p r i o r i t y s e t t i n g i n g l o b a l h e a l t h have we got our priorities right? child...

P r i o r i t y S e t t i n g i n G l o b a l H e a l t h

Have we got our priorities right?Child mortality, the Millennium Development Goal 4 and its impact on inequality in health

in sub-Saharan Africa

Ole F. NorheimDepartment of Public Health and Primary Care,

University of Bergen, Norway

Mira JohriDépartement d’administration de la santé, Faculté de médecine,

Université de Montréal, Canada

Yukiko AsadaDepartment of Community Health and Epidemiology,

Faculty of Medicine, Dalhousie University, Canada

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Ethiopia: 120 out of 1000 kids will die before they reach their fifth birthday

Have we got our priorities right?

• Background• Methods

– Inequality, Gini Index– Data from life tables

• Results– Changes in Gini from 1990-

2006– Potential MDG 4 impact on

Gini

• Policy implications


Background

1. The Millennium Development Goal 4 of reducing under-five mortality by two-thirds before 2015 is not on track.

• Worldwide under-5 mortality is expected to decline by 27% from 1990 to 2015

(Murray et al Lancet 2007)

• The target is 67% reduction


2. The Gini index can be used as a population summary measure of overall inequality in age at death

(Le Grand and Rabin 1986)

• No study has previously linked high child mortality to overall inequality in health


Two concepts of inequality

– Inequality in mortality associated with unequal socioeconomic status is well known.

– Overall inequality in the age of death is less well understood.


Two measures of inequality(Wolfson and Rowe, 2001)

• Bivariate measures: Concentration index

• “The poor have higher mortality than the less poor”


Under-5 mortalityDemocratic Republic of Congo (2007)

Concentration Index: 0.10

0

50

100

150

200

Lowest Second Middle Fourth Highest


• Univariate measures: Ginih

• “Those who die young have had less life years than those who complete a normal life span”


0

50

100

150

200

250

300

<5' '5-9' '10-14'

'15-19'

'20-24'

'25-29'

'30-34'

'35-39'

'40-44'

'45-49'

'50-54'

'55-59'

'60-64'

'65-69'

'70-74'

'75-79'

'80-84'

'85-89'

'90-94'

'95-99'

'100+'

Age group

Dea

ths

per

1000

Japan: LE: 82.6 - GINI: 0.09

Niger: LE: 42.2 - GINI: 0.41


Example showing how key variables are derived from a life table (Niger 2006)

Sex Age range … Number of deaths (=ndx)

hi (age at death)

both '<1' … 14815 0.5

both '1-4' … 10515 2.5

Both '5-9' … 2254 7.5

Both '10-14' … 1174 12.5

… … … … …

Both '80-84' … 5274 82.5

Both '85-89' … 2708 87.5

Both '90-94' … 746 92.5

Both '95-99' … 128 97.5


Ginih

(Brown, 1994)

• Xi = a groups proportion of the total population

• Yi = that group’s age at death as a proportion of life expectancy

• G = 0.0 perfect equality• G = 1.0 perfect inequality

1

1 11

1 ( )( )k

i i i ii

G Y Y X X


Aim

• Taking the realization of MDG4 in sub-Saharan Africa as a case study…

• …our aim was to assess the potential contribution of a univariate measure of health inequalities – the Gini index for health – to equity-based analysis of health policies.


Aim

• For all countries in sub-Saharan Africa we– Estimated overall inequality in the age of

death for the years 1990 and 2006– Estimated potential reduction in overall

inequality if Millennium Development Goal 4 was achieved.


Methods

• To estimate inequality in the age of death (Ginih )

….we used data on mortality patterns from WHO life tables for 1990 and 2006

Ginih is based on exactly the same data as estimates of life expectancy


• To estimate the potential reduction in inequality in age at death if the Millennium Development Goal 4 was achieved

…we calculated a two-third reduction in under-five mortality rates from the 1990 baseline and used these as modified input to the WHO life tables for 2006.


• Changes in mortality for the other age groups were calculated using Chiang’s standard life table method.

• From the modified tables we calculated impact on Ginih.


Results

• If Millennium Development Goal 4 is achieved the potential reduction in overall inequality is substantial for most countries

• The largest reduction in overall inequality is seen in Niger, from 0.48 to 0.31, an absolute change of 0.17


0,00

0,10

0,20

0,30

0,40

0,50

0,60Gini (1990)

Gini (MDG)


Life expectancy

(1990)

Life expectancy

(2006)

Ginihealth

(1990)

Ginihealth

(2006)

Ginihealth

if MDG 4 is achieved

Potential MDG Impact on Ginihealth

Ethiopia 48.6 56.5 0.34 0.26 0.22 0.12

Malawi 46.7 49.9 0.36 0.30 0.25 0.11

Niger 34.5 42.2 0.48 0.41 0.31 0.17

South Africa 62.8 51.3 0.19 0.26 0.22 -0.03

United Republic of Tanzania

51.5 50.3 0.31 0.29 0.23 0.07


Life expectancy

(1990)

Life expectancy

(2006)

Ginihealth

(1990)

Ginihealth

(2006)

Ginihealth

if MDG 4 is achieved

Potential MDG Impact on Ginihealth

Ethiopia 48.6 56.5 0.34 0.26 0.22 0.12

Malawi 46.7 49.9 0.36 0.30 0.25 0.11

Niger 34.5 42.2 0.48 0.41 0.31 0.17

South Africa 62.8 51.3 0.19 0.26 0.22 -0.03

United Republic of Tanzania

51.5 50.3 0.31 0.29 0.23 0.07

Comoros 58.5 64.7 0.25 0.19 0.16 0.08

Eritrea 55.4 63 .028 0.20 0.19 0.09


0

20

40

60

80

100

120

140

160

180

200

De

ath

s p

er

10

00

Japan: LE: 82.6 - GINI: 0.09

Ethiopia: LE: 56.5 - GINI: 0.26

Malawi: LE: 49.9 - GINI: 0.30

United Republic of Tanzania: LE: 50.3 - GINI: 0.29


Potential MDG impact

• Fifteen countries would see an absolute change in Gini that is equal or above 0.10


0,00

0,10

0,20

0,30

0,40

0,50

0,60Gini (1990)

Gini (MDG)

Countries with more than 0.10 reduction in Gini


Is Ginih relevant for health policy?

• The life table approach to inequality measurement provides a comprehensive (all-cause) portrait of mortality in the population.

• Because age is invariant, Ginih permits absolute comparisons between populations and within populations at different time points.


• Taking as a case study the realization of MDG4 in sub-Saharan Africa, we demonstrate that the Gini index for health provide information useful for equity-based analysis of health policies.

• If we value equal lifetime health, Ginih is relevant


0

50

100

150

200

250

300

<5' '5-9' '10-14'

'15-19'

'20-24'

'25-29'

'30-34'

'35-39'

'40-44'

'45-49'

'50-54'

'55-59'

'60-64'

'65-69'

'70-74'

'75-79'

'80-84'

'85-89'

'90-94'

'95-99'

'100+'

Age group

Dea

ths

per

1000

Japan: LE: 82.6 - GINI: 0.09

Niger: LE: 42.2 - GINI: 0.41


Have we got our priorities right?

• No

• High child mortality means that a high proportion of the population lives fewer life years than the others

• This is unfair


Criteria to judge unfairness:

1. Is there inequality in lifetime health?– Yes, this study (high Ginih)

2. Are the health conditions amendable to interventions?

– Yes: neonatal infections, malaria, pneumonia, HIV, and malnutrition

(Jones et al, Lancet 2003)

3. Is the problem concentrated in socially disadvantaged groups?

– Yes(Demographic Health Surveys)


1.Full implementation of the MDG goal 4 will have a substantial impact on reducing overall inequality of health for most sub-Saharan African countries.

2.Existing inequalities in age of death suggest that higher priority should be assigned to interventions targeting under-five mortality.

3.Ginih: a population summary measure that should be further explored

Although there is disagreement about perfect justice

…we agree and know enough to identify injustice

… and do something about itAmartya Sen: The Idea of Justice, 2009

p r i o r i t y s e t t i n g i n g l o b a l h e a l t h have we got our priorities right? child...

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