A national achievement?: A national achievement?: Changes in inequalities in risk Changes in inequalities in risk
factors for cardiovascular factors for cardiovascular disease in Australiadisease in Australia
Philip Clarke and Alison Hayes, Philip Clarke and Alison Hayes,
School of Public Health, University of Sydney
Work in Progress
Structure of the seminarStructure of the seminar
Background on inequality measures & Background on inequality measures & Achievement index;Achievement index;
Main focus on how to represent changes in Main focus on how to represent changes in inequalities and mean health;inequalities and mean health;
Some examples from selfSome examples from self--reported reported cardiovascular risk factors from Australian cardiovascular risk factors from Australian National Health Surveys.National Health Surveys.
Inequality comparisonsInequality comparisons
25%
Poor Rich
75%
Poor Rich
Hea
lthM
orbi
dity
50%
50%
50%
50%
75%
25%
Time 1 Time 2
Decreased?
Remained the same?
Increased?
Have inequalities:
Case for decreasing inequalitiesCase for decreasing inequalities
25%
Poor Rich
75%
Poor Rich
Hea
lthM
orbi
dity
50%
50%
50%
50%
75%
25%
Time 1 Time 2 Relative inequalitiesin “health”
Ratio= Health of RichHealth of Poor
Time 1 50%/25%=2
Time 2 75%/50%=1.5
Inequalities have decreased
Case for no change in inequalitiesCase for no change in inequalities
25%
Poor Rich
75%
Poor Rich
Hea
lthM
orbi
dity
50%
50%
50%
50%
75%
25%
Time 1 Time 2 Absolute inequalitiesin “health”
Time 1 50%-25%=25%
Time 2 75%-50%=25%
Inequalities have remained the same
Case for increasing inequalitiesCase for increasing inequalities
25%
Poor Rich
75%
Poor Rich
Hea
lthM
orbi
dity
50%
50%
50%
50%
75%
25%
Time 1 Time 2
Poor Rich Poor Rich
75%
25%
Hea
lthM
orbi
dity
50%
50%
50%
50%
25%
75%
Time 1 Time 2 Relative inequalitiesin “morbidity”
Ratio= Morbidity of PoorMorbidity of Rich
Time 1 75%/50%=1.5
Time 2 50%/25%=2
Inequalities have Increased!
Reads like a script from Reads like a script from ““Yes MinisterYes Minister””
Jim Hacker MP:Jim Hacker MP: ““So Humphrey are health So Humphrey are health inequalities rising or declining?inequalities rising or declining?””
Sir Humphrey:Sir Humphrey: ““Well Minister in terms of measures Well Minister in terms of measures of morbidity, inequalities are increasing, but in of morbidity, inequalities are increasing, but in terms of absolute inequalities they remain the terms of absolute inequalities they remain the same, and if instead we measure inequalities in same, and if instead we measure inequalities in terms of health they are actually declining.terms of health they are actually declining.””
Concentration curves Concentration curves
0 1
1
cumulativeproportion of morbidity
Cumulative proportion of population ranked by income/socioeconomic status
L(S3 )L(S2 )L(S1 )
Concentratio
n index
-ve indicatesPro-rich Inequality
Concentration curves Concentration curves
0 1
1
cumulativeproportion
of good-health
Cumulative proportion of population ranked by income/socioeconomic status
L(S3 )L(S2 )L(S1 )
Concentratio
n index
+ve indicatesPro-rich Inequality
Generalized concentration curves Generalized concentration curves
0 1
μ
cumulativemorbidity
Cumulative proportion of population ranked by income/socioeconomic status
L(S3 )L(S2 )L(S1 )
Gen Concentratio
n index
Extended Concentration indexExtended Concentration index
∑=
−−=n
iii Ry
nC
1)1(21
μ
∫ >−−−= −1
0
2 1,)()1()1(1)( vdppLpvvvC v
Wagstaff (2002) Inequality aversion, health inequalities, health achievement, JHE.
1
1)1(1)( −
=
−−= ∑ vi
n
ii Ry
nvvCμ
Inequality aversionInequality aversion
Wagstaff (2002)
How do we make meaningful How do we make meaningful comparisons across time?comparisons across time?
% o
f pop
ulat
ion
Health Measure
Poorest Richest
100%
0%
MeanTime 2
MeanTime 1
Average health hasincreased
Absolute and Relativeinequalities have declined
Had to argue things are not improving
More difficult caseMore difficult case%
of p
opul
atio
n
Health Measure
Poorest Richest
100%
0%
MeanTime 2
MeanTime 1
Average health hasincreased
Absolute inequalities
Relative inequalities
Hard to say if things are improving
Achievement IndexAchievement Index
121122
222111
22
)()()()(
)()())(1()(
μμυμυμυμμυμμ
υυμ
−>−−>−
>−=
CCCC
IvICvI
-15
-10
-5
0
5
10
15
-100 -80 -60 -40 -20 0 20 40 60 80 100
Diff. inequality (G2-G1)D
ifference in mean health (μ
2 -μ1 )
Madagascar
Kazakhstan
Egypt
Chad
45
12
NW
SW SE
NE
Region of increasing achievement
Incremental health achievement plane relative to Haiti
-50
-40
-30
-20
-10
10
20
30
-100 -80 -60 -40 -20 0 20 40 60 80 100
Incremental Effect
Incr
emen
tal C
ost
Kazakhstan
Egypt
Madagascar
Chad
-15
-10
-5
0
5
10
15
-100 -80 -60 -40 -20 0 20 40 60 80 100
Diff. inequality (G2-G1)D
ifference in mean health (μ
2 -μ1 )Madagascar
Kazakhstan
Egypt
Chad
45
NW
SW SE
NERegion of increasing achievement
-0.006
-0.005
-0.004
-0.003
-0.002
-0.001
0
0.001
0.002
0.003
0.004
0.005
-0.006 -0.004 -0.002 0 0.002 0.004 0.006 0.008 0.01
Change in mean health
Cha
nge
in a
bsol
ute
ineq
ualit
y
Increases in mean health
Increases in absolute inequality(v=2)
)2()2( 1122 CC μμ −
12 μμ −
Change in mean health
Increases in mean health
Increases in absolute inequality(v=8)
)8()8( 1122 CC μμ −
12 μμ −
-0.015
-0.01
-0.005
0
0.005
0.01
0.015
-0.01 -0.005 0 0.005 0.01 0.015
Incr
emen
tal C
ost
Probability of increase in health acheivement
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Inequality aversion (v)
Prob
abili
ty o
f inc
reas
ing
ache
ivem
ent
Series2
Cardiovascular risk in Australia Cardiovascular risk in Australia
NHS survey populationNHS survey population
Individuals participating in the last four ABS National Individuals participating in the last four ABS National Health Surveys, conducted in:Health Surveys, conducted in:–– 19891989--90, 1995, 2001, 200490, 1995, 2001, 2004--5.5.–– N=54,241, 53,828, 26,862, 25,906N=54,241, 53,828, 26,862, 25,906
Expanded surveys available onExpanded surveys available on--line from 2001 via the line from 2001 via the remote access data laboratory (RADL)remote access data laboratory (RADL)Urban and rural areas throughout all states and territoriesUrban and rural areas throughout all states and territoriesNonNon--institutionalized residential population;institutionalized residential population;Collects selfCollects self--reported information on health status, health reported information on health status, health behavior, health use (mainly over previous 2 weeks)behavior, health use (mainly over previous 2 weeks)Demographic and socioDemographic and socio--economic factors, e.g. selfeconomic factors, e.g. self--reported household incomereported household income
55.0 (53.2)52.2 (49.8)44.9 (43.5)39.0 (38.4)Overweight or obese
2.1 (1.8)2.8 (2.2)4.2 (4.6)5.0 (4.8)Previous heart disease
10.2 (9.1)9.4 (7.8)7.3 (7.7)10.9 (10.9)High cholesterol
5.1 (4.6)4.7 (4.2)3.0 (3.0)2.5 (2.3)Diabetes
22.8 (25.6)22.5 (24.5)24.1 (25.0)28.2 (29.1)Smoker
(33.7)29.6 (29.2)33.1 (32.4)35.9 (35.7)No exercise
15.4 (13.8)14.8 (12.9)15.0 (14.5)20.4 (20.5)High blood pressure
Risk factors %
39.940.232.733.9% over 50 years
51.252.850.450.9% female
15,00413,16715,71334,078N
2005200119951989Survey Year
Vigorous Vigorous ExercizeExercizePrevalence of vigorous exercise
0
0.05
0.1
0.15
0.2
0.25
0.3
0 2 4 6 8 10 12
19891995
20012005
Overweight, or obeseOverweight, or obeseprevalence of overweight or obese by income decile
0
0.1
0.2
0.3
0.4
0.5
0.6
0 2 4 6 8 10 12
Income decile
BM
I
1989
1995
2001
ObeseObeseAge and sex standardised prevalence of obesity by income quintile
0
0.05
0.1
0.15
0.2
0.25
0 2 4 6 8 10 12
1989199520012005
Smoking statusSmoking statusAge and sex standardised prevalence of smoking by income decile
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0 2 4 6 8 10 12
1989
1995
2001
2005
Diabetes (Type I & II)Diabetes (Type I & II)Age and sex standardised diabetes prevalence by income decile
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0 2 4 6 8 10 12
1989
1995
2001
High cholesterolHigh cholesterolAge and sex standardised high cholesterol
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0 2 4 6 8 10 12
1989
1995
2001
High blood pressureHigh blood pressureAge and sex standardised prevalence of high blood pressure
0
0.05
0.1
0.15
0.2
0.25
0 2 4 6 8 10 12
1989
1995
2001
-0.04
-0.03
-0.02
-0.01
0
0.01
0.02
0.03
0.04
0.05
-0.14 -0.12 -0.1 -0.08 -0.06 -0.04 -0.02 0 0.02 0.04 0.06
Increases in absolute inequality(v=2)
Change in mean health
Cha
nge
in a
bsol
ute
ineq
ualit
y
Normal weightVig. ExerciseNon Smokers
1995
2001
19952001
2005
2005
-0.04
-0.03
-0.02
-0.01
0
0.01
0.02
0.03
0.04
0.05
-0.14 -0.12 -0.1 -0.08 -0.06 -0.04 -0.02 0 0.02 0.04 0.06
Increases in absolute inequality(v=2)
Change in mean health
Cha
nge
in a
bsol
ute
ineq
ualit
y
DiabetesCholesterolBlood pressure
1995 2001 1995
2001
20052005
1995
2005
Smoking statusSmoking statusAge and sex standardised prevalence of smoking by income decile
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0 2 4 6 8 10 12
1989
1995
2001
2005
Measuring achievement: smokingMeasuring achievement: smoking
0.29180.70820.0358-0.03580.048-0.140.2562005
0.28130.71870.0363-0.03630.048-0.1480.2452001
0.2880.7120.038-0.0380.051-0.1520.251995
0.31950.68050.0285-0.02850.04-0.0980.2911989
AImAIhμCIHμCImCIhCImMean Survey year
Measuring achievement Measuring achievement AI vs v parameter for smoker
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0 5 10 15 20 25 30 35
1989
1995
2001
2005
Overweight, or obeseOverweight, or obeseprevalence of overweight or obese by income decile
0
0.1
0.2
0.3
0.4
0.5
0.6
0 2 4 6 8 10 12
Income decile
BM
I
1989
1995
2001
Overweight & obeseOverweight & obese
0.44040.45960.0084-0.00840.018-0.01570.5322005
0.49650.5035-0.00150.0015-0.0030.0030.4982001
0.4450.5550.01-0.010.018-0.0230.4351995
0.40160.59840.0177-0.01770.029-0.0460.3841989
AIm(v=2)
AIh(v=2)
μCIH(v=2)
μCIm(v=2)
CIhCImMean Survey year