1 / 24

A Methodology for Prioritizing Countries for Biofortification Interventions

A Methodology for Prioritizing Countries for Biofortification Interventions. Salomón Pérez S Dorene Asare-Marfo Ekin Birol Mourad Moursi Jana Schwarz Manfred Zeller. Introduction. Micronutrient deficiency is a public health problem in many developing countries. Objectives.

Download Presentation

A Methodology for Prioritizing Countries for Biofortification Interventions

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  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

More Related