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1 wealth and-health_of_children_in_india

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1 wealth and-health_of_children_in_india

  1. 1. Diane Coffey, Aparajita Chattopadhyay & Rajan Gupt
  2. 2. 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).
  3. 3. 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.
  4. 4.  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
  5. 5.  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, 2012  for 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.
  6. 6.  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.
  7. 7. 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?
  8. 8. 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.
  9. 9. Results:
  10. 10. Relationship between aggregate wealth and child’s health
  11. 11. 1 2 3 4 5 6 7 8 9 11 12 13 14 15 16 18 19 21 22 23 24 25 26 10 20 0 .2.4.6 0 5000 10000 15000 20000 25000 30000 state net domestic product in 1997 (1993 prices) fraction of stunted children under 3 Fitted values NFHS 2 23 4 5 6 7 8 910 11 12 13 14 15 16 19 20 21 22 23 25 26 1 0 .2.4.6 0 5000 10000 15000 20000 25000 30000 state net domestic product in 2004 (1993 prices) fraction of stunted children under 3 Fitted values NFHS 3 size of circle proportional to approximate population 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
  12. 12. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 18 19 21 22 23 24 25 20 26 -2.5 -2 -1.5 -1 0 5000 10000 15000 20000 25000 30000 state net domestic product in 1997 (1993 prices) average height for age z-score of children under 3 Fitted values NFHS 2 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 19 20 21 22 23 25 26 1 -2.5 -2 -1.5 -1 0 5000 10000 15000 20000 25000 30000 state net domestic product in 2004 (1993 prices) average height for age z-score of children under 3 Fitted values NFHS 3 size of circle proportional to approximate population of children under 6 Height for age Z score 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
  13. 13. Infant Death and NSDP 1 2 3 4 5 6 7 8 10 11 12 13 1415 16 18 19 20 21 22 23 24 25 26 9 0 .02.04.06.08 0 5000 10000 15000 20000 25000 30000 state net domestic product in 1997 (1993 prices) fraction of infant deaths Fitted values NFHS 2 1 2 3 4 5 6 7 8 10 11 12 13 14 15 16 19 20 21 22 23 25 26 9 0 .02.04.06.08 0 5000 10000 15000 20000 25000 30000 state net domestic product in 2004 (1993 prices) fraction of infant deaths Fitted values NFHS 3 size of circle proportional to approximate population of children under 6 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
  14. 14. 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
  15. 15. 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
  16. 16. State level relationship between growth of income and health improvements
  17. 17. 1 2 3 4 5 6 7 89 10 11 12 13 14 15 16 19 20 21 22 23 25 26 -.2-.1 0 .1 0 .1 .2 .3 growth in state net domestic product per capita between NFHS 2 and 3 change in stunting Fitted values 1 2 3 4 56 7 89 10 11 12 13 14 15 1619 20 21 22 2325 26 -.5 0 .5 1 0 .1 .2 .3 growth in state net domestic product per capita between NFHS 2 and 3 change in average height for age z-score Fitted values 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 19 20 21 22 2325 26 -.04-.02 0 .02 0 .1 .2 .3 growth in state net domestic product per capita between NFHS 2 and 3 change in fraction of infants who died Fitted values size of circle proportional to average of 1998 and 2005 under 6 population 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
  18. 18. 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
  19. 19.  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.
  20. 20. 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.
  21. 21. 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.
  22. 22. 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
  23. 23. 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)
  24. 24. 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.
  25. 25. 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.
  26. 26. 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
  27. 27. Thank you

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