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Immigrant mortality in Israel

Jon Anson Dept.of Social Work Ben Gurion University of the Negev 84105 Beer Sheva, Israel. BSPS, September 2004, Leicester Session 5: Health and Ethnicity Analysis made possible by a grant from the Israel Science Foundation Data provided by Central Bureau of Statistics, Israel.

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Immigrant mortality in Israel

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  1. Jon Anson Dept.of Social Work Ben Gurion University of the Negev 84105 Beer Sheva, Israel. BSPS, September 2004, Leicester Session 5: Health and Ethnicity Analysis made possible by a grant from the Israel Science Foundation Data provided by Central Bureau of Statistics, Israel Immigrant mortality in Israel

  2. Population Pyramid, Israel, Census 1995

  3. Period Pre-State 1948-1951 1952-1967 1968-1989 1990-1995 Unknown 10.9 3.5 0.8 0.3 0.1 America 1.6 0.7 5.5 24.5 3.1 Europe 78.2 47.5 35.1 55.2 90.8 Africa 0.8 13.7 47.6 10.0 4.9 Asia 8.5 34.5 11.1 10.0 1.0 Total 482,857 687,624 587,472 558,907 685,683 Avg / Year 196,464 36,717 25,405 114,281 Distribution of immigrants to Israel,by period and origin, 1948 – 1995

  4. Origin Group Percent Med Age Exposure Deaths CDR Arab 13.4 37.5 443,911 2,493 5.62 Jews Born In: Israel 35.4 37.5 1,181,206 2,415 2.04 Asia 6.7 57.5 216,278 2,860 13.2 N. Africa 9.3 52.5 300,888 3,503 11.6 Ethiopia 0.7 42.5 23,809 107 4.49 Balkans 2.1 62.5 64,998 1,335 20.5 E. Eur. 8.2 67.5 253,799 7,239 28.5 W. Eur. 6.3 47.5 203,597 2,465 12.1 FSU Eur 14.8 47.5 472,366 6,600 14.0 FSU As. 3.1 47.5 101,757 1,027 3.1 Total 546,294 42.5 3,262,611 30,044 9.21 Population groups, Israeli population at census, 1995 Population 25 and above; Age in 5 year categories; Exposure 4/11/95 – 31/12/2001

  5. Control Entered Exp(coefficient) Sex 0.683 0.683 0.611 0.561 Age 1.102 1.102 1.090 1.087 Immigrant 1.126 1.099 1.054 Working 0.522 0.518 Certificate (base: none) High School 0.806 0.808 University 0.687 0.689 Marital Status (base: married) Divorced 1.242 Widowed 1.236 Single 1.249 Householder 0.884 LR Gain (df) 70231 (11) 24 (1) 2146 (3) 344 (4) Survivorship Analysis, Control Variables, Ages 25+ N = 564,294, all coefficients significant at p < 0.05

  6. Relative Risks: Population Groups, Ages 25 and above, by Control Variables introduced

  7. Control Entered Exp(coefficient) Sex 0.369*** 0.369*** 0.347*** 0.372*** Age 1.017*** 1.017*** 1.029*** 1.063*** Immigrant 1.505 ** 1.486 ** 1.525 ** Working 0.592*** 0.620*** Certificate (base: none) High School 0.740*** 0.740*** University 0.608*** 0.588*** Marital Status (base: married) Divorced 3.242*** Widowed 1.066 Single 1.824*** Householder 0.917 LR Gain (df) 256 (11) 7 (1) 85 (3) 81 (4) Survivorship Analysis, Control Variables, Ages 15 -34 N = 314,867, ** p < 0.01, *** p < 0.001

  8. Relative Risks: Population Groups, Ages 15 -- 34, by Control Variables introduced

  9. Control Entered Exp(coefficient) Sex 0.605*** 0.604*** 0.461*** 0.445*** Age 1.109*** 1.109*** 1.097*** 1.098*** Immigrant 1.246*** 1.037 1.012 Working 0.426*** 0.440*** Certificate (base: none) High School 0.787*** 0.790*** University 0.655*** 0.651*** Marital Status (base: married) Divorced 1.566*** Widowed 1.326*** Single 1.966*** Householder 1.108 LR Gain (df) 2764 (11) 11 (1) 786 (3) 153 (4) Survivorship Analysis, Control Variables, Ages 35 -59 N = 273,496, *** p < 0.001

  10. Relative Risks: Population Groups, Ages 35 -- 59, by Control Variables introduced

  11. Control Entered Exp(coefficient) Sex 0.702*** 0.702*** 0.643*** 0.592*** Age 1.099*** 1.100*** 1.093*** 1.089*** Immigrant 1.098*** 1.094*** 1.052 Working 0.546*** 0.544*** Certificate (base: none) High School 0.808*** 0.811*** University 0.695*** 0.698*** Marital Status (base: married) Divorced 1.106 ** Widowed 1.191*** Single 0.982 Householder 0.871*** LR Gain (df) 15160 (11) 12 (1) 1350 (3) 198 (4) Survivorship Analysis, Control Variables, Ages 60-64 N = 131,880, ** p < 0.01,*** p < 0.001

  12. Relative Risks: Population Groups, Ages 60 and up, by Control Variables introduced

  13. Explanations • Non-selective migration? • Society of migrants? • Origins of migrants? • Quality of data?

  14. Conclusions • Need theory, not just empirical generalisations • Theory needs to look at migrant – resident relations • Be wary of data – socially generated

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