Presented by Kristi Mahrt, Derek Headey, and Ian Masias, all with the International Food Policy Research Institute, on April 4, 2023.

1. Photo Credit Goes Here
Photo credit: Aleksandar Todorovic/Shutterstock
April 4, 2023
9:00 AM – 10:00 AM MMT
MAPSA Learning Series
Dietary Quality and Nutrition in Myanmar: Past progress,
current and future challenges
SPEAKER
Kristi Mahrt
Senior Research Analyst,
International Food Policy Research Institute
PANELIST
Dr. Derek Headey
Senior Research Fellow,
International Food Policy Research Institute
MODERATOR
Ian Masias
Senior Program Manager,
International Food Policy Research Institute

2. INTRODUCTION
• Prior to COVID-19, Myanmar was experiencing a dietary transition driven by rapid economic
growth, falling poverty, and urbanization
• The impacts of COVID-19 and political shocks led to economic contraction: 18% contraction in
GDP in 2021; 13% decline between 2019 and 2022.
• In 2022, food prices rose by 50%.
- Bennett’s law : as incomes fall food composition shifts toward diets heavier in starchy
staples and away from diverse diets comprised of relatively more expensive foods
- Evidence from MAPSA phone surveys of declining dietary diversity and reduced food
expenditure as a coping mechanism
• Phone surveys are useful for rapid monitoring and when in person surveys are not possible.
Difficult to collect food consumption data by phone. Limits assessment of diet quality.
• To guide our understanding of current dietary shortfalls we turn to quantified data from 2015
and present two new indices of multidimensional dietary and nutrient intake deprivations.

3. GOALS OF THIS LEARNING SESSION
1. Review the types of food consumption indicators that can be calculated
from household survey data
2. Define measures dietary and nutrient deprivation relative to dietary
guidelines and required nutrient intake
3. Introduce multidimensional diet and nutrient indices for understanding
dietary shortfalls
4. Present simulation of change in dietary gaps after COVID-19 and political
shocks and explore the potential for social protection to close these gaps
“You have to know the past to understand the present.”
-Carl Sagan

4. FOOD CONSUMPTION DATA IN HOUSEHOLD SURVEYS
• Myanmar Poverty and Living Conditions Survey (MPLCS) 2015
- Most recent publicly available survey with food quantities
- Representative of the nation, agroecological zones, urban/rural areas
• Quantities of food consumed by the entire household in the past 7 days.
- Includes purchased foods, home-produced foods, and foods received in-kind
- Household level data – not individual
• Expenditures & quantities for food purchased in the past 30 days –
- used to calculate prices
• Food lists designed to capture most common types of foods
- 184 foods
- Does not include many processed foods
• Expenditure on food away from home (restaurants, teas shops, street vendors, etc.)
- No quantities & broad aggregate categories, e.g. breakfast, drinks
 Food away from home cannot be used in most diet quality indicators

5. HOW CAN SURVEY DATA BE USED TO MEASURE DIETARY QUALITY?
• Limitations
- Purpose is to measure value of food consumed – not to assess dietary quality
- 7-day recall for entire households and excludes food away from home.
- No measurement of intrahousehold distribution of food!
• Simple food group counts – similar to dietary diversity scores
- household rather than individual level data
- 7-day rather than 24-hour recall
- Does not account for quantities. No sense of under- or over-consumption
• Analysis of quantified data: expenditure, calories, nutrients
- in total, by food, or food categories
- Expenditure (price x quantity) analysis requires price calculations
- Calorie or nutrient analysis requires pairing with a food composition table
- Can be compared to dietary guidelines/recommendations
We focus on food group quantities and nutrient intakes compared to dietary guidelines

6. HEALTHY DIET GUIDELINES
Starchy
staples
Pulses
Animal
Source Foods
Vegetables Fruits Fats/Oils
330g 45g 142g 450g 200g 30g
Bangladesh food-based dietary guidelines
adapted for Myanmar
 Allow calcium-rich small fish to substitute
for dairy
 Specified for a moderately active adult
woman : 2,195 calories per day
Meat/fish/eggs combined with
dairy into a single food group
animal source foods (ASFs)

7. HOUSEHOLD FOOD CONSUMPTION
• Healthy diet food group recommendations are specified for an adult woman per day
• Convert total household food consumption in grams to daily consumption in grams per
adult woman equivalents (AE)
Daily food consumption (g) = total household consumption (g) /7 days/number of AEs
Adult equivalency = age-sex group’s calorie needs / 2,195 calories
sex age calorie needs Adult Equivalency
Female 1 835 0.38
Male 5 1,459 0.66
Female 14 2,282 1.04
Male 40 2,669 1.22
Female 40 2,195 1.00
Number of adult equivalents 4.30
Number of household members 5

8. • We evaluate the household’s nutrient intake compared to nutrient requirements for 15
nutrients.
• Estimated Average Requirements (EAR) – benchmark nutrient intake level
A nutrient’s EAR is an estimate of the daily nutrient intake that satisfies the needs of
half the healthy individuals in a specified population by age and sex
NUTRIENT REQUIREMENTS
Protein
Calcium
Iron
Copper
Folate
Niacin
Magnesium
Phosphorous
Riboflavin
Thiamin
Vitamin A
Vitamin C
Vitamin B6
Vitamin B12
Zinc

9. HOUSEHOLD NUTRIENT INTAKE
• Nutrient requirements by age-sex don’t correspond well to calorie requirements
• Adult equivalencies are not useful for estimating nutrient adequacy
• For each household and nutrient, calculate household specific EARs
Household EAR for each nutrient is the sum of the age-sex specific EAR of all members
Daily EAR
sex age Calcium (mg) vitamin A (RAE)
Female 1 390 205
Male 5 680 245
Female 14 960 480
Male 40 750 570
Female 40 750 490
Household EAR 3,530 1,990

10. NUTRIENT DEPRIVATION INDICATORS – DEFINED FOR EACH NUTRIENT
% of population with a nutrient deprivation. A household has a deprivation if:
daily total household intake the nutrient < household EAR
nutrient consumption gap in deprived households:
ℎ𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝐸𝐸𝐴𝐴𝐴𝐴 − 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 ℎ𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖
ℎ𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝐸𝐸𝐴𝐴𝐴𝐴
FOOD GROUP DEPRIVATION INDICATORS – DEFINED FOR EACH FOOD GROUP
% of population with a food group deprivation. A household has a deprivation if:
daily consumption (g) per AE of a food group < ℎ𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞(g)
food group consumption gap in deprived households:
ℎ𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞 − ℎ𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔 𝑝𝑝𝑝𝑝𝑝𝑝 𝐴𝐴𝐴𝐴
ℎ𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞𝑞

11. 0%
20%
40%
60%
80%
100%
HEALTHY DIET FOOD GROUP DEPRIVATIONS BY INCOME QUINTILE
Poor households have bigger shortfalls in nutrient dense food groups compared to richer households
% deprived
0%
20%
40%
60%
80%
100%
Starchy
staples
Pulses ASFs Veg. Fruits Fats
% consumption gap
% of the population deprived in
each food group and
consumption gaps decrease as
income quintiles increase
Exception – Staples
• Poor households consume
staple heavy diet – cheap
calories
• Missing food consumed
away from home –
consumption increases with
income.
• Likely undercounting
processed foods
• May also impact added fats.

12. 0%
20%
40%
60%
80%
100%
0%
20%
40%
60%
80%
100%
A lot of useful
information ...
... but what if you want
to have a sense of
overall diet quality?
do not improve with with increased income
% deprived
% consumption gap
NUTRIENT DEPRIVATIONS BY INCOME QUINTILE
Poor households are more likely to under-consume nutrients compared to richer households
% of population who are
deprived in nutrients
decreases as income
quintiles increase
Consumption gaps
decrease with income
quintiles for only half the
nutrients

13. MULTIDIMENSIONAL INDICES
Multidimensional poverty index (MPI): Alkire and Foster (2012) developed an index to
combine deprivations in many indicators/dimensions into a single indicator
People living in households that are deprived in at least 1/3 of the weighted dimensions
are MPI poor.
Two components:
- Incidence: share of the population
who are multidimensional poor
Intensity: average proportion of
weighted indicators in which poor
people are deprived
MPI = Intensity x Incidence

14. HEALTHY DIET DEPRIVATION INDEX
• Pauw et al. (2021): Reference Diet Deprivation Index (ReDD) – dimensions = food groups
• We follow ReDD using Bangladesh diet guidelines – Healthy Diet Deprivation Index
All food groups are essential to good health
- Food groups weighted equally
- Deprived if household falls short in ANY food group
Food group consumption is a quantitative variables
- Can measure food group % consumption gaps
- Incorporates, incidence, intensity AND depth of deprivations
Starchy
staples
Pulses
Animal Source
Foods
Vegetables Fruits Fats
330g 45g 142g 450g 200g 30g
1/6 1/6 1/6 1/6 1/6 1/6
6 dimensions

15. HEALTHY DIET DEPRIVATION INDEX
share of the population
who are healthy diet
deprived
Incidence
average proportion
of food groups with
deprivations among
the healthy diet
deprived
Intensity Depth
People living in households that consume less than the recommended quantity
of ANY food group are considered healthy diet deprived
Healthy Diet Deprivation Index = Incidence x Intensity x Depth
Higher index values
are associated with
lower dietary quality
average consumption
gap in deprived food
groups among the
healthy diet deprived

16. HOUSEHOLD
EXAMPLE
Healthy
Diet (g)
Household
consumption
per AE (g) Deficiency Gap
Staples 360 548 no
Pulses 45 25 yes 0.44
Animal Source Foods 142 161 no
Vegetables 450 288 yes 0.64
Fruits 200 142 yes 0.72
Oils 30 7.2 yes 0.23
Incidence Does household have any deficiencies? Yes 1
Intensity Average number of defficienies 4/6 0.67
Depth Average gap in deprived food groups (.44 + .64 +.72 +.23)/4 0.51
Index Incidence x intensity x depth 1 x .67 x .51 0.34
𝑔𝑔𝑔𝑔𝑔𝑔 =
ℎ𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔−ℎ𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔 𝑝𝑝𝑝𝑝𝑝𝑝 𝐴𝐴𝐴𝐴
ℎ𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔

17. NUTRIENT INTAKE DEPRIVATION INDEX
People living in households that consume less than the household EAR of ANY
nutrient are considered nutrient intake deprived
Nutrient Intake Deprivation Index = Incidence x Intensity x Depth
share of the population
who are nutrient intake
deprived
Incidence
average proportion of
nutrients with
deprivations among the
nutrient intake deprived
Intensity Depth
average % difference
between nutrient intake and
the household EAR among
the nutrient intake deprived
Higher index values
are associated with
lower dietary quality
A new multidimensional diet index for understanding nutrient intake shortfalls

18. 98%
59%
39%
23%
98%
63%
37%
23%
99%
57%
40%
22%
0% 20% 40% 60% 80% 100%
Incidence
Intensity
Depth
Index
100%
71%
59%
42%
100%
76%
52%
40%
100%
69%
62%
42%
0% 20% 40% 60% 80% 100%
Incidence
Intensity
Depth
Index
HEALTHY DIET NUTRIENT INTAKE
4.2/6
food groups
8.1/15
nutrients
• Intensity of healthy diet and nutrient intake deprivation is higher in urban areas than rural areas
• Depth of healthy diet and nutrient intake deprivation is higher in rural areas
• Overall, the difference between urban/rural areas for both deprivation indices is very small
DEPRIVATION INDICES: NATIONAL, URBAN, RURAL

19. 58%
39%
22%
55%
37%
20%
63%
38%
24%
61%
42%
25%
58%
41%
24%
0% 20% 40% 60% 80% 100%
Intensity
Depth
Index
68%
56%
38%
69%
60%
41%
76%
54%
41%
75%
62%
47%
71%
67%
47%
0% 20% 40% 60% 80% 100%
Intensity
Depth
Index
4.2/6
8.3/15
4.5/6
food groups
9.5/15
nutrients
• The deprivation indices help clarify varying levels of intensity and depth between agroecological zones.
• The Dry Zone and the Delta rank relatively high while coastal areas and hills/mountains rank relatively low
DEPRIVATION INDICES: AGROECOLOGICAL ZONES
HEALTHY DIET NUTRIENT INTAKE

20. 79%
68%
54%
74%
62%
46%
69%
59%
40%
66%
54%
35%
66%
50%
32%
Intensity
Depth
Index
37%
20%
71%
45%
32%
62%
41%
25%
57%
38%
22%
52%
35%
17%
51%
33%
16%
Intensity
Depth
Index
37%
4.7/6
food groups
4.0/6
food groups
10.7/15
nutrients
7.7/15
nutrients
40%
Q5 66% higher than Q1 Q5 100% higher than Q1
DIET DEPRIVATION INDICES: INCOME QUINTILES
HEALTHY DIET NUTRIENT INTAKE
• Differences between Q5 & Q1 deprivations are greater for nutrients intakes compared to food groups.
• The healthy diet deprivation index is 33% among Q5 households  Income constraints are not the only
factors limiting diet quality.

21. HOW MUCH CAN THE HEALTHY DIET DEPRIVATION
INDEX BE ATTRIBUTED TO EACH FOOD GROUP?
3%
4%
8%
22%
22%
24%
26%
27%
16%
14%
12%
10%
7%
23%
24%
25%
26%
27%
27%
30%
31%
30%
26%
11%
7%
6%
5%
5%
Q1
Q2
Q3
Q4
Q5
• Fruits, vegetables, and pulses are the largest contributors to the healthy diet deprivation index.
• Among protein-rich foods, animal source foods are relatively larger contributors in lower
quintiles while pulses are relatively larger contributors in higher quintiles.
RELATIVE CONTRIBUTIONS
(sums to 100)
3%
12%
10%
10%
9%
9%
8%
7%
5%
4%
2%
12%
11%
10%
9%
9%
15%
14%
12%
11%
8%
6%
3%
54%
46%
40%
35%
32%
Q1
Q2
Q3
Q4
Q5
ABSOLUTE CONTRIBUTIONS
(sums to index value)

22. SIMULATING IMPACTS OF COVID-19 + POLITICAL SHOCKS
• How can diet quality indicators be used for forward-looking analysis?
• What impacts have economic shocks had on diet quality in Myanmar?
• Pauw and co-authors use the ReDD index in economywide modeling to estimate
changes in household diet quality under different simulation scenarios.
• No similar analysis using the deprivation indices yet for Myanmar
• Ecker and co-authors use the relationships between income & food consumption
(income elasticities) to simulate impacts of income losses on food group consumption
changes
• Can also experiment with positive income changes through social protection scenarios

23. SIMULATING IMPACTS OF COVID-19 + POLITICAL SHOCKS
• The Ecker analysis uses data from the 2015 MPLCS and involves the following steps.
• Shock each household’s income sources with sector specific shocks designed to simulate a
short-term contraction in the Myanmar economy in the months following the onset of
political instability and coinciding with the delta wave of COVID-19.
- Overall, household income declines 32%
- Poverty increases from 32% to 61%
• Estimate the impact of reduced income on food group consumption and nutrient intake.
• Give transfers of 25,000 MMK (2020 ) /month household / to the poorest 40% of the
population and re-estimate the impact on food group consumption and nutrient intake.
- 3 types of transfers:
1. cash transfer
2. in-kind transfer of a common rice variety
3. In-kind transfer of fortified rice

24. FOOD GROUP GAPS FOR POOREST 40%, BY SCENARIO
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Starchy staples Vegetables Fruits Protein foods
17 % points
4 % points
4 % points
5 % points
Vegetable consumption
gap rose by 17 % points
after the simulated shock
Transfers have limited
impact on consumption
- Transfer not given to
all newly poor
households
- Transfer relatively
small
- Some of the transfer
spent on non-food
- Transfer spent on
food spread across
multiple food groups

25. NUTRIENT GAPS FOR POOREST 40%, BY SCENARIO
0%
10%
20%
30%
40%
50%
60%
70%
Calories Calcium Iron Vitamin A Folate
7 % points
8 % points 10 % points
9 % points
11 % points
-39
-49
-63
Red
arrows
highlight
% point
change
from
shocked
gap
• Cash transfers and in-
kind transfers of
common rice varieties
also have limited impact
on nutrient gaps.
• In-kind transfers of
fortified rice have
considerable impacts on
iron, vitamin A and folate
shortfalls
• Folate gaps among
fortified rice recipients
nearly eliminated.

26. CONCLUSIONS
• Household survey data is not ideal for nutritional analysis but provides nationally
representative quantified data not often available from other sources.
• New diet deprivation indices can be used for richer analyses and simulations
• Diet quality in Myanmar is poor, with large gaps for nutrient-dense foods
• Diet quality is strongly negatively correlated with household income – both the
share of the population facing diet deprivations and the extent of the gaps
• Suggests that recent declines in household income and increases in food prices in
Myanmar are likely resulting in declining diet quality
• Improving diet quality is challenging, and requires a combination of sustained
income growth, and also behavioral changes around food
• Social protection generally has limited impacts, but rice fortification can help
address a range of micronutrient deficiencies, potentially very effectively.

27. ေကျးဇူးတင်ပါတယ်
Thank you

28. www.feedthefuture.gov