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What has our landscape to offer for community’s food and nutrition security; a case of vihiga...
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Transcript of What has our landscape to offer for community’s food and nutrition security; a case of vihiga...
What has our landscape to offer for community’s food and nutrition
security; a case of Vihiga County, Kenya
Céline Termote, PhD; Francis Odhiambo Oduor, MSc Ibadan, March 2015
Introduction
Some challenges:
• Feeding over 9 billion people by 2050
• Double burden of malnutrition
• Climate change
• Vulnerability
• Reduction of agrobiodiversity in agricultural systems
Nutrition sensitive landscapes: setting nutritional, environmental
and agricultural targets and options that benefit these multiple
objectives simultaneously using a systems approach.
Create synergies and minimize trade-offs between reducing
malnutrition of vulnerable populations and restoring and employing
ecosystem services.
Nutrition cross-cutting research in HT
Phase II: Identification of entry points for diversification of farms and diets
through
- modelling
- participatory community work
- interactions with Innovation and R4D Platforms
Phase III: implementation of identified interventions (through cluster 4?)
Phase I: Diagnostic study
- Community food diversity
- Farm species diversity
- Dietary diversity
Research questions phase I
What is the available food biodiversity in the landscape and what
are its characteristics? (food biodiversity produced, sold, bought and consumed;
seasonality)
What are actual dietary patterns of women of childbearing age and
feeding practices for young children aged 12 to 23 months?
How can the use of locally available food biodiversity be improved
to improve dietary patterns (and thus nutritional and health
outcomes)?
What are entry points for improving diets while improving
productivity and sustainability of farming systems?
Study location: Vihiga County
Upper Midland (UM) and Humid Lower
Midland agro-ecological zone (LM1).
Mean temperature: 18.5-21.0°C,
Altitude:1500-1900 m a.s.l,
Average rainfall from 1800mm to
above 2000mm, bimodal with rains
April-June and Sept-Nov.
Cash crops: sugarcane, coffee and tea
Staple food crops: maize, beans and
cowpeas, among others.
Luhya, dominant ethnic group with subtribes such
as the Maragoli, Banyore and Terek.
According to 2009 census: 123,347 households.
methods
10 sublocations, 40 HH per sublocation with child 12 to 23 months of age
Field work: Sept-Oct 2014
(1) Two gender-disaggregated focus group discussions per sublocation to
(1) Document and charaterize all available food biodiversity in the community
(produced, sold, bought and consumed food biodiversity)
(2) Seasonal food availability calendars
(3) Food preference ranking/scoring/piling exercises
(2) Household head interviews to document species diversity on individual farms
(3) Focus group discussions to elicit general practices regarding infant and young
child feeding in the communities
(4) Caregiver interviews to document KAP (Knowledge, Attitudes and Practices) on
infant and young child feeding and 2 non-consecutive quantitative 24h food
intake recalls for mothers and children
Preliminary results
Some household characteristics n (%)
Gender of household head Male 314 (78.9)
Female 84 (21.1)
Age of household head* 41.52 ± 13.98
Household members* 6.23 ± 2.98
Dependency ratio* 1.6 ± 0.99
Type of marriage Monogamous 357 (93.7)
Polygamous 24 (6.3)
Educational level of the household head None 9 (2.3)
Primary incomplete 124 (31.3)
Primary complete 135 (34.1)
Secondary incomplete 32 (8.1)
Secondary complete 71 (17.9)
Tertiary 25 (6.3)
Religion of the household head Muslim 7 (1.8)
Christian 389 (98.0)
Pagan 1 (0.3)
Household monthly income Less than Ksh 3500 126 (31.8)
Between Ksh 3500 - 7000 179 (45.2)
Between Ksh 7000 - 14000 49 (12.4)
More than Ksh 14000 42 (10.6)
Does the household collect food from the wild Yes 259 (64.9)
No 140 (35.1)
Does the household have access to
agricultural land
Yes 393 (98.7)
No 5 (1.3)
Caregiver characteristics n (%)
Age* 29.67 ± 9.98
Marital status Married 344 (86.0)
Single 41 (10.3)
Widow 11 (2.8)
Separated 4 (1.0)
Relationship to the household head Wife 335 (83.8)
Daughter 52 (13.0)
Daughter in law 8 (2.0)
Others 5 (1.3)
Number of children* 3.32 ± 2.11
Educational level None 16 (4.0)
Primary incomplete 128 (32.1)
Primary complete 129 (32.3)
Secondary incomplete 48 (12.0)
Secondary complete 52 (13.0)
Tertiary 26 (6.5)
Lactating Yes 262 (65.7)
No 137 (34.3)
Pregnant Yes 29 (7.3)
No 370 (92.7)
Name Number of households Percentage (N=398)
Maize 367 92.21
Beans 352 88.44
Cowpeas 234 58.79
Banana 225 56.53
Blue gum 172 43.22
Kales 161 40.45
Mango 133 33.42
Cassava 130 32.66
Sweet potatoes 118 29.65
Slender leaf 112 28.14
Avocado 102 25.63
Jews mallow 95 23.87
onions 95 23.87
Napier grass 94 23.62
Sugar cane 88 22.11
Pumpkin 73 18.34
Groundnuts 67 16.83
African nightshade 55 13.82
Amaranth 50 12.56
Plums 45 11.31
Pawpaw 43 10.80
Species on farm 20% of species cultivated by more than 10% of HHs
80% of species cultivated by less than 10% of HHs
0
10
20
30
40
50
60
70
80
90
100
1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97 101
105
Plant species harvested from the wild
Species Number of households Percentage (N=398)
Cape gooseberry 259 65.08
Mushroom 181 45.48
Guavas 130 32.66
Amaranth 125 31.41
African night shade 50 12.56
Jew’s mallow 41 10.30
+ 34 species collected by less then 10% HHs
Animal species
+ 9 other (tail) species
Domesticated species Number of households Percentage (N=398)
Chicken 329 82.66
Cattle 244 61.31
Goat 81 20.35
Wild species Number of households Percentage (N=398)
Termites 128 32.16
Quail 50 12.56
+ 16 other (tail) species
Proportion of children/care-givers consuming different food group
0102030405060708090
100
Children
Care-givers
Food group Food item
Children Caregivers
n % n %
Starch Staples 396 99.5 396 99.5
Maize 382 95.98 391 98.24
Wheat 124 31.16 137 34.42
Rice 100 25.13 53 13.32
Irish potatoes 114 28.64 32 8.04
Bread 28 7.04 31 7.79
Cassava 33 8.29 26 6.53
Sweet potatoes 24 6.03 26 6.53
Millet 61 15.33 14 3.52
Sorghum 37 9.30 10 2.51
Yam 5 1.26 6 1.51
Chapati 4 1.01 3 0.75
Familia Infant Porridge 22 5.53 3 0.75
Maize porridge, fermented 2 0.50 1 0.25
Scones 2 0.50 1 0.25
USAID/NHP flour 1 0.25 1 0.25
Biscuit 2 0.50 0 0.00
Cake 1 0.25 0 0.00
Indomie 1 0.25 0 0.00
Spaghetti 2 0.50 0 0.00
Weetabix 4 1.01 0 0.00
Food group Food item
Children Caregivers
n % n %
Dark green leafy vegetables 283 71.10 311 78.10
Kales 150 37.69 186 46.73
Cowpea_leaf 86 21.61 90 22.61
Jews_Mallow 40 10.05 39 9.80
Pumpkin leaf 43 10.80 39 9.80
Amaranth_leaves 24 6.03 25 6.28
Slender leaf (Crotolaria spp) 19 4.77 21 5.28
African Nightshade 12 3.02 13 3.27
Spider plant 4 1.01 9 2.26
Bean_leaf 3 0.75 4 1.01
Spinach 1 0.25 1 0.25
Vinespinach 2 0.50 0 0.00
Food group Food item
Children Caregivers
n % n %
Other vitamin A rich fruits and vegetables 23 5.80 10 2.50
Pumpkin fruit 14 3.52 4 1.01
Papaya 3 0.75 3 0.75
Carrots 6 1.51 2 0.50
Mango 3 0.75 1 0.25
Passion fruit 1 0.25 1 0.25
Other fruits and vegetables 333 83.70 346 86.90
Onion 308 77.39 340 85.43
Tomato 266 66.83 289 72.61
Banana 74 18.59 43 10.80
Cabbage 21 5.28 29 7.29
Avocado 53 13.32 23 5.78
Corriander_leaves 6 1.51 8 2.01
Green_pepper 4 1.01 3 0.75
Guavas 5 1.26 2 0.50
Garlic 1 0.25 1 0.25
Jackfruit 0 0.00 1 0.25
Lemon_fruit 0 0.00 1 0.25
Orange 9 2.26 1 0.25
Water melon 1 0.25 1 0.25
Ginger 1 0.25 0 0.00
Food group Food item
Children Caregivers
n % n %
Legumes, nuts and seeds 90 22.60 110 27.60
Beans 52 13.07 72 18.09
Groundnuts 28 7.04 18 4.52
Almonds 8 2.01 12 3.02
Bean_mung 8 2.01 10 2.51
Cowpea_seeds 7 1.76 10 2.51
Soya beans 14 3.52 6 1.51
Amaranth_ grains 1 0.25 0 0.00
Bambara_groundnut 1 0.25 0 0.00
Food group Food item
Children Caregivers
n % n %
Meats and Fish 128 32.20 135 33.90
Omena (Dagaa/small fish, fresh water) 76 19.10 85 21.36
Fish 29 7.29 30 7.54
Beef 21 5.28 19 4.77
Chicken 4 1.01 4 1.01
Beef_tripe 2 0.50 2 0.50
Pork 1 0.25 1 0.25
Eggs 12 3.00 8 2.01
Egg_chicken 12 3.02 8 2.01
Milk and milk products 329 85.20 328 82.40
Whole milk 338 84.92 327 82.16
Milk powder 0 0.00 1 0.25
Goat milk 1 0.25 0 0.00
Nutrient Median (P25; P75) % <EAR
Energy (Kcals) 1109.04 (782.11; 1488.83)
Protein (% of Kcals) 10.19 (8.72; 11.62)
Carbohydrates (% of Kcals) 72.12 (65.98; 78.11 )
Fat (% of Kcals) 20.51 (15.66; 26.45)
Vitamin A (µg) 333.35 (115.4; 683.59) 35.7
Vitamin C (mg) 52.89 (22.36; 115;6) 16.3
Thiamin (mg) 0.64 (0.44; 0.93) 19.3
Riboflavin (mg) 1.03(0.57; 3.25) 11.3
Niacin (mg) 6.48 (4.53; 9.3) 31.7
Vitamin B6 (mg) 0.92 (0.59; 1.4) 11.3
Folate (µg) 131.52 (76.75; 212.93) 44.1
Vitamin B12 (mg) 0.7 (0.26; 1.39) 49.9
Iron (mg) 6.92 (4.81; 10.02) 67.2
Zinc (mg) 3.228 3.23; 6.45) 80.2
Children’s daily nutrient intakes
Lactating women’s daily nutrient intakes Nutrient Median (P25; P75) % <EAR
Energy (Kcals) 2707.46 (2084.04; 3485.93)
Protein (% of Kcals) 11.07 (9.96; 12.62 )
Carbohydrates (% of Kcals) 77.36 (70.00; 78.82 )
Fat (% of Kcals) 15.49 (13.35; 19.08 )
Vitamin A (µg) 1138.26 (419.73; 1831.54 ) 42.9
Vitamin C (mg) 180.23 (66.33; 286.97 ) 33.6
Thiamin (mg) 1.90 1.28; 2.60 ) 22.9
Riboflavin (mg) 2.65 (1.57; 8.22 ) 17.2
Niacin (mg) 18.03 (12.07; 24.43) 29.0
Vitamin B6 (mg) 2.22 (1.58; 3.22) 28.6
Folate (µg) 368.74 (236.41; 540.35 ) 63.4
Vitamin B12 (mg) 1.11 (0.44; 2.42) 74.4
Iron (mg) 19.74 (13.25; 27.40 ) 56.9
Zinc (mg) 12.10 (9.16; 16.35) 72.9
Next steps Further analysis of data and statistical analysis
household food insecurity measures, WHO feeding practices indicators, DDS
farm species richness, farm size, % for own-consumption/sale
analysis of focus group discussions (ABD and IYCF)
Lean season dietary intake survey (April 2015 + anthropometry and food preferences)
Linear programming and other modeling exercises (see also WUR) to identify options to
improve diets while improving farm sustainability/production
Participatory community workshops and Innovation Platform workshops to:
restitute results (discussion about nutrition and its importance)
identify entry points for dietary and farm diversification, ecological
intensification
Identify best-bet interventions (agriculture and/or nutrition education)
Triangulation of community/innovation work results and linear programming results for
final selection of intervention and policy recommendations
www.bioversityinternational.org
Thank you
Nutrition and Marketing Diversity Programme
Céline Termote; [email protected]