Food consumption analysis

Report
Food consumption analysis
5th - 9th December 2011, Rome
Contents

Food consumption score (FCS)




Dietary diversity (DD)




Explore the questionnaire module
Calculate
Create the FC groups
Explore the questionnaire module
Calculate
Validate the indicators
Present the outputs
Definitions
Dietary diversity
The number of individual foods or food
groups consumed over a reference period (7
days, 24 hours)
Food frequency
Number of days (in the past week) that a
specific food item has been consumed by a
household
Household Food
Consumption
The consumption patterns (frequency *
diversity) of households over the last seven
days
The FOOD CONSUMPTION SCORE
(FCS)
Food consumption module
Food consumption module continued
Information:

Weekly frequency of foods and/or food groups

Sources of foods

Numbers of meals
Indicators:
→ FCS
→ DD– dietary diversity
→ Food and Food group frequency (0-7)
→ Average number of meals (children/adults)
→ Sources of food
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.
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.
Calculation steps
1.
2.
3.
4.
5.
Using standard 7-day food frequency data, group all the
food items into specific food groups.
Sum all the consumption frequencies of food items of the
same group, and recode the value of each group above 7
as 7.
Multiply the value obtained for each food group by its
weight and create new weighted food group scores.
Sum the weighed food group scores, thus creating the
food consumption score (FCS).
Using the appropriate thresholds, recode the variable food
consumption score, from a continuous variable to a
categorical variable, to create the food consumption
groups.
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
ai
belonging to the same food group)
Weight of each food group
Food groups and weights
FOOD ITEMS
1
Maize , maize porridge, rice, sorghum, millet pasta,
bread and other cereals
2
Cassava, potatoes and sweet potatoes
3
Beans. Peas, groundnuts and cashew nuts
4
Vegetables and leaves
5
Fruits
6
Beef, goat, poultry, pork, eggs and fish
7
Milk yogurt and other diary
8
Sugar and sugar products
9
Oils, fats and butter
10
Condiments
Food groups
Weight
Cereals and
Tubers
2
Pulses
3
Vegetables
1
Fruit
1
Meat and fish
4
Milk
4
Sugar
0.5
Oil
0.5
Condiments
0


The score as a minimum of 0 and a maximum of 112.
Can be presented as mean or can be recoded into food
consumption groups
FCS thresholds
Once the FCS is calculated, the thresholds for the FC
Groups (FCG) should be determined based on the
frequency of the scores and the knowledge of the
consumption behaviour in that country/region.
The typical thresholds are:
Threshold
Profiles
0 – 21
Poor food
consumption
0-28
21.5 - 35
Borderline food
consumption
28.5 - 42
>35.5
Acceptable food
consumption
>42.5
Thresholds with oil
and sugar eaten on a
daily basis
(~7 days per week)
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 21 comes from an expected daily consumption of staple and
vegetables.
» frequency * weight, (7 * 2 = 14)+(7 * 1 = 7).
The value 35 comes from an expected daily consumption of staple and
vegetables complemented by a frequent (4 day/week) consumption of oil and
pulses.
» (staple*weight + vegetables*weight + oil*weight + pulses*weight =
7*2+7*1+4*0.5+4*3=35).
……Even though these thresholds are standardized there is
always room for adjustments based on evidence……
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.
3.
Based on the data information and the knowledge of
the country try to define the thresholds for poor and
borderline consumption.
The thresholds should be changed based on evidence
and should be remain the same if you want to compare
FCS of different surveys.
Example
Examples of different thresholds:
 Sudan


Two different thresholds were used for North and South Sudan
Haiti

26 & 46 were used because the consumption of oil and sugar
among the poorest consumption were about 5 days per week.
!!!! 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’ !!!!
DIETARY DIVERSITY analysis (DD)
Dietary Diversity definition
The number of individual foods or food
groups consumed over a reference period (7
days, 24 hours).
Dietary Diversity Score
There are different scores on based on:

Level


Recall


Individual (women or children) vs Household score
7 days vs 24 hrs
Different numbers of food groups ( 7 to 16)
Different DD scores
Score
HDDS – household
Groups
16 food groups
FAO
IDDS – women or children
IFPRI
DDS
16 food groups
7 food groups
6+ : high
4.5-6 : medium
<4.5 : low
Calculation steps
1.
2.
3.
Group all the food items into specific food groups if
necessary.
For each food group create a new binominal variable
that has 1 (yes) if the household/ individual consumed
that specific food group or 0 (no) if the food did not
consume that food.
Sum all the food groups variables in order to create
the dd score. The new variable will have 0 as
minimum and as maximum the total number of food
groups collected (7 to 16).
Dietary Diversity Score
DD = ∑ Pi
Where,
DD
dietary diversity score
Pi
1 if the food group was consumed, 0 if it was not
consumed
Validation of the indicators
Validation of the FCS
Run verifications of the FCS, FCGs DD DD groups by
comparing them to other proxy indicators of food
consumption, food access, and food security for example:
Cash expenditures,
 % expenditures on food,
 food sources,
 CSI,
 wealth index,
 number of meals eaten per day, etc.

Correlations
Correlations with FCS comparing FCS to other food security
proxies
Burundi
kcal/capita/day
CSI score
% total cash
expenditures on food
asset index
total cash monthly
expenditures (LOG)
Pearson Correlation
0.31
Sig. (2-tailed)
<0.01
Pearson Correlation
-0.27
Sig. (2-tailed)
<0.01
Pearson Correlation
-0.11
Sig. (2-tailed)
<0.01
Pearson Correlation
0.24
Sig. (2-tailed)
<0.01
Pearson Correlation
0.28
Sig. (2-tailed)
<0.01
Malawi
CSI score
No. of assets
No. of means (adults)
Total per cap. Cash
exp. (LOG)
Pearson Correlation
-0.30
Sig. (2-tailed)
<0.01
Pearson Correlation
0.40
Sig. (2-tailed)
<0.01
Pearson Correlation
0.33
Sig. (2-tailed)
<0.01
Pearson Correlation
0.31
Sig. (2-tailed)
<0.01
We use correlation
when we analyse 2
scale/continuous
variables ex.



FCS with DD
FCS with Kcal
DD with asset index
Compare means
FCS
DD
North
45
6.7
Central
38
5.1
South
27
4.2
Age household
head
Poor FC
36
Borderline FC
45
Good FC
42

We use compare mean
when we analyse a
scale/continuous variable
with a categorical/
nominal one.

ex.
FCS by urban/rural
FCGs by age household
head


PRESENT the RESULTS
Graph
Laos FCS
Staple
Vegetables
Anim protein
Oil
Sugar
Fruit
Pulses
Milk
Cumulative Consumption
Frequency
49
42
35
28
21
14
7
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
FCS

This graph aids in the interpretation and description of both dietary habits
and in determining cut-offs for food consumption groups (FCGs).
Graph continued
Staple
Fruit
consumed (*)
(Days/week)
Anim protein
Oil
Pulses
Sugar
Vegetables
Milk
7.00
6.00
5.00
4.00
3.00
2.00
1.00
0
10
20
30
40
50
60
70
80
90
100
Food Consumption Score
(*) 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.
How to create the graph
1.
2.
3.
4.
5.
6.
Truncate the FCS variable
Run a frequency of the FCS
Run a compare mean of the FCS and all the food groups
included in the FCS
Export frequency and compare mean in excel
Calculate an average of the surrounding values for each
food group (to smooth the graph).
Use the ‘area’ or the ‘line’ graph in excel.
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
acceptable
limite
pouvre
1
2
3
4
quintiles de indice de richesse
5
groupes de
consommation
alimetaire
acceptable
limite
pauvre
0
7
Maize
Other Cereals
Beans, Peas
Fruits
Fish
Milk/Yoghurt
Sugar, Honey, Jam
14
21
28
35
42
Rice
Casssava, Sweet Pots, Bananas
Vegetables
Meats
Eggs
Oils/Fat/Butter
49
D
Su N a hu
la in k
ym a
a n wa
Ta iya
m h
ee
m
Er
b
Di il
a
An la
Ba ba
gh r
da
Ba d
Ka bil
rb
Sa W ala
la a s
h sit
Al
D
in
Na
Q
ad jaf
M issi
ut a
Th han
i– a
M Qar
iss
Ba an
sr
ah
To
ta
l
% of households
35%
30%
25%
81
71
86
84
81 80 82 77 83
78 80 81
77
poor
borderline
77
Mean
83
91 89
81
69
20%
15%
10%
5%
0%
100
90
80
70
60
50
40
30
20
10
0
FCS
Poor and Borderline FCG
Spearman's rho
food consumption
score
Correlation Coefficient
1
Sig. (2-tailed)
.
N
Correlation Coefficient
CSI
Sig. (2-tailed)
N
Correlation Coefficient
wealth index
Sig. (2-tailed)
N
per capita total
expenditure
Correlation Coefficient
Sig. (2-tailed)
N
per capita non foof
expenditure
Correlation Coefficient
Sig. (2-tailed)
N
Correlation Coefficient
total_Income
food
consumption
score
Sig. (2-tailed)
N
24975
-.111(**)
0
8877
.378(**)
0
24972
.406(**)
0
24971
.343(**)
0
24971
.430(**)
0
24934
Food Sources
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)
Sources of food

Transform the single sources (x variables as the food items)
into n variables as the different sources of food;


Doing this we will have the percentage of food consumed
coming from different sources


Own production, purchase, food assistance, borrow, exchange,
gathering, social network, etc.
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.
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.
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.
4.
Calculate the % of each food source
COMPUTE
COMPUTE
COMPUTE
COMPUTE
COMPUTE
COMPUTE
COMPUTE
COMPUTE
pownprod = (ownproduction / totsource)*100.
pfishing = (fishing / totsource)*100.
ppurchase = (purchase / totsource)*100.
pborrow = (borrow / totsource)*100.
pexclabor = (exc_labor / totsource)*100.
pexcitem = (exc_item / totsource)*100.
pfoodaid = (food_aid / totsource)*100.
pother = (other / totsource)*100.
Sources of PDS food basket
100%
80%
60%
40%
64
20%
67
62
40
54
52
47
70
60
58
49
48
41
39
33
66
63
49
16
ppds_pds
ppds_purchase
To
ta
l
N
aj
af
ad
is
si
a
M
ut
ha
na
Th
i–
Q
ar
M
is
sa
n
Ba
sr
ah
Q
Ba
bi
Ka l
rb
al
a
W
as
Sa
si
t
la
h
A
lD
in
D
ia
la
An
ba
r
Ba
gh
da
d
Er
bi
l
in
Su
av
la
a
ym
an
iy
ah
Ta
m
ee
m
N
D
ah
uk
0%
ppds_ownproduction
ppds_family
OTHER
Sources of all foods
100%
90%
80%
70%
60%
50%
40%
30%
22
D
17
28
21
8
p_pds
29
15
24
28
21
32
34
26
24
17
p_purchase
p_ow nproduction
p_family
other
21
To
ta
l
16
Ba
b
Ka il
rb
al
a
W
Sa a ss
it
la
h
A
lD
in
N
aj
af
Q
ad
is
si
a
M
ut
ha
Th na
i–
Q
ar
M
is
sa
n
Ba
sr
ah
19
Er
bi
l
D
ia
la
An
ba
r
Ba
gh
da
d
30
ah
uk
N
in
Su
aw
la
a
ym
an
iy
ah
Ta
m
ee
m
20%
10%
0%
Food sources - urban model
Food sources - rural model
Phnom Penh
Plains
C oastal
C oastal
Total
Tonle Sap
Plains
Total
Tonle Sap
Plateau
0%
Plateau
20%
40%
60%
80%
type of source
% own producion
% purchased+traded
% fishing and hunting
% other
100%
0%
20%
40%
60%
80%
100%
type of source
% own producion
% purchased+traded
% fishing and hunting
% other

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