Household Consumption and Expenditure Surveys: A Tool for

Estimating Food and Nutrient Intake

Celeste Sununtnasuk International Food Policy Research Institute (IFPRI)

USAID SPRING Project

Smarter Futures Cost and Economic Benefit Training Workshop

Dar es Salaam, Tanzania

10-14 December 2013

2

A Tool for Better Understanding...

1. Diet and dietary patterns

2. Key food sources of essential micronutrients

3. Regional variations in diet

4. Seasonal variations in diet & food security

5. Designing fortification programs & estimating their impacts

6. Food markets

7. Harmonizing portfolios of nutrition programs

Cost, Frequency and Availability

• Already being conducted, paid for and processed – Cost of a nutrition analytic file based on typical 24HR

survey (8,500 HHs): $2.3 million

– Cost of a nutrition analytic file from already processed

HCES data: $40,000

– HCES costs are about 2% the cost of a 24HR survey

(Source: Fiedler, Martin-Prevel & Moursi, 2011)

• HCES are routinely, periodically updated (generally once every 3-5 years)

Understanding the Diet

Why is this so important?

• We need a good understanding of an

individual’s

– Overall nutrient intake

– Key sources of micronutrients

– Bioavailability of nutrients

to establish safe fortificant levels with the

appropriate fortification vehicles

Ex: Sources of Energy in Uganda

1078

391

91 44 35 31 65176

81 8519

139

Dietary Diversity: Sources of Energy by Food Groups Uganda

Average dietary energy consumption (kcal/person/day)Average dietary energy consumption (kcal/person/day) by food group

Fortificant Levels

• Where to get them? Bureau of standards and regulations

• What do we assume about their levels?

– Are they at the plant?

– At retail?

– At the household taking into account how foods

are prepared and consumed?

• Losses

• Bioavailability

• Current population intake

Calculating Individual Consumption and Nutrient Intake

• HCES provide consumption data at the

household level

• How do you calculate individual

consumption and nutrient intake?

– Calculate total household consumption of each

food item

– Match food items with items listed in country-

specific Food Composition Tables (FCTs)

– Apply Adult Male Equivalents (AMEs) concept

Food Composition Tables (FCTs)

• Provide the nutrient

content per 100g of edible food

• How precise are

they?

• How unambiguously can they be

matched to the HCES food item list?

UNPS: Consumption Module

56 Food Items

HarvestPlus FCT Nutrient Content per 100g of Edible Food

>700 Food Items

Calculating Adult Male Equivalents

• The Adult Male Equivalent (AME)

– An expression of household food intake that

accounts for the composition of the household

and allows the direct comparison of food or

energy intakes of households of different sizes

and compositions

• Individual AMEs are divided by total household AMEs, to estimate the intrahousehold distribution of food

Adult Male Equivalents (AMEs) ADULT MALE EQUIVALENT

MALE AGE (y) FEMALE

0.216721311 0 -1 0.216721311

0.311475410 1 -2 0.278688525

0.368852459 2 -3 0.344262295

0.409836066 3 -4 0.377049180

0.442622951 4 -5 0.409836066

0.483606557 5 -6 0.434426230

0.516393443 6 -7 0.467213115

0.557377049 7 -8 0.508196721

0.598360656 8 -9 0.557377049

0.647540984 9 -10 0.606557377

0.704918033 10 -11 0.655737705

0.770491803 11 -12 0.704918033

0.836065574 12 -13 0.745901639

0.909836066 13 -14 0.778688525

0.983606557 14 -15 0.803278689

1.040983607 15 -16 0.819672131

1.090163934 16 -17 0.819672131

1.114754098 17 -18 0.819672131

1 18 -30 0.786885246

0.967213115 30 -60 0.770491803

0.803278689 60 -150 0.688524590

Adult males, age 18-30 y, are the benchmark for comparison

Ex: Rice Consumption, AMEs

SEX AGE (y) AME HH AME IND AME Female 60 0.68852 3.61475 0.19048 Female 30 0.77049 3.61475 0.21315 Female 11 0.70492 3.61475 0.19501 Male 40 0.96721 3.61475 0.26757 Male 5 0.48361 3.61475 0.13379

Total Household consumption of rice: 1,571.43 g

Individual consumption (not using AMEs):

1,571.43 g ÷ HH size =

Individual consumption (using AMEs):

1,571.43 g x Individual AME =

314.26 g per person

Female, 60: 299.32 g Female, 30: 334.95 g Female, 11: 306.45 g Male, 40: 420.47 g Male, 5: 210.24 g

Calculating Nutrient Adequacies

• How do we determine whether or not

someone is deficient in a specific

nutrient? – If nutrient intake is below the corresponding Estimated

Average Requirement (EAR)

– Probability approach for iron

• How do we determine if nutrient intake

is excessive? – If intake exceeds the Tolerable Upper Level Intake (UL) for

the age and sex of the individual

Estimated Average Requirements (EARs)

ESTIMATED AVERAGE REQUIREMENT

AGE GENDER STATUS IRON (mg/d) VITAMIN A (µg/d) ZINC (mg/d) FOLATE (µg/d)

1 0-6 mos. Both .27 (AI) 400 (AI) 2 (AI) 65 (AI)

2 6-12 mos. Both 6.9 500 (AI) 2.5 80 (AI)

3 1-3 y Both 3 210 2.5 120

4 4-8 y Both 4.1 275 4 160

5 9-13 y Male 5.9 445 7 250

6 9-13 y Female 5.7 420 7 250

7 14-18 y Male 7.7 630 8.5 330

8 14-18 y Female NPNL 7.9 485 7.3 330

9 14-18 y Female P 23.0 530 10.5 520

10 19-30 y Male 6.0 625 9.4 320

11 19-30 y Female NPNL 8.1 500 6.8 320

12 19-30 y Female P 22.0 550 9.5 520

13 31-50 y Male 6.0 625 9.4 320

14 31-50 y Female NPNL 8.1 500 6.8 320

15 31-50 y Female P 22.0 550 9.5 520

16 51-70 y Male 6.0 625 9.4 320

17 51-70 y Female 5.0 500 6.8 320

18 >70 y Male 6.0 625 9.4 320

19 >70 y Female 7.0 500 6.8 320

NPNL= Non-pregnant, Non-lactating P = Pregnant AI = Average Intake

Tolerable Upper Intake Level (UL) TOLERABLE UPPER INTAKE LEVEL

AGE GENDER STATUS IRON (mg/d) VITAMIN A (µg/d) ZINC (mg/d) FOLIC ACID (µg/d)

1 0-6 mos. Both 40 600 4 ND

2 6-12 mos. Both 40 600 5 ND

3 1-3 y Both 40 600 7 300

4 4-8 y Both 40 900 12 400

5 9-13 y Male 40 1,700 23 600

6 9-13 y Female 40 1,700 23 600

7 14-18 y Male 45 2,800 34 800

8 14-18 y Female NPNL 45 2,800 34 800

9 14-18 y Female P 45 2,800 34 800

10 19-30 y Male 45 3,000 40 1,000

11 19-30 y Female NPNL 45 3,000 40 1,000

12 19-30 y Female P 45 3,000 40 1,000

13 31-50 y Male 45 3,000 40 1,000

14 31-50 y Female NPNL 45 3,000 40 1,000

15 31-50 y Female P 45 3,000 40 1,000

16 51-70 y Male 45 3,000 40 1,000

17 51-70 y Female 45 3,000 40 1,000

18 >70 y Male 45 3,000 40 1,000

19 >70 y Female 45 3,000 40 1,000

NPNL= Non-pregnant, Non-lactating P = Pregnant

Dietary Reference Intakes

WHO Nutrient Recommendations

Footnotes

1.These estimated levels consider only wheat flour as the main

fortification vehicle in a public health program. If other mass-

fortification programs with other food vehicles are implemented

effectively, these suggested fortification levels may need to be

adjusted downwards as needed.

2.Estimated per capita consumption of <75 g/day does not allow for

addition of sufficient level of fortificant to cover micronutrients

needs for women of childbearing age. Fortification of additional

food vehicles and other interventions should be considered.

3.NR = Not Recommended because very high levels of electrolytic

iron needed could negatively affect sensory properties of fortified

flour.

4.These amounts of zinc fortification assume 5 mg zinc intake and no

additional phytate intake from other dietary sources.

Ex: 2008 UFCS

• 24-hour recall conducted in three regions of Uganda to determine

– Food intake and nutrient inadequacies

– Adequacy of mass fortification

• Sample

– Children, 24-59 months

– Women, 15-49 years

– Central (Kampala), and rural Western and Northern regions

• After calculating dietary intakes and accounting for existing interventions

– The WHO recommended fortificant levels for folic acid and

vitamin A for populations consuming <75 g of flour would be

unnecessarily high and even excessive for WRA and children

Source: Kyamuhangire, William, Lubowa, Abdelrahman, Kaaya, Archileo, Kikafunda, Joyce, Harvey, Philip W. J., Rambeloson, Zo, Dary, Omar, Dror, Daphna K., and Lindsay H. Allen. 2013. “The importance of using food and nutrient intake data to identify appropriate vehicles and estimate potential benefits of food fortification in Uganda.” Food and Nutrition Bulletin, 34(2): 131-142.

Ex: 2010/2011 Cameroon

• Combined FFQ and 24-hour recall conducted in Cameroon to

asses potential fortification vehicles (vegetable oil, wheat

flour, sugar, and bouillon cube)

• Sample

– Children, 12-59 months

– Women, 15-49 years

– 3 ecological zones (north, south, large cities)

• Consumption of fortifiable foods varied by ecological

zone and socioeconomic status

– Lower SES groups were less likely to consume fortifiable foods and

consumed less amounts

• Micronutrient inadequacy greatest in the north, lower SES

groups, and children

Source: Engle-Stone, Reins, Ndjebayi, Alex O., Nankap, Martin, and Kenneth H. Brown. 2012. “Consumption of potentially fortifiable foods by women and young children varies by ecological zone and socio-economic status in Cameroon.” The Journal of Nutrition, 142(3): 555-565.

Ex: Cameroon

0

10

20

30

40

50

60

70

80

90

100

National South North Large Cities

Vegetable Oil Wheat Flour Sugar Bouillon Cube

0

10

20

30

40

50

60

70

80

90

100

National South North Large Cities

Vegetable Oil Wheat Flour Sugar Bouillon Cube

Women Children

Amount of fortifiable foods consumed in the previous day (g/d) **bouillon cubes in tenths of g/d

Ex: Cameroon

• Before coverage data was available, a preliminary

decision was made to fortify vitamin A

• But coverage turned out to be relatively low….

Proportion of Cameroonian women consuming fortifiable foods at least once in previous week

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

National South North Large Cities

Vegetable Oil Wheat Flour Sugar Bouillon Cube

9

5

12

10 8 7 7

11

7 6

7 7

14 14 14 13

**Food Frequencies listed above (number of times consumed in previous week)

ADePT

• Automated DEC’s Poverty Tables

• Developed in collaboration between the FAO statistics division and World Bank

• Food Security module can produce indicators from consumption data collected in household surveys

– Consumption of calories and micronutrients

– Availability of micronutrients and amino acids

– Distribution of calories

– Proportion of people undernourished

Food Security Module

Levels of Data

• Household − Size − Region − Area

• Individual − Age − Gender − Height − Relationship to HH head

• Food − Item code − Unit of quantity − Monetary value

• Country − FCT − Vitamins, minerals, etc.

Improving HCES

• To date, HCES have been overwhelmingly

used only as a source of data for secondary data

• How much could HCES be strengthened to

collect more relevant and precise data for food and nutrition analysis?

Shared Agenda for Improvements

• Standardizing units of measure

• Better capturing food away from home

• Improving the food item list

• Optimizing the recall period

• Distinguishing consumption and acquisition

• Collecting more information about individual consumption

Thank you

Questions?

Celeste Sununtnasuk

International Food Policy Research Institute (IFPRI)

C.Sununtnasuk@cgiar.org