Trends and changes in socio-economic inequality in self-rated health among migrants and non-migrants: repeated cross-sectional analysis of national survey data in Germany, 1995-2017
Socio-economic inequalities in health may change over time, and monitoring such change is relevant to inform adequate policy responses. We aimed to quantify socio-economic inequalities in health among people with direct, indirect and without migration background in Germany and to assess temporal tre...
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| Main Authors: | , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
7 July 2022
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| In: |
International journal of environmental research and public health
Year: 2022, Volume: 19, Issue: 14, Pages: 1-12 |
| ISSN: | 1660-4601 |
| DOI: | 10.3390/ijerph19148304 |
| Online Access: | Resolving-System, kostenfrei, Volltext: https://doi.org/10.3390/ijerph19148304 Verlag, kostenfrei, Volltext: https://www.mdpi.com/1660-4601/19/14/8304 
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| Author Notes: | Elisa Wulkotte and Kayvan Bozorgmehr |
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| 245 | 1 | 0 | |a Trends and changes in socio-economic inequality in self-rated health among migrants and non-migrants |b repeated cross-sectional analysis of national survey data in Germany, 1995-2017 |c Elisa Wulkotte and Kayvan Bozorgmehr |
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| 520 | |a Socio-economic inequalities in health may change over time, and monitoring such change is relevant to inform adequate policy responses. We aimed to quantify socio-economic inequalities in health among people with direct, indirect and without migration background in Germany and to assess temporal trends and changes between 1995 and 2017. Using nationally representative survey data from the Socio-Economic Panel (SOEP), we quantified absolute and relative socio-economic inequalities in self-reported general health by calculating the slope (SII) and relative index of inequality (RII) with 95% confidence intervals (CI) among each group and year (1995-2017) in a repeated cross-sectional design. Temporal trends were assessed using a GLM regression over the SII and RII, respectively. The total sample size comprised 492,489 observations, including 108,842 (22.23%) among people with migration background. About 31% of the population with and 15% of the population without migration background had a low socio-economic status. Socio-economic inequalities in health persisted in the group with migration background (1995 to 2017), while inequalities in the non-migrant population increased (SII: βTrend = 0.04, p < 0.01) and were on a higher level. The highest socio-economic inequalities in health were found among those with direct migration background (βSII, min = −0.23, p< 0.01; βSII, max = −0.33, p < 0.01). The results show that the magnitude and temporal dynamics of inequalities differ among populations with direct, indirect and without migration background. Monitoring systems can capture and investigate these inequalities if migrant populations are adequately integrated into the respective systems. | ||
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