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FAO-EU Joint Workshop to promote the workshop to promote the uptake and

dissemination of the MDD-W

Tajikistan team :

Mr. Abduvali Qulov - AoS;

Dr. Sherali Rakhmatulloev – MHSP

Dr. Sabir Kurbanov - Consultant

Integration and scaling up of the MDD-

W module into the Household Budget

Survey (HBS) in Tajikistan

Tajikistan faces the huge burden of undernutrition,

overnutrition and micronutrient deficiencies

� Only country in Central Asia not

met MDG for halving proportion

of hungry people by 2015

� 25% children stunted children

and 10% wasted

� 53% Under 5 and 59% women of

reproductive age are iodine

deficient

� 24% women are anaemic

� 38% women overweight and

obese, with higher rates in urban

areas

Source: AoS 2012; 2015

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Tajikistan is committed to improving the quality and

diversity of people diets, but information is lacking

� Improvement of nutrition status of population (women and children) became

priority of the country (support from donor communities, SUN initiative)

� Government has prioritized setting up of national information systems for

nutritional information and requested AoS to collect representative information

� FAO supported Tajikistan for mapping and assessing available nutrition

assessment capacity to collect food based nutrition information

� AoS has a long history of conducting Household Budget Survey (HBS) at national

level

� So far, HBS in Tajikistan does not include any nutrition module or dietary

information at individual or household level

� Integrating MDD-W into the HBS would:

• provide a simple proxy indicator for measuring dietary diversity

• allow investigation of associations between socio-economic and

demographic factors and diet adequacy

Change in poverty according to TLSS 1999, 2003, 2007 and 2009

0

10

20

30

40

50

60

70

80

90

1999 2003 2007 2009

82

73

53.547.2

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20.4

22.3

35.837.3

39.4

35.2

23.2

31.3

9.1 9.4

16.8

20.619.6

17.5

10.2

15.2

dushanbe sughd khatlon RRS GBAO rural urban Tajikistan

Basic poverty results, Tajikistan 2015

overall poverty extreme poverty

Evolution of poverty based on national estimation

37.4 35.4

32 31.3

2018

16.8 15.2

2012 2013 2014 2015

Уровень бедност Уровень крайной бедности

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Project Objective

• To build nationwide capacity (human and

institutional) in collecting, analysing and

interpreting MDD-W data at national level, to

allow country ownership of the tool

Project design and implementation

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The project was implemented in 3 Phases:

I. Preparatory phase

• Capacity mapping at country level

• financing for conducting three training courses and three

pilot studies.

II. Capacity development and adaptation of the MDD-W tool

• A 5-day training course for enumerators and AoS staff;

• Adaptation of MDD-W questionnaire to local context (food

variety, selection and dietary habits)

III. Design and implementation of the pilot study –

• Selection of HBS households for dietary diversity interview

with women of reproductive age (15 to 49 years);

• Data collection and logistics;

• Data analysis & Report writing - Supported by Food Systems

and Nutrition Division, FAO, Rome

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Project Overview� Operation Modality: MDD-W integrated into the National

Household Budget Survey; Dietary Diversity questionnaire was

adapted to local context through key informant meetings and

focus group discussions;

� Responsible Entity: Agency of Statistics of Tajikistan (AoS) with

the support of FAO

� Duration: 3 years (2014-2016)

� Budget and financial support: initial cost for all three phases of

MDD-W was ~USD 28 000 over 3 years, provided by the EU

(Approximately 11-12 USD$ per woman)

� Geographic Coverage: Nationwide including rural and urban

areas (Dushanbe city; Rayon Republican Subordination; Khatlon,

Sughd and GBAO regions)

� Number of women : [> 1000 WRA]

Project outputs

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� Capacity developed and

dietary diversity tool adapted to

the local context:

• A total of 3 training courses were

conducted and 66 AoS personnel

were trained

� Pilot studies, data collection and data

management• A total of 3 pilot studies were conducted, dietary diversity

data were collected from 1032 women across all regions of

the country

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Year Region MDD-W Median

2014 Khatlon (n= 331) (WDDS) 6.0

2015 Sughd (n= 286) 7.0

2015 Dushanbe (n=133) 7.4

2015 RRS (n=202) 6.5

2015 GBAO (n=80) 5.9

Key Findings: A. Median dietary diversity of women

11

.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

1 2 3 4 5 6 7 8 9 10

Pe

rce

nta

ge %

MDD-W Dushanbe, RRS and GBAO

Sughd

Dushanbe

RRS

GBAO

Region% of women

≥ the cut-off

% of women

< cut-off

Sughd (n= 286) 95.5 4.5

Dushanbe (n=133) 98.0 2.0

RRS (n=202) 88.0 12.0

GBAO (n=80) 86.0 14.0

Key Findings: B. Percentage of women that did not meet the

minimum dietary diversity

12

.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

1 2 3 4 5 6 7 8 9 10

Pe

rce

nta

ge %

MDD-W Dushanbe, RRS and GBAO

Sughd

Dushanbe

RRS

GBAO

Cut -off

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Key Findings: C. Least consumed food groups by cut-off group

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Nuts and seeds 8 % 9 % 0 %

Eggs 31 % 35 % 5 %

Beans and peas 52 % 54 % 14 %

0 10 20 30 40 50 60 70 80 90 100

SFG-1 All starchy staples

SFG-2 Beans and peas

SFG-3 Nuts and seeds

SFG-4 all dairy

SFG-5 Flesh foods

SFG-6 Eggs

SFG-7 Vitamin A-rich DGLV

SFG-8 Other vit A-rich veg. and fruits

SFG-9 Other vegetables

SFG-10 Other fruits

Total sample Equal or above cutoff Below cutoff

Key Findings: D. Consumption of nutrient-dense foods

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0 10 20 30 40 50 60 70 80 90 100

SFG-1 All starchy staples

SFG-2 Beans and peas

SFG-3 Nuts and seeds

SFG-4 all dairy

SFG-5 Flesh foods

SFG-6 Eggs

SFG-7 Vitamin A-rich DGLV

SFG-8 Other vit A-rich veg & fruits

SFG-9 Other vegetables

SFG-10 Other fruits

Sughd Dushanbe RRS GBAO

Fru

its

an

d v

ege

tab

les

An

ima

l-so

urc

e f

oo

dN

uts

/ b

ea

ns

�Women in

the GBAO

region

consumed less

nutrient-

dense foods

�Fish was

consumed by

only 2% of

the women

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Key Findings: E. Association between dietary diversity and

rural/urban areas

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Women living in rural areas had consumed less nutrient-

dense foods compared with women living in urban areas

0 10 20 30 40 50 60 70 80 90 100

SFG-1 All starchy staples

SFG-2 Beans and peas

SFG-3 Nuts and seeds

SFG-4 all dairy

SFG-5 Flesh foods

SFG-6 Eggs

SFG-7 Vitamin A-rich DGLV

SFG-8 Other vit A-rich veg. and fruits

SFG-9 Other vegetables

SFG-10 Other fruits

Rural Urban

0 10 20 30 40 50 60 70 80 90 100

SFG-1 All starchy staples

SFG-2 Beans and peas

SFG-3 Nuts and seeds

SFG-4 all dairy

SFG-5 Flesh foods

SFG-6 Eggs

SFG-7 Vitamin A-rich DGLV

SFG-8 Other vit A-rich veg. and fruits

SFG-9 Other vegetables

SFG-10 Other fruits

Low HHIEq Medium HHIEq High HHIEq

Key Findings: F. Association between dietary diversity and

household income (HHIEq)

Women of lower income had consumed less nutrient-

dense foods compared with women of higher income

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Conclusions and recommendations (1)

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� AoS completed 3 pilot studies in all five regions of country (Khatlon, Sughd,

Dushanbe, RRS and GBAO).

� The median dietary diversity was relatively high – between 6 and 7 (with the

lowest in GBAO 5.9). These data indicates an adequate dietary diversity in the

majority of the women (data collection was during harvest season).

• It is recommended to repeat data collection during lean season or during

periods of low food bioavailability. Dietary diversity score could

significantly vary by season.

� However, findings indicates that main group foods consumed by all WRA were

starchy staples and vegetables.

� The less consumed food groups were nuts, beans and eggs.

• By promoting the consumption of these food groups the dietary diversity

of the women could be improved

Conclusions and recommendations (2)

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� There were direct correlation between household income and

living in urban areas.

• To obtain additional valuable information, a joint analysis of

dietary diversity and HBS (food insecurity, poverty rate, food

availability) is recommended

� In order to obtain national representative nutritional data for

decision making it is recommended to undertake a nationwide

implementation of the dietary diversity integrated into the HBS:

• covering different seasons;

• different geographic regions and;

• different socio-economic groups.

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….Other possible associations

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RegionMDD-W HHIEq Rural area Poverty rate†

Food insecurity

Food availability

Median Median n (%) %

Sughd 7.00 898 39 23.1

?Dushanbe 7.35 850 0 19.9

RRS 6.47 756 80 37.8

GBAO 5.91 526 74 37.3

� A joint statistical analysis of MDD-W and HBS data provides valuable

information on how the dietary diversity of women is affected by:

• household food insecurity;

• food availability;

• poverty rate (see example below)

† Poverty rate, AoS 2015

Women of higher income and living in urban areas of lower poverty

rate showed to have a higher dietary diversity

Key Success Factors

� Political commitment on nutrition progress – lacking nutrition

indicator.

� Integration of nutrition indicators into National sustainable

development strategy 2016-2030 – Goal 3- food security and

improvement of access of population to quality of food.

� Country ownership of the MDD-W indicator:

• Integration of MDD-W indicator as one of the modules into

the ongoing national initiative (HBS)

• Adapted for use throughout the country

• Institutional & human capacity are developed for data

collection, analysis, M&E and reporting.

� Relatively low cost survey compare to classic methodologies,

easy to integrate to existing HH survey modules

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Opportunities Challenges

� Existing and ongoing

nationwide HH survey (HBS)

� Existing capacity of field staff

on data collection

� Integration of MDD-W into any

national or sectoral policies and

actions on food security and

nutrition surveys….

� Resource mobilisation for data

collection and refresher training

for staff

� Limited Financial capacity of

stakeholders on motivation

of field staff at grassroots

levels

� To many other priorities of

the country

� MDD-W – a proxy indicator,

does not provide

quantitative measurement

of dietary intake

Policy and Programming Implications

� Regular data collection will allow identification of regions and

population groups at high risk of malnutrition;

� Policymakers can use this information to track nutrition progress,

target setting and advocacy

� Accelerate education programme at rural areas specifically

targeted for women to broaden their understanding of the

nutritional health benefits of a diverse diet;

� Promotion of home gardens;

� Strengthen linkages between AOS and other key stakeholders

(MoH, MoA, MoEd);

� Strategic policy targeting, research and investment can play a

significant role towards improving rural household dietary

diversity and household food security

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Policy and Programming Implications

�Based on results of MDD-W MHSP has initiated

revision of existing nutrition training guidelines

and curriculums;

�MDD-W module will be integrated into

forthcoming nutrition survey ( in 2016);

�MDD-W Indicators also included as a key

indicator under Goal # 3 of Country

Development Strategy 2016-2030

Plans to follow-up/scale up (1)

� National Integration from 2016 onwards, ensuring

sustainability of project

� Use of data set for monitoring of nutrition status of

women

� Conduct MDD-W survey in different seasons of the

year

� Publish results of MDD-W Survey on quarterly-based

Food Security bulletin of the AoS

� Widely disseminate results of MDD-W among key

stakeholders- MOHSP, Institute of Nutrition, MoAgr

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Plans to follow-up/scale up (2)

� Approximate implementation cost of MDD-W

will be following (2 times per year, in USD):

• Support human resources - $ 7950

• Transportation expenses – $ 3800

• Admin and operation cost of MDD-W ( data

analysis, M&E, data quality control– $ 3600

TOTAL cost per year: ~$ 15350

Acknowledgements

Tajikistan team would like to thank:

� EU-FAO project “Improve Global Governance for Hunger Reduction’’ and “Support thestrengthening of the National Food Security Information System in Tajikistan” forfinancial support of project

� FAO-ESNA Team for technical support: Warren Lee, Claudia Lazarte, TheodoraMouratidou, Saba Marzara and Giorgia Nicolo

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