A Methodology for Prioritizing Countries for Biofortification Interventions

1. A Methodology for Prioritizing Countries for Biofortification Interventions Salomón Pérez S Dorene Asare-Marfo EkinBirol MouradMoursi Jana Schwarz Manfred Zeller

2. Introduction Micronutrient deficiency is a public health problem in many developing countries

3. Objectives • To build an index for biofortification intervention prioritization in Africa, Asia, Latin America and the Caribbean (LAC) • To prioritize countries for iron biofortification intervention (beans and pearl millet) • To prioritize countries for zinc biofortification intervention (rice and wheat) • To prioritize countries for vitamin A biofortification intervention (cassava, maize, sweet potato)

4. Conditions for H+ priority country Country must: • Produce the crop - a significant proportion of production must be used for domestic consumption • Consume much of the crop on a per-capita basis • Have a high level of micronutrient deficiency (vitamin A, Iron or zinc)  Saltzman et al. (2013)

5. Methodology The biofortification priority index (BPI) captures the three conditions with three sub-indices: • Production Index • Consumption Index • Micronutrient deficiency index

6. Production Index • Shows intensity of crop production in country • Variables: • Per capita area harvested (sqm per capita) • Share of area harvested allocated to crop (%) • Export share (%) Production Index = [1 – export share] [(0.5 x per capita area harvested ) + (0.5 x % land area allocated to crop )]

7. Consumption Index • Measures the magnitude of per-capita consumption of crop in the country which is supplied by domestic production • Variables: • Consumption per capita (kg/cap/year) • Import share (%) Consumption Index = Consumption per capita x (1-Import Share*) *Import share = Imports/(Production + Imports - Exports)

8. Micronutrient Deficiency Index • Describes the extent of micronutrient deficiency • Variables for Vitamin-A deficiency index: • Proportion of preschool-age children with retinol < 0.7 μmol/l • Age-standardized DALYs per 100,000 inhabitants by VAD Vitamin A Deficiency Index = (0.5 x Proportion of preschool-age children with retinol < 0.70 umol/l) + ( 0.5 * Age-standardized DALYs per 100,00 inhabitants by VAD)

9. Micronutrient Deficiency Index (cont.) • Variables for Iron deficiency index: • Proportion of preschool-age children with Hb< 110 g/dl • Age-standardized DALYs per 100,000 inhabitants by IDA Iron Deficiency Index = + (0.5 x Proportion of preschool-age children with Hb < 110 g/l) + (0.5 x Age-standardized DALYs per 100,000 inhabitants by IDA)

10. Micronutrient Deficiency Index (cont.) • Variables for Zinc deficiency index: • Percentage of population at risk of inadequate intake of zinc • Prevalence of stunting among children 6-59 months Zinc Deficiency Index = (0.5 x Percentage of population at risk of inadequate intake of zinc) + (0.5 x Prevalence of stunting)

11. Summary of Indices and variables used

12. Biofortification Priority Index BPI = (0.25 x Consumption Index) + (0.25 x Production Index) + (0.5 x Micronutrient Deficiency Index) • HDI and PCA

13. Results - Top 10 BPI Ranking for LAC

14. Results - Top 10 BPI Ranking for Africa

15. Results - Top 10 BPI Ranking for Asia

16. BPI for Beans and Rice in LAC

17. BPI for Cassava and Sweet Potato in LAC

18. Weighing the BPI • PopulationWeight BPI: The country weight is calculated as the country’s rural target population share in “global” rural target population • Area- share WeightBPI: For each crop, the area-share weighted BPI is calculated as the country’s share of area harvested in “global” area harvested for the respective crop “Target population” - Women in childbearing age and children 6-59 months (latter variable proxied by 0-59 months) “Global” - 127 countries in our database (all countries in Africa, Asia and LAC, except high-income OECD countries)

19. Unweighted vs. Weighted BPI: Global Ranks Compared

20. Unweightedvs.Weighted BPI for Maize in LAC

21. Limitations of the BPI • Lack of data for some countries (assumptions for replacing missing values, e.g. micronutrients – Wessels et al. (2012)) • Aggregated national level data but concept can be easily adapted using spatially disaggregated/ nationally representative micro-level data • BPI does not explicitly tell us about costs of DALYs saved through biofortification, but uses proxy indicators for variables being part of the cost-benefit-function for DALYs saved thru biof.. • Arbitrary weights (similar to GHI and HDI)

22. Strengths of BPI/Conclusions • BPI allows for cross-country prioritization w.r.t. to H+ crops • BPI is not sensitive (i.e. robust) to changes in the weights for micronutrient deficiency index compared to consumption/production index • Reassured that wheat and rice for Asia; Beans, sweet potato and cassava for Africa and LAC; Maize and Pearl Millet for Africa • Need to examine weighted and unweighted BPIs to get a better picture

23. Thank you

24. Variable scaling (0-1) • All variables were rescaled to a range between 0 and 1 by applying the next formula: Rescaled value = actual value-minimum value maximum value-minimum value