1. Revisiting the urban graveyard debate
An analysis of mortality differences between migrants and natives in North-Western European port cities:
Antwerp, Rotterdam & Stockholm,
Paul Puschmann, Robyn Donrovich, Per-Olof Grönberg, Graziela Dekeyser & Koen Matthijs
Seminar at the Cambridge Group for the History of Population and Social Structure
February 9, 2015

2. Content of the seminar Personal background PhD thesis in a nutshell
Paper presentation

3. Personal background Bachelor in History, Radboud University Nijmegen
Research Master in Historical Sciences (track Historical Demography), Radboud University Nijmegen
Two research stays at the Dutch Institute in Morocco (NIMAR)
PhD program Social Sciences, KU Leuven, Belgium
Research group Family and Population Studies
PhD. Fellowship from Research Foundation Flanders (FWO)
Associate editor of Historical Life Course Studies

4. Faculty of Humanities, Radboud University Nijmegen
Dutch Institute in Morocco (NIMAR), Rabat
Faculty Social Sciences,
KU Leuven

5. Family and Population Studies
Group on contemporary demography
Group on historical demography
Antwerp COR* database
Databases on marriage certificates
Historical Life Course Studies

6. Overview of PhD thesis
Main Question: How did processes of social inclusion and exclusion of migrants evolve in Northwestern European port cities in the period ?
Setting
Antwerp, Rotterdam & Stockholm
Data
Antwerp COR* database, Historical Sample of the Netherlands (HSN) and Stockholm Historical Database (SHD)
Four Sub-Topics
Meeting and mating
Marriage and family formation
Career paths and social mobility
Health and later-life mortality

7. Social inclusion and exclusion
Social inclusion: Process which leads to a situation in which migrants have increasingly access to (public) education, health care, social security systems, affordable housing, the labor and the marriage market and cultural and political activities (Papillon 2002).
“Social inclusion extends beyond bringing the ‘outsiders’ in … It is about closing physical, social and economic distances separating people, rather than only about eliminating boundaries or barriers between us and them” (Omidvar & Richmond 2003).
Social exclusion is the opposite process of social inclusion.

8. Social inclusion of migrants, 1850-1930
Contemporary observers and sociologists of the time were worried about the fate of the growing number of urban in-migrants.
Chicago School of Sociology: Migrants became uprooted and ended up at the edge of urban society.
Lack of a social network.
Migrants were believed to be disproportionately involved in poverty, crime, alcohol abuse, prostitution, etc.
Quantitative turn from the 1970’s on: Stayers fared better than leavers, and often even better than natives.
Aim of PhD thesis is to revisit this intriguing debate with the help of new data and new techniques.

9. Paper presentation

10. Urban graveyards

11. Urban graveyard theory
John Graunt
Mortality in cities higher than in countryside
Burials outnumbered christenings in 17th century London
Cities grow as a result of rural-to-urban migration
Allan Sharlin
Migrants responsible for high urban mortality rates
Debate on mortality differences between migrants and natives

12. Migration and mortality: Theory and empirical evidence
Selection effects
Healthy migrant effect
Hispanic Paradox
Salmon bias effect
Short term negative effects
Migrants lacked defenses against epidemics
Reverse: Migrants brought in new diseases to which natives were not resistant
Long term positive effects
Less exposure to disease in youth leads to higher post-reproductive life expectancy
Long term negative effects
Long-term residence nullifies healthy migrant effect
Some studies report excess mortality of migrants for the age category 50+

13. Disfavored in life, favored in death?
Due to healthy migrant effect, excess mortality among natives is the rule.
Excess mortality among migrants is exceptional and asks for explanations.
Discrimination of migrants in the labour and housing market, no or limited access to poor relief, as well as anti-migrant violence, could lead to excess mortality among certain groups of migrants.
Mortality as an indicator of social exclusion among migrants.
Mortality differences among migrants and natives teach us about differences in the fulfillment of primary needs between both groups.

14. Mortality as an indicator of social inclusion
Adaption of Maslow's Hierarchy of Needs
Source: McAdams 2006

15. Aims of the paper
Describing and explaining mortality differences between natives and migrants at ages 30+
Over the life course
In three different port cities
Detecting excess mortality among certain categories of migrants.
Gaining more insight into processes of social in- and exclusion, and the mechanisms behind those processes.

16. Historical context: Antwerp, Rotterdam & Stockholm
Three port cities
Similar demographic development
Differences in economic development
Different urban functions
Divergent paths of social in- and exclusion?

17. Total population,

18. Crude death rates,

19. Urban in- and out-migration, 1850-1920
In-Migration
Out-Migration

20. Total population according to migration status

21. Data
Three large historical demographic databases with micro- level data:
Antwerp COR* database
Historical Sample of the Netherlands (HSN)
Life Course Release
HSN Release DVI _Beta
Stockholm Historical Database (SHD)

22. Datasets
Three datasets consisting of life course information of migrants and natives.
Research persons are followed within the city from age 30 on, until they died, left the city or until the end of registration.
Information is stored in a person-period file.
Antwerp
Rotterdam
Stockholm
No. of research persons
13,658
1,907
226,113
Time at risk (person years)
239,436
38,664
3,473,387
Mean age at first entry 30
30.2
31.47
Mean age at exit
47.5
50.4
46.84
No. of failures (recorded deaths)
1,799
573
27,951

23. Age at death distribution (%)
Antwerp (n=1799)
Rotterdam (n=573)
Stockholm (n=27,951)

24. Method Kaplan-Meier survival curves
Gompertz proportional hazard models
Time at risk starts at age 30 or immediately upon arrival in case migrants arrived after age 30
Failure event: death
Censoring moments:
Out-migration
End of registration

25. KM survival estimates by migration status
Antwerp
Rotterdam
Stockholm
Strongest healthy migrant effect in Rotterdam
In Antwerp and Stockholm no differences in the first twenty years; during later ages migrants fare better.

26. KM survival estimates by birth region
Antwerp
During later life migrants have lower mortality risk

27. KM survival estimates by birth region
Rotterdam
Especially migrants from elsewhere in the Netherlands fared well

28. KM survival estimates by birth region
Stockholm
Small relative increase of mortality risk of international migrants after 50 years of observations

29. KM survival estimates by urban/rural birthplace
Antwerp
Rotterdam
Stockholm
In Antwerp and Stockholm advantage of having grown up in the countryside appeared only during later ages.

30. KM survival estimates by age at immigration
Antwerp
Arriving late reduced mortality risks

31. KM survival estimates by age at immigration
Rotterdam
Arriving late reduced mortality risks
Fast increase in mortality risk of early arrivals after 40 years of analysis time

32. KM survival estimates by distance
Rotterdam
Migrants who were born between 50 and 100 km from Rotterdam had smaller mortality risks.
Migrants who had moved more than 250 km fared relatively bad.

33. Table 1a Gompertz Proportional Hazard Model, Antwerp (n=1799)
RR SE
Controlled for age, civil status and occupation. Exponentiated coefficients and standard errors
+ p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001

34. Table 1b Gompertz Proportional Hazard Model, Antwerp (n=1799)
RR SE
Controlled for age, civil status and occupation. Exponentiated coefficients and standard errors
+ p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001

35. Table 2a Gompertz Proportional Hazard Model, Rotterdam (n=573)
RR SE
for women only!
Controlled for age, civil status and occupation. Exponentiated coefficients and standard errors
+ p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001

36. Table 2b Gompertz Proportional Hazard Model, Rotterdam (n=573)
RR SE
Controlled for age, civil status and occupation. Exponentiated coefficients and standard errors
+ p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001

37. Table 3a Gompertz Proportional Hazard Model, Stockholm (n=27,951)
RR SE
For men and women, but stronger for women
Controlled for age, civil status and occupation. Exponentiated coefficients and standard errors
+ p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001

38. Table 3b Gompertz Proportional Hazard Model, Stockholm (n=27,951)
RR SE
Controlled for age, civil status and occupation. Exponentiated coefficients and standard errors
+ p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001

39. Interaction sex* birth region
Rotterdam
Standardized for age, urban/rural birthplace, birth cohort, age at arrival, marital status, and occupation

40. Interaction sex* distance
Rotterdam
Antwerp
Stockholm
Standardized for age, urban/rural birthplace, migration status, birth cohort, age at arrival, marital status, and occupation; + p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001

41. Interaction migrant status* civil status
Rotterdam
A significantly less widowing and divorced effect for domestic migrants.

42. Summary of results
General picture: Migrants experienced lower mortality risks
Strongest healthy migrant effect in Rotterdam
No significant healthy migrant effect in Antwerp
In Antwerp and Stockholm healthy migrant effect absent during first twenty years of analysis.
Opposite developments of later-life mortality risks over time in Antwerp compared to Rotterdam and Stockholm; Increased risk for women in the two industrializing cities.
Some groups of migrants had higher mortality risks than natives.
Male domestic migrants in Antwerp
Male international migrants in Rotterdam

43. Discussion I What caused healthy migrant effect in urban areas?
Selection effect:
People who move are on average healthier than people who do not move
Duration of stay in a city
Arriving later is better
Early life factors
Being born in the countryside reduced mortality risk
Why don’t we find always a healthy migrant effect in all cities and in all migrant groups?
Role of migrants in society and degree of societal openness
Specific situation in Antwerp: Migrant men ended up in dangerous port labour.
Discrimination of certain groups of migrants?
Italian and German men in Rotterdam had increased mortality risks.
The same is true for migrants in Antwerp who moved over medium-distances ( km)
Did these men end up in the most dangerous jobs?

44. Discussion II Gender differences
Over-all women (both migrants and natives) fare better than men.
However, strange increase in mortality of women over time in Rotterdam and Stockholm.
Related to industrialization?
Role of social network
Results interaction migration status* civil status in Rotterdam
Were migrants better able to cope with hardship?
Were migrants less in want of a network in times of trouble?

45. Future improvements of the paper
In the next stage all three datasets will be appended in order to directly compare the three cities.
Dig further into excess mortality among certain migrant groups
Cross-tabs (profile of migrants)
Role of occupation
More interaction effects will be tested
Residence within the city

46. Questions and comments

47. Thank you for your attention!