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Food consumption analysis Food consumption analysis Food Security Indicators Training Bangkok 12-17 January 2009

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Food consumption analysis. Food Security Indicators Training Bangkok 12-17 January 2009. Objectives. To describe the analysis of food consumption To describe the analysis on food sources To discuss experiences/problems related with the analysis of food consumption. Steps. - PowerPoint PPT Presentation

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Page 1: Food consumption analysis

Food consumption analysisFood consumption analysis

Food Security Indicators Training

Bangkok 12-17 January 2009

Page 2: Food consumption analysis

Objectives

• To describe the analysis of food consumption

• To describe the analysis on food sources • To discuss experiences/problems related

with the analysis of food consumption

Page 3: Food consumption analysis

Steps

1. Explore the module of food consumption2. Calculate the FCS3. Graph the result 4. Create the Food consumption score

groups5. Validate the FCS with other indicators6. Analyze the sources of food

Page 4: Food consumption analysis

Definitions

Dietary Dietary diversitydiversity

The number of individual foods or food groups consumed over a reference period

Food frequency Food frequency Number of days (in the past week) that a specific food item has been consumed by a household

Household Household Food Food ConsumptionConsumption

The consumption patterns (frequency * diversity) of households over the last seven days

Page 5: Food consumption analysis

Food consumption module

Page 6: Food consumption analysis

FC module info

Information: Weekly frequency of foods and food groups Sources of foods Numbers of meals

Indicators: → FCS – dietary diversity → Food and Food group frequency (0-7)→ Average number of meals (children/adults)→ Sources of food

Page 7: Food consumption analysis

Food consumption score - FCS

The Food Consumption Score is a composite score based on dietary diversity, food frequency and relative nutrition importance of different food groups.The FCS can be considered as a proxy of food access and food security.

Page 8: Food consumption analysis

Data collection

• The data have to be collected according to usual food items consumed that are specific to the country’s context.

• Food items are grouped into food groups that are standard.

• The difference between foods and condiments must be captured during the data collection.

Page 9: Food consumption analysis

Calculation steps

1. Using standard 7-day food frequency data, group all the food items into specific food groups.

2. Sum all the consumption frequencies of food items of the same group, and recode the value of each group above 7 as 7.

3. Multiply the value obtained for each food group by its weight and create new weighted food group scores.

Page 10: Food consumption analysis

Calculation steps

4. Sum the weighed food group scores, thus creating the food consumption score (FCS).

5. Using the appropriate thresholds, recode the variable food consumption score, from a continuous variable to a categorical variable.

Page 11: Food consumption analysis

FCS

FCS = astaplexstaple+ apulsexpulse+ avegxveg+ afruitxfruit

+ aanimalxanimal+ asugarxsugar + adairyxdairy+ aoilxoil

Where, FCS Food consumption score

xi Frequencies of food consumption = number of days for which each food group was consumed during the past 7 days

(7 days was designated as the maximum value of the sum of the frequencies of the

different food items belonging to the same food group)

ai Weight of each food group

Page 12: Food consumption analysis

Food groups and weights

  FOOD ITEMSFOOD ITEMS Food groupsFood groups Weight Weight

1Maize , maize porridge, rice, sorghum, millet pasta, bread and other cereals Cereals and

Tubers2

2 Cassava, potatoes and sweet potatoes

3 Beans. Peas, groundnuts and cashew nuts Pulses 3

4 Vegetables and leaves Vegetables 1

5 Fruits Fruit 1

6 Beef, goat, poultry, pork, eggs and fish Meat and fish 4

7 Milk yogurt and other diary Milk 4

8 Sugar and sugar products Sugar 0.5

9 Oils, fats and butter Oil 0.5

10 Condiments Condiments 0

Page 13: Food consumption analysis

Weights

Food groups Weight J ustification

Main staples 2 Energy dense, protein content lower and poorer quality (PER less) than legumes, micro-nutrients

(bound by phytates).

Pulses 3 Energy dense, high amounts of protein but of lower quality (PER less) than meats, micro-nutrients (inhibited by phytates), low fat.

Vegetables 1 Low energy, low protein, no fat, micro-nutrients

Fruit 1 Low energy, low protein, no fat, micro-nutrients

Meat and fish 4

Highest quality protein, easily absorbable micro-nutrients (no phytates), energy dense, fat. Even

when consumed in small quantities, improvements to the quality of diet are large.

Milk 4

Highest quality protein, micro-nutrients, vitamin A, energy. However, milk could be consumed only in very small amounts and should then be

treated as condiment and therefore re-classification in such cases is needed.

Sugar 0.5 Empty calories. Usually consumed in small

quantities.

Oil 0.5 Energy dense but usually no other micro-

nutrients. Usually consumed in small quantities

Page 14: Food consumption analysis

Graph

This graph aids in the interpretation and description of both dietary habits and in determining cut-offs for food consumption groups (FCGs).

Laos FCS

-

7

14

21

28

35

42

49

15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90

FCS

Cum

ula

tive C

onsum

pti

on

Fre

quency

Staple Vegetables Anim protein Oil

Sugar Fruit Pulses Milk

Page 15: Food consumption analysis

How to create the graph

1. Truncate the FCS variable 2. Run a frequency of the FCS3. Run a compare mean of the FCS and all the

food groups included in the FCS4. Export frequency and compare mean in excel5. Calculate an average of the surrounding

values for each food group (to smooth the graph).

6. Use the ‘area’ graph in excel

Page 16: Food consumption analysis

Graph cont’

-

1.00

2.00

3.00

4.00

5.00

6.00

7.00

0 10 20 30 40 50 60 70 80 90 100

Food Consumption Score

Staple Anim protein Pulses Vegetables

Fruit Oil Sugar Milkconsumed (*) (Days/week)

(*) w eighted moving average over 7 point range

This graph shows the consumption frequency of different food groups by FCS independently and not stacked as the previous graph.

Page 17: Food consumption analysis

How to create the graph

1. Use the same steps from the graph above;2. Use the ‘line’ graph in excel.

Page 18: Food consumption analysis

FCS thresholds

Once the FCS is calculated, the thresholds for the FCGs should be determined based on the frequency of the scores and the knowledge of the consumption behaviour in that country/region.

Page 19: Food consumption analysis

The typical thresholds are:

Threshold Profiles Thresholds with oil and sugar eaten on a daily basis (~7 days per week)

0 – 21Poor food

consumption 0-28

21.5 - 35 Borderline food consumption

28.5 - 42

>35.5Acceptable food

consumption>42.5

Page 20: Food consumption analysis

Why 21 and 35?

A score of 21 was set as barely minimum, scoring below 21, a household is expected NOT to eat at least staple and vegetables on a daily base and therefore considered to have poor food consumption. Between 21 and 35, households are assessed having borderline food consumption.

The value 2121 comes from an expected daily consumption ofdaily consumption of staplestaple and vegetables.vegetables.

» (frequency * weight, 7 * 2 = 14)+(7 * 1 = 7).

The value 3535 comes from an expected daily consumption of daily consumption of staple and vegetables complemented bystaple and vegetables complemented by a frequent (4 day/week) consumption of oil and pulses. oil and pulses.

» (staple*weight + vegetables*weight + oil*weight + pulses*weight = 7*2+7*1+4*0.5+4*3=35).

Page 21: Food consumption analysis

……Even though these thresholds are standardized there is always room for adjustments based on evidence……

Page 22: Food consumption analysis

How to adapt the thresholds

1. Consider the basic/minimum food consumption in the country.

Ex. Laos diet is mainly rice and vegetables, but in some country you can have oil and/or sugar consumed daily

2. Based on the data information and the knowledge of the country try to define the thresholds for poor and borderline consumption.

3. The thresholds should be changed based on evidence and should be remain the same if you want to compare FCS of different surveys.

Page 23: Food consumption analysis

Example

Examples of different thresholds:• Sudan

– Two different thresholds were used north and the south Sudan

• Haiti – 26 & 46 were used because the

consumption of oil and sugar among the poorest consumption were about 5 days per week.

Page 24: Food consumption analysis

!!!! We have to be careful that changes from the standard are very well justified and reported otherwise we can be viewed as changing the threshold ‘ to get the numbers we want’ !!!!

Page 25: Food consumption analysis

Validation of the FCS

• Run verifications of the FCS and FCGs by comparing them to other proxy indicators of food consumption, food access, and food security:

Cash expenditures, % expenditures on food, food sources, CSI, wealth index,number of meals eaten per day, etc.

Page 26: Food consumption analysis

Which is the analysis that we should use to compare 2 continuous variables?

Page 27: Food consumption analysis

Correlations

Correlations with FCS comparing FCS to other food security proxies

Burundi

Pearson Correlation 0.31 kcal/capita/day

Sig. (2-tailed) <0.01

Pearson Correlation -0.27 CSI score

Sig. (2-tailed) <0.01

Pearson Correlation -0.11 % total cash expenditures on food Sig. (2-tailed) <0.01

Pearson Correlation 0.24 asset index

Sig. (2-tailed) <0.01

Pearson Correlation 0.28 total cash monthly expenditures (LOG) Sig. (2-tailed) <0.01

Malawi

Pearson Correlation -0.30 CSI score

Sig. (2-tailed) <0.01

Pearson Correlation 0.40 No. of assets

Sig. (2-tailed) <0.01

Pearson Correlation 0.33 No. of means (adults)

Sig. (2-tailed) <0.01

Pearson Correlation 0.31 Total per cap. Cash exp. (LOG) Sig. (2-tailed) <0.01

Page 28: Food consumption analysis

Proxy for food security

If the FCS captures several elements of food consumption, food access, and food security

(such as in the previous slide’s example) FCS is an adequate proxy for CURRENT

food security

Page 29: Food consumption analysis

Sources of food

We have information about source of single food but we need an indication of sources of all the food items consumed in the households.

This indicator can be used as proxy of food access. ( ex. dependency on market, food assistance or own production)

Page 30: Food consumption analysis

Sources of food

• Transform the single sources (x variables as the food items) into n variables as the different sources of food;– Own production, purchase, food assistance, borrow,

exchange, gathering, social network, etc.• Doing this we will have the percentage of food

consumed coming from different sources– Ex % coming from purchase and % from food aid

etc.• In this computation the sources of food should be

weighted on the frequency of the food items consumed.

Page 31: Food consumption analysis

Steps

1. Copy the food frequency value into new variable called as the different sources.

IF (source_rice =1) ownproduction_rice =consumption_rice. IF (source_rice =2) purchase_rice = consumption_rice. IF (source_rice =3) foodaid_rice = consumption_rice . IF (source_rice =4) gathering_rice = consumption_rice. IF (source_rice =5) borrowrice = consumption_rice . execute.

Do this computation for all the food items and all the sources.

Page 32: Food consumption analysis

Steps

2. Add all the variables of different foods with the same sources together in order to create the unique variable of the specific source

COMPUTE ownproduction = ownproduction_rice + ownproduction_tubers + ownproduction_eggs + ownproduction_vegetable + ownproduction_meat + ownproduction_fruit + ……

3. COMPUTE the total sources of food

totsource = ownproduction + fishing + purchase + traded + borrow + exc_labor + exc_item + gift + food_aid +other.

Page 33: Food consumption analysis

4. Calculate the % of each food source

COMPUTE pownprod = (ownproduction / totsource)*100.COMPUTE pfishing = (fishing / totsource)*100.COMPUTE ppurchase = (purchase / totsource)*100.COMPUTE pborrow = (borrow / totsource)*100.COMPUTE pexclabor = (exc_labor / totsource)*100.COMPUTE pexcitem = (exc_item / totsource)*100.COMPUTE pfoodaid = (food_aid / totsource)*100.COMPUTE pother = (other / totsource)*100.

Page 34: Food consumption analysis

Example

S ourc es of food

3 419

7

25 23 24

2

195

22

95 9072

8961 71

53 9473

9365

11 7 3

125 2 7 1

1222

0

10

20

30

40

5060

70

80

90

100

Urban Urban R ural Urban R ural Urban R ural Urban R ural Urban R ural

P hnomP enh

P lains Tonle S ap P lateau C oas tal Total

% own produc ion % purc has e% fis hing and hunting % traded % borrowed % exc hange of labor for food% exc hange of items for food % gift% food aid % exc hange other

Page 35: Food consumption analysis

Questions?Questions?

Page 36: Food consumption analysis

Some examples

Page 37: Food consumption analysis

0%10%20%30%40%50%60%70%80%90%

100%

1 2 3 4 5

quintiles de indice de richesse

acceptable

limite

pouvre

Page 38: Food consumption analysis

0 7 14 21 28 35 42 49

pauvre

limite

acceptable

gro

up

es

de

con

som

ma

tio

na

lime

tair

e

Maize Rice Other Cereals Casssava, Sweet Pots, Bananas Beans, Peas Vegetables Fruits Meats Fish Eggs Milk/Yoghurt Oils/Fat/Butter Sugar, Honey, Jam

Page 39: Food consumption analysis

Poor and Borderline FCG

8171

81 80 8277

83 8678 80 81 84

7769

7783

91 8981

0%

5%

10%

15%

20%

25%

30%

35%

Dahuk

Ninaw

a

Sulaym

aniyah

Tamee

mErb

il

Diala

Anbar

Baghd

adBab

il

Karbala

Wass

it

Salah

Al Din

Najaf

Qadiss

ia

Mut

hana

Thi –

Qar

Miss

an

Basra

hTot

al

% o

f h

ou

seh

old

s

0102030405060708090100

FC

S

poor borderline Mean

Page 40: Food consumption analysis

Wealth I ndex Quintiles

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

poorconsumption

borderlineconsumption

acceptableconsumption

poorest second third fourth richest

Page 41: Food consumption analysis

% high dependency

mean0.36 mean

0.37 mean0.29

0%

10%

20%

poorconsumption

borderlineconsumption

acceptableconsumption

household with high dependency rate

Page 42: Food consumption analysis

Spearman's rho

food consumption

score

Correlation Coefficient 1

Sig. (2-tailed) .

N 24975

Correlation Coefficient -.111(**)

Sig. (2-tailed) 0

N 8877

Correlation Coefficient .378(**)

Sig. (2-tailed) 0

N 24972

Correlation Coefficient .406(**)

Sig. (2-tailed) 0

N 24971

Correlation Coefficient .343(**)

Sig. (2-tailed) 0

N 24971

Correlation Coefficient .430(**)

Sig. (2-tailed) 0

N 24934

wealth index

per capita total expenditure

per capita non foof expenditure

total_Income

food consumption score

CSI

Page 43: Food consumption analysis

Sources of all foods

3019 16 22 17

8

2821 15

29 24 2821

32 3426 24

17 21

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Dahuk

Ninaw

a

Sulay

man

iyah

Tamee

mErb

il

Diala

Anbar

Baghd

adBab

il

Karba

la

Wass

it

Salah

Al D

inNaj

af

Qad

issia

Mut

hana

Thi – Q

ar

Miss

an

Basra

hTot

al

p_pds p_purchase p_ow nproduction p_family other

Page 44: Food consumption analysis

Sources of PDS food basket

64

4033

4739

16

6252

41

6754

63

48

66 7060 58

49 49

0%

20%

40%

60%

80%

100%

Dahuk

Ninav

a

Sulay

man

iyah

Tamee

mErb

il

Diala

Anbar

Baghd

adBab

il

Karba

la

Wass

it

Salah

Al D

inNaj

af

Qad

issia

Mut

hana

Thi – Q

ar

Miss

an

Basra

hTot

al

ppds_pds ppds_purchase ppds_ownproduction ppds_family OTHER

Page 45: Food consumption analysis

Food sources - rural model

0% 20% 40% 60% 80% 100%

Plateau

Total

Tonle Sap

Coastal

Plains

type of source

% own producion % fishing and hunting

% purchased+traded % other

Page 46: Food consumption analysis

Food sources - urban model

0% 20% 40% 60% 80% 100%

Plateau

Tonle Sap

Plains

Total

Coastal

Phnom Penh

type of source

% own producion % fishing and hunting% purchased+traded % other