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Nutrition Baseline Surveys Summary

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Table of contents
Survey methods
Country overview
Definitions of Key Indicators
Results
• Key Indicator Results
• Availabi...

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Survey methods
• Sample size needed was calculated at
n=347, sample size of the NBS ranged
from 396-487 with the exception...

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Nutrition Baseline Surveys Summary

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Gina Kennedy presents the results of GIZ's survey covering 10 countries at the event „A Global Approach to Assess Food and Nutrition Security" on 16 September in Bonn.
Transcript presentation:http://corbecoms.com/2016-09-16_KennedyPres.pdf
Transcript interview: http://corbecoms.com/2016-09-16_Transcript_interview_GinaKennedy.pdf
The survey was conducted by GIZ’s Global Programme Food and Nutrition Security, Enhanced Resilience, financed by BMZ.
The video, produced by Corbecoms, includes the Q&A session.

Gina Kennedy presents the results of GIZ's survey covering 10 countries at the event „A Global Approach to Assess Food and Nutrition Security" on 16 September in Bonn.
Transcript presentation:http://corbecoms.com/2016-09-16_KennedyPres.pdf
Transcript interview: http://corbecoms.com/2016-09-16_Transcript_interview_GinaKennedy.pdf
The survey was conducted by GIZ’s Global Programme Food and Nutrition Security, Enhanced Resilience, financed by BMZ.
The video, produced by Corbecoms, includes the Q&A session.

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Nutrition Baseline Surveys Summary

  1. 1. Table of contents Survey methods Country overview Definitions of Key Indicators Results • Key Indicator Results • Availability and access to food • Water, Sanitation and Health • Care practices and MAD • Dietary intake of women and children • Preliminary Logistic regression results Conclusions Recommendations Bioversity InternationalS. Collins 2
  2. 2. Survey methods • Sample size needed was calculated at n=347, sample size of the NBS ranged from 396-487 with the exception of India (n=803) • Data from 4700 women-child pairs • Selection criteria: Respondents were women (15-49 yrs) who also had at least one child (6-23 months) Bioversity InternationalJ. Lauderdale 3
  3. 3. Country overview: Africa Mali • GDP per capita* (World Bank, 2015): 744.3 • Human Development Index (UNDP, 2014): 0.419 • Prevalence of stunting (UNICEF, 2013): 39% Burkina Faso Togo Benin Malawi Zambia Kenya Ethiopia • GDP per capita* (World Bank, 2015): 613 • Human Development Index (UNDP, 2014): 0.402 • Prevalence of stunting (UNICEF, 2013):33% • GDP per capita* (World Bank, 2015): 548 • Human Development Index (UNDP, 2014): 0.484 • Prevalence of stunting (UNICEF, 2013): 30% • GDP per capita* (World Bank, 2015): 779.1 • Human Development Index (UNDP, 2014): 0.480 • Prevalence of stunting (UNICEF, 2013): 45% • GDP per capita* (World Bank, 2015): 381.4 • Human Development Index (UNDP, 2014): 0.445 • Prevalence of stunting (UNICEF, 2013): 48% • GDP per capita* (World Bank, 2015): 619.1 • Human Development Index (UNDP, 2014): 0.442 • Prevalence of stunting (UNICEF, 2013): 44% • GDP per capita* (World Bank, 2015): 1376.7 • Human Development Index (UNDP, 2014): 0.548 • Prevalence of stunting (UNICEF, 2013): 35% • GDP per capita* (World Bank, 2015): 1307.8 • Human Development Index (UNDP, 2014): 0.586 • Prevalence of stunting (UNICEF, 2013):46% *current US$ 4
  4. 4. Country overview: Asia India Cambodia • GDP per capita* (World Bank, 2015): 1581.6 • Human Development Index (UNDP, 2014): 0.609 • Prevalence of stunting (UNICEF, 2013): 48% • GDP per capita* (World Bank, 2015): 1158.7 • Human Development Index (UNDP, 2014): 0.555 • Prevalence of stunting (UNICEF, 2013): 41% *current US$ 5
  5. 5. Definitions of Key Indicators of the Program Individual Dietary Diversity Score – Women of Reproductive age - IDDS-W - and Minimum Dietary Diversity – Women of reproductive age - MDD-W Minimum Acceptable Diet - MAD (6-23 months of age) • MDD (Minimum Dietary Diversity) • MMF (Minimum Meal Frequency) Food Insecurity Experience Scale-Household - FIES-H 6
  6. 6. Definitions of Key Indicators Individual Dietary Diversity Score and MDD-W Photo credit: Klaus Wohlmann 7 IDDS-W: is the sum of ten food groups consumed over the past 24 hours by women 15-49 years of age. MDD-W: is the proportion of women 15-49 years of age who consumed food items from at least 5 out of 10 defined food groups the previous day or night. Interpretation: Higher prevalence of MDD-W is a proxy for better micronutrient adequacy among women of reproductive age in the population
  7. 7. Definitions of Key Indicators Food groups for women • Eggs • Dark green leafy vegetables • Other vitamin A-rich fruits & vegetables • Other vegetables • Other fruits • Grains, white roots/tubers, plantains • Pulses (beans, peas and lentils) • Nuts and seeds • Dairy • Meat, poultry and fish 8
  8. 8. Definitions of Key Indicators Minimum Acceptable Diet (MAD) Minimum Dietary Diversity (MDD) Minimum Meal Frequency (MMF) Source, WHO, 2008 Minimum acceptable diet (MAD): Proportion of children 6-23 months of age who receive a minimum acceptable diet which is a composite indicator of minimum dietary diversity and minimum meal frequency during the previous day Minimum dietary diversity (MDD): Proportion of children 6-23 months of age who receive foods from 4 or more food groups out of seven Interpretation: proxy for adequate micronutrient-density of foods and liquids other than breast milk Minimum meal frequency (MMF): Proportion of breastfed and non-breastfed children 6-23 months of age who receive solid, semi-solid, or soft foods (but also including milk feeds for non-breastfed children) the minimum number of times or more. Interpretation: proxy for energy intake from foods other than breast milk 9
  9. 9. Definitions of Key Indicators Food Insecurity Experience Scale-H (FIES-H) Prevalence of Experienced Food Insecurity at moderate or severe levels (FImod+sev) Prevalence of Experienced Food Insecurity at severe levels (FIsev) Interpretation: estimates of the proportion of the population facing difficulties in accessing food, at levels of moderate and severe food insecurity - During the last 4 weeks, was there a time when: 1. You or others in your household worried you would run out of food because of a lack of money or other resources? 2. You or others in your household were unable to eat healthy and nutritious food because of a lack of money or other resources? 3. You or others in your household ate only a few kinds of foods because of a lack of money or other resources? 4. You or others in your household had to skip a meal because there was not enough money or other resources to get food? 5. You or others in your household ate less than you thought you should because of a lack of money or other resources? 6. Your household ran out of food because of a lack of money or other resources? 7. You or others in your household were hungry but did not eat because there was not enough money or other resources for food? 8. You or others in your household went without eating for a whole day because of a lack of money or other resources? Source: FAO, Voices of the Hungry, 2016 10
  10. 10. Results according to the UNICEF Framework Health Services and WASH Presence of soap in household,Use of soap for hand- washing, Access to improved sanitation facility, Access to improved water Care Environment Access to nutrition counselling Knowledge about prevention of malnutrition Availability and access to food Land access. Crop diversity, Home gardening, Livestock keeping, Access to fruit trees Prevalence of moderate and severe food insecurity (FIES-H) Nutritional Status (Prevalence of stunting, underweight, overweight and micronutrient deficiencies) Food Intake MAD (MDD and MMF) in children 6-23 mo MDD-W of women 15-49 years Health Status Prevalence of diarrhea 11 Education Women’s education level
  11. 11. Results: Presentation of the Nutrition Baseline Survey results In order to summarize visually different percentages across the ten countries, a dashboard categorization was used. Red: ‘Very Poor” Yellow: ‘Poor” Green: ‘Better’ 0-32% Very low/poor 33-66% Low 67-100% Better 12 The inverse percentages used for Food Insecurity as increasing percentage reflects a worse situation
  12. 12. Results: Summary of Key Indicators of the Program Many patterns are consistent (Kenya, Togo, Zambia, Benin) Malawi does a bit better with MDD-W and MAD than could be expected with such high food insecurity Households experience of moderate and severe food insecurity is relatively low in Ethiopia and India, however MAD and MDD very low. FIES-H here refers to moderately and severely food insecure Numbers represent % Country FIES-H MAD MDD-W Kenya 87 15 12 Malawi 86 34 43 Mali 55 11 8 Togo 55 33 28 Zambia 41 34 57 Benin 32 26 34 Cambodia 24 41 53 Ethiopia 23 19 7 Burkina Faso 22 38 38 India 18 18 20
  13. 13. Results: Female education Very large range across countries in female education (20-100%) According to MDG for sub-Saharan Africa in 2000, 60% of all children were enrolled in primary school (MDG report of the United Nations, 2015). 5 out of 8 project sites in Africa are below this benchmark. Benin Burkina Faso Cambodia Ethiopia India Kenya Malawi Mali Togo Zambia Some school 20% 33.6% 90.4% 45% 51% 100% 87% 33.6% 56% 69% 14
  14. 14. Results: Availability and access to food - access to land Benin Burkina Faso Cambodia Ethiopia India Kenya Malawi Mali Togo Zambia Access to land for agriculture 97% 81% 85% 95% 71.5% 21% 90% 78% 92% 99% Access to land for agriculture is OK for all countries except Kenya. Kenya reports a low access to land; it should be noted that the survey area in Kenya represents an area where the population is mainly pastoral and practice a nomadic lifestyle. 15
  15. 15. Results: Availability and access to food - Main crops grown (% of households growing the crop) Benin Burkina Faso Cambodia Ethiopia India Kenya Malawi Mali Togo Zambia Maize 94 Maize 97 Rice 95 Maize 70 Wheat 93 Maize 88 Maize 91 Rice 88 Maize 98 Maize 100 Sorghum 75 Millet 78 Cassava 15 Teff 60 Mustard 66 Legumes 74 Groundnuts 45 Maize 19 Manioc 94 Groundnuts 67 Soya 76 Groundnuts 63 Beans 8 Barley 50 Sesame 56 - Soya 20 Millet 19 Beans 66 Sunflower 57 Yams 77 Red sorghum 61 - Legumes 43 Bengal gram 55 - Rice 20 - Groundnuts 58 - 16
  16. 16. Results: Availability and access to food - households with home gardens, access to fruit and livestock  India, Kenya and Togo twenty percent or fewer hh had home gardens.  1/3 of hh or fewer with access to fruit in Ethiopia, India, Kenya and Mali  Fifty percent or more of all hh keep livestock, except Malawi Photo: Kuldeep Singh Jadon 17
  17. 17. Results: Availability and access to food - food insecurity experience scale (FIES-Household) Prevalence rates are representative of project area (not national). Within the surveyed areas food insecurity is greatest in Kenya, followed by Malawi, Mali and Togo. Results from Ethiopia are better than expected given one of the lowest MDD-W and MAD. Country FImod+sev (%) FIsev (%) Kenya 86.6 46.5 Malawi 86.1 35.8 Mali 54.8 29.7 Togo 54.6 2.5 Zambia 41.4 10 Benin 31.7 12.8 Cambodia 23.8 0.09 Ethiopia 22.7 0.8 Burkina Faso 21.9 4.7 India 17.7 8.4 18
  18. 18. Results: Health - drinking water and sanitation 2015 MDG targets for sub-Saharan Africa 74% access to safe water and 62% access to safe sanitation. Water goal met in at least one season for six project areas in Africa. Sanitation in nearly every project area is very far away from goal. 0 10 20 30 40 50 60 70 80 90 100 Ethiopia Kenya East Africa Access to improved sanitation Access to improved water – Wet season Access to improved water – Dry season 0 10 20 30 40 50 60 70 80 90 100 Benin Burkina Faso Mali Togo West Africa 0 10 20 30 40 50 60 70 80 90 100 Malawi Zambia Southern Africa 0 10 20 30 40 50 60 70 80 90 100 Cambodia India Asia
  19. 19. Results: Care - Maternal knowledge compared to prevalence of MAD 20 Gap between knowledge and practice is high in Kenya and Ethiopia. WHY? Knowledge and practice are similar for other countries, so behavior change communication a plausible strategy. What should we do to prevent malnutrition in children?
  20. 20. Results: Dietary Intake Women (15-49 years) The IDDS-W ranged from 3.1 (0.9) (Ethiopia) to 4.7 (1.3) (Zambia) with percent of women achieving MDD ranging from 6.8 % in Ethiopia to 57 % in Zambia. IDDS-W and MDD-W pretty consistent except in Cambodia. In Cambodia, high percentage of women consume the same 4 food groups. Country IDDS-W MDD-W (%)* Ethiopia 3.1 7 Kenya 3.2 12 Mali 3.2 8 Cambodia 3.3 53 India 3.6 20 Malawi 3.9 43 Togo 3.9 28 Benin 4.1 34 Burkina Faso 4.2 38 Zambia 4.7 57 21
  21. 21. Results: Dietary intake children 6-23 months MMF higher than MDD for all countries, focus needed on diversification. Important to also disaggregate results by breastfeeding and age Results are presented for full sample not by breastfed/non-breastfed as >75% of children breastfed yesterday Mali Kenya Ethiopia India Benin Togo Malawi Zambia Burkina Faso Cambodia MAD 11 15 17 18 26 33 34 34 38 41 MDD 27 22 19 23 33 43 43 55 50 47 MMF 57 71 66 58 67 71 70 77 63 93
  22. 22. Hypothesis 1: Women’s dietary diversity, measured by the Individual Dietary Diversity Score Women (IDDS-W) or Minimum Dietary Diversity Women (MDD-W), is higher for households with a more diverse agricultural production pattern and a better knowledge of adequate nutrition. Hypothesis 2: Children aged 6-23 months are more likely to receive a minimum acceptable diet (MAD) the more diverse the household’s agricultural production and the higher the household’s level of nutrition knowledge. Results: Preliminary testing of hypotheses 23
  23. 23. Results: Preliminary testing of hypotheses IDDS-W and MDD-W In 9 out of 10 country models at least one and max. three agricultural variables have a causal positive effect on women's dietary diversity: (crop diversity, home garden, access to fruit/fruit production in homestead, year- round vegetable production, vegetable diversity, fruit diversity) Nutrition counselling was significant in some but not all countries Other significant predictors are very country specific and do not occur consistently amongst countries (secondary education, geographical location, ethnicity, income score)
  24. 24. Results: Preliminary testing of hypotheses: Minimum acceptable diet  Results seem to confirm the program’s hypotheses of relationships between agriculture production and particularly women’s dietary diversity.  For Minimum acceptable diet, interventions need to incorporate a focus on youngest children and breastfeeding In 5 out of 10 country models at least one and max. two agricultural variables have causal positive effect on infants’ MAD (vegetable diversity, crop diversity, home garden) In 9 out of 10 country models infant’s age, breastfeeding status, and/or under 5 child clinic visits positively and significantly influence MAD Within countries district was also often a significant predictor
  25. 25. Conclusions 1. The project sites represent vulnerable areas and are appropriate sites for the proposed interventions. 2. The chosen key indicators of IDDS-W and MAD match well with the program intervention packages in most countries. 3. There are plausible impact pathways to achieve the objectives of the program given the combination of interventions in most countries. 26
  26. 26. Recommendations for the program General  Try to assess level and intensity of participation in interventions Availability and access to food  Own production was a big focus of the NBS but market and market access was not, more exploration of market access and food availability in markets could be undertaken at mid-term  Seasonal fluctuations in food availability should be further explored and addressed when designing interventions  Divergence between access to fruit and vegetables and consumption should be explored using qualitative methods 27
  27. 27. Recommendations for the program Care  Country specific qualitative data collection is needed to understand divergence in knowledge and practice of dietary diversity for children in Ethiopia and Kenya  Most knowledge questions were based on maternal recall of general topics, the uptake of program specific messaging should be tested  Assess different channels of communication for uptake of messages Health/WASH  Advocate especially access to sanitation 28
  28. 28. Thank you www.bioversityinternational.org/subscribe @BioversityInt Gina Kennedy g.kennedy@cgiar.org
  29. 29. Results: Dietary intake - percent food group consumption across countries using dashboard classification 75 % or more of all women in every country consume staple foods. Other vegetables are the next food group most frequently consumed. Food groups rarely consumed include nuts and seeds, dairy, eggs, vitamin A rich fruits/veg and other fruit. 30
  30. 30. Country Agriculture /production (9/10) Direct nutrition education (6/10) Support to extension staff to provide education (9/10) Multi-sectoral coordination (8/10) Other (media campaigns, WASH, Social transfers) Benin X X X X x Burkina Faso X X X X x Cambodia X X X X X Ethiopia X X X X India X Improve efficiency of TPDS Kenya X X X X Malawi x x x X Support to education and health facilities Mobile advisory services via telephone for pregnancy and post- pregnancy Mali X x Togo X X X X Zambia X X X X x Project intervention types by country 38 31
  31. 31. • Based on the project interventions in support of agricultural production, training and support to extension staff, direct nutrition education (including cooking demonstrations and other methods) and support to multi-stakeholder groups for improving nutrition several of the NBS indicators could be expected to change, including; – Agriculture indicators of home gardening, access to fruit and potentially number of crops grown – Increased Knowledge, attitudes and practices – Improved MDD-W and MAD Interventions (II) 39 32
  32. 32. • Basic services including primary education and access to safe sanitation need urgent attention in some of the project areas • The NBS also showed uneven coverage of access to safe water in wet/dry season, this aspect also needs to be addressed with national stakeholders • The project interventions working with multi-sectoral bodies need to make sure to highlight the lack of basic services in some of the project areas Recommendations for the project area: Basics for development 30 33

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