What do we know Johan Fritzell Professor of Sociology and Social Gerontology Director Aging Research Center ARC Karolinska Institutet amp Stockholm University johanFritzellkise ID: 649286
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Slide1
Health
and welfare models:
What do we know?
Johan Fritzell
Professor of Sociology and Social Gerontology
Director
Aging Research Center (ARC)
Karolinska
Institutet
& Stockholm University
johan.Fritzell@ki.se
Presentation
at the JPI
mybl
Conference: Health, Ageing and Migration, Rome 161202Slide2
Short intro to the welfare modelling bussiness
Welfare models and population health indicatorsExpected and surprising
findings
Going
beyond
”the black box”
of
welfare
models
Example
:,
Poverty
, Minimum
income
benefits
and
mortality
Knowledge
and
knowledge
gapsSlide3
Johan FritzellWelfare models: the classical welfare regime typology
“The three worlds of welfare capitalism” (Esping-Andersen 1990) Slide4
Johan FritzellWelfare models: the classical welfare regime typology
“The three worlds of welfare capitalism” (Esping-Andersen 1990) Slide5
Population health and welfare state provision
Comparative social epidemiology has almost invariably concluded that population health is enhanced by the relatively generous and universal welfare provision in the Scandinavian countries (Bambra 2011).Studies analysing the relationship between health (mortality) and the political determinants
or policies of welfare states
….report
results consistent with welfare regime theory
(
Brennenstuhl
,
Quesnel-Vallée
, McDonough 2011)
YES, WELFARE STATE PROVISION SEEMS TO BE GOOD FOR POPULATION HEALTH
BUT NOT WITH REGARD TO HEALTH INEQUALITY?Slide6
Why do health inequalities persists or even grow in advanced welfare states? The “puzzle”The Scandinavian welfare states do not, as would generally be expected, have the smallest health inequalities
Bambra, C. (2011) Health inequalities and welfare state regimes: theoretical insights on a public health puzzle, JECH See also Mackenbach, J.P. (2012). The persistence of health inequalities in modern welfare states: The explanation of a paradox.
Soc
Sci
& Med
,
75
, 761-769.
Dahl, E.; Fritzell, J.;
Lahelma
, E.; Martikainen, P.;
Kunst
, A.;
Mackenbach
, J. (2006) Welfare
state
regimes and health inequalities. In J. Siegrist & M. Marmot (eds.), Social inequalities in health: New evidence and policy implications. Oxford University Press, Slide7
Go beyond the typologies and the countriesItaly
is not Sweden……. Open up the black box of welfare regimesIt is what
welfare states actually do, rather than how they are
labeled,
that
matters
for
health
. (
e.g
.
Mackenbach
& McKee 2013)Slide8
Health care – Social policy – Welfare statesHealth care is - hopefully -of value when you become illBut ill health is – hopefully – produced outside of the health care systemSocial policy is much more than health careSocial policy may influence both determinants of health and the consequences of ill-health
Social determinants of healthSlide9Slide10
Welfare states and poverty reduction
We know that welfare
state
redistribution
(
taxes
and transfers)
are
of
importance
for
poverty
reductionSlide11
So if welfare state programmes
are important for poverty reduction and poverty is a social determinant of
health
than
social policy
could
make a
difference
.
”
The proof of the pudding is in the eating”Slide12Slide13
Paper 1: Objectives
To investigate whether cross-national variation in relative poverty rates is associated with cross-national variation in death rates in 26 countries among infants, children and among working-age adultsSlide14
Data, design and measurementsData Sources
Poverty (The Luxembourg Income Study(LIS), 26 countries with at least 2 waves of data) www.lisdatacenter.orgMortality (Human Mortality Database)
www.mortality.org
+ other databases for control (Penn’s world tables; OECD database)
Design
Poverty measure (LIS): household equivalent disposable
income below
40
per cent (sensitivity with 60 %) of the median
Age-standardized mortality rates; average of LIS year and 3 following years (for infant mortality only immediate year)
Age-specific poverty associated with age-specific mortality
Mortality among
Infants,
< 1 year
Children, 1-17 years of age
Adults, 25-64 years of ageSlide15
Methods
Pooled cross-sectional time series analysisSmall n-problemUnbalanced panels -> Panel corrected standard errors
Controls
Wave of data (time)
GDP per capita
Social spending
Welfare regimes (Nordic countries reference)Slide16Slide17
Logged age-standardized mortality rates women and men 25-64 (p-values in parenthesis)
Women, Model 2
Model 3
Men,
Model 2
Model 3
Poverty,
relative (40%)
0,010
(
0,004)
0,017
(0,004)
0,013
(
0,082
)
0,0029 (0,000)
Model 2 adjusted for
data wave and GDP
Model 3 adjusted for data wave, GDP, social spending,
welfare regime
typeSlide18
DETOUR
Men (25-64)
Coef.
p-values
Constant
2,226
0,000
Adult poverty (40%)
0,029
0,000
Wave
-0,069
0,000
GDP /1000 US dollars
-0,011
0,000
Social spending
-0,007
0,001
Welfare regime:
Central European
-0,058
0,070
Liberal
-0,195
0,001
South-European
-0,256
0,000
Post-Socialist
0,397
0,000
Other
-0,315
0,003
Whats
the
implication
of
the
fact
that
a)
regime
type
is
highly
significant
? And
b) The
poverty
estimate
gets
much
larger
once
we
adjust
for
regime
?Slide19
Conclusions (1)Relative poverty matters also among rich countries, especially so for children
For both children and adults: The poverty effects more marked once welfare regimes are adjusted for.Slide20
Welfare states and population health: minimum income benefits and mortalityIf poverty matters can social policy make a difference? On the importance of the generosity of minimum income benefitsSlide21
The Social Assistance and Minimum Income Protection Interim Data Set (SaMip)● Type-case data based on national (regional) legislation.
● Three type-cases are used: a single person, family (2+2) and a lone parent (1+2).● Benefit levels are expressed in PPPs adjusted $US.● Minimum income includes all income received by these household types, excl.
employm
. income, contributory benefits and transfers between families.Slide22
Australia
SA (Special Benefit), CB (
Family tax allowance), HB (Rent assistance)
Austria
SA (Bedarfsorientierte mindestsicherung), CB (
Familienbeihilfe
,
Alleinerzieherabsetz-betrag
,
Kinderabsetzbetrag
), HB (
Mietbeihilfe
)
Belgium
SA (Revenu d'intégration),
CB (
Allocations
familiales belges)Canada
SA (Ontario Works), CB (Federal child tax benefit, National child benefit supplement, Back to school allowance, Winter clothing allowances), HB (SA supplements for housing), TC (Ontario sale tax and property tax credits, Federal goods and services tax credit, Ontario child benefit)
Denmark
SA (
Kontanthjælp
), CB (
Børnetilskud
), HB (
Boligsikring
)
Finland
SA (
Toimeentulotuki
), CB (
Lapsilisälaki
), HB (
Asumistuki
)
France
SA (
Revenu
de
solidarité
active
),
CB (Allocations
familiales
), HB (
L'aide
personnalisée au logement)GermanySA (Hilfe zum lebensunterhalt), CB (Kindergeld), HB (Wohngeld)IrelandSA (Supplementary welfare allowance), CB (Child benefit, One parent family payment), HB (Rent supplement)ItalySA (Minimo vitale, Reddito minimo), CB (Assegno per nuclei familiari)Japan
SA (Public assistance), CB (Child allowance, Lone parent benefit), HB (Housing aid)NetherlandsSA (Algemene bijstand), CB (Algemene kinderbijslagwet), HB (Huurtoeslag)New ZealandSA (Jobseeker support), FB (Family tax credit, Domestic Purposes Benefit); HB (Accommodation supplement)NorwaySA (økonomisk stønad), CB (Barnebidrag), HB (Bostøtte)SwedenSA (Försörjningsstöd), CB (Barnbidrag), HB (Bostadsbidrag, SA supplements for housing)SwitzerlandSA (Aide sociale), CB (Kinderzulage), HB (Social assistance supplements for housing)United KingdomSA (Income support), CB (Child benefit, Child tax credit), TC (Council tax benefit)United StatesSA (Foodstamps, Temporary assistance to needy families)Programs included in the minimum income benefit packages of 18 OECD countries, 2009.SA=social assistance, CB= child benefit, HB= housing benefit, TC=tax credit (TC for children see CB). Slide23
Examples of minimum income benefit levels ($US PPP) and life expectancy, as averages 1990-2009 in four countriesSwitzerland 21 447 83,1
Sweden 15 936 82,2United Kingdom 13 043 80,5United States 7 532 79,7Slide24
Age-standardized death rates (18 OECD-countries, 1990-2009, fixed effects regressions for women and men.
Source: Nelson & Fritzell, 2014 (standard errors within parenthesis)Level of minimum income benefits Crude Adjusted
Women
-
21,86 -11.32
(
3.13
) (2.58
)
Men
-
42.38 -14.54
(
6.83
) (5.22)
Adjusted
for
e.g. GDP; alcohol consumption; social expenditure/GDP; % public financing in health expenditure; tobacco consumption; health employment. Slide25
Conclusions: minimum income benefits and mortality Is social protection and anti-poverty programs important for mortality and population health? According to our analyses the answer is affirmative.
The association between minimum income benefits and mortality is remarkable robust in presence of other estimated effects of other determinants. Particularly, effects of exposure seem to be short-term rather than long-term.Slide26
But what about old age mortality, inequality and
welfare state programmes
Income
gradient in Sweden
(
Fritzell
2016, report to the Swedish Commission for Equity in Health
)
Age-
standardised
death
rates 65-89
years
of
ageSlide27
In sum: knowledge and knowledge gaps
We find clear differences in population health indicators by
welfare
regimes
Welfare
state
programs
seems
to be
of
importance
for cross-national variations in
mortality
Socioeconomic
health inequalities do not necessarily coincides with welfare modelsSocioeconomic health inequalities persists in old ageThe vast majority of all deaths occur at relatively old age butSurprisingly little is known
about the role
of
social policy in the
explanation
of
mortality
risks in old age
Surprisingly
little
is
known
on cross-national variations
of
health
and
mortality
inequalities
in old age
.
Slide28
Johan
Fritzell
Professor of Sociology and Social Gerontology
Director
Aging Research Center (ARC)
Karolinska
Institutet
& Stockholm University
johan.Fritzell@ki.se