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Multi-state stories:Insights from the frontrunners of stunting reduction

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Presented at on 'Strengthening National, State and District-level Actions for Nutrition: Insights from the National Family Health Survey Data' on 13th December, 2017 at IIC, New Delhi.

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Multi-state stories:Insights from the frontrunners of stunting reduction

  1. 1. Presented by Phuong Hong Nguyen International Food Policy Research Institute Multi-state stories: Insights from the frontrunners of stunting reduction
  2. 2. 2016 38.4% 2006 Significant stunting reduction in all states in India in the last decades 2006 48%
  3. 3. Stunting reduction varies by state -3.8 -3.8 -3.8 -3.5 -3.5 -3.4 -3.1 -3.0 -2.9 -2.9 -2.9 -2.8 -2.7 -2.6 -2.5 -2.4 -2.4 -2.4 -2.3 -2.2 -2.2 -2.1 -2.0 -1.9 -1.7 -1.4 -1.3 -1.1 -0.9 -4.0 -3.5 -3.0 -2.5 -2.0 -1.5 -1.0 -0.5 0.0 -20 -18 -16 -14 -12 -10 -8 -6 -4 -2 0 AARR percentagepointchange pp change AARR
  4. 4. 1,11,20,920 78,64,654 36,51,636 - 20,00,000 40,00,000 60,00,000 80,00,000 1,00,00,000 1,20,00,000 Numberofstuntedchildren 9 states account for ~80% of stunted children Number of stunted children reduced from ~76 million in 2006 to ~50 million in 2016
  5. 5. In 2016, prevalence stunting is still >30% in 16 states 0 10 20 30 40 50 60 Stuntingpercentage
  6. 6. If current trend of AARR continues, only 5 states reach the WHA target in 2025 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 7.0% 8.0% Averageannualreductionrate Required AARR (2016-2025) Current AARR
  7. 7. What can the frontrunners, who have achieved lower rates of stunting, tell us? 48.3 46.3 45.3 42.0 39.1 27.1 25.7 24.3 20.1 19.7 0 10 20 30 40 50 60 %stuntingin2016
  8. 8. Conceptual framework for examining determinants of stunting
  9. 9. Immediate determinants: Maternal nutrition status, in high versus low stunting states Low BMI women Anemia in women of reproductive age 25.3 27 28.3 30.4 31.5 9.7 11.7 14.6 14.7 18.9 0 10 20 30 40 50 60 70 % 49.9 53.1 55.9 67.4 69.5 32.8 38 38 53.2 65.1 0 10 20 30 40 50 60 70 %
  10. 10. Immediate determinants: Infant and young child feeding practices in high versus low stunting states Early initiation of breastfeeding Adequate diet 25.2 28.4 33.2 34.5 34.9 30.7 44.4 54.7 64.3 73.3 0 10 20 30 40 50 60 70 80 % 3.4 5.3 6.6 7.2 7.5 5.9 5.9 10.4 21.4 30.7 0 10 20 30 40 50 60 70 80 %
  11. 11. Intervention coverage: Antenatal care and IFA consumption, in high versus low stunting states At least 4 ANC visits Consume 100+ IFA tablets 14.4 26.4 30.3 35.7 38.5 64.3 68.5 81.2 89 90.2 0 20 40 60 80 100 % 9.7 12.9 15.3 17.3 23.6 13.4 42.6 64.0 67.1 67.4 0 20 40 60 80 100 %
  12. 12. Intervention coverage: Immunization and vitamin A supplementation for children, in high versus low stunting states Fully immunized Vitamin A supplementation 51.1 53.6 54.8 61.7 61.9 54.5 69.7 82.1 88.4 89.1 0 20 40 60 80 100 % 39.5 39.6 52.9 60.4 62.3 62.8 68.3 70.6 74.4 89.5 0 20 40 60 80 100 %
  13. 13. Underlying determinants: Women’s education and age at marriage, in high versus low stunting states Women with 10y+ education Married before 18y of age 22.8 23.2 25.1 28.7 32.9 23.4 50.9 55.1 58.2 72.2 0 20 40 60 80 % 21.2 30 35.4 38 39.1 7.6 7.6 9.8 15.7 32.2 0 20 40 60 80 %
  14. 14. Underlying determinants: Water and sanitation, in high versus low stunting states Improved drinking water Improved sanitation 24.4 25.2 33.7 35.0 45.0 52.2 61.3 78.3 81.5 98.1 0 20 40 60 80 100 % 77.8 84.7 85.5 96.4 98.2 87.3 90.6 94.3 96.3 99.1 0 20 40 60 80 100 %
  15. 15. Regression analysis comparing very high burden (stunting >40%) and low burden districts (stunting<20%) also provides some insights on important determinants Asset score 13% Women with 10+ years school 17% Adequate diet 5% ANC 4+ times 4% Open defecation density 7% Married at 18+ years 5% Household size 8% ST/SC population 3% Unexplained 38%
  16. 16. Differences between high and low stunting states/districts are attributable to factors related to immediate and underlying determinants, and intervention coverage ▪Determinants o Maternal nutrition o Infant feeding o Sanitation o Women’s education o Age at marriage ▪Intervention coverage o ANC o IFA o Others (not shown) Changing malnutrition outcomes requires an investment in changing intervention coverage and subsequently in changing determinants. The POSHAN Policy Notes for each state can help with diagnostic assessments
  17. 17. Looking forward: Stories of Change in nutrition for different successful states in India Initial SoC studies will be done in 5 states: Odisha, Arunachal Pradesh, Tamil Nadu, Gujarat, Chhattisgarh. Stories of Change research for Odisha, available in: Menon et al., Nourishing Millions, 2016; Kohli et al., Global Food Security, 2017
  18. 18. Closing thoughts ➢ Malnutrition burden in India remains high despite some progress ➢ Tremendous inter-state and inter-district variability ➢ Inter-district and inter-state differences in stunting are not explained by any single factor, but rather by a set of maternal, economic, health, hygiene and demographic factors. ➢ Most importantly, many success stories across India, which are important to learn from. ➢ POSHAN state Policy Notes help policy community examine state of nutrition outcomes, immediate and underlying determinants and intervention coverage: diagnose and identify challenges that need attention. ➢ Analysis of unit-level data, when available, from NFHS-4, and Stories of Change studies at the state-level will help to support India’s nutrition policy community

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