aparajita - wealth and-health_of_children_in_india
TRANSCRIPT
WEALTH AND HEALTH OF CHILDREN IN INDIA :
A STATE-LEVEL ANALYSIS
Diane Coffey, Aparajita Chattopadhyay & Rajan Gupt
Objectives: What do relationships between wealth and health look
like within India, a nation whose states are as populous as many other countries?
We also describe how these relationships seem to be changing in recent years.
We present a state level analysis of the association between state net domestic product per capita and children’s health indicators ( Infant mortality, Height for age Z score and Proportion Stunted).
The contradictions and the questions:
Preston’s describes a strong, log-linear relationship between country level mortality and income, suggesting that cross country wealth is strongly associated with health, but that this relationship is less steep at higher levels of wealth.
Yet, measures of health do not always behave in the same way. For example, Preston’s famous cross country correlation between mortality and wealth contrasts with the puzzling result from Deaton that average height across countries, another important measure of population health, does not correlate with gross domestic product per capita.
Bozzoli et al, 2009: no association between adult heights and
GDP per capita in European countries.
Fogel, 2004 and others: in resource constrained settings, there is a
strong association between income and stature
James & Syamala, 2010:strong association between rising incomes in India and
longer life expectancies.
the relationship between income and life expectancy has become less steep over time.
Coffey, 2012for state cohorts born in India between 1970 and 1983,
there is a robust relationship between state net domestic product per capita in a cohort’s year of birth and the state cohort’s adult height.
Indian Economy grew fast in the last decade. But this economic growth has not led to commensurate improvements in health (Drèze and Sen, 2011).
Deaton and Drèze, 2002: rates of decline in child mortality in India do not match the
unprecedented rates of economic growth.
Declines in child malnutrition as measured by anthropometric measures such as height and weight have also been slow (Radhakrishnan & Ravi, 2004).
Subramanyam et al., 2011: growth does not predict indicators of anthropometric faltering.
So the questions are:
What is the relationship of child health and wealth in India?
Does this relationship change over time?
What is the relationship between growth of income and health improvements?
Data and methods:
NFHS, 1998-99 & NFHS, 2004-2005
§ Child height
§ Stunting prevalence
§ Infant mortality
o EPW Research Foundation
§ State net domestic product per capita, base year 1993
o Census of India, 1991, 2001, 2011
§ Population weights
Only the heights of children under three years old were used.
Results:
Relationship between aggregate wealth and child’s health
1
2
3
4
5
6
7
8
9
11
12
13
14
15
16
18
19
21
2223
24
25
26
10 20
0.2
.4
.6
fraction stunted according to CDC-W
HO
77
0 5000 10000 15000 20000 25000 30000st at e net domest ic product in 1997 (1993 pr ices)
f r act ion of st unt ed childr en under 3 Fit t ed values
NFHS 2
23
4
5
6
7
8
910
11
12
13
14
15
16
19
20
21
22
23
25
261
0.2
.4
.6
fraction stunted according to CDC-W
HO
77
0 5000 10000 15000 20000 25000 30000st at e net domest ic product in 2004 (1993 pr ices)
f r act ion of st unt ed childr en under 3 Fit t ed values
NFHS 3
size of circle proport ional to approximat e populat ion of children under 6
Stunting and NSDP 1 Andhra Pradesh
2 Arunchal Pradesh
3 Assam
4 Bihar & Jharkhand
5 New Delhi
6 Goa
7 Gujarat
8 Haryana
9 Himachal Pradesh
10 Jammu & Kashmir
11 Karnataka
12 Kerala
13 Madhya Pradesh & Chhattisgarh
14 Maharashtra
15 Manipur
16 Meghalaya
17 Mizoram
18 Nagaland
19 Orissa
20 Punjab
21 Rajasthan
22 Sikkim
23 Tamil Nadu
24 Tripura
25 Uttar Pradesh & Uttarakhand
26 West Bengal
1
2
34
5
6
7
8
9
1011
12
13
14
15
16
18
19
21
22 23
24
25
20
26
-2.5
-2
-1.5
-1
height for age z-scores, CDC-W
HO
77
0 5000 10000 15000 20000 25000 30000st at e net domest ic product in 1997 (1993 pr ices)
aver age height f or age z- scor e of childr en under 3 Fit t ed values
NFHS 2
2
3
4
5
6
7
8
910
11
12
13
14
15
1619
20
21
22
23
25
261
-2.5
-2
-1.5
-1
height for age z-scores, CDC-W
HO
77
0 5000 10000 15000 20000 25000 30000st at e net domest ic product in 2004 (1993 pr ices)
aver age height f or age z- scor e of childr en under 3 Fit t ed values
NFHS 3
size of circle proport ional to approximat e populat ion of children under 6
Height for age Z score and NSDP1 Andhra Pradesh
2 Arunchal Pradesh
3 Assam
4 Bihar & Jharkhand
5 New Delhi
6 Goa
7 Gujarat
8 Haryana
9 Himachal Pradesh
10 Jammu & Kashmir
11 Karnataka
12 Kerala
13 Madhya Pradesh & Chhattisgarh
14 Maharashtra
15 Manipur
16 Meghalaya
17 Mizoram
18 Nagaland
19 Orissa
20 Punjab
21 Rajasthan
22 Sikkim
23 Tamil Nadu
24 Tripura
25 Uttar Pradesh & Uttarakhand
26 West Bengal
Infant Death and NSDP
1
2
3
4
5
6
7
8
1011
12
13
1415
16
18
19
20
21
2223
24
25
26
9
0.02
.04
.06
.08
fraction of infant deaths am
ong births in 3 years prior to survey
0 5000 10000 15000 20000 25000 30000st at e net domest ic product in 1997 (1993 pr ices)
f ract ion of inf ant deat hs Fit t ed values
NFHS 2
12
3
4
5
6
7
810 11
12
13
1415
16
19
20
21
22
23
25
26
9
0.02
.04
.06
.08
fraction of infant deaths am
ong births in 3 years prior to survey
0 5000 10000 15000 20000 25000 30000st at e net domest ic product in 2004 (1993 pr ices)
f ract ion of inf ant deat hs Fit t ed values
NFHS 3
size of circle proport ional to approximat e populat ion of children under 6
1 Andhra Pradesh2 Arunchal Pradesh3 Assam4 Bihar & Jharkhand5 New Delhi6 Goa7 Gujarat8 Haryana9 Himachal Pradesh
10 Jammu & Kashmir11 Karnataka12 Kerala13 Madhya Pradesh & Chhattisgarh
14 Maharashtra15 Manipur16 Meghalaya17 Mizoram18 Nagaland19 Orissa20 Punjab21 Rajasthan22 Sikkim23 Tamil Nadu24 Tripura25 Uttar Pradesh & Uttarakhand26 West Bengal
Magnitude of the association between wealth and health
The relationships between wealth and children’s health are weaker in the later survey than the earlier survey
Pooled regression :
NFHS2 NFHS3
a difference of 1.5 infant deaths per thousand
a difference of 1 infant death per thousand.
a 7 percentage point difference in stunting prevalence,
a 3 percentage point difference in stunting prevalence.
0.25 standard deviation difference in the average height for age z-score of children under 3.
0.13 standard deviation difference in the average height for age z-score of children under 3.
a 5000 rupee difference in state net domestic product per capita is associated with
State level relationship between growth of income and health improvements
1
2
3
4
5
6
7
89
10
1112
13
14
15
1619
20
21
2223
25 26
-.2
-.1
0.1
change in fraction stunted
0 . 1 . 2 . 3growt h in st at e net domest ic product per capit a bet ween NFHS 2 and 3
change in st unt ing Fit t ed values
1
2
3
4
567
8910
1112
13
14
15
1619
20
21
222325
26
-.5
0.5
1
change in average height for age z-score
0 . 1 . 2 . 3growt h in st at e net domest ic product per capit a bet ween NFHS 2 and 3
change in average height f or age z-score Fit t ed values
1
2
3
45
6
7
8
910
1112
13
1415
16
19
20
21
22
2325
26
-.04
-.02
0.02
change in fraction of infant deaths
0 . 1 . 2 . 3growt h in st at e net domest ic product per capit a bet ween NFHS 2 and 3
change in f ract ion of inf ant s who died Fit t ed values
size of circle proport ional to average of 1998 and 2005 under 6 populat ion
1 Andhra Pradesh2 Arunchal Pradesh3 Assam4 Bihar & Jharkhand5 New Delhi6 Goa7 Gujarat8 Haryana9 Himachal Pradesh
10 Jammu & Kashmir11 Karnataka12 Kerala
13Madhya Pradesh & Chhattisgarh
14 Maharashtra15 Manipur16 Meghalaya17 Mizoram18 Nagaland19 Orissa20 Punjab21 Rajasthan22 Sikkim23 Tamil Nadu24 Tripura
25Uttar Pradesh & Uttarakhand
26 West Bengal
Why is economic growth associated with less improvement in children’s health?
This might be the case if states which were already healthier experienced more economic growth over the period under study; in states which already had healthier children, it would have been harder to make improvements in health
There is a high correlation between state averages of children’s health in 1998 and economic growth between the two rounds of the survey.
The correlation between height for age in 1998 and economic growth between the two survey rounds was 0.4; comparable figures for stunting and infant death are -0.31 and 0.39.
States with better initial health environments (1998), experienced more economic growth in the period under study.
Findings: aggregate wealth and children’s health indicators are
positive for all three chosen health indices.
Yet the association was less steep in the mid-2000s than in the late 1990s.
negative relationship between growth in state net domestic product per capita and improvement in state level children’s health indicators between these two surveys.
That means, more state level income growth between the late 1990s and mid-2000s is associated with less improvement in child health indicators.
Discussion and Concluding remarks Finding 1:
Level of wealth and health are strongly positively associated in India.
Part of the association is because wealth allows people to afford better food, medical care and better home environments. Societies that are richer can invest in public goods like sanitation, vector control and education.
Finding 2:
But the association between wealth and health outcomes is becoming weaker with time.
Plausible reasons:
○ Based on IHDS (2005) data it is observed that within India, Gini coefficients extend from Chhattisgarh (3.8) and Delhi (3.9) to Karnataka (5.2),Kerala (5.4) Gujarat and the NE.
○ This range is even greater than for the differences between Sweden (2.4) and the United States(3.7) (Nanneman & Dubey, 2011). Gini for India is 5.2.
○ Interestingly, within India, higher income states have almost the same
average levels of inequality as lower income states
(r= 0.04).
○ Development of basic factors that help improvement of health is too slow
In MH (Comprehensive Nutrition Survey)
No toilet facility, 43 % improved sanitation, 38 %, food insecure ( HFIAP), 43% had no food to eat last month at least once, 11 % cooking inside house with no separate room,
40% Exclusively breastfed, 60 % The dietary diversity of food for 6-23 months
children are appallingly low.
( report to be released in August, 2013)
Finding :3
States which improved their state net domestic products per capita did not see corresponding improvements in children’s health, and some states which did not achieve faster economic growth did improve children’s health indicators.
Why is economic growth associated with less improvement in children’s health?
This might be the case if states which were already healthier experienced more economic growth over the period under study;
in states which already had healthier children, it would have been harder to make improvements in health.
Indeed, it was those states with better initial health environments, experienced more economic growth.
Going forward
These associations suggest that policy makers must work to improve children’s health.
1. good governance and women’s education : Long term
2. Short term:
factors like women’s health and sanitation are likely to be increasingly important reasons for differences in health across states in India and between India and the rest of the world.
make a difference in the 1000 days window improvements to women’s health and nutrition in India
Sanitation and hygiene:60% of the people who openly defecate without a toilet or latrine live in India, and the country’s progress in improving latrine coverage has been worse than Pakistan, Bangladesh and much of sub-Saharan Africa.
Health = wealth
for growth in Wealth you must have a good Health
Creating demand side through Household empowerment
Improving supply side of basic needs
Health Wealth
Thank you