- Dr. Ursula KARL-TRUMMER, MSc
Barcelona, 8-9 March 2012
populations in Europe Dr. Ursula KARL-TRUMMER, MSc Barcelona, 8-9 - - PowerPoint PPT Presentation
Social determinants of health for migrant populations in Europe Dr. Ursula KARL-TRUMMER, MSc Barcelona, 8-9 March 2012 CENTER FOR HEALTH AND MIGRATION Roadmap Social determants of health The Gradient debate and its limitations
Barcelona, 8-9 March 2012
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(WHO, http://www.who.int/social_determinants/en/)
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Concentrates on socio-economic health determinants Recent research provides strong evidence that income and
Research on socio-economic determinants of health does
The question whether (lower) socio-economic status is
It therefor remains unclear in this discourse whether health
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EDU.1 EDU.2 EDU.3 INC.1 INC.2 INC.3 INC.4
Austria NON_MIGR
20.6 63.4 16.0 22.1 25.0 26.0 27.0
EU_MIGR
15.6 57.3 27.1 29.4 24.0 23.5 23.1
OTH_MIGR
44.3 43.6 12.1 50.8 26.0 16.7 6.4
Belgium NON_MIGR
33.6 35.4 31.0 22.5 25.2 26.4 25.9
EU_MIGR
37.1 33.6 29.3 33.3 24.4 17.7 24.6
OTH_MIGR
40.3 32.8 26.8 59.8 22.3 9.4 8.4
Greece NON_MIGR
50.1 32.5 17.4 24.0 24.5 25.3 26.2
EU_MIGR
25.4 53.5 21.0 28.9 29.4 25.0 16.7
OTH_MIGR
43.0 42.1 14.9 38.1 31.1 21.3 9.6
Ireland NON_MIGR
48.3 30.3 21.4 25.1 25.0 24.9 25.0
EU_MIGR
31.8 30.5 37.8 23.8 24.0 25.4 26.7
OTH_MIGR
14.3 25.6 60.1 23.7 27.6 29.6 19.2
Italy NON_MIGR
52.2 37.3 10.6 24.2 24.7 25.3 25.7
EU_MIGR
33.7 57.0 9.3 31.1 29.1 22.5 17.2
OTH_MIGR
47.4 41.8 10.8 40.1 29.4 18.4 12.0
Spain NON_MIGR
58.3 19.0 22.6 24.0 25.0 25.1 25.9
EU_MIGR
38.6 35.3 26.1 31.3 23.6 25.4 19.7
OTH_MIGR
52.0 28.4 19.6 39.3 25.5 23.2 12.0
Sweden NON_MIGR
22.0 49.6 28.4 23.3 25.1 25.5 26.1
EU_MIGR
26.9 47.6 25.6 30.7 24.6 22.7 22.0
OTH_MIGR
23.9 45.7 30.4 44.4 24.1 19.6 11.9
UK NON_MIGR
23.6 49.7 26.7 24.7 25.3 25.2 24.8
EU_MIGR
26.7 41.9 31.5 22.8 22.8 27.2 27.16
OTH_MIGR
21.4 37.7 40.9 31.6 21.4 20.2 26.8
Education Income
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Austria Belgium Greece Ireland Italy Spain Sweden UK Intercept
2.325*** 1.255* 1.031*** 1.403***
0.461 AGE
MALE
0.093° 0.236*** 0.121 0.222*** 0.311*** 0.251***
EU_MIGR 0.132
0.082
0.061 OTH_MIGR
0.047
EDU.1
EDU.3 0.528*** 0.257*** 0.312** 0.233* 0.350*** 0.281*** 0.420*** 0.416*** INCOME 0.605*** 0.484*** 0.355*** 0.260*** 0.325*** 0.280*** 0.379*** 0.263*** HH_SIZE 0.057** 0.112*** 0.042* 0.081** 0.049*** 0.018 0.154*** 0.118*** SELF
0.138 0.138 0.005 0.198*** 0.058 0.231
UNEMP
RETIRED
SCHOOL 0.596** 0.601***
0.458*** 0.318° 0.159 HOUSE
OTHER
0.137
AIC 10,413 10,019 10,546 7,309 41,452 26,410 6,072 11,806 LIK
n 10,873 11,059 13,838 9,448 42,984 28,940 7,015 13,994
Notes: Calculations have been carried out with R using the AER package 1.1-7. Standard errors are in parentheses, asterisks display probabilities: ***p ≤ 0.001, **p ≤ 0.01, *p ≤ 0.05, °p ≤ 0.1. AIC and LIK refer to the values of the Akaike information criterion and the maximised log-likelihood, respectively. n is the sample size.
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Language ethno-cultural sensitivity / cultural safety Racism Control of social capital (the “minarett-debate” in
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evidence from quantitative and qualitative research that
US Study: spanish-speaking patients with language barriers
Main problems identified (Suurmond et.al.2010, 2011)
Inappropriate responses to patient characteristics (command of
Inadequate information exchange with providers Misunderstandings due to different perceptions and expectations Inappropriate care due to stereotyping/prejudices
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Inadequate communication between clinicians/providers and
Migrant patients get worse information and in consequence are
“The happy migrant effect” Migrant patients do not complain as
Possible explanations:
Feeling of extreme powerlessness in combination with inability to
communicate in local language
Positive comparison to healthcare in the “old country” Politeness, social desirability
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