immigrant mortality in israel jon anson dept.of social work ben gurion university of the negev 84105...
TRANSCRIPT
Immigrant mortality in Israel
Jon AnsonDept.of Social Work
Ben Gurion University of the Negev84105 Beer Sheva, Israel.
BSPS, September 2004, LeicesterSession 5: Health and Ethnicity
Analysis made possible by a grant from the Israel Science FoundationData provided by Central Bureau of Statistics, Israel
Population Pyramid, Israel, Census 1995
6 4 2 0 2 4 6
0
10
20
30
40
50
60
70
80
90
Age
Gro
up
Population percentages
Jews (m) born in Israel
Jews (f) born in Israel
Arabs (Palestinians) Male
Arabs (Palestinians) Female
Jews (m) born abroad
Jews (f) born abroad
Distribution of immigrants to Israel,by period and origin, 1948 – 1995
114,28125,40536,717196,464Avg / Year
685,683558,907587,472687,624482,857Total
1.010.011.134.58.5Asia
4.910.047.613.70.8Africa
90.855.235.147.578.2Europe
3.124.55.50.71.6America
0.10.30.83.510.9Unknown
1990-19951968-19891952-19671948-1951Pre-State
Period
Population groups, Israeli population at census, 1995
9.2130,0443,262,611
42.5546,294Total
3.11,027101,75747.53.1FSU As.
14.06,600472,36647.514.8FSU Eur
12.12,465203,59747.56.3W. Eur.
28.57,239253,79967.58.2E. Eur.
20.51,33564,99862.52.1Balkans
4.4910723,80942.50.7Ethiopia
11.63,503300,88852.59.3N. Africa
13.22,860216,27857.56.7Asia
2.042,4151,181,206
37.535.4Israel
Jews Born In:
5.622,493443,91137.513.4Arab
CDRDeathsExposureMed AgePercentOrigin Group
Population 25 and above; Age in 5 year categories; Exposure 4/11/95 – 31/12/2001
Survivorship Analysis, Control Variables, Ages 25 +
Exp(coefficient)Control Entered
344 (4)2146 (3)24 (1)70231 (11)
LR Gain (df)
0.884Householder
1.249Single
1.236Widowed
1.242DivorcedMarital
Status(base: married)
0.6890.687University
0.8080.806High SchoolCertificate
(base: none)
0.5180.522 Working
1.0541.0991.126Immigrant
1.0871.0901.1021.102Age
0.5610.6110.6830.683Sex
N = 564,294, all coefficients significant at p < 0.05
Relative Risks: Population Groups, Ages 25 and above,
by Control Variables introduced
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
Ethiopia W.Europ AsiaE.Europe Balkans FSU EurAfrica Arab FSU Asia
Survivorship Analysis, Control Variables, Ages 15 -34
Exp(coefficient)Control Entered
81 (4)85 (3)7 (1)256 (11)LR Gain (df)
0.917Householder
1.824***Single
1.066Widowed
3.242***DivorcedMarital
Status(base: married)
0.588***0.608***University
0.740***0.740***High SchoolCertificate
(base: none)
0.620***0.592*** Working
1.525 **1.486 **1.505 ** Immigrant
1.063***1.029***1.017***1.017***Age
0.372***0.347***0.369***0.369***Sex
N = 314,867, ** p < 0.01, *** p < 0.001
Relative Risks: Population Groups, Ages 15 -- 34,
by Control Variables introduced
0
0.5
1
1.5
2
2.5
3
3.5
4
Ethiopia W.Europ AsiaE.Europe Balkans FSU EurAfrica Arab FSU Asia
Survivorship Analysis, Control Variables, Ages 35 -59
Exp(coefficient)Control Entered
153 (4)786 (3)11 (1)2764 (11)LR Gain (df)
1.108Householder
1.966***Single
1.326***Widowed
1.566***DivorcedMarital
Status(base: married)
0.651***0.655***University
0.790***0.787***High SchoolCertificate
(base: none)
0.440***0.426*** Working
1.0121.0371.246*** Immigrant
1.098***1.097***1.109***1.109***Age
0.445***0.461***0.604***0.605***Sex
N = 273,496, *** p < 0.001
Relative Risks: Population Groups, Ages 35 -- 59,
by Control Variables introduced
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
Ethiopia W.Europ AsiaE.Europe Balkans FSU EurAfrica Arab FSU Asia
Survivorship Analysis, Control Variables, Ages 60-64
Exp(coefficient)Control Entered
198 (4)1350 (3)12 (1)15160 (11)
LR Gain (df)
0.871***Householder
0.982Single
1.191***Widowed
1.106 **DivorcedMarital
Status(base: married)
0.698***0.695***University
0.811***0.808***High SchoolCertificate
(base: none)
0.544***0.546*** Working
1.0521.094***1.098*** Immigrant
1.089***1.093***1.100***1.099***Age
0.592***0.643***0.702***0.702***Sex
N = 131,880, ** p < 0.01, *** p < 0.001
Relative Risks: Population Groups, Ages 60 and up,
by Control Variables introduced
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
Ethiopia W.Europ AsiaE.Europe Balkans FSU EurAfrica Arab FSU Asia
Explanations•Non-selective migration?
•Society of migrants?•Origins of migrants?•Quality of data?
Conclusions• Need theory, not just empirical generalisations
• Theory needs to look at migrant – resident relations
• Be wary of data – socially generated