Cross-country studies of the role of policy on health inequalities. Different approaches and different inequality dimensions, by Christophe Vanroelen. Presented at the 7th European Public Health Conference: "Mind the gap: Reducing inequalities in health and health care". Glasgow, 20th to 22nd November 2014.
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Cross-country studies of the role of policy on health inequalities. Different approaches and different inequality dimensions
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Cross-country studies of the role of policy on
health inequalities
Different approaches and different inequality dimensions
Christophe Vanroelen
cvroelen@vub.ac.be
Interface Demography
Department of Sociology
Vrije Universiteit Brussel, Belgium
7th European Public Health Conference
19-22 of November 2014, Glasgow, UK
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Typologies or Macro data?
Advantages a macro data approach
Real data (avoid artifact effects of summarizing)
Detailed analyses of policies, efforts and results
Dynamic analyses (e.g. change over time)
Modeling cross-level interactions
Advantages a typological approach
Upstream policy entrances (distal causes, theory driven)
From analyses of policies to analyses of politics
Taking into account complex and durable constellations
Sensible solution for (sparse) cross-national data
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Typology studies
Some challenges of typological analyses:
• There are no one-size-fits-all-typologies
Specific populations (migrants, employed women, young workers, …)
Specific policy domains (integration policies, work-family balancing, active labour
market policies)
Specific outcomes (all-cause mortality, specific disorders, healthy life style factors)
• Internal consistency: outliers and escapers
The Netherlands: structure of the (female) labour market
Sweden: deterioration of welfare state outcomes (e.g. poverty)
• Disentangling country/typology and time effects
Spain: crisis effects on a flexible labour market decreasing temporary
employment
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Cross-country policy analysis in SOPHIE
• Different domains of study:
Labour market and quality of work
Housing and built environment
Migration policies
Gender and work and family reconciliation policies
• Different axes of social inequality:
Social class
Gender
Immigrant background
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Example: evolution of “job strain” 1995-2010
BUT
Huge inter-European variation:
Denmark 2010: 5% (EWCS 2010)
Greece 2010: 18% (EWCS 2010)
AND
Important evolutions over time:
Mean score EU15:
EWCS 1995: 9.2%
EWCS 2010: 14.1%
Job Strain (= high work demands & low job control) is a sensitive “upstream
indicator” of work-related health (inequalities).
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P Value = 0.174 (Nordic); 0.000 (All others)
Alternative typology:
Employment regimes (Gallie,
2011): Production regime
(Hall and Soskice, 2001) +
Wage bargaining regimes
(Gallie, 2007):
• Nordic:
– Denmark, Finland,
Norway, Sweden;
• Continental Coordinated:
– Germany, Belgium,
Luxembourg, The
Netherlands, Austria;
• State coordinated:
– France, Italy, Spain,
Portugal;
• Transition:
– Eastern Europe (not
included here)
• Liberal:
– UK, Ireland;
Example: evolution of “job strain” 1995-2010
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Innovative approaches: constructing empirical typologies
MIPEX – Migrant Integration Policy Index
Based on 140 different indicators (www.mipex.eu)
Dimensions of integration policy
• Access to nationality;
• Political rights;
• Socio-economic rights;
• Cultural rights;
• Anti-discrimination legislation
Latent Class Analysis of dimensions scores
(Meuleman & Reeskens 2008)
Blue=Multiculturalist
Orange=Assimilationist
Red= Exclusionist
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Innovative approaches: constructing empirical
typologies
Application of MIPEX-based Meuleman’s typology of integration policy to study cross-
national differences in self-rated health and mortality among migrants and non-migrants
Malmusi, D. (2014). Eur J Public Health cku156
Self-rated health (EU-SILC 2011, 11 countries)
Ikram, U. et al. (2014). EPH conference C.3
All-cause mortality (MEHO, 3 countries)
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Innovative approaches: including typologies and
macro indicators
Category Countries Description
Dual-earner Denmark, Finland,
Norway, Sweden
Public policies enable a transfer of childcare from the family to the public
sector and stimulate fathers to take more active part in caring for their
minor children.
Traditional-Central Belgium, Germany,
France, Netherlands
These countries have traditional family policies with high support to all
families, as for example: child allowances for minor children, part-time day-
care services, home care allowances or marriage subsidies.
Traditional-Southern Cyprus, Spain, Greece,
Portugal
These countries have residual family policies with lack of support to families
and rely on unpaid help. Spain, Greece and Portugal have had a long period
or right-wing dictatorship
Market-oriented Switzerland, United
Kingdom, Ireland
Absence of strong action to support households, the market is the principal
institution governing individuals' and families' access to resources
Contradictory Bulgaria, Czech Republic,
Estonia, Croatia,
Hungary, Lithuania,
Poland, Russia, Slovenia,
Slovakia, Ukraine
Simultaneously attempts to both preserve a highly gendered division of
domestic labour and support the dual earner family. Consist of former
socialist countries where family policies have changed after the transition
(before they were more supporting to women's labour force participation).
Typology adopted from: Korpi et al.,2013; Ferrarini and Sjörberg, 2010
Application of Korpi’s family policies model to study cross-national differences in gender
inequality in self-rated health (In: Palencia et al. (2014). ScoSciMed, 117: 25-33)
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Innovative approaches: domain-sensitive
typologies
Multilevel associations between gender and self-perceived in each country typology (PR: prevalence ratios and 95%CI:
95% confidence intervals). GEM= Gender Empowerment measure; GDP= Gross Domestic Product
Application of Korpi’s family policies model to study cross-national differences in gender
inequality in self-rated health (In: Palencia et al. (2014). ScoSciMed, 117: 25-33)
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Summary: challanges and possible solutions
• Alternative domain-specific typologies
Korpi – Gender policy
MIPEX – Migration policy
Gallie – Employment regimes
• Recalibration and (re)construction of (updated) typologies
LCA
Fuzzy set analysis
• Mixing typological and (multilevel) macro-approaches
Including a typology variable in multilevel models with macro indicators
Fairbrother’s approach: disentangling institutional and time effects
(Fairbrother & Martin, 2013. Social Science Research, 42: 347-360)
Editor's Notes
my first comments would be:
1-I would start from results (labour market / gender / migration) then use remaining time to set out challenges/solutions...
2-Did you receive an answer from Olle? I think his part will be exactly on the Bergqvist et al paper, so I would omit that slide
3-My immigration paper uses typologies based on LCA of MIPEX subdimensions (and that are then interpreted as similar to historical typologies)
We are aware of the shortcomings of typological studies – but we do not want to throw this approach away since there are also some advantages related to:
Upstream policy entrances (distal causes, theory driven eg. Democratic traditions, structure of the productive system, …);
From analyses of policies to analyses of politics (= configurations of policies – eg. Social democratic welfare state approaches);
Taking into account complex and durable constellations (this would be a very complex story of many indicators – impossible to model);
Sensible solution for (sparse) cross-national data (re-arranging countries in meaningful – internally consistent – groups, when cross-country comparison is not the primary objective);
Regime or Typological approach:
Institutional configurations;
Political traditions;
Expenditure, performance, … based Often empirically based:
Macro-data or Comparative approach:
Institutional approach;
Expenditure approach;
Performance approach;
See also: Bergqvist et. al., 2013.
One of the challenges has to do with internal consistency and evolutions over time.
Take this example
BUT
Huge inter-European variation:
Denmark 2010: 5% (EWCS 2010)
Greece 2010: 18% (EWCS 2010)
Important evolution over time: Mean score EU15:
EWCS 1995: 9.2%
EWCS 2010: 14.1%
We took an alternative typology that corresponds with the sub-domain under study Pyschosocial work environment;
In fact the pattern for the continental coordinated countries is hiding two different patterns BENELUX and Aus + GER
This is a demonstration of how even the thoretically adequate typology may generate internally divergent patterns One should always check the data and never “blindly” adopt a typology!
Gallie himself is sceptical about the empirical merits of this typology.
Another way to deal with change when using country typologies is applying empirical approaches in combination with theory-based selections of indicators to construct or adapt typologies. A good example is MIPEX – a typology suitable to investigate relations with integration policies in migrant groups
Introducing the most relevant macro level variables does not take out the power of the typology – neither when controlling for a set of individual level variables