Nutrition Baseline Surveys Summary

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 International\S. Collins

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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 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 International\J. Lauderdale

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Country overview: AfricaMali

• 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


2015): 613


(UNDP, 2014): 0.402


2013):33%

• GDP per capita* (World Bank, 2015):

548

• Human Development Index (UNDP,

2014): 0.484


2013): 30% • GDP per capita* (World Bank,

2015): 779.1


(UNDP, 2014): 0.480


2013): 45%


2015): 381.4


(UNDP, 2014): 0.445


2013): 48%


2015): 619.1


(UNDP, 2014): 0.442


2013): 44%


2015): 1376.7


(UNDP, 2014): 0.548


2013): 35%


2015): 1307.8


(UNDP, 2014): 0.586


2013):46%

*current US$

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Country overview: Asia

India

Cambodia• GDP per capita* (World Bank,

2015): 1581.6


(UNDP, 2014): 0.609


2013): 48%


2015): 1158.7


(UNDP, 2014): 0.555


2013): 41%

*current US$

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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

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Definitions of Key IndicatorsIndividual Dietary Diversity Score and MDD-W

Photo credit: Klaus Wohlmann

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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

Definitions of Key IndicatorsFood 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

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Definitions of Key IndicatorsMinimum 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 milk9

Definitions of Key IndicatorsFood 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, 201610

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

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EducationWomen’s education level

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

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The inverse percentages used for Food Insecurity as increasing percentage reflects a worse situation

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 insecureNumbers 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

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.

BeninBurkina

FasoCambodia Ethiopia India Kenya Malawi Mali Togo Zambia

Some

school20% 33.6% 90.4% 45% 51% 100% 87% 33.6% 56% 69%

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Results: Availability and access to food - access to land

BeninBurkina


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.

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Results: Availability and access to food - Main crops grown

(% of households growing the crop)

BeninBurkina


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-

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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

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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

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Results: Health - drinking water and sanitation2015 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 seasonAccess to improved water – Dry season

0

10

20

30

40

50

60

70

80

90

100

Benin BurkinaFaso

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

Results: Care - Maternal knowledge compared to prevalence of

MAD

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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?

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

Faso4.2 38

Zambia 4.7 57

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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 ZambiaBurkina

FasoCambodia

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

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

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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)

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

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.

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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

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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

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Thank you

www.bioversityinternational.org/subscribe

@BioversityInt

Gina Kennedy

[email protected]

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.

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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

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• 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)

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• 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

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Nutrition Baseline Surveys Summary

Presentations & Public Speaking

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