1 Computing DQQ indicators
2 Urban consumers
- 2.1 project level
  - 2.1.1 cluster analysis
  - 2.1.2 FGDS tertiles
- 2.2 country level
  - 2.2.1 Kenya
3 Rural consumers
- 3.1 respondents
  - 3.1.1 project level
    - 3.1.1.1 cluster analysis
    - 3.1.1.2 FGDS tertiles

1 Computing DQQ indicators

Table 1.1: Aggregation of food groups from the questionnaire to create FGDS
FGDS.code	FGDS.descr	variable	question	question.descr
1	Grains, white roots and tubers, and plantains	DQQ_01	Q10.1	01 staple foods made from grains
DQQ_02	Q10.2	02 whole grains
DQQ_03	Q10.3	03 white roots/tubers
2	Pulses (beans, peas and lentils)	DQQ_04	Q10.4	04 legumes
3	Nuts and seeds	DQQ_21	Q10.21	21 nuts & seeds
4	Dairy	DQQ_14	Q10.14	14 cheese
DQQ_15	Q10.15	15 yogurt
DQQ_25	Q10.25	25 fluid milk
5	Meat, poultry and fish	DQQ_16	Q10.16	16 processed meat
DQQ_17	Q10.17	17 unprocessed red meat (ruminant)
DQQ_18	Q10.18	18 unprocessed red meat (non-ruminant)
DQQ_19	Q10.19	19 poultry
DQQ_20	Q10.20	20 fish & seafood
6	Eggs	DQQ_13	Q10.13	13 eggs
7	Dark green leafy vegetables	DQQ_061	Q10.6.1	06.1 dark green leafy vegetables
DQQ_062	Q10.6.2	06.2 dark green leafy vegetables
8	Other vitamin A-rich fruits and vegetables	DQQ_05	Q10.5	05 vitamin A-rich orange veg
DQQ_08	Q10.8	08 vitamin A-rich fruits
9	Other vegetables	DQQ_071	Q10.7.1	07.1 other vegetables
DQQ_072	Q10.7.2	07.2 other vegetables
10	Other fruits	DQQ_09	Q10.9	09 citrus
DQQ_101	Q10.10.1	10.1 other fruits
DQQ_102	Q10.10.2	10.2 other fruits
Diet Quality Questionnaire (DQQ) - Indicator Guide (https://www.globaldietquality.org/dqq)

Table 1.2: All-5: Consumed all five recommended food groups
All.5.code	All.5.descr	variable	question	question.descr
1	Starchy staples	DQQ_01	Q10.1	01 staple foods made from grains
DQQ_02	Q10.2	02 whole grains
DQQ_03	Q10.3	03 white roots/tubers
2	Vegetables	DQQ_05	Q10.5	05 vitamin A-rich orange veg
DQQ_061	Q10.6.1	06.1 dark green leafy vegetables
DQQ_062	Q10.6.2	06.2 dark green leafy vegetables
DQQ_071	Q10.7.1	07.1 other vegetables
DQQ_072	Q10.7.2	07.2 other vegetables
3	Fruits	DQQ_08	Q10.8	08 vitamin A-rich fruits
DQQ_09	Q10.9	09 citrus
DQQ_101	Q10.10.1	10.1 other fruits
DQQ_102	Q10.10.2	10.2 other fruits
4	Pulses, nuts and seeds	DQQ_04	Q10.4	04 legumes
DQQ_21	Q10.21	21 nuts & seeds
5	Animal-source foods	DQQ_13	Q10.13	13 eggs
DQQ_14	Q10.14	14 cheese
DQQ_15	Q10.15	15 yogurt
DQQ_17	Q10.17	17 unprocessed red meat (ruminant)
DQQ_18	Q10.18	18 unprocessed red meat (non-ruminant)
DQQ_19	Q10.19	19 poultry
DQQ_20	Q10.20	20 fish & seafood
DQQ_25	Q10.25	25 fluid milk

Table 1.3: NCD-Protect score
NCD_P.code	NCD_P.descr	variable	question	question.descr
1	Whole grains	DQQ_02	Q10.2	02 whole grains
2	Pulses	DQQ_04	Q10.4	04 legumes
3	Nuts and seeds	DQQ_21	Q10.21	21 nuts & seeds
4	Vitamin A-rich orange vegetables	DQQ_05	Q10.5	05 vitamin A-rich orange veg
5	Dark green leafy vegetables	DQQ_061	Q10.6.1	06.1 dark green leafy vegetables
DQQ_062	Q10.6.2	06.2 dark green leafy vegetables
6	Other vegetables	DQQ_071	Q10.7.1	07.1 other vegetables
DQQ_072	Q10.7.2	07.2 other vegetables
7	Vitamin A-rich fruits	DQQ_08	Q10.8	08 vitamin A-rich fruits
8	Citrus	DQQ_09	Q10.9	09 citrus
9	Other fruits	DQQ_101	Q10.10.1	10.1 other fruits
DQQ_102	Q10.10.2	10.2 other fruits

Table 1.4: NCD-Risk score
NCD_R.code	NCD_R.descr	variable	question	question.descr
1	Soft drinks (sodas)	DQQ_28	Q10.28	28 SSBs (sodas)
2	Baked / grain-based sweets	DQQ_11	Q10.11	11 grain sweets
3	Other sweets	DQQ_12	Q10.12	12 other sweets
4	Processed meat	DQQ_16	Q10.16	16 processed meat
5	Unprocessed red meat	DQQ_17	Q10.17	17 unprocessed red meat (ruminant)
DQQ_18	Q10.18	18 unprocessed red meat (non-ruminant)
6	Deep fried food	DQQ_24	Q10.24	24 deep fried foods
7	Fast food & Instant noodles	DQQ_23	Q10.23	23 instant noodles
DQQ_29	Q10.29	29 fast food
8	Packaged ultra-processed salty snacks	DQQ_22	Q10.22	22 ultra-processed packaged salty snacks

Table 1.5: Diet quality indicators for the general population (from 7 to 11) and Indicators of individual WHO dietary recommendations (from 12 to 15)
index	descr	variable	question	question.descr
7	Zero vegetable or fruit consumption (-)	DQQ_05	Q10.5	05 vitamin A-rich orange veg
		DQQ_061	Q10.6.1	06.1 dark green leafy vegetables
		DQQ_062	Q10.6.2	06.2 dark green leafy vegetables
		DQQ_071	Q10.7.1	07.1 other vegetables
		DQQ_072	Q10.7.2	07.2 other vegetables
		DQQ_08	Q10.8	08 vitamin A-rich fruits
		DQQ_09	Q10.9	09 citrus
		DQQ_101	Q10.10.1	10.1 other fruits
		DQQ_102	Q10.10.2	10.2 other fruits
8	Animal-source food (ASF) consumption	DQQ_13	Q10.13	13 eggs
		DQQ_14	Q10.14	14 cheese
		DQQ_15	Q10.15	15 yogurt
		DQQ_17	Q10.17	17 unprocessed red meat (ruminant)
		DQQ_18	Q10.18	18 unprocessed red meat (non-ruminant)
		DQQ_19	Q10.19	19 poultry
		DQQ_20	Q10.20	20 fish & seafood
		DQQ_25	Q10.25	25 fluid milk
9	Sweet beverage consumption (-)	DQQ_26	Q10.26	26 sweetened tea/coffee/milk drinks
		DQQ_27	Q10.27	27 fruit juice
		DQQ_28	Q10.28	28 SSBs (sodas)
10	Sweet foods consumption (-)	DQQ_11	Q10.11	11 grain sweets
		DQQ_12	Q10.12	12 other sweets
11	Salty or fried snack consumption (-)	DQQ_22	Q10.22	22 ultra-processed packaged salty snacks
		DQQ_23	Q10.23	23 instant noodles
		DQQ_24	Q10.24	24 deep fried foods
12	Whole grain consumption	DQQ_02	Q10.2	02 whole grains
13	Pulse consumption	DQQ_04	Q10.4	04 legumes
14	Nuts & seeds consumption	DQQ_21	Q10.21	21 nuts & seeds
15	Processed meat consumption (-)	DQQ_16	Q10.16	16 processed meat

2 Urban consumers

2.1 project level

2.1.1 cluster analysis

Table 2.1: variable used in cluster analysis
Variabile	Tipo	Levels
vegetable_fruit	factor	No; Yes
animalSource	factor	No; Yes
sweetBeverage	factor	No; Yes
sugarSweetDrink	factor	No; Yes
sweetFood	factor	No; Yes
saltyFriedSnack	factor	No; Yes
WholeGrain	factor	No; Yes
Pulse	factor	No; Yes
NutsSeeds	factor	No; Yes
ProcessedMeat	factor	No; Yes
All.5	factor	No; Yes
NCD_P	numeric	0:9
NCD_R	numeric	0:9
GDR	numeric	0:18
FGDS	numeric	0:10

Figure 2.1: optimal cluster solution

Table 2.2: number of units by cluster
cluster	N	%
1	1,556	29.8
2	757	14.5
3	1,445	27.7
4	1,468	28.1
Total	5,226	100.0

Table 2.3: clusters description by the variables in analysis
variable	1	2	3	4	Total
vegetable_fruit	94.30	97.50	100.00	100.00	98.00
animalSource	79.90	95.50	96.20	98.00	91.80
sweetBeverage	78.50	94.70	85.70	87.00	85.20
sugarSweetDrink	6.60	72.50	19.40	33.10	27.10
sweetFood	19.60	81.00	23.90	63.50	42.00
saltyFriedSnack	20.40	80.60	30.30	76.20	47.50
WholeGrain	27.40	26.40	28.90	75.10	41.10
Pulse	21.30	19.30	89.00	76.30	55.20
NutsSeeds	12.50	21.70	28.40	79.30	37.00
ProcessedMeat	5.80	22.20	9.10	19.70	13.00
All.5	2.40	19.20	90.20	95.20	55.20
NCD_P	3.09	3.79	5.03	6.56	4.70
NCD_R	1.16	4.08	1.76	3.73	2.47
GDR	10.93	8.71	12.27	11.84	11.23
FGDS	4.91	6.15	7.14	8.33	6.67
variable from vegetable_fruit to All.5: % values variable from NCD_P to FGDS: average values

Figure 2.2: clusters description by the variables in analysis

Figure 2.3: clusters by socio-economic variables

Table 2.4: clusters by socio-economic variables (row %)
variable	levels	1	2	3	4	Total
Total	Total	29.8	14.5	27.7	28.1	100
country	KE	22.4	13.7	28.8	35.1	100
	MO	51.0	14.5	19.4	15.0	100
	TN	23.2	20.5	26.2	30.1	100
	TZ	22.3	11.7	36.3	29.7	100
	UG	35.7	13.4	25.9	24.9	100
gender	Male	30.5	13.9	28.3	27.4	100
	Female	29.2	15.0	27.1	28.7	100
education	no qualification, literate	55.4	7.8	20.0	16.8	100
	primary	29.7	12.5	32.2	25.7	100
	secondary	27.7	15.3	26.7	30.3	100
	more than secondary	25.1	17.2	26.8	30.9	100
	other	24.3	17.9	26.0	31.8	100
income	lower than average	40.5	12.9	24.0	22.7	100
	somewhat lower than average	30.2	14.9	26.5	28.5	100
	about average	22.9	17.1	26.4	33.7	100
	somewhat higher than average	26.6	15.1	28.1	30.2	100
	higher than average	23.5	12.3	37.5	26.7	100
age	[18,25]	27.6	19.3	26.6	26.5	100
	(25,35]	27.0	15.9	28.2	28.9	100
	(35,45]	27.8	12.5	28.3	31.4	100
	(45,55]	32.0	12.3	25.7	30.0	100
	(55,Inf]	40.3	9.6	29.2	20.8	100
household size	[0,2]	37.9	16.1	28.2	17.8	100
	(2,4]	28.5	14.5	29.2	27.7	100
	(4,6]	28.8	13.4	26.3	31.5	100
	(6,Inf]	27.0	14.8	26.2	32.0	100

Table 2.5: Test on relationship between clusters and the following variables at project level
variable	test	statistic	df	p.value	signif
gender	Chi.square	3.16	3	0.3669
country	Chi.square	331.95	12	9.0e-64	***
city	Chi.square	855.49	33	2.1e-158	***
educ	Chi.square	192.89	12	9.5e-35	***
income_avg	Chi.square	130.15	12	5.8e-22	***
cl.age	Chi.square	92.00	12	2.0e-14	***
cl.hhs	Chi.square	70.67	9	1.1e-11	***

Figure 2.4: clusters by city

Table 2.6: clusters by city (row %)
variable	levels	1	2	3	4	Total
Total	Total	29.8	14.5	27.7	28.1	100
city	KE_Kisumu	8.3	17.7	8.3	65.7	100
	KE_Kitui	25.2	12.9	38.4	23.5	100
	KE_Nyeri	32.7	10.7	38.2	18.4	100
	MO_Beni Mellal	54.8	15.3	17.5	12.3	100
	MO_Meknes	47.3	13.7	21.3	17.8	100
	TN_Sousse	18.8	21.2	23.8	36.2	100
	TN_Tunis	27.6	19.9	28.6	24.0	100
	TZ_Daressalaam	25.5	12.3	38.2	24.1	100
	TZ_Morogoro	19.4	11.2	34.6	34.8	100
	UG_Kalerwe	23.2	22.5	22.5	31.8	100
	UG_Kampala	44.5	9.9	29.5	16.1	100
	UG_Kapeeka	38.8	8.5	25.5	27.3	100

Figure 2.5: cluster by socio-economic variables by country

Table 2.7: Test on the relationship between clusters and the following variables at country level (chi-squared test)
variable	country	statistic	df	p.value	Signif
gender	KE	4.18	3	0.2425
	MO	3.03	3	0.3875
	TN	2.28	3	0.5157
	TZ	3.78	3	0.2868
	UG	5.77	3	0.1234
	Total	3.16	3	0.3669
education	KE	26.38	12	0.0095	**
	MO	83.91	12	7.4e-13	***
	TN	15.11	12	0.2357
	TZ	22.64	12	0.0310	*
	UG	42.03	12	3.3e-05	***
	Total	192.89	12	9.5e-35	***
income	KE	93.14	12	1.2e-14	***
	MO	63.67	12	4.8e-09	***
	TN	20.10	12	0.0651	.
	TZ	19.27	12	0.0821	.
	UG	13.57	12	0.3292
	Total	130.15	12	5.8e-22	***
age	KE	25.94	12	0.0110	*
	MO	25.51	12	0.0126	*
	TN	41.07	12	4.8e-05	***
	TZ	24.30	12	0.0185	*
	UG	21.18	12	0.0478	*
	Total	92.00	12	2.0e-14	***
hh size	KE	68.36	9	3.2e-11	***
	MO	1.04	9	0.9993
	TN	12.78	9	0.1729
	TZ	11.86	9	0.2213
	UG	31.39	9	0.0003	***
	Total	70.67	9	1.1e-11	***

2.1.2 FGDS tertiles

Table 2.8: Tertiles distribution
tertile	N	%
1	289	5.5
2	2,000	38.3
3	2,937	56.2
Total	5,226	100.0

Food groups consumed by more than 50% of households by dietary diversity tertile - project level; lowest dietary diversity: ≤ 4 food groups; medium: 5 to 6 food groups; high: ≥ 7 food groups

Figure 2.6: Food groups consumed by more than 50% of households by dietary diversity tertile - project level; lowest dietary diversity: ≤ 4 food groups; medium: 5 to 6 food groups; high: ≥ 7 food groups

Figure 2.7: tertiles by socio-economic variables

Table 2.9: tertiles by socio-economic variables (row %)
variable	levels	1	2	3	Total
Total	Total	5.5	38.3	56.2	100
country	KE	3.3	27.4	69.3	100
	MO	9.7	50.1	40.2	100
	TN	3.5	35.8	60.7	100
	TZ	3.0	35.2	61.8	100
	UG	8.8	47.8	43.3	100
gender	Male	5.1	37.5	57.4	100
	Female	5.9	38.9	55.2	100
educ	no qualification, literate	15.5	52.2	32.3	100
	primary	6.1	39.6	54.3	100
	secondary	4.5	35.8	59.7	100
	more than secondary	3.3	35.4	61.3	100
	other	4.0	39.9	56.1	100
income_avg	lower than average	9.5	44.9	45.6	100
	somewhat lower than average	6.7	41.0	52.3	100
	about average	2.5	35.3	62.2	100
	somewhat higher than average	2.9	34.6	62.5	100
	higher than average	2.5	28.1	69.3	100
cl.age	[18,25]	5.2	42.9	51.9	100
	(25,35]	4.5	38.3	57.2	100
	(35,45]	5.1	35.5	59.3	100
	(45,55]	6.0	34.5	59.5	100
	(55,Inf]	8.6	39.7	51.7	100
cl.hhs	[0,2]	9.0	45.7	45.2	100
	(2,4]	5.0	37.2	57.8	100
	(4,6]	5.1	35.9	59.0	100
	(6,Inf]	4.3	37.9	57.8	100

Figure 2.8: cluster by socio-economic variables by country

2.2 country level

2.2.1 Kenya

Table 2.10: number of units by cluster
cluster	N	%
1	346	23.4
2	193	13.1
3	422	28.6
4	516	34.9
Total	1,477	100.0

Table 2.11: clusters description by the variables in analysis
variable	1	2	3	4	Total
vegetable_fruit	94.50	99.50	100.00	100.00	98.60
animalSource	85.50	98.40	99.80	99.60	96.20
sweetBeverage	71.10	83.40	85.30	82.60	80.80
sugarSweetDrink	15.30	36.30	33.90	24.60	26.60
sweetFood	11.80	85.50	64.50	15.10	37.60
saltyFriedSnack	24.90	93.80	81.00	62.20	63.00
WholeGrain	24.30	31.10	78.90	23.60	40.60
Pulse	22.30	17.60	71.80	96.30	61.70
NutsSeeds	8.10	13.00	81.80	17.10	32.90
ProcessedMeat	3.20	65.80	23.50	16.50	21.80
All.5	4.60	16.10	97.90	93.00	63.60
NCD_P	3.35	4.15	6.65	5.12	5.02
NCD_R	1.44	5.11	4.08	2.52	3.05
GDR	10.92	8.04	11.58	11.59	10.97
FGDS	5.33	6.57	8.56	7.52	7.18
variable from vegetable_fruit to All.5: % values variable from NCD_P to FGDS: average values

Figure 2.9: clusters description by the variables in analysis

Figure 2.10: clusters by socio-economic variables

Table 2.12: clusters by socio-economic variables (row %)
variable	levels	1	2	3	4	Total
Total	Total	23.4	13.1	28.6	34.9	100
city	KE_Kisumu	8.1	23.5	53.3	15.1	100
	KE_Kitui	27.2	8.7	18.1	45.9	100
	KE_Nyeri	33.9	7.7	16.0	42.4	100
gender	Male	24.1	11.5	27.4	36.9	100
	Female	22.9	14.2	29.4	33.5	100
education	no qualification, literate	33.8	18.2	22.1	26.0	100
	primary	23.4	12.1	24.4	40.1	100
	secondary	22.6	12.5	31.2	33.7	100
	more than secondary	22.4	14.3	30.9	32.4	100
	other	30.0	0.0	10.0	60.0	100
income	lower than average	25.4	22.0	33.7	19.0	100
	somewhat lower than average	18.4	11.2	42.8	27.6	100
	about average	20.3	12.0	37.8	29.9	100
	somewhat higher than average	24.6	15.1	22.1	38.2	100
	higher than average	24.7	8.7	22.7	43.9	100
age	[18,25]	26.6	13.6	20.8	39.0	100
	(25,35]	21.9	13.9	30.2	34.0	100
	(35,45]	19.8	13.2	32.9	34.1	100
	(45,55]	23.4	10.8	31.6	34.2	100
	(55,Inf]	28.3	12.8	26.1	32.8	100
household size	[0,2]	31.3	11.7	12.6	44.4	100
	(2,4]	24.6	9.8	29.3	36.3	100
	(4,6]	21.1	13.2	34.6	31.1	100
	(6,Inf]	19.1	20.1	29.5	31.3	100

Table 2.13: Test on relationship between clusters and the following variables at country level
variable	test	statistic	df	p.value	signif
gender	Chi.square	4.02	3	0.2596
city	Chi.square	356.06	6	7.7e-74	***
educ	Chi.square	22.43	12	0.0330	*
income_avg	Chi.square	87.20	12	1.7e-13	***
cl.age	Chi.square	18.89	12	0.0912	.
cl.hhs	Chi.square	58.38	9	2.8e-09	***

Figure 2.11: cluster by socio-economic variables by country

Table 2.14: Test on the relationship between clusters and the following variables at city level (chi-squared test)
variable	city	statistic	df	p.value	Signif
gender	KE_Kisumu	0.71	3	0.8706
	KE_Kitui	3.96	3	0.2656
	KE_Nyeri	2.93	3	0.4018
	Total	4.02	3	0.2596
education	KE_Kisumu	21.97	12	0.0378	*
	KE_Kitui	16.39	12	0.1739
	KE_Nyeri	26.14	12	0.0103	*
	Total	22.43	12	0.0330	*
income	KE_Kisumu	31.69	12	0.0015	**
	KE_Kitui	14.03	12	0.2990
	KE_Nyeri	52.52	12	5.0e-07	***
	Total	87.20	12	1.7e-13	***
age	KE_Kisumu	8.13	12	0.7747
	KE_Kitui	33.17	12	0.0009	***
	KE_Nyeri	23.53	12	0.0235	*
	Total	18.89	12	0.0912	.
hh size	KE_Kisumu	19.32	9	0.0226	*
	KE_Kitui	7.85	9	0.5490
	KE_Nyeri	18.21	9	0.0328	*
	Total	58.38	9	2.8e-09	***

3 Rural consumers

3.1 respondents

3.1.1 project level

3.1.1.1 cluster analysis

Figure 3.1: cluster solution

Table 3.1: number of units by cluster
cluster	N	%
1	402	19.2
2	895	42.8
3	249	11.9
4	544	26.0
Total	2,090	100.0

Table 3.2: clusters description by the variables in analysis
variable	1	2	3	4	Total
m_vegetable_fruit	99.50	95.40	100.00	87.30	94.60
m_animalSource	86.80	83.70	93.20	7.50	65.60
m_sweetBeverage	88.80	85.00	94.00	22.20	70.50
m_sugarSweetDrink	6.20	4.20	24.50	1.30	6.30
m_sweetFood	14.40	12.80	76.30	6.40	19.00
m_saltyFriedSnack	19.40	17.10	84.70	16.90	25.60
m_WholeGrain	68.70	21.60	25.70	29.80	33.30
m_Pulse	92.30	8.50	87.10	59.40	47.20
m_NutsSeeds	29.60	7.40	30.90	11.60	15.60
m_ProcessedMeat	1.50	1.10	7.60	0.40	1.80
m_All.5	78.40	1.10	81.10	1.30	25.60
m_NCD_P	4.90	2.69	4.79	2.75	3.38
m_NCD_R	0.87	0.70	2.93	0.28	0.89
m_GDR	13.03	10.99	10.86	11.47	11.49
m_FGDS	6.20	4.30	6.72	3.45	4.73
variable from vegetable_fruit to All.5: % values variable from NCD_P to FGDS: average values

Figure 3.2: clusters description by the variables in analysis

Figure 3.3: clusters by socio-economic variables

## # A tibble: 25 × 7
## # Groups:   variable, levels [150]
##    variable  levels                        `1`   `2`   `3`   `4` Total
##    <fct>     <fct>                       <dbl> <dbl> <dbl> <dbl> <dbl>
##  1 Total     Total                         402   895   249   544  2090
##  2 country   KE                            144   189   121    82   536
##  3 country   MO                             53   397    15    19   484
##  4 country   TZ                             31   178    74   287   570
##  5 country   UG                            174   131    39   156   500
##  6 education 1-Illiterate                   66   250    39   188   543
##  7 education 2-No qualification/literate    26    48     2    21    97
##  8 education 3-Primary                     144   330    90   251   815
##  9 education 4-Secondary                   122   201    87    72   482
## 10 education 5-More than secondary          41    60    29    12   142
## # … with 15 more rows

Table 3.3: clusters by socio-economic variables (row %)
variable	levels	1	2	3	4	Total
Total	Total	19.2	42.8	11.9	26.0	100
country	KE	26.9	35.3	22.6	15.3	100
	MO	11.0	82.0	3.1	3.9	100
	TZ	5.4	31.2	13.0	50.4	100
	UG	34.8	26.2	7.8	31.2	100
education	1-Illiterate	12.2	46.0	7.2	34.6	100
	2-No qualification/literate	26.8	49.5	2.1	21.6	100
	3-Primary	17.7	40.5	11.0	30.8	100
	4-Secondary	25.3	41.7	18.0	14.9	100
	5-More than secondary	28.9	42.3	20.4	8.5	100
	6-other	27.3	54.5	18.2	0.0	100
income	1-A very limited part (less than 25%)	26.6	45.5	9.2	18.7	100
	2-Less than half (from 25% to 50%)	17.4	48.3	8.4	25.8	100
	3-About half (50%)	18.2	42.7	14.4	24.7	100
	4-More than half (from 50% to 75%)	18.6	34.9	14.8	31.8	100
	5-Almost all (from 75% to 100%)	15.6	45.2	12.0	27.2	100
age	[15,20]	17.4	34.3	12.1	36.1	100
	(20,25]	20.8	40.4	13.1	25.7	100
	(25,30]	20.5	42.6	14.1	22.8	100
	(30,35]	20.5	42.4	11.9	25.2	100
	(35,49]	15.2	55.5	6.6	22.7	100
household size	[0,2]	19.5	41.5	24.4	14.6	100
	(2,4]	16.6	46.2	13.3	23.8	100
	(4,6]	17.6	46.2	10.1	26.1	100
	(6,Inf]	24.4	34.7	11.3	29.6	100

##  [1] "clust"             "m_vegetable_fruit" "m_animalSource"   
##  [4] "m_sweetBeverage"   "m_sugarSweetDrink" "m_sweetFood"      
##  [7] "m_saltyFriedSnack" "m_WholeGrain"      "m_Pulse"          
## [10] "m_NutsSeeds"       "m_ProcessedMeat"   "m_All.5"          
## [13] "m_NCD_P"           "m_NCD_R"           "m_GDR"            
## [16] "m_FGDS"            "country"           "educ"             
## [19] "income_food"       "cl.age"            "HH_size"          
## [22] "m_DQ01"            "m_DQ02"            "m_DQ03"           
## [25] "m_DQ04"            "m_DQ05"            "m_DQ06"           
## [28] "m_DQ07"            "m_DQ08"            "m_DQ09"           
## [31] "m_DQ10"            "cl.hhs"            "FGDS.ter"

Table 3.4: Test on relationship between clusters and the following variables at project level
variable	test	statistic	df	p.value	signif
country	Chi.square	723.47	9	6.2e-150	***
educ	Chi.square	147.01	15	9.5e-24	***
income_food	Chi.square	52.98	12	4.2e-07	***
cl.age	Chi.square	51.32	12	8.2e-07	***
cl.hhs	Chi.square	40.46	9	6.3e-06	***

Figure 3.4: cluster by socio-economic variables by country

Table 3.5: Test on the relationship between clusters and the following variables at country level (chi-squared test)
variable	country	statistic	df	p.value	Signif
education	KE	26.37	9	0.0018	**
	MO	11.68	15	0.7030
	TZ	35.06	12	0.0005	***
	UG	20.14	15	0.1665
	Total	147.01	15	9.5e-24	***
income	KE	12.02	12	0.4438
	MO	13.79	12	0.3143
	TZ	18.01	12	0.1154
	UG	11.32	12	0.5013
	Total	52.98	12	4.2e-07	***
age	KE	10.97	12	0.5314
	MO	6.66	12	0.8793
	TZ	15.80	12	0.2005
	UG	17.29	12	0.1389
	Total	51.32	12	8.2e-07	***
hh size	KE	10.01	9	0.3494
	MO	9.71	9	0.3746
	TZ	13.57	9	0.1385
	UG	15.43	9	0.0797	.
	Total	40.46	9	6.3e-06	***

3.1.1.2 FGDS tertiles

Table 3.6: Tertiles distribution
tertile	N	%
1	533	25.5
2	1,222	58.5
3	335	16.0
Total	2,090	100.0

##  [1] "clust"             "m_vegetable_fruit" "m_animalSource"   
##  [4] "m_sweetBeverage"   "m_sugarSweetDrink" "m_sweetFood"      
##  [7] "m_saltyFriedSnack" "m_WholeGrain"      "m_Pulse"          
## [10] "m_NutsSeeds"       "m_ProcessedMeat"   "m_All.5"          
## [13] "m_NCD_P"           "m_NCD_R"           "m_GDR"            
## [16] "m_FGDS"            "country"           "educ"             
## [19] "income_food"       "cl.age"            "HH_size"          
## [22] "m_DQ01"            "m_DQ02"            "m_DQ03"           
## [25] "m_DQ04"            "m_DQ05"            "m_DQ06"           
## [28] "m_DQ07"            "m_DQ08"            "m_DQ09"           
## [31] "m_DQ10"            "cl.hhs"            "FGDS.ter"

Figure 3.5: Food groups consumed by more than 50% of households by dietary diversity tertile - project level; lowest dietary diversity: ≤ 4 food groups; medium: 5 to 6 food groups; high: ≥ 7 food groups

Figure 3.6: tertiles by socio-economic variables

Table 3.7: tertiles by socio-economic variables (row %)
variable	levels	1	2	3	Total
Total	Total	25.5	58.5	16.0	100
country	KE	14.2	65.1	20.7	100
	MO	21.3	65.3	13.4	100
	TZ	38.6	51.8	9.6	100
	UG	26.8	52.4	20.8	100
educ	1-Illiterate	34.3	55.8	9.9	100
	2-No qualification/literate	33.0	53.6	13.4	100
	3-Primary	25.8	60.4	13.9	100
	4-Secondary	16.8	60.8	22.4	100
	5-More than secondary	16.2	52.8	31.0	100
	6-other	9.1	63.6	27.3	100
income_food	1-A very limited part (less than 25%)	25.5	53.7	20.9	100
	2-Less than half (from 25% to 50%)	28.5	57.2	14.3	100
	3-About half (50%)	21.3	60.2	18.4	100
	4-More than half (from 50% to 75%)	26.2	60.0	13.8	100
	5-Almost all (from 75% to 100%)	25.9	61.1	13.0	100
cl.age	[15,20]	30.5	55.8	13.7	100
	(20,25]	25.0	58.4	16.6	100
	(25,30]	24.4	59.2	16.4	100
	(30,35]	21.7	60.5	17.8	100
	(35,49]	27.0	58.0	14.9	100
cl.hhs	[0,2]	22.0	51.2	26.8	100
	(2,4]	24.8	59.2	16.0	100
	(4,6]	25.8	59.6	14.6	100
	(6,Inf]	26.2	56.8	16.9	100

Figure 3.7: cluster by socio-economic variables by country

DQQ cluster

2023-03-01