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Revisiting the urban graveyard debate An analysis of mortality differences between migrants and natives in North-Western European port cities: Antwerp,

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Presentation on theme: "Revisiting the urban graveyard debate An analysis of mortality differences between migrants and natives in North-Western European port cities: Antwerp,"— Presentation transcript:

1 Revisiting the urban graveyard debate An analysis of mortality differences between migrants and natives in North-Western European port cities: Antwerp, Rotterdam & Stockholm, 1850-1930 Paul Puschmann, Robyn Donrovich, Per-Olof Grönberg, Graziela Dekeyser & Koen Matthijs

2 Urban Graveyards

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

4 Migration and mortality: Theory and empirical evidence Selection effects o Healthy migrant effect o Salmon bias effect Short term negative effects o Migrants lacked defenses against epidemics o Reverse: Migrants brought in new diseases to which natives were not resistant Long term positive effects o Less exposure to disease in youth leads to higher post-reproductive life expectancy Long term negative effects o Long-term residence nullifies healthy migrant effect

5 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 labor and housing market could lead to excess mortality among certain groups of migrants. o Mortality as an indicator of social exclusion among migrants. o Mortality differences among migrants and natives learn us about differences in the fulfillment of primary needs between both groups

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

7 Aims of the paper Describing and explaining mortality differences between natives and migrants at ages 30+ o Over the life course o 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.

8 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?

9 Total population development, 1850-1930

10 Crude death rates, 1850-1930

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

12 Data and method Antwerp COR* database Historical Sample of the Netherlands (HSN) Stockholm Historical Database (SHD) Kaplan-Meier survival curves Gompertz proportional hazard models o Time at risk starts at age 30 o Failure event: death o Censoring moments: Out-migration End of registration

13 Bivariate results by migration status Antwerp Rotterdam Stockholm

14 Bivariate results by birth region Antwerp Rotterdam Stockholm

15 Bivariate results by age at immigration Antwerp Rotterdam Stockholm

16 Multivariate results Antwerp Relative mortality risks and standard errors for death at ages 30+, Antwerp (n=1799) Sex RRSE Women(ref) Men 1.577***.086 Birth cohort 1800-1839.833 +.080 1840-18591.480***.131 1860-1879(ref) 1880-1890.355*.147 Birth region Abroad.849*.070 Antwerp district1.034.089 Antwerp metro area(ref) Elsewhere in Belgium.964.056 Unknown.473***.070 Age at arrival <161.015.390 16-30(ref) 31-451.168.242 45+.509**.104 Unknown.975.155 Civil status Unmarried.827.099 Married(ref) Widowed / divorced / other.603***.061 Unknown2.477***.150 Occupation Professionals(ref) Foremen and skilled.896.172 Farmers1.090.313 Day laborers and unskilled1.174.216 Unknown.575***.090 Controlled for age Exponentiated coefficients and standard errors + p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001

17 Multivariate results Rotterdam Relative mortality risks and standard errors for death at ages 30+, Rotterdam (n=380) Sex RRSE Women(ref) Men1.376*.182 Birth region Abroad.812.219 Province of Zuid-Holland.650.193 Rotterdam(ref) Elsewhere in the Netherlands.490*.144 Unknown.510**.105 Birth cohort <1860(ref) 1860-18791.100.157 1880-19001.302.287 1900-19201.486.896 Age at arrival >15(ref) 15-24.882.252 25+.708.197 Unknown.709.222 Civil status Unmarried(ref) Married.800.131 Widowed / separated1.390*.272 Unknown - Occupation Professionals(ref) Foremen and skilled1.284.218 Day laborers and unskilled1.427 +.306 Unknown1.661**.309 Controlled for age Exponentiated coefficients and standard errors + p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001

18 Multivariate results Stockholm Relative mortality risks and standard errors for death at ages 30+, Stockholm (n=27 951) Sex RRSE Women(ref) Men1.563***.020 Birth region Abroad.747***.032 Stockholm county.843***.020 Stockholm city(ref) Elsewhere in Sweden.793***.012 Birth cohort <1860(ref) 1860-18691.120***.020 1870-18891.262***.026 1890-19301.454***.126 Age at arrival >15(ref) 15-24.845*.061 25+.899.063 Unknown.686***.047 Civil status Unmarried(ref) Married1.097***.015 Divorced/ Widowed.704***.013 Unknown - Occupation Professionals(ref) Foremen and skilled1.118**.041 Day laborers and unskilled1.295***.056 Unknown.804***.026 Controlled for age Exponentiated coefficients and standard errors + p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.00

19 Interaction sex* birth region RotterdamStockholm Antwerp

20 Summary of results General picture: Migrants experienced lower mortality risks o Strongest healthy migrant effect in Rotterdam Healthy migrant effect less clear or even absent at working ages, more pronounced in later life. Opposite development of mortality risks over time in Antwerp and Stockholm Some groups of migrants had higher mortality risks than natives o Male domestic migrants in Antwerp (opposite in Rotterdam)

21 Future improvements of the paper Add more cases for Rotterdam o Domestic migrants who moved to suburbs (Kralingen, Feijenoord, Charlois, etc.) o Domestic migrants from DVI sample Add more variables o Urban/rural variable o Distance to birth place Conduct sensitivity analyses More interaction effects will be tested


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