whose family name starts with the letter combination COR* (for example Coremans, Corluy, Cornelissens, etc.) are selected in the historical sources. The two main sources for this database are the population registers and the vital registration records (birth, marriage and death certificates). The population registers, which are of high quality in Belgium, were set up as follows: every household of every house number in every street, and this for each municipality, had to been registered. From 1846 onwards, all changes ‐ such as births, deaths, marriages, divorces and also internal moves and external migration ‐ were

3 continuously recorded in the population registers (Gutmann & van de Walle, 1978; Leboutte & Obotela, 1988). The population registers also include information on family relationship, occupation, nationality, the militia and a list of all households that succeeded each other in the house. The head of the household was always listed first, followed by spouse, kids, relatives, servants, and people strange to the household (Bracke, 2008, 286; De Belder & Vanhaute, 1993, 101‐103). Moreover, because the vital registration records are more reliable (Gutmann & van de Walle, 1978) and sometimes even provide additional data (for example for stillbirths), this information was supplemented to the information of the population registers. By linking all observations of a given individual together, individual life courses have been reconstructed.

In the Antwerp COR*‐database, around thirty thousand complete life courses were constructed, which amounts to more than 800,000 person‐years (Matthijs & Moreels, 2010). The database contains extensive micro‐data on individual life courses, family patterns and migration processes, which thus allows investigating the fertility behaviour of natives and migrants in depth.

Figure 1. Map of Belgium with the district of Antwerp, 1900.

4 4. Fertility and migration Detailed information on both the fertility behaviour and the migration process is crucial when investigating the impact of migration on fertility during the fertility decline. Before going deeper into the analysis, it is important to identify (1) the direct determinants of fertility and (2) the characteristics of the migration process. The direct determinants of fertility refer to all biological and social factors that affect the conception of a (new) child. These determinants have a direct impact on the starting (when the first child was born), the spacing (interval between successive births) and the stopping (when the couple finally stop reproducing) of fertility (Bongaarts, 1978, 105‐132; Mosley, 1979, 87‐90). Because this research focuses on the spacing behaviour of couples and will only examine closed birth intervals, more information is given on factors influencing the length of closed birth intervals. The length of interbirth intervals indicates whether couples had many or few children born during their fertile life course (period between 15‐49 years). If the time between the previous birth and the next conception is limited, more children can be produced while the crude parity will be restricted if birth intervals are longer (Knodel, 1987). The length of the waiting time to conception is determined by the fecundability (i.e. the monthly chance of conception for fertile, non‐contraceptive women, which is directly dependent on the coital frequency of these women). Differences in coital frequency (e.g. the absence of men with certain occupations or health problems) and physiological differences make that fecundability varies from woman to woman (Bongaarts & Potter, 1983; Wood, 1994). Closed birth intervals are also strongly affected by postpartum amenorrhea. During this period after childbirth, a woman can not become pregnant again, regardless of whether or not there was sexual intercourse (Santow, 1987; Wood, 1994, 331‐370). The length of this period is mainly determined by the breastfeeding practice. Intensive breastfeeding delays the resumption of menstruation and ovulation, which postpones the following pregnancy (Coale, 1986). Prolonged intensive breastfeeding thus extends the closed birth intervals (Bongaarts, 1978, 115‐119). Research also demonstrates the impact of breastfeeding on the survival of children. By breastfeeding the infant, the child is better protected against certain diseases and infections (Scott & Duncan, 2000; Vandenbroeke, Van Poppel & Van der Woude, 1983) and it indirectly promotes the survival of the infant by (temporarily) postponing the next pregnancy (Scott & Duncan, 2000, 71‐87). Migration is a complex phenomenon and depending on various circumstances and motivations, a variety of migration patterns can be distinguished. Some came from the neighbouring rural areas, others from just over the border, yet others from much further; some came alone, others with their entire family; some migrated only temporary and quickly turned back, others stayed their whole lives; some came to work, others to find a partner, yet others with unclear motives. Because of this diversity, it is crucial to pay attention to the specific characteristics of the migration process. When focusing on this, it is important to identify that the migratory characteristics refer both to the individual characteristics of the migrant and the characteristics of the migration process itself. The individual characteristics of the migrant, such as sex, age at migration, place of origin and socio‐economic status of the migrant each have an effect on the fertility

5 behaviour of migrants. Alter (1988), for example, found a similar demographic behaviour between the indigenous population and women who immigrated before the age of 15 to Verviers. However, women of the ‘Pays de Herve’ (a rural area in the Belgian Ardennes) who migrated before their marriage (around the age of 27) had a different fertility pattern (Neven, 2003). The place of origin (rural, semi‐rural, urban or foreign) is also crucial. During the 19th century, people born in an urban context who migrated to a rural area retained their (urban) fertility pattern, while immigration to a city modified the fertility behaviour of rural and semi‐rural migrants (Alter, Oris and Neven, 2007; Oris , 1996; Quaranta, Creighton & Matthys, 2007; Reher & Iriso‐Napal, 1989). Oris (1996) showed in this context that the reproductive behaviour of foreign migrants also differed from that of the internal migrants (Oris, 1996). Moreover, research stated that the chance of social mobility for a migrant depended strongly on the area of origin (e.g. internal versus international migration) and the period of migration. In times of a favourable economic situation, migrants improved their social position while a stagnating or declining economy forced people to migrate (Delger, 2006). The general characteristics of the migration process that have an impact on the fertility behaviour are length of residence, migration network, migration distance, type of migration (individual or family migration) and direct or multi‐stage migration. Vanhaute and Matthys (2007) proved that the fertility patterns of servants differed according to the duration of the migration, and Eggerickx (2001) mentioned a similar reproductive behaviour between the permanent migrants and the indigenous inhabitants of Charleroi. The social network of the migrant is also important for the spreading of birth control attitudes and practices. Because migrants not only make decisions on their own, the knowledge and experience of other relatives and non‐ relatives are also important (Casterline, 2001; Lee, 2000). Moreover, the distance between the place of origin and the new destination is also crucial. Family migration (whether or not associated with chain migration) usually happened within a limited distance, while individual migration was often a medium or long‐distance move (Kok, 2004; Oris, 1996). Frequent (and mostly shorter) migration was mainly associated with a decline in social status, while long‐distance migration stimulated upward mobility (Delger, 2006). Multi‐stage migration, which was strong during the industrialization, also encouraged the integration and adaptation of migrants in their place of arrival (Anderson, 1971; Eggerickx, 2001).

5. Analysis In this research, the spacing behaviour is analysed in the port city of Antwerp and this during a period characterized by fast urbanization (1846‐1920). By investigating the spacing behaviour of both the indigenous and immigrant population, it is possible to identify different fertility strategies. In this paper, we focus specifically on the impact of the individual characteristics (sex, age at migration, place of origin, socio‐economic status) on the fertility behaviour of migrants. In a follow‐up paper, we will also incorporate the general characteristics of the migration process in the analyses.

6 By analogy with the work of Kolk (Kolk, 2009), we opted for only analysing the transition from second to third birth because this is a good choice for several reasons. First, when studying historical marital fertility, it is important to avoid family related factors that affect fertility (e.g. the connection between family formation and the transition to first birth). Because most couples have a stable life situation at the birth of the second child, we expect their behaviour to be comparable with their general pattern of marital fertility. Second, during the 19th century, most couples made a transition from the second to the third birth, so a large share of all mothers are covered. When choosing a later birth interval, more couples will have experienced either the death of one of the parents or a declining fertility because of lower fecundity. By opting for the transition to the third birth, most mothers are relatively young, fecundity is reasonably high and mortality is low. Finally, stopping behaviour is expected to be detected in later birth intervals, because most families had more than two children during the 19th century. In this way, we avoid mixing up indications of spacing and stopping behaviour.

Out of the COR*‐database2 (containing the whole district of Antwerp), we selected the native Antwerp population and all immigrant couples who went to the port city of Antwerp and became parents (i.e. gave birth) inside the city. In this way, it is possible to compare the spacing behaviour of immigrants with this of the native Antwerp population. As mentioned above, all married couples with (at least) 2 children are incorporated in this research. Moreover, all unions are included and only first marriages for the mother are used in this work. Illegitimate children are excluded from the analysis and twins were considered as a single birth. Stillbirths (which are only registered in the death certificates and not recorded in the population registers) are also included in this research. In our analyses, the following variables are included as explanatory variables: • Age at second birth: the age of the mother influences the probability of another conception, because biological factors and decreased coital activity decline women’s fertility at older age (Coale & Trussel, 1974). • Marriage duration: marriage duration is also associated with fecundability. As Wood and Weinstein (1988) proved, coital frequency declines when marriage duration increases. • Death of the previous child(ren): if the previous child died while being breast fed, the stopping of breastfeeding increases the fecundity of the mother (Santow, 1987). Moreover, even if (one of) the previous child(ren) died after the breastfeeding period, parents may be willing to ‘replace’ this child (Preston, 1978). In this way, the death of one of the previous children may decrease the parent’s interest in birth control, so by taking both the death of the first and the second child into account, a indicator of family size regulation may be found. • Sex of the previous children: if parents had a sex preference, the sex composition of the previous children may affect their fertility behaviour (Zhao, 1997).

2 In this paper, we made use of the COR*‐database, release February 2010.

7 • Occupation of the parents: the occupation declared at marriage is used as occupational covariate and is further categorized into different social classes3. Although female occupations were often not well registered in the 19th century, it is still interesting to take the mother’s occupation into account when investigating fertility behaviour, because the mother’s occupation is often stronger related to birth spacing than the father’s occupation (Van Bavel, 2002). • Origin of the parents: as mentioned before, the place of origin is crucial when examining the fertility behaviour of migrants. Migrants coming from urban areas behaved differently from rural or foreign migrants (Oris , 1996; Reher & Iriso‐Napal, 1989). In this paper, the various kinds of migrants are discerned by birth place and population size in 1900. People originating from places with a population smaller than 3,000 are considered rural migrants, those from places with populations between 3,000 and 10,000 are considered semi‐rural migrants, and those from places with a population higher than or equal to 10,000 are considered urban migrants. • Immigration to Antwerp: the timing of immigration also determines one’s demographic behaviour. In the COR*‐database, exact information on migration is known (by a migration date), so we are able to group people by their timing of immigration. In this paper, a division is made between immigration to the port city of Antwerp (1) before the age of 15, (2) after the age of 15 and until marriage and (3) immigration after marriage. • Period: by taking different time periods into account, it is possible to interpret the fertility behaviour during the fertility transition. In Belgium, the fertility transition reached cruising speed during the second half of the 19th century. Aggregated data for the district of Antwerp shows that the fertility reached its culmination point in the period 1866‐1880, followed by a clear decline in subsequent years (Lesthaeghe, 1977). By splitting up our research period, pre‐ transitional couples (giving birth before 1880) can be compared with couples who lived during the fertility transition. In our analyses, occupational status, origin and timing of immigration were investigated for both parents. However, because father’s occupation, migration status and his timing of immigration to Antwerp did not influence the transition from second birth to third conception, these covariates are not presented in the final models. As Van Bavel already revealed in his work for Leuven (Van Bavel, 2002), individual level female characteristics are in the Antwerp context also more decisive for fertility behaviour than the male characteristics. Table 1 presents the descriptive statistics of the explanatory variables of our final models. In these analyses, only intervals that ended with the conception of a third child

3 In the dataset used for this article, the professional registrations on the marriage certificates are coded according to the Historical International Standard Classification of Occupations (HISCO) (Van Leeuwen, Maas & Miles, 2002). After coding, the Social Power scheme (SOCPO), constructed by Van de Putte and Miles (2005), is used as social class scheme in this research. People with ‘no occupation’ and people with missing occupational information were classified in separate groups (see table 1).

8 within 5 years after the previous one are used (this to exclude extremely sub‐fecund couples). Table 1. Descriptive statistics of the variables N % Mothers age at second birth <25 years 540 30,82 25‐27,4 years 420 23,97 27,5‐29 years 285 16,27 30‐34 years 318 18,15 >=35 years 189 10,79 Time from marriage to second birth (in years) * 3,99 (2,39) Only first child died 23,08 Only second child died 21,79 Both previous children died 7,18 Sex of previous children male male 535 29,62 female male 404 22,37 male female 427 23,64 female female 440 24,36 Occupation of mother elite 152 12,29 middle class 173 13,99 semi‐skilled 84 6,79 no occupation 150 12,13 missing 678 54,81 Origin of mother native (born in Antwerp) 795 43,73 rural born migrant 256 14,08 semi‐rural born migrant 261 14,36 urban born migrant 388 21,34 foreign born migrant 118 6,49 Timing of immigration to Antwerp (mother) as a child (<= 15 years) 87 4,79 before marriage (>15 years ‐ until marriage) 286 15,73 after marriage 561 30,86 no immigration to Antwerp 884 48,62

Year at second birth < 1880 498 27,44 1880‐1894 511 28,15 > 1894 806 44,41 * mean and standard deviation presented

By making use of a Cox proportional hazard model, the transition from second birth to the conception of the third child is investigated. In this research, only closed birth

9 intervals (i.e. birth intervals that did end with a new birth) are examined, which indicates that we are interested in the pacing component of birth spacing4. In our analyses, time to (third) conception is thus the event of interest, also called ‘failure’ in event history analysis (Allison, 1984). The hazard ratios represent that the hazard rate increases or decreases for a one unit change in the corresponding covariates. Values greater than one indicate an increased risk of conception (i.e. the time to conception is shorter), values lower than one indicate a reduced risk of conception (i.e. the time to conception is longer). Our models in table 2 give information on the spacing behaviour of couples who gave birth in the port city of Antwerp during the years 1818‐1923. By investigating the fertility behaviour over a period of more than 100 years, a good indication of changing spacing behaviour over time is given. To interpret the spacing behaviour specifically during the fertility transition, our research period is split up into three time periods in model 2. Model 1 presents some interesting results. Although not statistically significant, the hazard ratios by the age of the mother clearly show the interval length was greater for older women. Time to third conception was significantly influenced by the duration of the marriage. For each extra year between marriage and second birth, it took 9 percent longer for the third conception (p < 0,0001). The death of the previous children also affected the hazard rate strongly. When only the first child died, the interval shortened with 39 percent. When only the second child died, the interval was 29 percent shorter. So these findings show that the time to a third conception was always shorter when one of the previous children died. The death of the infant had thus a clear impact on the hazard rate of the next conception. When both previous children died, the interval length reduced with about 70 percent. Mothers in the port city of Antwerp of which both previous children died, delayed their third conception significantly during the 19th century. The sex composition of the previous children also affected time to third conception. When taking both previous births into account, a statistically significant decrease of 27% appears for the ‘male – female’ combination compared to two boys. Although statistically indistinguishable, the combination ‘female – male’ also delays the third birth with 16%. These findings thus suggest that parents in the city of Antwerp retarded their next conception when their previous children had a different sex. Occupation of the mother also seems to have an effect on birth spacing. In comparison with mothers with no occupation, all other social groups have a shorter third birth interval. Especially the higher social classes speed up their third conception with respectively 41% (elite) and 73% (middle class). Different breastfeeding patterns among various social classes or a different fertility behaviour (e.g. having children on limited time) may explain these findings (Knodel, 1988). Moreover, knowing that women with no occupation were active in housebound sectors during the 19th century (Moreels, 2010), they devised strategies that allowed combining child care and work. Probably for this reason, the time to next conception was longer for these women.

4 For an elaborated explanation of modelling the length of closed birth intervals, see Van Bavel and Kok (2010).

10 Table 2. Cox proportional hazard model of the transition from second birth to the conception of the third child, city of Antwerp, 1818‐1923 MODEL 1 MODEL 2 Haz. Std. Haz. Std. Mothers age at second birth Ratio Err. p Ratio Err. p <25 years 0,95 0,14 0,700 0,99 0,14 0,942 25‐27,4 years 0,96 0,14 0,787 0,86 0,13 0,295 27,5‐29 years 1 1 30‐34 years 0,77 0,13 0,108 0,76 0,13 0,096 * >=35 years 0,81 0,16 0,282 0,70 0,14 0,070 * Time from marriage to second birth 0,91 0,02 0,000 *** 0,91 0,02 0,000 *** Death of first child 1,39 0,20 0,024 ** 1,37 0,20 0,031 ** Death of second child 1,29 0,27 0,228 1,42 0,30 0,098 * Death of second child * death of first child 0,24 0,09 0,000 *** 0,22 0,08 0,000 *** Sex of previous children male male 1 1 female male 0,84 0,11 0,174 0,86 0,11 0,240 male female 0,73 0,10 0,020 ** 0,73 0,10 0,017 ** female female 1,02 0,13 0,883 1,04 0,13 0,772 Occupation of mother elite 1,41 0,27 0,073 * 1,35 0,26 0,120 middle class 1,73 0,30 0,002 *** 1,36 0,24 0,084 * semi‐skilled 1,29 0,28 0,247 0,96 0,22 0,855 no occupation 1 1 missing 1,10 0,16 0,537 1,07 0,16 0,651 Origin of mother native (born in Antwerp) 1 1 rural born migrant 0,75 0,12 0,075 * 0,86 0,14 0,360 semi‐rural born migrant 0,77 0,12 0,098 * 0,75 0,12 0,071 * urban born migrant 0,96 0,13 0,763 0,96 0,13 0,751 foreign born migrant 0,97 0,21 0,887 1,02 0,22 0,925 Timing of immigration to Antwerp (mother) as a child (<= 15 years) 1 1 before marriage (>15 years ‐ until marriage) 1,75 0,44 0,027 ** 1,30 0,33 0,300 after marriage 1,73 0,42 0,024 ** 1,51 0,37 0,090 * no immigration to Antwerp 1,73 0,41 0,022 ** 1,36 0,33 0,201 Year at second birth < 1880 1 1880‐1894 0,79 0,10 0,050 ** > 1894 0,37 0,05 0,000 *** Failures N=469 N=469 Wald chi2 (p<0,0001) 84,74 (df=22) 160,22 (df=24) P‐values * p<0,1 ** p<0,05 *** p<0,01

11 Origin of the mother and her timing of immigration to the city of Antwerp emphasize the importance of including migratory variables in the analysis. For migrants born in a rural or semi‐rural area, it takes about 25% longer to conceive a third child, while urban and foreign born migrants show a similar spacing behaviour with the native population. Various factors can explain these findings. Variations in the duration of breastfeeding, mostly more and longer practised in rural and semi‐rural areas, can delay the next conception. Rural and semi‐rural immigrants maybe also had more difficulty with the living situation at arrival (e.g. integration and housing problems) than the urban migrants which might explain the longer birth intervals. Moreover, periods of time with no or limited contact between the partners (because of migration or work opportunities) could also influence the birth interval. By analogy with the work of Reher and Sanz‐Gimeno (2007), it is possible that the Antwerp urban and foreign migrants also implemented fertility limitation more efficiently during the fertility transition. The age at migration also has a statistically significant effect on the time to conception. The spacing behaviour of women who immigrated to Antwerp at older age was comparable to the native Antwerp population (i.e. people who didn’t migrate), while migrating to the port city of Antwerp as a child influences (i.e. delayed) the third birth interval significantly. For a better understanding of the question why immigration as a child retarded the length to third conception so drastically, we tested if the origin of the migration interacts with the timing of migration. Although the interaction terms are statistically indistinguishable (probably because of the scarce amount of data for each group), the findings suggest that for all migrants, regardless of their place of origin5, migration as a child or before marriage always delayed the next conception with about 50% (see table 3 in the appendix6). This suggests a different fertility behaviour among women who immigrated before marriage to the port city of Antwerp. Although we could expect that women who arrived early in life in Antwerp would adapt to the fertility behaviour dominant in the city, our results show that this was not the case. In the Antwerp context, immigrating at younger age clearly influenced one’s spacing behaviour later on in life. On the other hand, our findings demonstrate that women who migrated after marriage showed a similar spacing behaviour as the native population, which suggests that these migrant women adapted quickly to the fertility behaviour dominant at destination or that the fertility preferences of these immigrants were already more similar to the fertility behaviour of the Antwerp population. In model 2, a period effect is added to the model. The results discussed above are all present in this second model, sometimes even with more significant results (e.g. mother’s age, death of the second child). Moreover, the period variable significantly shows a trend in longer birth intervals throughout the end of the 19th century. Couples giving birth during the early stages of the fertility transition (period 1880‐1894) had a lower speed (21% lower) than pre‐transitional couples. For people who were born and procreated during the fertility transition (period > 1894), it took even 63 percent longer for conceiving a third child, so the interval between the second birth and the next

5 Only the semi‐rural born migrants were an exception on this. 6 For an easier interpretation of the results, “no immigration to Antwerp” was taken here as reference group by the variable “timing of immigration to Antwerp (mother)”.

12 conception is much longer for these couples. This reflects a changing spacing behaviour – i.e. spreading successive births ‐ during the last quarters of the 19th century in the port city of Antwerp. The lengthening of birth intervals during the more advanced stage of the fertility transition, together with increases in women’s age at first birth and the practice of stopping behaviour, led to the unprecedented fall in completed family size in other historical settings (Reher & Sanz‐Gimeno, 2007). In the Antwerp context, we also expect prolonged birth intervals during the latter stages of the fertility transition to be decisive for the Antwerp reproductive change during the second half of the 19th and the early decades of the 20th century.

6. Conclusion The effect of migration on childbearing is hardly investigated in past societies. For this reason, this paper focuses specifically on the fertility behaviour of migrants and non‐ migrants. By paying specific attention to the individual characteristics of the immigrant (sex, age at migration, place of origin, socio‐economic status), differences in spacing behaviour can be identified among various groups of migrants. The port city of Antwerp (Belgium), characterized by a fast urbanisation and demographic expansion during the second half of the 19th century, is the perfect setting for our research. The recently developed historical demographic COR*‐database which contains socio‐demographic life courses at the individual level is the basic source of this research. The COR*‐database, containing the migration paths of individuals and their families for the entire district of Antwerp during the period 1846‐1920, allows for studying historical migration in detail. The results prove that, besides the natural determinants of the interval length, individual characteristics of the migrant also clearly influenced one’s spacing behaviour. By dividing migrants by origin, it became clear that rural and semi‐rural born migrants delayed their third conception with 25%. Urban and foreign born migrants on the contrary had a similar fertility behaviour as the native Antwerp population. Integration problems in the new setting, together with different ideas and habits about fertility probably affected the birth interval of rural and semi‐rural born migrants in the Antwerp context. The timing of migration also affected the spacing behaviour of migrants strongly during our research period. When migrating to the port city after marriage, women exhibited a similar spacing behaviour as the non‐migrating Antwerp population, while migration before marriage always prolonged the birth interval strongly. These results demonstrate that it is crucial to identify different groups of migrants when investigating the impact of migration on fertility. When comparing the fertility behaviour of migrants with the fertility levels at origin, it will be possible to understand how immigrants’ fertility was affected by the move to the port city of Antwerp. By adding the general characteristics of the migration process and their interaction with the individual characteristics of the migrant in new analyses, a deeper understanding of the migration‐fertility theories (socialisation, adaptation, selection or disruption hypothesis) may emerge.

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18 Table 3. Cox proportional hazard model of the transition from second birth to the conception of the third child, city of Antwerp, 1818‐1923 MODEL 1 MODEL 2 MODEL 3 Haz. Std. Haz. Std. Haz. Std. Mothers age at second birth Ratio Err. p Ratio Err. p Ratio Err. p <25 years 0,95 0,14 0,700 0,99 0,14 0,942 1,00 0,15 0,986 25‐27,4 years 0,96 0,14 0,787 0,86 0,13 0,295 0,87 0,13 0,353 27,5‐29 years 1 1 1 30‐34 years 0,77 0,13 0,108 0,76 0,13 0,096 * 0,77 0,13 0,108 >=35 years 0,81 0,16 0,282 0,70 0,14 0,070 * 0,73 0,14 0,105 Time from marriage to second birth (in years) 0,91 0,02 0,000 *** 0,91 0,02 0,000 *** 0,91 0,02 0,000 *** Death of first child 1,39 0,20 0,024 ** 1,37 0,20 0,031 ** 1,39 0,20 0,026 ** Death of second child 1,29 0,27 0,228 1,42 0,30 0,098 * 1,46 0,32 0,079 * Death of second child * death of first child 0,24 0,09 0,000 *** 0,22 0,08 0,000 *** 0,22 0,08 0,000 *** Sex of previous children male male 1 1 1 female male 0,84 0,11 0,174 0,86 0,11 0,240 0,86 0,11 0,252 male female 0,73 0,10 0,020 ** 0,73 0,10 0,017 ** 0,71 0,10 0,011 ** female female 1,02 0,13 0,883 1,04 0,13 0,772 1,01 0,13 0,960 Occupation of mother elite 1,41 0,27 0,073 * 1,35 0,26 0,120 1,38 0,27 0,098 * middle class 1,73 0,30 0,002 *** 1,36 0,24 0,084 * 1,35 0,24 0,097 * semi‐skilled 1,29 0,28 0,247 0,96 0,22 0,855 0,96 0,22 0,857 no occupation 1 1 1 missing 1,10 0,16 0,537 1,07 0,16 0,651 1,05 0,16 0,751 Origin of mother native (born in Antwerp) 1 1 1 rural born migrant 0,75 0,12 0,075 * 0,86 0,14 0,360 0,99 0,27 0,962 semi‐rural born migrant 0,77 0,12 0,098 * 0,75 0,12 0,071 * 0,64 0,17 0,093 * urban born migrant 0,96 0,13 0,763 0,96 0,13 0,751 1,01 0,25 0,974

19 foreign born migrant 0,97 0,21 0,887 1,02 0,22 0,925 1,05 0,34 0,869 Timing of immigration to Antwerp (mother) as a child (<= 15 years) 0,58 0,14 0,022 ** 0,73 0,18 0,201 1,26 0,50 0,557 before marriage (>15 years ‐ until marriage) 1,01 0,15 0,930 0,96 0,15 0,777 1,71 0,64 0,156 after marriage 1,00 0,12 0,998 1,11 0,14 0,416 1,14 0,21 0,466 no immigration to Antwerp 1 1 1 Year at second birth < 1880 1 1 1880‐1894 0,79 0,10 0,050 ** 0,77 0,10 0,035 ** > 1894 0,37 0,05 0,000 *** 0,36 0,04 0,000 *** Rural born * immigration as child 0,22 0,24 0,172 Rural born * immigration before marriage 0,60 0,31 0,320 Rural born * immigration after marriage 1,18 0,46 0,664 Semi‐rural born * immigration as child 0,41 0,31 0,240 Semi‐rural born * immigration before marriage 0,38 0,20 0,061 * Semi‐rural born * immigration after marriage 0,59 0,22 0,160 Urban born * immigration as child 0,52 0,28 0,229 Urban born * immigration before marriage 0,49 0,23 0,124 Urban born * immigration after marriage 0,97 0,30 0,923 Foreign born * immigration as child 0,38 0,45 0,409 Foreign born * immigration before marriage 0,49 0,34 0,298 Foreign born * immigration after marriage 0,90 0,47 0,834 N failures N=469 N=469 N=469 Wald chi2 (p<0,0001) 84,74 (df=22) 160,22 (df=24) 168,56 (df=36) P‐values * p<0,1 ** p<0,05 *** p<0,01

20