DEVELOPING VALUE CHAIN INNOVATION PLATFORMS TO …

LIVELIHOOD ANALYSIS OF HOUSEHOLDS IN MANAFWA

AND KAPCHORWA

DEVELOPING VALUE CHAIN INNOVATION PLATFORMS TO IMPROVE FOOD SECURITY IN EAST AND SOUTHERN

AFRICA (VIP4FS) PROJECT (FST/2014/093)

JULY 2017

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CONTRIBUTORS

Joan Kimaiyo1, Evelyne Kiptot1, Joseph Tanui1, Judith Oduol1, Hilda Kegode1, Prossy Isubikalu2, Joel

Buyinza3, Awadh Chemangei4, Simon Nyangas4 and Clement Okia5

1World Agroforestry Centre (ICRAF), P .O. Box 30677-00100 Nairobi, Kenya 2Makerere University, P.O. Box 7062. Kampala, Uganda 3National Forestry Resources Research Institute (NaFORRI), P O Box 1752, Kampala, Uganda 4Kapchorwa District Landcare Chapter (KADLACC), P.O box 127, Kapchorwa, Uganda 5World Agroforestry Centre (ICRAF), Uganda Country Office, P .O. Box 26416, Kampala, Uganda

Correct citation:

Kimaiyo J, Kiptot E, Tanui J, Oduol J, Kegode H, Isubikalu P, Buyinza J, Chemangei A, Nyangas S and

Okia C 2017. Livelihood Analysis of Households in Manafwa and Kapchorwa. Research Report.

World Agroforestry Centre, Nairobi, Kenya, 81pp.

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ACKNOWLEDGEMENTS

The Value Chains Innovations Platform for Food Security (VIP4FS) project is generously

funded by the Australian government through the Australian Centre for International

Agricultural Research (ACIAR). The project team is grateful to all the people who

contributed in one way or another in data collection and analysis of the VIP4FS baseline

data in Manafwa and Kapchorwa districts.

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TABLE OF CONTENTS

Contributors ...................................................................................................................................................................................................... ii

Acknowledgements ....................................................................................................................................................................................... iii

List of Tables ......................................................................................................................................................................................................v

List of Figures ................................................................................................................................................................................................... vi

Acronyms ........................................................................................................................................................................................................ viii

Executive summary ....................................................................................................................................................................................... ix

1.0 Background ........................................................................................................................................................................................ 1

1.1 Livelihood analysis.................................................................................................................................................................... 3

2.0 Methodology ...................................................................................................................................................................................... 5

2.1 Site description ........................................................................................................................................................................... 5

2.2 Sampling and data collection ................................................................................................................................................ 7

2.2 Data Analysis ............................................................................................................................................................................... 8

3.0 Results and discussion ................................................................................................................................................................ 10

3.1 Demographic Characteristics of households in Kapchorwa and Manafwa district ................................... 10

3.2 Agriculture and livestock production ............................................................................................................................. 13

3.2.1 Land ownership .................................................................................................................................................................. 13

3.2.2 Main and secondary occupation .................................................................................................................................. 14

3.2.3 Crop enterprises ................................................................................................................................................................. 15

3.2.4. Livestock production ........................................................................................................................................................ 20

3.3 Institutions and farmer groups ......................................................................................................................................... 26

3.3.1 Participation in farmer groups ..................................................................................................................................... 26

3.4 Household income ................................................................................................................................................................... 32

3.4.1Off farm Income ......................................................................................................................................................................... 35

3.5 Dietary diversity ...................................................................................................................................................................... 36

3.5.1 Comparison in consumption of different food categories ................................................................................ 39

3.5.2 Determining total consumption score for different households ................................................................... 42

3.6 Asset endowments .................................................................................................................................................................. 45

3.6.1 Wealth index ......................................................................................................................................................................... 50

3.7 Infrastructure ............................................................................................................................................................................ 61

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3.7.1 Transport services, road systems ............................................................................................................................... 61

3.7.2 Market Infrastructure and other facilities .............................................................................................................. 63

4.0 Conclusion and recommendations ........................................................................................................................................ 65

5.0 References ........................................................................................................................................................................................ 69

LIST OF TABLES

Table 1: Site description of the different sub counties ................................................................................................................... 7

Table 2: Categorization of different Food types ................................................................................................................................ 9

Table 3: Household types in Manafwa and Kapchorwa ............................................................................................................... 11

Table 4: Age of household members ..................................................................................................................................................... 11

Table 5: Education level of household head in each subcounty ............................................................................................... 12

Table 6: Land ownership ........................................................................................................................................................................... 13

Table 7: Land ownership in season 2014/2015 .............................................................................................................................. 13

Table 8: Land tenure in Uganda .............................................................................................................................................................. 14

Table 9: Main occupation ........................................................................................................................................................................... 14

Table 10: Secondary household occupation ...................................................................................................................................... 15

Table 11: Crop enteprises in Manafwa and Kapchorwa .............................................................................................................. 16

Table 12: Coffee production ..................................................................................................................................................................... 17

Table 13: Main source of seedlings ....................................................................................................................................................... 17

Table 14: Input use in coffee production ............................................................................................................................................ 20

Table 15: Livestock enterprises .............................................................................................................................................................. 20

Table 16: Livestock types .......................................................................................................................................................................... 21

Table 17: Main purpose of livestock enterprise .............................................................................................................................. 22

Table 18: Ownership of dairy cows ....................................................................................................................................................... 22

Table 19: Mode of acquisition of the dairy cows ............................................................................................................................. 23

Table 20: Fodder grown by smallholder farmers ........................................................................................................................... 24

Table 21:Reasons for not growing fodder .......................................................................................................................................... 25

Table 22: Apiary locations ......................................................................................................................................................................... 25

Table 23: Main source of bee hives ....................................................................................................................................................... 26

Table 24: Reasons farmers did not join groups ............................................................................................................................... 28

Table 25: Main reason for joining groups .......................................................................................................................................... 28

Table 26: Farmer group characteristics .............................................................................................................................................. 30

Table 27: Challenges faced by groups .................................................................................................................................................. 31

Table 28: Income ratings from different sources in Manafwa district .................................................................................. 33

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Table 29: Income ratings from different sources in Kapchorwa District ............................................................................. 34

Table 30: Off farm income sources in Manafwa and Kapchorwa ............................................................................................ 35

Table 31: Household consumption of different food types ........................................................................................................ 37

Table 32: Food type consumption across subcounties ................................................................................................................ 38

Table 33: Food types in different household types ........................................................................................................................ 39

Table 34: Count of food categories consumed by households .................................................................................................. 40

Table 35: Household dietary diversity ................................................................................................................................................ 40

Table 36: Number of times food category was consumed .......................................................................................................... 41

Table 37: Patterns of dietary diversity ................................................................................................................................................ 42

Table 38: Food consumption score between Manafwa and Kapchorwa .............................................................................. 42

Table 39: Food categories consumed by different food consumption clusters ................................................................. 44

Table 40: Farm assets owned by households ................................................................................................................................... 47

Table 41: Household asset ownership ................................................................................................................................................. 48

Table 42: Other household assets owned by households in Manafwa and Kapchorwa ................................................ 49

Table 43: Summary of assets used to compute wealth index .................................................................................................... 52

Table 44: Difference in wealth score between Manafwa and Kapchorwa ........................................................................... 54

Table 45: Summary statistics of wealth categories ........................................................................................................................ 55

Table 46: Wealth categories of households in different subcounties .................................................................................... 57

Table 47: Asset ownership of households in different subcounties ....................................................................................... 58

Table 48: Ownership of household assets by different wealth categories .......................................................................... 60

Table 49: Access to transport and road systems ............................................................................................................................. 62

Table 50: Distance and time to different roads in the community .......................................................................................... 63

Table 51: Market and inputs infrastrucre .......................................................................................................................................... 64

Table 52: Distance and time to different markets .......................................................................................................................... 65

LIST OF FIGURES

Figure 1: The sustainable livelihood framework (DFID 2000) ................................................................................................... 4

Figure 2: Map of Kapchorwa and Manafwa and locations of households interviewed ................................................... 6

Figure 3: Gender of household members ........................................................................................................................................... 12

Figure 4: Form which coffee is sold ...................................................................................................................................................... 18

Figure 5: Challenges in Coffee production ......................................................................................................................................... 19

Figure 6: Breeding methods for dairy cows ...................................................................................................................................... 23

Figure 7: Membership in groups ............................................................................................................................................................ 27

Figure 8: Farmer group registration ..................................................................................................................................................... 29

Figure 9: Farmer group composition ................................................................................................................................................... 29

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Figure 10: Proportion of households with household incomes ............................................................................................... 32

Figure 11: Food consumption categories ........................................................................................................................................... 43

Figure 12: Food consumption clusters in Manafwa and Kapchorwa ..................................................................................... 44

Figure 13: Food consumption clusters between different household types ...................................................................... 45

Figure 14: Wealth categories proportions in Manafwa and Kapchorwa .............................................................................. 54

Figure 15: Wealth categories by gender ............................................................................................................................................. 55

Figure 16: Wealth categories of different household types ....................................................................................................... 56

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ACRONYMS

ACIAR Australian Centre for International Agricultural Research

AI Artificial insemination

BCU Bugisu Cooperative Union

ICRAF World Agroforestry Centre

ICT Information and Communication Technology

KACODA Kapchorwa Community Development Association

KADLACC Kapchorwa District Landcare Chapter

NAADS National Agricultural Advisory Services

UCDA Uganda Coffee Development Authority

UWA Uganda Wildlife Authority

VIP4FS Value Chains Innovation Platforms for Food Security

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EXECUTIVE SUMMARY

The Value chain Innovation Platforms Project for Food Security (VIP4FS) aims to identify

principles and drivers that support scalable establishment of effective and equitable

innovation platforms that enhance food security through greater engagement of

smallholder farmers with markets. As a starting point, the project needed to understand

the context in which smallholder farmers operate in order to be able to propose

interventions that will improve food security and hence enhance their livelihoods. A

household survey was carried out in Uganda project sites, Manafwa and Kapchorwa, to

understand the livelihood status of communities living in the Mt. Elgon ecosystem. This

report presents a livelihood analysis by focusing on household characteristics, institutions,

income, assets, dietary diversity, wealth status and infrastructure.

Data was collected from a total of 306 and 321 farmers from Manafwa and Kapchorwa

districts respectively. The farmers interviewed spread across three sub-counties from each

of the project sites: Mukoto, Namabya and Butiru sub-counties in Manafwa and

Kapchesombe, Tegeres and Kabeywa in Kapchorwa. The sub counties were selected based

on their representation of different agro-ecological zones of the Mt Elgon ecosystem:

highland, midland and lowland zones and also based on availability of farmers practicing

the different value chains of interest: coffee, dairy and honey. Of the respondents

interviewed, 55.9% were male and 44.1 % female in Manafwa while 50.8% of farmers were

male and 49.2 % female in Kapchorwa. Data analysed was on demographic characteristics

of households, education, land ownership, crop enterprises, household assets, income,

institutions, agricultural and livestock production with a focus on coffee, dairy and bee

keeping. Dietary diversity and wealth index was computed as a proxy for food security and

poverty levels of households in the area respectively.

Demographics, agricultural production and institutions

From the study, basic characteristics of households showed that households consisted of

mainly the Sebei and Bagisu in Kapchorwa and Manafwa respectively. These two tribes

have distinct language and culture and accounted for the highest inhabitants of the Mt

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Elgon ecosystem. The majority of households were male headed. Agriculture was found to

be the main income generating activity in both sites with maize, beans and bananas being

the main crops grown by farmers. Coffee came in fourth produced by 43.1% and 67.5% of

farmers in Manafwa and Kapchorwa respectively. Farming was also considered a major

income generating activity with the highest percentage of household heads listing farming

as their main occupation. More than half of the households did not have alternative

occupation or income sources. Livestock production was also highly prevalent in both sites

where farmers reared an average number of 2 and 3 animals in Manafwa and Kapchorwa

respectively. Chicken rearing was the most preferred livestock enterprise in both Manafwa

and Kapchorwa district with dairy cattle and goats for meat coming in second and third

respectively.

Although farmer groups have been widely recommended for high level impacts in

smallholder farmer livelihoods, only a few farmers in the study sites belonged to groups.

Only 22.9% of members of households in Manafwa and 35.2% in Kapchorwa ever belonged

to groups in the past. The main reason given was that there were no groups to join in the

area with a few farmers indicating to having no time for group activities and the benefits

obtained from group were unseen. In both areas, farmer groups were mainly mixed with a

few male only and women only groups. There were barely any youth groups in both areas.

Most groups mainly engaged in agricultural related production. Other activities included

savings and credit, input purchases, joint extension services, marketing, welfare and

advocacy.

Dietary diversity

Dietary diversity was used as a proxy indicator of food security. From the analysis, more

than 90% of households in both Manafwa and Kapchorwa districts consumed cereals,

sugars, beverages, vegetables and oils with cereals being the highest consumed food item in

both areas. The consumption of the food types did not significantly differ between sub-

counties in both districts as well as in the different household types. Consumption of all

food types did not significantly differ between household types with exception of eggs and

oils where a higher proportion of male headed households consumed them more than

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proportion of female headed households. In Kapchorwa and Manafwa, all households

consumed at least three different food categories with a higher proportion of households

consuming all five food categories within a seven day period. Food types were categorized

into 6 distinct types: proteins, vitamins A rich, pulses, staples, sugars and oils.

Categorization was important to avoid duplication of food items with similar nutrients

counted as different food types. From the analysis, almost all of the households could be

considered diet diverse as over 50% of the households consumed all the food categories

within a 7 day period before the study. An analysis of the number of times households

consumed the different food varieties, showed that proteins were consumed most than any

other food category. Households consumed proteins an average of 24.05 and 29.73 times in

a 7 day period for Manafwa and Kapchorwa respectively. The patterns of dietary diversity

between different households did not significantly differ between male and female headed

households. The total number of different food types taken within the 7 day period by each

of the food consumption categories between poor, borderline and acceptable categories

also differed. Households in “acceptable” category consumed all food categories in both

districts while consumption of food in “poor” category varied.

Wealth index

Wealth index provides a stable and understandable yardstick for evaluating and comparing

the economic situation of households, social groups and societies across regions. To

compute the wealth index, assets that contribute to material well-being were used. Three

categories of wealth were used; low income, middle income and high income. From the

analysis, households in Kapchorwa district had higher scores than in Manafwa, and the

difference in the mean score was significant (p value<0.000). Kapchorwa households could

therefore be considered wealthier than households in Manafwa on average. Wealth status

also significantly differed between male and female producers. A higher proportion of

female farmers were in the middle and high income category compared to their male

counterparts. Households in high income categories owned televisions, radios, mobile

phones, bicycles, solar panels. Some even had internet access, owned computers, motor

vehicles and electricity in their houses.

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Infrastructure

At least 70% of households in both Manafwa and Kapchorwa had access to some form of

road especially feeder and community roads. However households in Kapchorwa also

accessed other types of roads such as murram and tarmac than households in Manafwa.

The distance travelled to different roads was shorter, both in minutes and in kilometers,

and were mostly accessed through walking by households in Kapchorwa than those in

Manafwa. Despite having slightly less access to different types of roads, Manafwa

households had readily available market for crops and livestock and even agrovet shops.

About 38%, 42% and 37% of farmers indicated to be aware of markets for crops, livestock

and agrovet shops respectively in Manafwa compared to 16%, 13% and 21% of farmers in

Kapchorwa. Manafwa’s proximity to Mbale town provides a good avenue for market and

information accessibility.

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1.0 BACKGROUND

Agriculture is a core sector of Uganda’s economy, and contributes about 23% of GDP with

60 percent of the population engaged in agriculture, forestry and fishing. Agriculture in the

country has had a steady growth over the years. It also presents immense opportunities for

growth in other sectors like manufacturing especially agro-processing. Out of 3.95 million

agricultural households in Uganda, 28.1% of the households are found in the Eastern

region of Uganda with over 70% of these households headed by males. Uganda's key

agricultural products can be divided into cash crops, food crops, and horticultural produce.

Uganda’s most important traditional cash crops are coffee, tea, cotton, tobacco, and cocoa.

Other non-traditional cash crops include: maize, rice, beans, soya beans, palms and

horticulture produce. Suggestion on developments for future growth focuses on increasing

production and productivity, improving household food security, increasing farmers’

income and increasing the value of exports.

The Mt. Elgon Sub-region in particular, which constitutes the Value Chain Innovation

Platforms for Food Security (VIP4FS) project sites in Manafwa and Kapchorwa districts has

a high population density, ranging from 295 persons per km² in Kapchorwa to 586 persons

per km² in Manafwa making it the second most densely populated sub-region in Uganda.

With annual growth rate of 3.0% (UBOS, 2014), communities in the Mt. Elgon sub-region

depend largely on smallholder agriculture and natural resource-based commodities

obtained in the Mt Elgon ecosystem for their livelihoods. Farmers are constrained by

factors such as the remoteness of urban market outlets, poor infrastructure, limited range

of processing opportunities, access to market information, lack of collective institutional

arrangements and limited land holdings.

A key challenge facing the management of the Mt Elgon ecosystem is to maintain and

develop its natural resource base to meet the increasing demands for goods and services

while maintaining the ecosystem’s ecological integrity. This challenge is largely attributed

to the fact that local livelihoods are primarily based on smallholder subsistence agriculture,

hence directly dependent on the natural resource endowment. High population density

coupled with small land landholdings and declining agricultural production builds pressure

http://www.nationsencyclopedia.com/knowledge/Horticulture.html

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on protected areas such as Mt. Elgon National Park. For instance, wood production for fuel,

timber and construction has significantly decreased in the farming system over the years

forcing many households to source it from the protected areas. The role of trees in the

landscape and their contribution to soil conservation, soil fertility maintenance, the

generation of goods and services essential to livelihoods and the regulation of ecosystem

processes have gained increased recognition over the years. In order to tackle some of the

challenges facing smallholder farmers in the Mt. Elgon ecosystem, the VIP4FS project was

initiated. The main aim of the project is to identify principles and drivers that support

scalable establishment of effective and equitable innovation platforms that enhance food

security through greater engagement of smallholder farmers with markets. The project has

a particular focus on enabling women and young people to improve their livelihoods. There

are five specific objectives.

1. To assess smallholder livelihoods, institutional arrangements across scales, and identify drivers that enable value chain IP development for sustainable agricultural commercialization.

2. To identify best fit value chain development strategies and market information delivery systems, and examine their influence on the success of value chain innovation platforms in enhancing rural enterprise development.

3. To develop and evaluate scalable approaches for promoting value chain innovation platforms among smallholders and other stakeholders in ways that generate inclusive and sustainable economic benefits.

4. To engage with and strengthen the capacity of key stakeholder groups to both enhance the research process and promote the widespread scaling up of approaches generated by the project.

5. To systematically monitor and review project implementation and evaluate its outcomes and impacts

The project’s objectives are being realized through the use of a participatory action

research process involving different stakeholders to improve income and food security in

the project sites.

As a starting point, the project needed to understand the context in which smallholder

farmers operate in order to be able to propose interventions that will improve food

security and hence enhance their livelihoods. A household survey was therefore carried out

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in order to understand the livelihood status of communities living in the Mt. Elgon

ecosystem. This report presents livelihoods analysis by focusing on household

characteristics, agricultural production, institutions, income, assets, dietary diversity,

wealth status and infrastructure.

1.1 LIVELIHOOD ANALYSIS

The project adapted the sustainable livelihoods framework (Figure 1) by (DFID, 2000) and

the five capitals by (Donovan and Stoian, 2012) to identify opportunities for inclusive and

sustainable value chain development to achieve balanced improvement of key livelihood

assets (human, social, natural, physical and financial) as elaborated in the 5Capitals tool.

This links household access to livelihood assets with greater well-being and resilience.

Likewise, the economic viability and performance of smallholder enterprises is linked to

their access to business assets. We used this framework to assess the extent to which

existing asset endowments determine the outcomes of value chain development,

relationships between asset building at enterprise and household levels, and the role of

market, political and institutional factors in facilitating or hindering favourable outcomes,

separating the changes caused by interactions and interventions in value chains from those

induced by the overall context. Trade-offs and synergies amongst natural, social and

financial assets are explicitly considered. Livelihood is the material means whereby people

live and involves a myriad of activities that people partake to provide for their basic needs.

Livelihood is a concept of research and development and includes what people do (given

their resources and assets) and what they achieve by doing it. Livelihood analysis

investigates people, their capabilities and their means of living including food, income, and

properties one owns. According to (DFID, 2000), a livelihood is considered sustainable

when it can cope with and recover from stresses and shocks and maintain or enhance its

capabilities and assets now and in future, while not undermining the natural resource base.

Livelihood strategies consist of a set of activities that an individual undertakes in order to

meet basic needs. Understanding livelihood strategies will assist the VIP4FS project

identify interventions that can be acted upon in order to improve livelihood prospects

which is a prerequisite to reduction of rural poverty. According to the World Bank group,

strategies seek patterns that can be acted upon in order to improve the livelihood

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prospects of the poor through discovering alternatives and increasing options. In order to

adequately address rural poverty, farmers are required to adopt sustainable livelihood

strategies.

Using the DFID framework we conceptualize how households in Uganda operate within a

vulnerability context that is shaped by different factors and opportunities and how they

draw on different types of livelihood assets or capitals which may be influenced by the

vulnerability contexts, institutions and processes and how they use their asset base to

develop a range of livelihood strategies to achieve desired livelihood outcomes (de Satge et

al., 2002)

FIGURE 1: THE SUSTAINABLE LIVELIHOOD FRAMEWORK (DFID 2000)

The study aims at providing useful information for understanding initial livelihood status

of households in the area. The assessment was guided by the five capitals; human capital,

natural capital, financial capital, physical capital and social capital. The three value chains

of interest (coffee, honey and dairy) were preselected based on agreed upon nine point

criteria by the project team after extensive consultation with the implementing partners.

The nine-point criteria included (i) potential for large impact, particularly for women and

the youth, (ii) prospects for tractable interventions that could yield useful results from

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planned comparisons, (iii) existence of the private sector actor who could be approached to

co-finance planned comparisons, (iv)existence of the development partners who are

already working on the value chains to effect interventions, (v)co-benefits to smallholder

livelihood systems, (vi)availability of resource persons within the project team, (vii)clear

institutional access necessary to effect change and (viii) supportive policy context within

which the interventions can be developed.

2.0 METHODOLOGY

2.1 SITE DESCRIPTION

The data for this study was collected from Eastern Uganda in two districts: Manafwa and

Kapchorwa. The two sites are located at the slopes of the Mt Elgon. Mt Elgon ecosystem

consists of forests, farm land and Mt Elgon national park. The Mt. Elgon Sub-region has a

high population density, ranging from 295 persons per km² in Kapchorwa to 586 persons

per km² in Manafwa making it the second most densely populated sub-region in Uganda

and with annual growth rate of 3.0% (UBOS, 2014). The number of households for

Kapchorwa and Manafwa are 21,652 and 72,740, respectively both with an average of 4.8

persons per household (UBOS, 2014). The majority of people are engaged in smallholder

agriculture as the main economic activity. Crops grown include maize, Arabica coffee,

bananas, sorghum, potatoes, beans, tomatoes, cabbage, and passion fruits in a dominantly

coffee-banana system. Most households also own livestock, usually kept in zero grazing

units or in combination with partial grazing. The main animals kept include cattle, goats,

sheep, pigs and chicken.

Kapchorwa district is divided into three agro-ecological zones, namely, Mt. Elgon high

farmlands, Kapchorwa farm forest and North East short grass plains with clay soils. The

average altitude in the three zones is 1466 m, 1455 m, and 1093 m respectively. Rainfall

varies from less than 1000 mm in the north increasing to 2000 mm towards Mt. Elgon

Kapchorwa district is divided into 11 sub counties; Kaptanya, Kapchorwa town council,

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Kapchesombe, Kapteret, Tegeres, Chema, Sipi, Chepterech, Kawowo, Amukol and Kaserem.

Kapchorwa district is bordered by Kween district to the northeast and east, Sironko district

to the south, and Bulambuli district to the west and northwest (Figure 2). The priority cash

crops for Manafwa district are coffee, maize, beans, banana and potatoes. Coffee is mainly

marketed through farmer primary societies which are linked to the Bugisu Cooperative

Union (BCU) which undertakes processing and marketing under the brand “Elgon Coffee”.

On the other hand, the main cash crops in Kapchorwa are maize, coffee, barley, wheat,

beans, banana, potatoes, sesame, sunflower, onions and cabbage. The main coffee

marketing agency is Kawacom which also undertakes processing and export. Other coffee

dealers include; Kapchorwa-Bukwa Marketing Association. Kapchorwa Community

Development Association (KACODA) specializes in the marketing of milk and honey.

FIGURE 2: MAP OF KAPCHORWA AND MANAFWA AND LOCATIONS OF HOUSEHOLDS INTERVIEWED

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2.2 SAMPLING AND DATA COLLECTION

Three sub-counties from each district were selected for this exercise: Mukoto, Namabya

and Butiru sub-counties in Manafwa and Kapchesombe, Tegeres and Kabeywa (Table 1).

The sub counties were selected based on representation of the different agro-ecological

zones of the Mt Elgon ecosystem: highland, midland and lowland zones in the district and

also based on availability of farmers practicing the different value chains of interest: coffee,

dairy and honey. In Manafwa district, Mukoto, Namabya and Butiru sub-counties were

selected to represent highland, midland and lowland zones. In Kapchorwa district,

Kapchesombe was selected to represent high altitude while Tegeres and Kabeywa were

selected to represent high to mid altitudes (Table 1). Sub-counties in the lowlands were

dropped from the sampling frame because the three enterprises were not predominantly

undertaken by the farmers. Kapchesombe and Kabeywa were selected for dairy and apiary

while Tegeres was prioritised for dairy. All the three sub-counties were predominantly

coffee growing zones although Kabeywa was reported to be the main coffee producing

zone. A total of 18 and 30 villages were selected in Manafwa and Kapchorwa district

respectively.

TABLE 1: SITE DESCRIPTION OF THE DIFFERENT SUB COUNTIES

District Sub-county n Percentage Predominant crop in the area

Manafwa Mukoto 70 22.9 Coffee, dairy and apiary

Namabya 98 32.0 Coffee and dairy

Butiru 138 45.1 dairy

Total 306

Kapchorwa Kapchesombe 105 32.7 Coffee and apiary

Tegeres 126 39.3 Dairy

Kabeywa 90 28.0 Coffee

Total 321

Grand Total 627

Of the respondents interviewed, 55.9% were male and 44.1 % female in Manafwa while

50.8% of farmers were male and 49.2 % female in Kapchorwa. The sampling frame for the

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households was constructed during the surveys, because the lists were not available at the

government offices. The sampled households were allocated to the six sub-counties

proportionately based on the total number of households in a given sub-county. A total of

306 and 321 farmers were selected for interviews in Manafwa and Kapchorwa districts

respectively (Table 1).

2.2 DATA ANALYSIS

Variables from households and individual respondent characteristics were assessed to

capture relevant information from respondents. Descriptive statistics such as frequency

counts, percentages, mean and standard error of mean were used to display the data. Data

analysed was on demographic characteristics of households, education, land ownership,

crop enterprises, household assets, income, institutions, agricultural and livestock

production with a focus on coffee, dairy and bee keeping. Dietary diversity was computed

as a proxy of food security. Dietary scores and percentage of households consuming each

food group was used as a one-time measure. The dietary score in this study was measured

by the following criteria:

i) Creating food group variables for each of the food groups and aggregations done

by the food group category. For the purposes of the study the categorization in

Table 2 was used.

ii) Generating a combined variable for all food groups falling under each of the

defined categories in Table 2. The combination was defined to be 1 if a

household consumed at least one of the food items

iii) Dietary diversity was computed by summing all food groups consumed by the

household within a 7 day period.

iv) Food consumption score was computed as a factor of the household consuming

the food category and the number of days the households have consumed the

food item in a period of seven days multiplied by the assigned food consumption

score

v) Summation of the total household consumption score for each household

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vi) Categorization of households in different food consumption categories using

percentiles. Those households with less than 25th percentile were considered

having ‘poor’ dietary diversity, households with greater that 25th and less than

75th percentile were considered to have “borderline” diversity while those with

greater than 75th percentile were considered to have “acceptable” diversity and

food consumption.

TABLE 2: CATEGORIZATION OF DIFFERENT FOOD TYPES

Food Category Types of foods Food consumption score

Proteins Meat, milk, fish and eggs 4

Vitamins A rich Fruits and vegetables 1

Pulses Beans and peas 3

Staples Tubers, roots, cereals and grains 2

Sugars Sugars and beverages 0.5

Oils Oils 0.5

Dietary diversity was presented by use of “count” which is the number of food categories

consumed by a given household. Counting the number of food categories is more indicative

of diversity than count of different food types as the types would be providing similar

nutrients for instance a household that consumes proteins, vitamins and roots would be

considered more diet diverse than a household that consumes different type of cereals.

Wealth index

The wealth index which is a composite measure of a household cumulative living standard

was calculated using household ownership of different items such as television, bicycles

and cars. Type of roofing materials, type of drinking water sources, toilet facility and other

characteristics related to wealth status were also used. Each of the assets was assigned a

weight or factor score generated through principal component analysis. The scores were

then standardized in relation to standard normal distribution with a mean of zero and

standard deviation of one. The standardized scores were then used to create the break

points that define wealth quintiles: low, middle and high income households. Asset index

has replaced previous popular income and consumption data and depicts an individual or a

10

household’s long-run economic status and therefore do not necessarily account for short-

term fluctuations in economic wellbeing (Filmer and Pritchett, 2001). The wealth index of a

given household, i, is a linear combination of assets owned.

The wealth index, yi, calculated as below:

𝑦𝑖 = 𝛼1 (𝑥1 − 𝑥1̅̅ ̅

𝛿1) + 𝛼2 (

𝑥2 − 𝑥2̅̅ ̅

𝛿2) + ⋯ … . + 𝛼𝑘 (

𝑥𝑘 − 𝑥𝑘̅̅ ̅

𝛿𝑘)

Where, �̅� and k are mean and standard deviations of assets 𝑥𝑘 and α represents the

weight for each variable 𝑥𝑘 for the first principal component. The first principal

component, y, yields a wealth index that assigns a larger weight to assets that vary the most

across households so that an asset found in all households is given a weight of zero

(McKenzie, 2005). The first principal component or wealth index can take positive as well

as negative values.

3.0 RESULTS AND DISCUSSION

3.1 DEMOGRAPHIC CHARACTERISTICS OF HOUSEHOLDS IN KAPCHORWA AND

MANAFWA DISTRICT

From the survey, 78.1%of the respondents in Manafwa were from Bagisu community

followed by the Teso tribe (19.9%). In Kapchorwa, 73.8% of the respondents were from

Sebei community with the rest 26.2% being from the Bagisu tribe. Households in Manafwa

and Kapchorwa were mostly male headed with more than 85 % headed by males in both

districts. Of this, most were male headed (monogamous) households, 71.7% and 69.2% for

Manafwa and Kapchorwa respectively (Table 3). Female headed households (12.2%) were

few in both sites. More than 95.1% of the respondents in both districts had at least one

person living with them in the household. Households in Manafwa and Kapchorwa had an

average of five people with few households having up to 12 and 11 household members in

Manafwa and Kapchorwa respectively. Highest percentage of households members in both

11

districts were below 18 years with a number of members in the young adults category. The

minorities were older members above 50 years old (Table 4).

TABLE 3: HOUSEHOLD TYPES IN MANAFWA AND KAPCHORWA

What is the type of household?

Manafwa (n=306) Kapchorwa (n=321)

Percent Percent

Male headed (monogamous) 71.2 69.2

Male headed (polygamous) 9.5 13.4

Female headed (spouse living in another town) 1.3 0.3

Female headed (widowed) 9.8 8.4

Female headed (divorced/separated) 2.3 1.6

Female headed (single-never been married) 0.6

Male headed (single-never been married) 0.7 0.9

Male headed (divorced/separated) 2.3 4

Male headed (widowed) 2.3 1.2

Child headed 0.3

Male headed (spouse living in another town) 0.3 0.3

TABLE 4: AGE OF HOUSEHOLD MEMBERS

HH members characteristics

Manafwa

Percentage of

HH members

(n=306)

Kapchorwa

Percentage of HH

members

(n=321)

YOUTH BELOW 18 below 18 71.6 65.4

YOUNG ADULTS Between 18> years>35 17.6 20.6

ADULTS 35> years>50 7.0 7.8

OLDER MEMBERS Above 50 3.9 6.1

The gender of the different household members is presented in Figure 3. Manafwa district

has more females in the households than males while Kapchorwa had more males than

females in the household.

12

FIGURE 3: GENDER OF HOUSEHOLD MEMBERS

The highest education level of the respondents varied between and within sites. Most of the

farmers in Manafwa and Kapchorwa had primary level education levels with less having

attained secondary, college and university education (Table 5). In Kapchorwa more

farmers had secondary level of education than Manafwa but still few had college and

university education. Majority of household heads are males in both districts (Kapchorwa

88%; Manafwa 85 %).

TABLE 5: EDUCATION LEVEL OF HOUSEHOLD HEAD IN EACH SUBCOUNTY

Highest level of

education of

Household head

Manafwa Kapchorwa

Mukoto

(n=70)

Namabya (n=98) Butiru (n=138) Total (N=306) Kapchesombe

(n=105)

Tegeres

(n=126)

Kabeywa

(n=90)

Total

(N=321)

None (%) 12 15 11 12 11 14 17 14

Primary (%) 74 52 68 64 39 51 63 51

Secondary (%) 14 24 18 19 29 31 16 26

Tertiary (%) 0 9 4 4 21 4 4 10

Gender of household

head (%female)

16 18 12 15 10 12 15 12

47

.7%

52

.3%

51

.6%

48

.4%

M A N A F W A K A P C H O R W A

GENDER COMPOSITION OF HH MEMBERS

Male Female

13

3.2 AGRICULTURE AND LIVESTOCK PRODUCTION

3.2.1 LAND OWNERSHIP

Agriculture is the backbone of Uganda’s economy and almost all households in rural areas

practice agriculture. Of the respondents interviewed almost all households owned land.

More than 95% of the households owned land in both districts as shown in Table 6.

Average sizes of land owned in the two sites were 1.90 and 2.11 acres in Manafwa and

Kapchorwa respectively (Table 6).

TABLE 6: LAND OWNERSHIP

District Percent Average land

size (acres)

Stand

Dev

Manafwa (N=306) No 1.6

Yes 98.4 1.90 1.91

Kapchorwa

(N=321)

No 3.1

Yes 96.9 2.11 2.31

The total land owned and land under cultivation in Manafwa and Kapchorwa did not

significantly differ. This is due to the fact that land owned is very small. Farmers in

Kapchorwa cultivated more land than farmers in Manafwa. These difference was however

not significant (Table 7).

TABLE 7: LAND OWNERSHIP IN SEASON 2014/2015

Land ownership in Season 2014/2015

(acres)

Mean SE

Size of land owned in

previous season

Manafwa 1.78 0.11

Kapchorwa 2.05 0.13

Total land under

cultivation

Manafwa 1.83 0.10

Kapchorwa 1.95 0.11

Total land rented in Manafwa 1.04 0.12

Kapchorwa 1.10 0.14

Total land rented out

(leased)

Manafwa 0.90

Kapchorwa 1.17

14

The land owned in both districts was either freehold and/or customary (Table 8).

Customary tenure is whereby access to land is governed by customs, rules, and regulation

of the community. The holders of land do not have formal titles to the land they use. Free

hold system is where owners of the land have a deed to their land which allows them to

hold the registered land indefinitely. The land owner has a right to use, sell, lease, transfer,

subdivide, mortgage and give as they see fit. The rights are well respected by the

government.

TABLE 8: LAND TENURE IN UGANDA

Land tenure

Manafwa (%)

(n=306)

Kapchorwa (%)

(321)

Freehold 49.3 47.7

Leasehold 0.0 0.6

Customary 49.3 48.3

None 1.6 3.4

3.2.2 MAIN AND SECONDARY OCCUPATION

Farming is a major income generating activity in both sites. More than 85% of household

heads mentioned farming as their main occupation (Table 9.)

TABLE 9: MAIN OCCUPATION

Variable

Manafwa Kapchorwa

Mukoto

(n=70)

Namaby

a (n=98)

Butiru

(n=138)

Total

(N=306)

Kapchesombe

(n=105)

Tegeres

(n=126)

Kabeywa

(n=90)

Total

(N=321)

Main occupation

Farming (%) 99 84 92 91 74 89 84 83

Regular employment

(%) 1 4 2 3 10 5 6 7

Business (%) 0 5 1 2 5 2 6 4

Casual labourer (%) 0 3 4 3 5 1 2 3

Others 0 3 1 1 7 3 2 4

15

Farming is relied on as an income generating activity as most farmers are not employed

nor do they have other activities that can bring income. Only a few farmers got involved in

small scale businesses while others served as casual laborers (Table 9). The majority of

farmers do not have a secondary occupation (Table 10).

TABLE 10: SECONDARY HOUSEHOLD OCCUPATION

Secondary Job or Occupation District (%) Total

(n=627) Manafwa

(n=306)

Kapchorwa

(n=321)

None 76.1 51.4 63.5

Not involved in productive work due to age or health

reasons 0.0 2.2 1.1

Farmer (crop and/or livestock) 9.2 19.0 14.2

Runs self-owned off-farm business 9.8 9.3 9.6

Regular employment 0.7 2.5 1.6

Casual off-farm employment like construction labourer 2.3 2.2 2.2

Agricultural casual labourer 1.6 11.8 6.9

Student 0.3 0.3 0.3

Other specify 0.0 1.2 0.6

3.2.3 CROP ENTERPRISES

Households in Kapchorwa and Manafwa had an average of four and five enterprises

respectively, with a small number of farmers having up to 11 crop enterprises in their farm

in the cropping season 2014-2015. The major crops practiced by households in Manafwa

and Kapchorwa were: maize, beans and bananas (Table 11). Maize and beans are major

staple foods in East Africa and highly contributes to the household food security. Coffee, a

value chain of interest to the VIP4FS project, comes in fourth with only 43.1% and 67.6% of

households in Manafwa and Kapchorwa growing it respectively (Table 11).

16

TABLE 11: CROP ENTEPRISES IN MANAFWA AND KAPCHORWA

Crop enterprises on the farm in the last cropping season of 2015/2016

District (%)

Manafwa (n=306)

Kapchorwa (n=321)

Total (n=627)

Maize 90.8 81.6 86.1

Beans 92.5 73.2 82.6

Bananas (matooke) 58.5 65.1 61.9

Coffee 43.1 67.6 55.7

Cassava 57.5 5.6 30.9

Irish potato 2.3 56.7 30.1

Onions 27.1 8.4 17.5

Sweet potato 28.8 3.1 15.6

Groundnuts 22.5 0.3 11.2

Finger millet 18.3 0.0 8.9

Cabbage 4.6 11.5 8.1

Passion fruits 3.3 11.2 7.3

Tomato 12.1 2.5 7.2

Sorghum 11.8 0.0 5.7

Yams 3.6 4.4 4.0

Soya beans 7.2 0.0 3.5

Kales 0.3 5.6 3.0

3.2.3.1 COFFEE PRODUCTION

Coffee is the main export crop in Uganda together with tea, cotton and tobacco. Coffee

accounts for the highest export in tons for the country. The crop is relatively important to

the household livelihoods. In the study sites, more farmers produced coffee in Kapchorwa

(71%) than in Manafwa (40%). Although land acreage under coffee production was not

significantly different between Manafwa and Kapchorwa sites, the results show that

farmers in Kapchorwa allocate relatively more land to coffee than those in Manafwa. The

production yields in kgs between the two sites were however different: farmers in

Kapchorwa harvested significantly more coffee, mean 220kgs, than farmers in Manafwa in

year 2014/2015 who sold an average of 134kgs (Table 12).

The numbers of farmers that sold coffee in Manafwa also significantly decreased from the

farmers that harvested coffee in year 2014/2015 season with those that sold coffee in the

same period. The amount of coffee harvested significantly decreased between years

2014/2015 to 2015/2016 season. The amount sold between Kapchorwa and Manafwa also

differed significantly with farmers in Kapchorwa selling more coffee, 218kgs than farmers

in Manafwa that sold 129 kgs of coffee per household in the 2015/2016 season (Table 12)

17

TABLE 12: COFFEE PRODUCTION

District n Mean SE T test

Coffee area in (acres) Manafwa 121 1.62 0.154 0.129

Kapchorwa 228 1.95 0.133

Amount of coffee

harvested in 2014/2015

in kg

Manafwa 152 134.57 9.709

0.000** Kapchorwa 233 220.86 15.052

Amount of coffee sold in

kg in 2014/2015

Manafwa 91 226.63 109.176 0.497

Kapchorwa 221 299.75 52.350

Total quantity of coffee

sold in 2015/2016 in kg

Manafwa 91 129.19 12.56 0.000**

Kapchorwa 221 218.08 15.752

During planting, almost all farmers in Manafwa (95%) and Kapchorwa (100%) plant

Arabica coffee in their farms. A few households in Manafwa plant Robusta coffee. Slightly

over half of the farmers in Manafwa (58.7%) and 45.2% in Kapchorwa establish their own

seedlings. A few source them from a private trader in the village (Table 13 )

TABLE 13: MAIN SOURCE OF SEEDLINGS

Main source of coffee seedlings

District

Manafwa (%)

(n=121)

Kapchorwa (%)

(n=228)

Own 58.7 45.2

Private trader in the local/village market 16.5 34.2

Government 13.2 3.9

Fellow farmer 5.8 3.9

Neighbor/ Relative 2.5 3.1

Farmer Group 1.7 1.3

NGO 0.8 1.8

Other (specify) 0.8 1.8

Private trader in the district market 0.0 1.8

Cooperative 0.0 3.1

18

Coffee value addition

There was no value addition to the coffee sold. Harvested coffee was mainly sold as fresh

unprocessed or dry processed coffee beans (Figure 4). This presents an opportunity as

farmers would fetch more income if they sold processed coffee.

FIGURE 4: FORM WHICH COFFEE IS SOLD

Constraints faced by coffee producers

Even with the high level of production of coffee in Kapchorwa and Manafwa, farmers faced

a number of constraints during its production (Figure 5). A higher proportion of

households in Kapchorwa experienced challenges than coffee farmers in Manafwa. More

than 20% of farmers in Kapchorwa experienced low productivity of coffee, high incidence

of pests and diseases, limited knowledge on coffee production and lack of proper storage

facilities (Figure 5). Other challenges include limited access to extension and market

information. Lack of storage was mentioned by over 30% of producers in Kapchorwa.

64.8%

2.2%

2.2%

30.8%

63.1%

5.4%

0.9%

30.6%

0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0%

Fresh unprocessed beans (red cherries)

Fresh processed (pulped and washed, sold beforedrying, mainly Arabica)

Dry processed beans (for Robusta - red cherriesfloated to remove insects, then dried)

Dry processed (for Arabica - pulped, washed anddried)

Form in which coffee is sold

Kapchorwa Manafwa

19

FIGURE 5: CHALLENGES IN COFFEE PRODUCTION

Despite challenges facing farmers in both districts, only a few of the coffee producing

households used inputs such as fertilizer and pesticides (Table 14). Chemical fertilizer

used was sourced from private traders in the local market and village while a few farmers

had own pesticides for coffee.

0 5 10 15 20 25 30 35 40

Lack of storage facilities

Limited access to extension and market information

Lack of reliable buyers

High incidence of diseases

High incidence of pests

Low productivity (limited surplus for sale)

Low demand (poor prices)

Unstandardized packaging

Unavailability of clean planting material

High transport cost to the main market/ point of sale

Adulterated inputs

Coffee production challenges

Kapchorwa Manafwa

20

TABLE 14: INPUT USE IN COFFEE PRODUCTION

Input use Manafwa (%)

(n=121)

Kapchorwa (%)

(n=228)

Use of chemical fertilizer 5.8 3.1

Use of pesticides in coffee

production

7.4 16.2

Use of hired labour 19.8 31.6

3.2.4. LIVESTOCK PRODUCTION

Livestock production in Uganda also forms an integral part of daily livelihoods. Although

crop production is highly prevalent in Manafwa and Kapchorwa, there were a number of

farmers practicing livestock farming. Only 14% of farmers did not have any livestock

enterprises. Farmers reared an average number of two and three animals in Manafwa and

Kapchorwa respectively. Chicken rearing was the most preferred livestock enterprise in

both Manafwa and Kapchorwa district (Table 15). The second most practiced livestock

enterprise was dairy cattle and rearing of goats for meat.

TABLE 15: LIVESTOCK ENTERPRISES

Livestock enterprises in the

households (2015/2016 )

season

Manafwa (%)

(n=306)

Kapchorwa (%)

(n=321)

Local chicken 40.8 32.0

Dairy cattle 20.6 32.1

Goats (meat) 14.6 20.5

Pigs 10.3 4.3

Goats (milk) 4.9 1.5

Beef cattle 4.9 0.5

Others 2.3 1.5

Sheep 1.4 5.1

Bee keeping 0.2 2.6

21

The livestock reared were mainly of local breed except dairy animals in Kapchorwa where

more farmers had improved breeds than local breeds (Table 16). A higher percentage of

farmers in Kapchorwa had improved dairy cattle than Manafwa.

TABLE 16: LIVESTOCK TYPES

Livestock enterprises in the

last cropping season of

2015/2016

Manafwa (%)

Kapchorwa (%)

Livestock type N Livestock type N

Improved Local Improved Local

Dairy cattle 45.6 54.4 114 66.8 33.2 196

Sheep 0.0 100.0 8 3.2 96.8 31

Pigs 0.0 100.0 57 15.4 84.6 26

Goats (milk) 7.4 92.6 27 11.1 88.9 9

Goats (meat) 0.0 100.0 81 0.8 99.2 125

Local chicken 0.9 99.1 226 1.5 98.5 195

Bee keeping 0.0 100.0 1 0.0 100.0 16

Beef cattle 48.1 51.9 27 0.0 100.0 3

Most of the livestock enterprises were kept for commercial purposes in Manafwa. Farmers

sold dairy products, sheep, pigs, goats, honey products and beef cattle. Only local chicken

was mainly reared for household consumption. In Kapchorwa, dairy products and local

chicken were mostly for subsistence and household consumption. Other livestock

enterprises in Kapchorwa were for commercial purposes (Table 17).

A farmer in Kapchorwa feeding her dairy cow

22

TABLE 17: MAIN PURPOSE OF LIVESTOCK ENTERPRISE

MAIN purpose of

livestock

enterprise

Manafwa (%)

n

Kapchorwa (%)

n Subsistence/

Consumption

Commercial

/Sale

Subsistence/

Consumption

Commercial

/Sale

Dairy cattle 41.2 58.8 114 54.1 45.9 196

Sheep 37.5 62.5 8 19.4 80.6 31

Pigs 10.5 89.5 57 23.1 76.9 26

Goats (milk) 48.1 51.9 27 55.6 44.4 9

Goats (meat) 18.5 81.5 81 28.8 71.2 125

Local chicken 68.6 31.4 226 69.7 30.3 195

Bee keeping 0.0 100.0 1 18.8 81.3 16

Beef cattle 7.4 92.6 27 33.3 66.7 3

Other (specify) 38.5 61.5 13 77.8 22.2 9

3.2.4.1 DAIRY PRODUCTION

Farmers in Kapchorwa have embraced dairy farming more than farmers in Manafwa. About 29.7% and

54.8% of farmers in Manafwa and Kapchorwa respectively owned dairy cattle within the agricultural year

preceding the interview. Farmers owned an average of one dairy cow in Manafwa and two in Kapchorwa

(Table 18). Kapchorwa had more dairy cattle of improved breeds than in Manafwa. There was no significant

difference in the number of local dairy breeds owned by farmers in the two sites (Table 18).

TABLE 18: OWNERSHIP OF DAIRY COWS

District n Mean SE

Improved cows Manafwa 91 0.71 0.089

Kapchorwa 176 1.51 0.114

Local cows Manafwa 91 0.96 0.120

Kapchorwa 176 0.99 0.164

Total no. of dairy cows in

the last agricultural year

Manafwa 67 1.52 0.109

Kapchorwa 137 2.34 0.184

More than 80% of the farmers sold milk in Kapchorwa, while 43% sold milk in Manafwa. The dairy cattle

were mostly purchased from other farmers in both Kapchorwa and Manafwa (Table 19)

23

TABLE 19: MODE OF ACQUISITION OF THE DAIRY COWS

Main mode of acquisition of the

dairy cows

Manafwa (%)

(n=91)

Kapchorwa (%)

(n=176)

Purchased 25.8 46.1

Gift 1.6 0.0

Inherited 1.0 0.3

Born into the herd 0.7 5.9

Government programmes (e.g.

NAADs/Operation wealth creation)

0.3 2.5

Other(specify) 0.3

A few households about 10 % in Manafwa and 16.3% in Kapchorwa lost at least one dairy

cow due to accidents, diseases and/or theft. The average number of cows lost by

households was one cow on average in both districts. In both districts, cow breeding was

mostly by using locally shared bull from the village. A few farmers from Kapchorwa also

use improved shared bull. Only a few households in Kapchorwa used improved methods

for breeding such as artificial insemination (AI)(Figure 6).

FIGURE 6: BREEDING METHODS FOR DAIRY COWS

57

.14

13

.19

28

.57

0

0

47

.16

3.9

8

43

.75

2.8

4

2.2

7

MAIN BREEDING METHOD

Manafwa Kapchorwa

24

Despite farmers using bulls within the village, the households paid for services rendered

from the shared bulls. More than 60% of the farmers paid for services in both districts. The

willingness of farmers to pay for breeding services shows that if such services are made

accessible to farmers, they will be able to improve productivity.

Livestock feed and feeding practices

Most farmers in both sites planted their own forage (68% and 77% in Manafwa and

Kapchorwa respectively). At least 20.3% and 42.7% of farmers in Manafwa and Kapchorwa

had some kind of forages in their farm respectively. Forages included fodder crops,

legumes and/or fodder trees. The different types of forages planted by farmers are shown

in Table 20.

TABLE 20: FODDER GROWN BY SMALLHOLDER FARMERS

Fodder grown Manafwa %

(N= 306)

Kapchorwa %

(N=321)

Napier 19.6 44.1

Calliandra 2.0 0.6

Mucuna 0.0 0.3

Desmodium 0.0 0.3

Most smallholder dairy farmers in both sites planted Napier grass as the main source of

forage. There were very few farmers planting calliandra, a fodder shrub. Improved milk

production in both districts highly depends on the quality of feeds and one of the entry

points for the VIP4FS project would be the promotion of improved feeds and forages.

Reasons cited by farmers for not planting forages are: not having enough land to plant

forages, unavailability of planting material, lack of technical knowledge and the high cost of

planting material (Table 21).

25

3.2.4.2 BEE KEEPING AND HONEY PRODUCTION

Bee keeping is practiced by very few smallholder farmers in districts; 1% and 13.1% of the

farmers in Manafwa and Kapchorwa respectively (Table 22). In Kapchorwa, a higher

number of bee hives were sited inside the national park. According to previous field work,

Uganda Wildlife Authority (UWA) had allowed farmers living adjacent to the forest to site

their beehives in the forest as long as the farmers followed rules set by the authority. Very

few farmers sited their bee hives in their own land.

TABLE 22: APIARY LOCATIONS

Apiary location Manafwa (%)

(n=306)

Kapchorwa (%)

(n=321)

Practicing 1.00 13.1

Own land 0.7 5.0

Forest Reserves 0.3 0.6

National Park 0 6.2

Communal land 0 0.3

Other (specify) 0.9

Of the farmers that practiced bee keeping, the bee hives were often produced by the

farmers themselves using own materials and a few farmers purchased the bee hives from

the market (Table 23). The hives are locally baited to attract bees in both sites.

TABLE 21:REASONS FOR NOT GROWING FODDER

Manafwa (%)

(n=306)

Kapchorwa (%)

(n=321)

Total (%)

(n=627)

Not enough land 72 85 79

Unavailability of planting material 24 26 25

Lack technical knowledge 7 18 13

High cost of planting material 3 5 4

Not aware of the benefits 3 3 3

No interest 0 5 3

Lack of labour 0 18 10

26

TABLE 23: MAIN SOURCE OF BEE HIVES

Main source of bee hives Manafwa (%)

(n=306)

Kapchorwa (%)

(n=321)

From own local materials 0.7 8.1

Purchased from the market 0.3 4.0

NGOs 0.3

Other (specify) 0.6

Households owned an average of 18 and three bee hives in Kapchorwa and Manafwa

respectively. There were no improved bee hives in Manafwa. Households owned three

improved bee hives on average in Kapchorwa. Farmers harvested an average of 2.78 litres

of honey per hive in Kachorwa in the 2015/2016 period. There were no harvests indicated

for Manafwa district during this period.

3.3 INSTITUTIONS AND FARMER GROUPS

3.3.1 PARTICIPATION IN FARMER GROUPS

Farmer groups bring farmers together to obtain benefits collectively through mechanisms

such as collective action that leverage on factors such as bargaining power. They have been

seen as a way to reduce transaction costs by smallholders and of improving their levels of

commercialization. Although farmer groups have been widely recommended for high level

impacts in smallholder farmer livelihoods, only a few farmers in the study sites belonged to

groups. Only 22.9% of members of households in Manafwa and 35.2% in Kapchorwa ever

belonged to groups in the past (Figure 7).

27

FIGURE 7: MEMBERSHIP IN GROUPS

Only one member of the household belonged to groups in both sites. About 17.4% and

23.7% of households in Manafwa and Kapchorwa respectively had only one member

belonging to groups. Only a few households had more than one member belonging to

groups; 7.4% and 4.8% in Manafwa and Kapchorwa respectively.

Some farmers and households members did not join groups mainly because they thought

that there were no groups to join (68.3% and 60.1%) for Manafwa and Kapchorwa

respectively). Other reasons given include not having time for group activities and groups

not seen as beneficial (Table 24)

Kabeywa bee keepers group , Kapchorwa

22

.9%

22

.5%

35

.2%

31

.2%

E V E R B E L O N G E D T O G R O U P B E L O N G E D T O G R O U P W I T H I N 1 2 M O N T H S O F S U R V E Y

MEMBERSHIP IN GROUPS

Manafwa Kapchorwa

28

TABLE 24: REASONS FARMERS DID NOT JOIN GROUPS

Reasons for not joining groups Manafwa (%)

(n=236)

Kapchorwa (%)

(n=208)

No group to join 68.2 60.1

Groups are not beneficial 9.8 14.4

Do not have time for group activities 7.2 17.8

No money to pay for membership fee 7.2 1.9

No money to save or contribute in the group 2.1 0

Not able to find a group that matches interests 1.7 0.96

No information on appropriate group to join 1.3 1.4

Health condition is not good 0.85 0.48

Lack of trust among neighbours 0.85 1.9

Poor leadership of existing groups 0.85 0.48

No reason or need to join the group 0 0.48

Despite a higher number of farmers not joining groups in Kapchorwa and Manafwa, those

farmers that joined groups thought that groups assisted them generate income for the

household (Table 25).

TABLE 25: MAIN REASON FOR JOINING GROUPS

Main reason for joining a group Manafwa %

(n=70)

Kapchorwa %

(n=113)

Increased income generation for my house 75.71 64.6

Social (meeting people and support each other) 8.57 18.58

Access to information and technology 7.14 8.85

Access to benefits e.g. from donor/government 5.71 6.19

Access to labour 2.86 0

Savings accumulation 0 0.88

Other (specify) 0 0.88

Registration of groups in Manafwa was mostly done informally: this is where groups have

internal member registrations but are not registered with formal government structures or

29

organizations working in the area. In Kapchorwa more groups were registered formally

either with local government or with other governing authority (Figure 8).

FIGURE 8: FARMER GROUP REGISTRATION

The groups in both sites were mixed, with a few male only and women only groups in Manafwa. There were

barely any youth groups in both areas.

FIGURE 9: FARMER GROUP COMPOSITION

The farmer groups in the study sites mainly focused on agriculture with the majority of

groups in Manafwa focusing on coffee ( 33%) and dairy (17%) while in Kapchorwa focus

15.8

48.2 84.2

51.8

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

Manafwa Kapchorwa

Formally

Informally

13

.2

6.6

78

.9

1.3

2.7

9.1

0.9

85

.5

1.8

M E N O N L Y W O M E N O N L Y W O M E N Y O U T H M I X E D M I X E D Y O U T H O N L Y

Manafwa Kapchorwa

30

was on coffee (25%), dairy (27%) and honey (27%). Most of the groups in Manafwa

concentrated on financial savings while Kapchorwa groups were more agricultural based

groups (Table 26). Most of the groups in Manafwa are savings (52%) and credit groups

(43%) while those in Kapchorwa offer varied services, ranging from savings (31%) and

credit (30%) to input purchases (7%), joint extension services (11%) and marketing

(16%). There were a few environmental, user associations and advocacy groups in both

study sites.

TABLE 26: FARMER GROUP CHARACTERISTICS

Farmer group

characteristics

Manafwa Kapchorwa

Mukoto Namabya

(n=98)

Butiru

(n=138)

Total

(N=306)

Kapchesombe

(n=105)

Tegeres

(n=126)

Kabeywa

(n=90)

Total

(N=321) (n=70)

Agricultural (%) 17 37 5 21 48 50 61 52

Coffee (%) 67 25 0 33 4 25 62 25

Dairy (%) 33 13 0 17 17 33 0 17

Honey (%) 0 0 0 0 30 17 31 27

Other enterprises

(%)

30 17 0 19 0 63 0 42

Services

received from

farmer groups

Credit/loan (%) 22 30 43 32 38 21 22 30

Produce

marketing (%)

0 7 0 3 12 13 30 16

Input purchases

(%)

0 11 0 5 10 4 4 7

Savings (%) 61 41 52 50 28 42 26 31

Joint extension

services (%)

0 15 5 8 8 17 13 11

Market

information (%)

6 0 0 2 6 0 4 4

Others (%) 11 11 5 9 14 8 13 12

31

Smallholder farmers received credit or loans from the groups which also provided an

avenue for savings. Only a few groups in Kapchorwa provided marketing services and

marketing information to its members. Even with the realization of the importance of

farmer groups, many farmers in the project sites haven’t taken into consideration the

benefits they would derive from membership in groups. Either the farmers are not aware

of these benefits or the groups do not function to its maximum capacity. These results are

quite unexpected as Kapchorwa was thought to be more advanced with institutions on the

ground, with strong farmer groups that provide benefits to their members. Farmer groups,

albeit their perceived importance, also fall short in some of the areas important to the

overall performance of the group. Farmer groups faced challenges such as lack of

commitment to group activities from members, poor leadership and lack of trust among

members (Table 27).

TABLE 27: CHALLENGES FACED BY GROUPS

Main challenges faced by

groups

Manafwa (%)

(n=76)

Kapchorwa (%)

(n=110)

None 47.4 47.3

Embezzlement of funds 14.5 3.6

Lack of trust among

members

13.2 8.2

Lack of commitment from

members

11.8 18.2

Other (specify) 7.9 16.4

Poor leadership 5.3 6.4

To solve the challenges identified, a few solutions by members were suggested comprising:

having clearly defined laws and rules to govern the group especially on property

management owned by the group, training on membership roles and responsibilities,

training on good leadership, putting measures to ensure proper accountability and

transparency with group funds, having more linkages with governing structure such as the

local government for training purposes and also punishment of offenders.

32

3.4 HOUSEHOLD INCOME

Smallholder farmers in both districts have diverse income sources. Among them sale of

crops, sale of coffee, livestock and livestock products were frequently mentioned. Highest

proportion of farmers obtained income from sale of crops in Manafwa (73.0%) and

Kapchorwa (89.1%) (Figure 10

FIGURE 10: PROPORTION OF HOUSEHOLDS WITH HOUSEHOLD INCOMES

2.9

10.6

1.0

0.6

12.9

13.8

17.4

14.1

38.3

17.7

35.7

73.0

0.6

1.0

4.7

8.4

12.8

19.0

26.5

28.7

36.8

40.8

65.1

89.1

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0

Sale of charcoal

Sale of cow's milk

Sale of other milk products

Sale of honey and honey products

Sale of firewood

Sale of non-timber products

Sale of any agroforestry products

Sale of fruits

Sale of livestock

Sale of livestock products

Sale of coffee

Sale of crops

Proportion of households with on farm income sources

Kapchorwa Manafwa

33

A higher proportion of smallholder farmers in Kapchorwa received income from more

sources than farmers in Manafwa. The sources are: sale of crops, sale of coffee, sale of

livestock products, sale of milk and milk products, sale of honey, sale of agroforestry

products, sale of charcoal and sale of fruit (chi2 , p <0.05)(Figure 10).

The respondents were also asked to rate the importance of the different income streams to

contribution to overall households livelihoods and well-being on a scale that ranged from

no importance to very important in contributing to overall contribution to household

income. These ranks were then assigned scores where rating of least importance was given

a score of 1 while very important was given a score of 4. The scores were then weighted to

obtain a standardized score (Table 28).

TABLE 28: INCOME RATINGS FROM DIFFERENT SOURCES IN MANAFWA DISTRICT

Income ratings from different sources

% of households receiving income from this source N=306

Manafwa average income scores

Rank

Income from business 22.9 2.66 1.00

Sale of charcoal 2.6 2.63 2.00

Sale of crops 72.5 2.59 3.00

Income from salaries and wages 13.1 2.58 4.00

Sale of coffee 35.0 2.56 5.00

Sale of livestock 37.9 2.56 6.00

Income from casual work 31.4 2.41 7.00

Sale of any agroforestry products 17.0 2.38 8.00

Sale of cow's milk 10.8 2.33 9.00

Sale of other milk products 1.0 2.33 10.00

Sale of firewood 12.7 2.31 11.00

Sale of livestock products 17.6 2.28 12.00

Sale of non-timber products 13.7 2.26 13.00

Rent 6.9 2.10 14.00

Sale of fruits 14.1 2.07 15.00

Remittance 29.1 2.07 16.00

Sale of honey and honey products 0.7 2.00 17.00

In Manafwa, all income sources were considered somewhat important (average score of 2)

by the households receiving the income. These ratings suggest that the income sources

were thought to be intermittent and might not adequately cover household expenses

(Table 28). There were barely any ratings on sale of honey in the district. This therefore

suggests that farmers either do not practice bee keeping in Manafwa or that they do not

34

receive any income from this venture. Other practices with not enough ratings include sale

of milk products such as ghee, cheese, yoghurt. Farmers in these areas do not add any value

to their products and only sold milk in its raw form.

In Kapchorwa, sale of crops and coffee were considered important to the contribution of

overall livelihoods of the household (average score of 3). The number of farmers selling

coffee was also considerably higher than in Mnafwa. Income from sale of crops, coffee,

livestock products, milk and milk products, honey and agroforestry products were

considered reliable but not sufficient to meet the households needs (average score of 2)

(Table 29).

TABLE 29: INCOME RATINGS FROM DIFFERENT SOURCES IN KAPCHORWA DISTRICT

Income ratings from different sources

% of households receiving income from this source N=321

Kapchorwa average income scores

Ranks

Income from salaries and wages 17.1 3.49 1.00

Sale of coffee 65.1 3.03 2.00

Sale of crops 89.1 3.00 3.00

Income from business 22.7 2.93 4.00

Sale of livestock 36.8 2.84 5.00

Sale of cow's milk 36.4 2.82 6.00

Sale of livestock products 40.8 2.73 7.00


Sale of any agroforestry products 26.5 2.66 9.00

Rent 10.0 2.59 10.00




Remittance 25.2 2.51 14.00


Sale of fruits 28.7 2.48 16.00


Households in Manafwa and Kapchorwa greatly differed between scoring of the different

incomes sources. Kapchorwa households significantly considered almost income sources to

be of greater importance than those in Manafwa (Table 30).

35

TABLE 30: OFF FARM INCOME SOURCES IN MANAFWA AND KAPCHORWA

Income ratings from different sources Manafwa Kapchorwa P-Value

Sale of crops 2.59 3.0 0.00***

Sale of coffee 2.56 3.03 0.00***

Sale of livestock 2.56 2.83 0.00***

Sale of livestock products 2.28 2.72 0.00***

Sale of cow's milk 2.33 2.82 0.00***



Sale of any agroforestry products 2.39 2.66 0.04**



Sale of fruits 2.07 2.48 0.00***



Income from business 2.66 2.93 0.04**

Income from salaries and wages 2.58 3.49 0.00***

Remittance 2.07 2.51 0.00***

Rent 2.10 2.59 0.01**

3.4.1OFF FARM INCOME

In both Manafwa and Kapchorwa districts, only a few smallholder farmers received income

from off-farm income such as casual work, business, wages, remittances and rent from

commercial buildings. The proportion of farmers that received income from casual work in

Manafwa and Kapchorwa varied significantly (p<0.05), where 42.1% and 31.4% of farmers

received income from casual work in Kapchorwa and Manafwa respectively ( Table 28 and

Table 29). Business was considered the highest contributor by households in Manafwa

while wages and salaries was considered more important in Kapchorwa; these two

activities were only practiced by 22.9% and 17.1% of households in Manafwa and

Kapchorwa respectively. Agriculture, even if not ranked highly in importance, has the

highest proportion of farmers dependent on it for general livelihood and well-being.

36

3.5 DIETARY DIVERSITY

Dietary diversity is a proxy indicator of household food security. Dietary diversity presents

the number of unique foods consumed over a given period of time and is considered a good

measure of household food access. Household food security as a measure of well-being

encompasses three dimensions: availability (measure of food that is physically available in

the relevant vicinity of a population: access (measure of the population ability to food

during a given period and utilization (whether the population will be able to derive

sufficient nutrition during a given period. A dietary diversity score can be created, which is

the sum of the different food groups consumed. Dietary diversity aims to identify

households that are food insecure, to characterize their insecurity, monitor changes in their

circumstances and assess the impact of interventions. Varied diet is associated with

improved birth weight and general health in the households.

Dietary diversity was presented by use of “count” which is the number of food categories

consumed by a given household. Counting the number of food categories is more indicative

of diversity than count of different food types as the types would be providing similar

nutrients for instance a household that consumes proteins, vitamins and roots would be

considered more diet diverse than a household that consumes different type of cereals.

More than 90% of households in both Manafwa and Kapchorwa districts consumed cereals,

sugars, beverages, vegetables and oils (Table 31). Consumption of cereals, beverages and

vegetables significantly varied between the districts. A higher number of households in

Manafwa significantly consumed roots & tubers and pulses than households in Kapchorwa.

On the other hand more farmers in Kapchorwa consumed milk at a higher rate that those

households in Manafwa. The least number of households consumed fish and eggs in both

districts. Fruits were consumed by at least 50% of households in Manafwa and Kapchorwa

(Table 31).

37

TABLE 31: HOUSEHOLD CONSUMPTION OF DIFFERENT FOOD TYPES

Household Consumption of

different food types

Manafwa (%)

n=306

Kapchorwa (%)

n=321

Chi-square

test

Cereals 97.4 99.4 0.047**

Sugar and sugar products 94.8 96.3 0.366

Beverages 94.1 96.9 0.094*

Vegetables 93.1 88.2 0.033**

Oils 91.8 94.7 0.15

Roots and tubers 90.5 58.9 0.000***

Pulses 83.7 76.9 0.035*

Meat 83.7 76.9 0.335

Milk 57.8 77.3 0.000***

Fruits 52.3 53.9 0.687

Eggs 37.9 38.9 0.791

Fish 19.9 20.6 0.845

Further analysis of consumption trends between sub-counties show that some sub-

counties varied slightly in consumption of different food types. In Manafwa, consumption

of roots & tubers, meat, eggs, milk and vegetables did not significantly differ between the

different sub-counties of interest (Table 32). Households in Mukoto consumed more

cereals, sugars, oils, fruits and beverages than the other two sub-counties. While

households in Namabywa consumed pulses more than the other two sub-counties and

households in Butiru consumed more fish than the households in other households. In

Kapchorwa, households that consumed cereals, roots & tubers, meat, fish, sugars,

vegetables, fruits and beverages did not significantly differ between the three sub-counties.

Tegeres sub-counties, which is situated in the upper highlands, consumed more pulses,

eggs and milk than the other sub-counties. Kapchesombe sub-counties consumed more oils

than the other sub-counties.

38

TABLE 32: FOOD TYPE CONSUMPTION ACROSS SUBCOUNTIES

Food type

by different

sub-

counties

Manafwa (%)

n=306

Chi-

square

Kapchorwa (%)

n=321

Chi-

square

Mukoto

(n=70)

Namabya

(n=98)

Butiru

(n=138)

P value Kapchesombe

(n=105)

Tegeres

(n=126)

Kabeywa

(n=90)

P value

Cereals 100.0 99.0 94.9 0.047** 99.0 100.0 98.9 0.517

Roots and

tubers

91.4 86.7 92.8 0.286 61.9 52.4 64.4 0.514

Pulses 87.1 90.8 76.8 0.011** 76.2 85.7 65.6 0.002***

Meat 44.3 55.1 61.6 0.059 55.2 55.6 42.2 0.105

Fish 5.7 6.1 37.0 0.000*** 19.0 23.8 17.8 0.500

Eggs 44.3 39.8 33.3 0.275 42.9 49.2 20.0 0.000***

Milk 65.7 54.1 56.5 0.294 81.0 84.9 62.2 0.000***

Sugar and

sugar

products

98.6 96.9 91.3 0.043** 94.3 99.2 94.4 0.082

Oils 98.6 93.9 87.0 0.010** 96.2 98.4 87.8 0.002***

Vegetables 95.7 95.9 89.9 0.120 91.4 87.3 85.6 0.417

Fruits 62.9 56.1 44.2 0.026** 61.0 54.0 45.6 0.099

Beverages 100.0 94.9 90.6 0.022** 95.2 99.2 95.6 0.156

A comparison was also undertaken on how the different household types: male headed and

female headed households differed in consumption of different food types. Female and

male headed households did not significantly differ in consumption of almost all the

different food types. Only consumption of eggs and oils differed between male and female

headed households in Manafwa as higher proportion of male headed households consumed

eggs. In Kapchorwa, a higher proportion of male headed households consumed cereals and

oils than female headed households (Table 33).

39

TABLE 33: FOOD TYPES IN DIFFERENT HOUSEHOLD TYPES

Food types per

household

type

Manafwa (%) Kapchorwa (%)

Male headed

households

(n=264)

Female

headed

households

(n=41)

Chi-

square

Male

headed

households

(n=286)

Female

headed

households

(n=35)

Chi-

square

Cereals 97.3 97.6 0.937 99.7 97.1 0.075*

Roots and

tubers

91.3 85.4 0.229 42.3 471.4 0.217

Pulses 83.3 85.4 0.744 76.6 80.0 0.65

Meat 57.2 43.9 0.111 52.1 48.6 0.694

Fish 20.5 14.6 0.383 20.6 20.0 0.931

Eggs 40.9 19.5 0.009** 38.8 40.0 0.892

Milk 57.6 61.0 0.682 76.9 80.0 0.682

Sugar and

sugar products

94.7 95.1 0.91 96.2 97.1 0.771

Oils 93.6 80.5 0.005** 95.8 85.7 0.012**

Vegetables 93.6 90.2 0.435 88.1 88.6 0.937

Fruits 53.8 43.9 0.238 53.8 54.3 0.961

Beverages 94.3 92.7 0.679 96.9 97.1 0.926

3.5.1 COMPARISON IN CONSUMPTION OF DIFFERENT FOOD CATEGORIES

In Kapchorwa and Manafwa, all households consumed at least three different food

categories with a higher proportion of households consuming all five food categories

within a seven day period (Table 34). The average number of food categories consumed by

households in Kapchorwa and Manafwa did not significantly differ. The averages were 4.52

and 4.54 for Manafwa and Kapchorwa respectively.

40

TABLE 34: COUNT OF FOOD CATEGORIES CONSUMED BY HOUSEHOLDS

Number of foods categories

consumed by households

Manafwa (%)

N=306

Kapchorwa

(%)

N=321

1 1.0 0.3

2 2.9 2.2

3 5.2 5.6

4 25.2 27.4

5 65.7 64.5

During the time of the study, almost all of the households could be considered diet diverse

as over 50% of the households consumed all the food categories within a 7 day period

before the study (Table 35). More than 75% of the households consumed proteins, pulses,

fruits and vegetables, grains, sugars and oils. The consumptions of food items such as: fruits

and vegetables, sugars and oils, did not differ significantly for the different districts p>0.05.

Consumption of proteins was higher in Kapchorwa households than those in Manafwa

p<0.05. On the other hand, pulses were consumed by households in Manafwa more than

households in Kapchorwa. Grains, roots & tubers were consumed by all households

interviewed.

TABLE 35: HOUSEHOLD DIETARY DIVERSITY

Households Dietary

Diversity (HDD)

Manafwa (%)

N=306

Kapchorwa (%)

N=321

Chi-square

Proteins 78.1 86.6 0.00

Pulses 83.7 76.9 0.035

Fruits and vegetables 93.1 91.3 0.386

Staples 100.0 100.0 -

Sugars 96.7 98.8 0.087

Oils 91.8 94.7 0.15

41

An analysis of the number of times households consumed the different food varieties,

showed that proteins were consumed more than any other food category. Households

consumed proteins an average of 24.05 and 29.73 times in a 7 day period for Manafwa and

Kapchorwa respectively (Table 36). The difference in consumption of proteins was higher

in Kapchorwa than in Manafwa (p<0.000). This could be attributed to the high number of

dairy cattle in Kapchorwa and as earlier indicated most of the households consumed dairy

products from their farm.

TABLE 36: NUMBER OF TIMES FOOD CATEGORY WAS CONSUMED

Number of times food

category was consumed

within a 7 day period

Manafwa Kapchorwa T test

Mean SE Mean SE p value

Proteins 24.05 0.91 29.73 0.88 0.000***

Staples 17.37 0.29 15.91 4.56 0.000***

Pulses 10.84 0.33 10.62 0.35 0.639

Fruits and vegetables 7.19 0.18 6.70 0.18 0.063

Sugars 5.41 0.12 5.98 0.09 0.000***

Oils 2.33 0.07 2.89 0.06 0.000***

Sugars and oils were consumed a significantly higher number of times in Kapchorwa than

in Manafwa. Households in Manafwa consumed roots, tubers and grains significantly more

times than households in Kapchorwa, average of 17.37 and 15.91 times respectively. There

was no significant difference in consumption of pulses and fruits and vegetables between

the districts.

The patterns of dietary diversity between different households did not significantly differ

between male and female headed households (Table 37).

42

TABLE 37: PATTERNS OF DIETARY DIVERSITY

Total number of food categories

consumed by households

Male headed

Households (%)

(N=550)

Female headed

households (%)

(N=76)

1 0.36

2 1.27 5.26

3 2.18 5.26

4 6.36 5.26

5 26.18 19.74

6 63.64 64.47

There was no significant difference in patterns of consumption between female and male

headed households P>0.05.

3.5.2 DETERMINING TOTAL CONSUMPTION SCORE FOR DIFFERENT HOUSEHOLDS

Food consumption scores between the two districts differed significantly as households in

Kapchorwa district had higher scores than households in Manafwa (p<0.05) (Table 38)

TABLE 38: FOOD CONSUMPTION SCORE BETWEEN MANAFWA AND KAPCHORWA

Group Observations Mean SE

Manafwa 306 59.63 1.31

Kapchorwa 321 64.81 1.31

Combined 627 62.28 0.93

As earlier highlighted in the methodology section, percentiles were used to categorize

households into different food consumption categories: poor, borderline and acceptable.

The percentage of households in the three categories are presented in Figure 11. The

proportion of households in the different food consumption categories were significantly

different in both district (p<0.1). The mean scores for each of the food consumption

categories were: 32.99, 62.10 and 92.49 for poor, borderline and acceptable respectively.

43

FIGURE 11: FOOD CONSUMPTION CATEGORIES

Analysis of variance (ANOVA) was used to validate the categorization. The ANOVA results

showed that there is a significant difference in total numbers of times households

consumed different food categories (Fig 12). There was significant difference between

consumption levels of different household types.

FIGURE 12: ANOVA OF FOOD CONSUMPTION SCORE BETWEEN HOUSEHOLD TYPES

The total number of different food types taken within the 7 day period by each of the food

consumption categories also differed between poor, borderline and acceptable categories

29

.41

47

.39

23

.2

21

.5

52

.02

26

.48

P O O R B O R D E R L I N E A C C E P T A B L E

HH FOOD CONSUMPTION CATEGORIES

Manafwa Kapchorwa

Total 501.71292 626 .80145834

Residual 309.17616 624 .49547462

fcs_ug 192.53676 2 96.268379 194.30 0.0000

Model 192.53676 2 96.268379 194.30 0.0000

Source Partial SS df MS F Prob>F

Root MSE = .7039 Adj R-squared = 0.3818

Number of obs = 627 R-squared = 0.3838

. anova total_dds fcs_ug;

44

in both districts. In the acceptable category, households consumed all food categories in

both districts while the consumption in the poor category varied (Table 39).

TABLE 39: FOOD CATEGORIES CONSUMED BY DIFFERENT FOOD CONSUMPTION CLUSTERS

Total number

of food

categories

consumed

Manafwa

(n=306)

Kapchorwa

(n=321)

Poor Borderline Acceptable Poor Borderline Acceptable

1 2.2 0.0 0.0 0 0 0

2 6.7 0.0 0.0 7.2 0.0 0.0

3 11.1 0.0 0.0 7.2 0.6 0.0

4 16.7 2.1 1.4 24.6 1.8 0.0

5 42.2 21.4 2.8 49.3 28.1 8.2

6 21.1 76.6 95.8 11.6 69.5 91.8

A comparison between the food consumption categories and proportion of different

household types showed no significant difference in the households categorizations (Chi-

square p=0.899) (Figure 13).

FIGURE 12: FOOD CONSUMPTION CLUSTERS IN MANAFWA AND KAPCHORWA

29

.2%

31

.7%

47

.7%

43

.9%

23

.1%

24

.4%

M A L E H E A D E D H O U S E H O L D S F E M A L E H E A D E D H O U S E H O L D S

MANAFWA HH

poor borderline acceptable

45

In Kapchorwa, even though a higher proportion of female headed households belonged to

the borderline and acceptable categories, there was no significant difference with the

proportion of male headed households in the different food consumption categories

(p=0.487)(Figure 14).

FIGURE 13: FOOD CONSUMPTION CLUSTERS BETWEEN DIFFERENT HOUSEHOLD TYPES

3.6 ASSET ENDOWMENTS

We adapted the DFID sustainable livelihoods framework to identify opportunities for

inclusive and sustainable value chain development to achieve balanced improvement of

key livelihood assets (human, social, natural, physical and financial) as elaborated in the

5Capitals tool. This links household access to livelihood assets with greater well-being and

resilience. Likewise, the economic viability and performance of smallholder enterprises is

linked to their access to business assets. We used this framework to assess the extent to

which existing asset endowments determine the outcomes of value chain development,

relationships between asset building at enterprise and household levels, and the role of

market, political and institutional factors in facilitating or hindering favourable outcomes,

separating the changes caused by interactions and interventions in value chains from those

induced by the overall context.

22

.4%

14

.3%

51

.0%

60

.0%

26

.6%

25

.7%

M A L E H E A D E D H O U S E H O L D S F E M A L E H E A D E D H O U S E H O L D S

KAPCHORWA HH

poor borderline acceptable

46

The sustainable livelihood framework comprises of five assets namely human capital,

financial capital, physical capital, natural capital and social capital, then households

combine these assets with activities which leads to a construction of a portfolio of activities

such as agriculture, livelihood diversification to achieve their livelihood goals which can

also be called a livelihood strategy which in turn generates a higher income leading to the

reduction of poverty, reduced vulnerability(economic shocks, stress and seasonality) and

improved food security.

People’s livelihood strategies are determined by the diversity of assets that they can access

taking into account the vulnerability context as well as transforming structures and

processes. In Manafwa and Kapchorwa the assets in Table 40 were owned by the

interviewed households. Almost all households owned a hoe and a machete while a

substantial proportion owned an axe and some a slasher. Even though a substantial

percentage of farmers in both districts owned livestock, none of the households owned a

chaff cutter which is used for chopping livestock feed. Similarly, few households owned an

aluminium bucket for storing milk. Less than 10% had zero grazing units. This also applies

to coffee, the number of coffee farmers was found to be high in both districts but only a few

farmers owned coffee hullers.

A dairy cow in a zero-grazing unit

47

TABLE 40: FARM ASSETS OWNED BY HOUSEHOLDS

Farm assets owned Manafwa (%)

(n=306)

Kapchorwa (%)

(n=321)

Hoe 100.00 98.80

Panga/Machete 91.80 92.20

Axe 68.00 73.80

Slasher 31.70 22.10

Spade 14.10 20.90

Fork or Hoe 5.20 2.50

Plough/animal drawn plough 4.20 9.00

Pruning Knives 4.20 5.60

Watering can 3.90 10.30

Wheelbarrow 3.60 8.10

Sprayer pump 3.30 15.00

Milk Can 2.90 13.70

Zero grazing units 2.60 7.50

Aluminium bucket 1.30 1.20

Coffee Huller 0.70 0.60

Tractor 0.30 0.60

Water storage 0.30 1.90

Livestock feed mixture 0.00 3.40

Modern bee hives 0.00 0.60

Harrow/Cultivator 0.00 0.00

Smoker 0.00 0.30

Animal drawn cart 0.00 0.30

Motorized spray pump 0.00 0.30

Motorized watering pump 0.00 0.30

Chaff Cutter 0.00 0.00

Households were also asked to indicate the household assets they owned at the time of the

study. From the results, a higher percentage of farmers owned furniture and furnishings,

radio and mobile phones in both districts. The proportion of farmers in Manafwa that

owned furniture, mobile phones and bicycles was significantly higher than farmers in

48

Kapchorwa (Table 41). A higher percentage of households in Kapchorwa owned radio,

jewelry, household appliances and non-farm land than households in Manafwa.

TABLE 41: HOUSEHOLD ASSET OWNERSHIP

Household assets Manafwa (%)

N=306

Kapchorwa %

N=321

Test of

significance

Furniture and furnishings 76.80 51.10 ***

Radio/cassette/DVD player 60.80 72.90 ***

Mobile phone 51.60 44.20 **

Bicycle 24.50 2.80 ***

Jewelry and watches 6.50 14.60 ***

Households appliances 5.20 12.80 ***

Solar panel/electrical inverters 4.20 17.10 ***

Rental house 2.30 5.30

Non-farm land 2.30 21.20 ***

Television 2.30 4.70

Motor cycle 2.30 3.70 ***

Generators 1.00 0.30

Internet access 0.70 2.80 ***

Commercial building 0.30 1.60

Computer 0.30 1.60

Other household assets 0.30 0.60

Motor vehicle 0.00 2.50

Transport equipment 0.00 0.00

Electronic equipment 0.00 1.60 ***

***p value <0.000, ** p value<0.05

Other household assets that are necessary for the households’ well-being are summarized

in Table 42. From the table, most households more than one room in their main house

excluding kitchen and toilets. Firewood was the main source of fuel in both districts, mud

was the main floor material, a higher percentage of household got their drinking water

from a protected dug well and have traditional toilet pit, the main wall materials were

sticks and mud while iron sheets were mainly used as roofing materials (Table 42)

49

TABLE 42: OTHER HOUSEHOLD ASSETS OWNED BY HOUSEHOLDS IN MANAFWA AND KAPCHORWA

Different asset types in households Manafwa (%)

(n=306)

Kapchorwa (%)

(n=321)

Total

(%)

(n=627)

Households with

Electricity

1.0 11.8 6.5

Number of rooms

in the main house

Zero or one room 17.0 14.0 15.5

Two rooms 26.5 16.2 21.2

Three rooms 23.2 26.2 24.7

Four rooms 20.3 26.5 23.4

More than 4 rooms 13.1 17.1 15.2

Main source of

fuel

Gas 0.0 0.6 0.3

Charcoal 1.0 1.6 1.3

Firewood 98.7 100.0 99.4

Kerosene 0.3 0.0 0.2

Main material

used for floor

Dirt/soil/dung 90.2 80.4 85.2

Wood 2.6 8.1 5.4

Cement 6.9 11.5 9.3

Other 0.3 0.0 0.2

Main source of

drinking water

Piped water into home 0.3 13.4 7.0

Public tap/stand pipe 0.7 21.8 11.5

Borehole/tube well 28.1 0.9 14.2

Protected dug well 50.7 44.9 47.7

Unprotected well/spring 13.1 13.7 13.4

Water provided by car 0.0 0.3 0.2

River, pond, stream 7.2 5.0 6.1

Main type of toilet

facility

Private flush toilet 0.0 0.6 0.3

Private improved pit 1.6 4.7 3.2

Private traditional pit 72.5 84.7 78.8

Shared pit latrine 24.2 8.7 16.3

Bush, forest 1.0 1.2 1.1

Other 0.7 0.0 0.3

Main material

used for walls

Wood 0.0 5.6 2.9

Cement block 2.0 4.7 3.3

Zinc (Iron sheet) wall 2.9 2.8 1.4

50

Stone and mud 3.9 0.6 2.2

Dirt bricks 45.8 18.1 31.6

Sticks and mud 44.1 64.5 54.5

Other 0.0 0.3 0.2

Stone and cement 2.3 3.1 2.7

Burnt bricks 2.0 0.3 1.1

Main Material

used for roof

Iron sheet (zinc) 71.2 87.9 79.7

Grass/thatch/bamboo 27.8 10.9 19.1

Plastic

sheet/tarpaulin/canvas

0.0 0.3 0.2

Stone and mud 0.0 0.6 0.3

Other 1.0 0.3 0.6

3.6.1 WEALTH INDEX

Wealth index provides a stable and understandable yardstick for evaluating and comparing

the economic situation of households, social groups and societies across all regions of the

developing world. A household’s ranking on wealth index indicates to what extent the

household possesses basic set of assets, valued highly by people all across the globe.

Wealth index also measures a household’s level of material well-being by looking at the

household’s possession of durables, access to basic services, and characteristics of the

house in which it is living. Households that own more expensive durables, have a better

quality house and have access to basic services are considered to have a higher level of

material well-being than household with less expensive durables, worse housing and no

access to services. During computation of the wealth index, assets that contribute to

material well-being are important depending on the country or site of interest (Smits and

Steendijk, 2014). Material well-being is associated with the satisfaction of the basic needs

of food, clothing and safety/shelter, which have to be met to survive. Material well-being

therefore refers to the possession of goods and access to basic services that make life easier

and more comfortable. Such assets include: all kinds of relatively cheap assets but make

people more comfortable (tables, chairs, carpets, beds). Household access to electricity

opens up infinite new possibilities for increasing material well-being in relatively cheap

ways. With electric light, the time that can be spent on useful and leisure activities

51

increases considerably. Electric tools and utensils reduce time spent on cooking and on

work around the home. Access to clean water allows households workload to reduce, as

this may save an often considerable amount of time spent on fetching water.

The quality of the house in which the household lives in is also an important aspect of

material well-being. The kind of building and flooring material determines how much

maintenance there is to the house, whether rain, wind and pests are kept outside well, and

how comfortable the house is. Having more than one room, a separate kitchen and

bathroom, and a decent in-house toilet facility greatly enhances quality of living. Besides

technical equipment that makes life easier, material wellbeing can also be improved by

means of transportation and communication equipment. With a bike, cart, boat, motorbike

or car transportation of heavy loads becomes easier and travelling time is reduced. Radio

and television bring the world into the home and phones, computers and the internet

greatly enhance communication and access to information (Smits and Steendijk, 2014).

Assets, including farm level and household level assets, that are durable with ability to

contribute to the household livelihood were included in the analysis of the wealth index

(Table 43).

In Table 43, last column contains the 1st principal component index obtained by running a

principal component analysis on all the identified assets. The 1st principal index is used to

standardize the scores. The first principal follows a normal distribution with a mean of zero

and standard deviation of . The first principal component yields a wealth index that

assigns larger weight to assets that vary the most across households so that an asset found

in all households is given a weight of zero.

Fuel wood, floor materials, roof, water resources had to be categorized into: high, medium

and low quality assets to allow for agglomeration of different assets that are thought to

have similar weights be included in the same category.

52

TABLE 43: SUMMARY OF ASSETS USED TO COMPUTE WEALTH INDEX

Household assets Manafwa (%)

N=306

Kapchorwa %

N=321

1st Principal

Component index

Furniture and furnishings 76.80 51.10 -0.0454

Radio/cassette/DVD player 60.80 72.90 0.0634

Mobile phone 51.60 44.20 0.1101

Bicycle 24.50 2.80 -0.0054

Solar panel/electrical inverters 4.20 17.10 0.1429

Rental house 2.30 5.30 0.1616

Land ownership 98.4% 96.9% 0.012

Television 2.30 4.70 0.2295

Motor cycle 2.30 3.70 0.0596

Generators 1.00 0.30 -0.0033

Internet access 0.70 2.80 0.0983

Computer 0.30 1.60 0.2013

Motor vehicle 0.00 2.50 0.2732

Fuel wood

High quality 0.0 0.6 0.2769

Medium quality 1.3 1.6 0.048

Low quality 98.7 97.8 -0.1624

Floor material

High quality 6.9 11.5 0.2979


Low quality 90.2 80.4 -0.2604

Wall materials


Medium quality 45.8 23.7 -0.0383

Low quality 44.1 67.3 -0.1156

Toilet



Low quality 97.7 94.7 -0.277

Roof materials

High quality 71.2 87.9 0.0854


Low quality 27.8 11.5 -0.1065

Water sources

High quality 0.3 13.4 0.2367

Medium quality 51.3 67.0 -0.0664

Low quality 48.4 19.6 -0.0589

Number of

rooms in the

households

Zero or one room 17.0 14.0 -0.0916

two rooms 26.5 16.2 -0.0759

three rooms 23.2 26.2 -0.0138

four rooms and more 33.3 43.6 0.144

53

The categorization was as follows:

Water supply:- high quality is bottled water or water piped into dwelling or premises;

- medium quality is public tap, protected well, tanker truck, etc;

- low quality is unprotected well, borehole, spring, surface water, etc.

Toilet facility:- high quality is any kind of private flush toilet;

- medium quality is public toilet, improved pit latrine, etc.;

- low quality is traditional pit latrine, hanging toilet, or no toilet facility.

Floor quality: - high quality is finished floor with parquet, carpet, tiles, ceramic etc.;

- medium quality is cement, concrete, raw wood, etc.;

- low quality is none, earth, dung etc.

3.6.1.1 WEALTH CATEGORIES

Using the equation and formula described above, the following three categories of

households were generated: low income, middle income and high income . Households

in low income category were those that their wealth scores fell below the 25th percentile

while middle income category scores fell between 25th and 75th percentiles of the wealth

index score, high level income category were considered to fall above the 75th percentile

score. The wealth categories had an average score of-1.3179, -0.54933 and 2.418 for low,

middle and high income levels respectively. Due to the application of PCAs 1st component

the wealth score can take both negative and positive values.

The proportion of households for each wealth category are presented in Figure 15

54

FIGURE 14: WEALTH CATEGORIES PROPORTIONS IN MANAFWA AND KAPCHORWA

The average wealth scores for each of the districts are presented in Table 45. Kapchorwa

district had a higher score than households in Manafwa, and the difference in mean score

was significant (p value<0.000). Kapchorwa households can therefore be considered

richer than households in Manafwa on average (Table 44).

TABLE 44: DIFFERENCE IN WEALTH SCORE BETWEEN MANAFWA AND KAPCHORWA

Group N Mean SE

Manafwa 306 -0.414 0.071

Kapchorwa 321 0.395 0.168

Combined 627 -0.000 0.094

diff -0.810 0.186

The low income category differed in scores between the two districts where the average

wealth score for households in Manafwa was lower than households in Kapchorwa (Table

45). The number of farmers in this category in Manafwa was also significantly higher than

households in Kapchorwa.

30

.4%

53

.9%

15

.7%

20

.2%

45

.8%

34

.0%

L O W I N C O M E M I D D L E I N C O M E H I G H I N C O M E

WEALTH INDEX

Manafwa Kapchorwa

55

TABLE 45: SUMMARY STATISTICS OF WEALTH CATEGORIES

Wealth

categories

Manafwa Kapchorwa T test

Mean SD Mean SD

Low income -1.36 0.2295 -1.258 0.2062 0.0049***

Middle income -0.5505 0.2625 -0.5481 0.2642 0.9358

High income 1.8834 1.6165 2.6534 4.3616 0.2375

There were no significant differences in average score between middle and high income

categories in Manafwa and Kapchorwa. The percentages between the two districts were

however distinct: Kapchorwa had a higher proportion of farmers in the high income

category while Manafwa had more households in the lower category.

3.6.1.2 WEALTH CATEGORIES BY GENDER

There was a significant difference between the gender of the farmer in the different wealth

categories. A higher proportion of female farmers were in the middle and high income

category compared to their male counterparts (Figure 16).

FIGURE 15: WEALTH CATEGORIES BY GENDER

27

.7%

47

.1%

25

.1%

22

.1%

53

.7%

24

.3%


GENDER OF FARMER

male female

56

A comparison between household types shows that there was no significant difference in

the wealth categories of the different household types although male headed households

had a slightly higher proportion in the low income category. A higher percentage of female

headed households belonged to the middle income category (Figure 17).

FIGURE 16: WEALTH CATEGORIES OF DIFFERENT HOUSEHOLD TYPES

A comparison of wealth categories between different sub counties indicated that in

Manafwa district; majority of households in Mukoto and Namabya sub-counties were in the

middle income category, 71.4% and 65.3% respectively while Butiru sub county had more

households in the low income category (Table 46). In Kapchorwa district, a higher

proportion of households belonged to the middle income category. Kapchesombe and

Tegeres however had more households in the high income while Kabeywa had more

farmers in the low income category (Table 46).

25

.5%

49

.3%

25

.3%

22

.4%

53

.9%

23

.7%


WEALTH CATEGORIES OF DIFFERENT HOUSEHOLD TYPES

Male headed households Female headed household

57

TABLE 46: WEALTH CATEGORIES OF HOUSEHOLDS IN DIFFERENT SUBCOUNTIES

Wealth categories

of households

Manafwa Kapchorwa

Sub-county (%) Sub-county (%)

Mukoto

(n=70)

Namabya

(n=98)

Butiru

(n=138)

Total

(n=306)

Kapchesombe

(n=105)

Tegeres

(n=126)

Kabeywa

(n=90)

Total

(n=321)

Low income 21.4 11.2 48.6 30.4 13.3 16.7 33.3 20.2

Middle income 71.4 65.3 37.0 53.9 45.7 43.7 48.9 45.8

High income 7.1 23.5 14.5 15.7 41.0 39.7 17.8 34.0

These results indicate that Namabya and Kapchesombe are high income sub counties in

Manafwa and Kapchorwa respectively. On the other hand, Butiru and Kabeywa are low

income sub counties in Manafwa and Kapchorwa respectively. The difference in asset

ownership between the six sub counties are presented in Table 48. In all sub counties, a

high percentage of farmers owned furniture with highest proportion of 90% of households

owning furniture in Butiru and Tegeres sub county having a higher percentage of 59% of

furniture in Kapchorwa. The average number of households owning furniture in

Kapchorwa was lower than those in Manafwa. Very few households in Manafwa owned

household appliances (kettle, flat iron etc) while 85% of farmers owned them in

Kachesombe and 13% in Tegeres sub county. This could be attributed to availability of

electricity in the area where 13% and 17% of farmers indicated to have electricity in their

homes in the two sub counties in Kapchorwa. Only 1% of households had electricity in

Manafwa district (Table 47).

In terms of mobility around the district, 25% percentage of households in Manafwa owned

bicycles with more households in Butiru (36%) of total households owning them. In

Kapchorwa, only 3% of households owned bicycles and 4 % owning motorcycles most of

whom were from Kapchesombe sub county. Whereas none of the households interviewed

in Manafwa owned any vehicles, 2% of farmers in Kapchorwa of whom resided in

Kapchesombe and Tegeres owned vehicles. Practically all households used firewood as

main source of fuel for working. This therefore means that use of firewood did not

contribute much to the wealth scores. An asset owned by all farmers has a component

score of zero and does not therefore contribute to overall wealth score.

58

TABLE 47: ASSET OWNERSHIP OF HOUSEHOLDS IN DIFFERENT SUBCOUNTIES

Manafwa Kapchorwa

Sub-county (%) Sub-county (%)

Mukoto

(n=70)

Namabya

(n=98)

Butiru

(n=138)

Total

(n=306)

Kapchesombe

(n=105)

Tegeres

(n=126)

Kabeywa

(n=90)

Total

(n=321) Rental house 1 5 1 2 9 5 2 5 Commercial building 0 0 1 0 0 1 4 2 Non-farm land 1 2 3 2 17 28 17 21 Furniture 74 60 90 77 54 59 47 54 Household appliances 3 8 4 5 85 13 9 36 Television 3 3 1 2 9 5 0 5 Radio/Cassette/DVD 59 77 51 61 27 79 64 58 Generator 0 2 1 1 1 0 0 0 Panel/electric inverter 0 9 3 4 15 28 4 17

Bicycle 6 21 36 25 5 2 1 3 Motor cycle 0 5 1 2 10 1 0 4 Vehicle 0 0 0 0 3 4 0 2 Mobile phone 57 54 47 52 59 45 26 44 Computers 0 0 1 0 1 2 1 2 Internet access 0 2 0 1 0 4 4 3

Fuel for cooking 0 0 0 0 0 0 0 0 Gas 0 0 0 0 1 1 0 1 Charcoal 0 2 1 1 3 0 9 3 Firewood 100 98 99 99 96 98 100 98 Kerosene 0 0 0 0 0 0 0 0

Electricity 0 1 1 1 13 17 2 12

Type of toilet

Private flush toilet 0 0 0 0 1 1 0 1 Private improved pit latrine 1 3 1 2 9 5 0 5 Private traditional pit 76 74 70 73 84 86 84 85 Shared pit latrine 20 19 30 24 5 8 14 9 Bush, forest 1 2 0 1 2 1 1 1 Floor material

Dirt/soil/dung 96 87 90 90 79 76 88 80 Wood 4 2 2 3 7 8 10 8 Cement 0 10 8 7 14 16 2 12 Wall material

Wood 0 0 0 0 8 6 3 6 Cement block 0 3 2 2 5 8 0 5 Zinc wall 0 0 0 0 3 2 3 3 Stone and mud 0 6 4 4 2 0 0 1 Dirt bricks 39 48 48 46 19 16 20 18 Sticks and mud 61 36 41 44 59 63 72 64

59

Stone and Cement 0 4 2 2 4 5 0 3 Burnt bricks 0 3 2 2 1 0 0 0 Roof material

Iron sheets 83 90 52 71 90 88 86 88 Grass/thatch/bamboo 16 9 47 28 10 10 14 11 Plastic sheet/tarpaulin 0 0 0 0 0 1 0 0 Stone and mud 0 0 0 0 0 2 0 1 Water source

Piped water into home 0 1 0 0 20 16 2 13 Public tap/stand pipe 0 2 0 1 20 13 37 22 Borehole/tube well 1 9 55 28 0 1 2 1 Protected dug well/spring 57 66 36 51 38 52 42 45 Unprotected well/ spring 14 20 7 13 17 10 14 14 Water provided by car 0 0 0 0 0 1 0 0 River, pond, stream 27 1 1 7 5 7 2 5

A higher proportion of households in the different sub counties in both districts had private

pit latrines within their compound. Some however had shared latrines with neighbors. A

comparison between asset ownership in different wealth categories shows a higher

percentage of households in high income categories owned information communication

technologies (ICTs) such as television and radios than those in medium and lower

categories. Other characteristic include: ownership of mobile phones, bicycles, solar panels,

television, have internet access, own computers, have motor vehicles and electricity in the

house (Table 48). Although almost all households used firewood as main source of fuel

wood, high income households still used other sources of energy such as charcoal, kerosene

and gas. Medium and low income households only used firewood and crop residue as fuel

for cooking.

The floor material used by low and most of the middle income households was of low

quality such as dirt soil or dung. High income households had other floor materials such as

wood, cement and tiles. Middle and low income used dirt/molded bricks, wood, iron sheets

and sticks and mud in making walls of their homes. High income used high quality

materials such as burnt bricks, stone and cement.

60

TABLE 48: OWNERSHIP OF HOUSEHOLD ASSETS BY DIFFERENT WEALTH CATEGORIES

WEALTH CATEGORIES (% of households)

Household assets Low (n=158)

Middle (n=312)

High (n=157)

P value

Furniture and furnishings 76 63 55 ***

Radio/cassette/DVD player 41 74 79 *** Mobile phone 21 48 75 *** Bicycle 13 12 17 0.401 solar panel/electrical inverters 0 6 32 *** Rental house 0 0 0 Land ownership 96 99 97 0.051 Television 0 0 14 *** Motor cycle 1 2 7 0.002** Generators 1 0 1 0.473 Internet access 0 1 6 *** Computer 0 0 4 *** Motor vehicle 0 0 5 *** Electricity 2 2 20 *** Fuel wood High quality 0 0 1 ***

Medium quality 0 0 6 ***

Low quality 100 100 93 ***

Floor material

High quality 0 0 37 ***


Low quality 100 97 46 ***

Wall materials


Medium quality 25 40 33 0.007**


Toilet High quality 0 0 1 0.05**


Low quality 100 100 85 ***

Roof materials


Medium quality 0 0 1 0.223


Water sources


Medium quality 59 63 52 0.075


Number of rooms

mean (Std error) 2 (0.71) 3 (1.2) 4 (2.3) ***

***p value <0.000, ** p value<0.05

61

Toilet facilities in low and middle income households are mainly of low quality such as use

of traditional pit latrines, shared pit latrines and use of nearby bushes or forest. High

income households have private flush toilets and private improved pit latrines. Shared

latrines pose such risks such as cholera and other sanitation related diseases that may pose

a risk to the general health of the households.

The quality of drinking water and sources of water are also important in determining the

overall wellbeing of the family. Having a good source of water ensures that women and

children are prevented from water related diseases. Having a high quality water source

such as bottled or piped water is not only hygienic but also the water quality is assured. In

both Manafwa and Kapchorwa, almost all households accessed water from medium quality

sources such as protected well or spring with a few obtaining water from unprotected well

and boreholes. A higher proportion of households in the high income category obtained

water from medium and high quality sources while low income households mainly

depended on low quality sources such as unprotected well, springs, rivers and boreholes.

3.7 INFRASTRUCTURE

3.7.1 TRANSPORT SERVICES, ROAD SYSTEMS

Access to transport and good road network is important to the livelihoods and wellbeing of

communities. Accessibility of usable roads ensures that farmers have access to markets,

inputs and also the convenience offered when farmers are in need of other services related

to wellbeing such as health and information. In Manafwa and Kapchorwa districts, there

are different forms of road infrastructure in existence within and outside the village and

the roads were considered somewhat usable. Feeder and community type of roads were

accessible to more than 70% of farmers in both districts (Table 49). A higher percentage of

farmers in Kapchorwa accessed all roads than farmers in Manafwa. This implies that

Kapchorwa farmers have better access to several services such as easy mobility to and

from the local government and also easy access to different types of markets.

62

The most common ways to reach the nearest roads are through walking and/or use of boda

boda rides. Bodaboda are commercial motorcycles used for ferrying people from remote

and often inaccessible areas of the villages to the main road to either catch a bus to travel

to the nearby town. Community and feeder roads are mostly accessed by walking. Usability

of roads in Manafwa and Kapchorwa is mainly hampered by bad weather and terrain; this

is due to the fact that the two project sites are located at the slopes of Mt Elgon.

TABLE 49: ACCESS TO TRANSPORT AND ROAD SYSTEMS

Different Road Infrastructure Manafwa Kapchorwa Manafwa Kapchorwa Manafwa Kapchorwa Manafwa Kapchorwa Trunk road Murram road Feeder road Community access

road Access to: (% ) No 89 86 62 40 30 21 22 21 Yes 11 14 38 60 70 79 78 79 Usability of the different road types (%) No 1 1 8 5 20 11 26 19 Yes 99 99 90 83 80 89 74 81 Commonest way of reaching nearest trunk road (%) Walking 4 50 38 89 89 91 100 94 Taxi (car) 32 1 2 0 0 0 0 0 Boda-boda 50 49 58 8 11 7 0 2 Bus/minibus 5 0 0 0 0 0 0 0 Motorcycle 7 0 1 0 0 0 0 0 Bicycle 2 0 1 0 0 0 0 0 Other (Specify) 0 0 0 2 0 0 0 0 If un usable, Why (%)

Bad weather 0 0 3 3 6 7 5 10 Bad terrain 0 0 1 1 7 3 11 3 Poor drainage 0 0 0 0 2 0 2 0 Pot holes 0 0 3 0 6 0 4 0 Not applicable to the context 0 0 0 1 0 0 4 0 Bushy roads 0 0 0 0 0 0 0 6

Other (specify) 0 0 0 0 0 2 0 6

The distance and the number of minutes to reach each of the different roads was

significantly different between Kapchorwa and Manafwa. Manafwa households travelled

more distance and hence used more time to reach tarmac, murram, feeder and community

roads (Table 50). Kapchorwa roads are more accessible and not far from the villages.

63

TABLE 50: DISTANCE AND TIME TO DIFFERENT ROADS IN THE COMMUNITY

District Mean SE

Time taken to travel to the nearest trunk road

(tarmac) in minutes

Manafwa 99.58 12.98

Kapchorwa 26.11 1.57

Distance in KM from homestead to the nearest

trunk road (tarmac)

Manafwa 29.41 1.09

Kapchorwa 3.86 0.19

Time taken in minutes to travel to the nearest

trunk road (murram)

Manafwa 34.28 2.86



trunk road (murram)

Manafwa 42.39 34.90

Kapchorwa 0.67 0.05


district feeder road

Manafwa 19.50 1.56



district feeder road?

Manafwa 2.53 0.25

Kapchorwa 0.65 0.08


community access road

Manafwa 8.18 0.68

Kapchorwa 6.39 0.65


community access road

Manafwa 0.69 0.09

Kapchorwa 0.33 0.02

3.7.2 MARKET INFRASTRUCTURE AND OTHER FACILITIES

Despite having slightly less access to different types of road, Manafwa has readily available

market for crops and livestock and even agrovet shops. About 38%, 42% and 37% of

farmers indicated to be aware of markets for crops, livestock and agrovets respectively in

Manafwa compared to 16%, 13% and 21% of farmers in Kapchorwa (Table 51). This can be

attributed to Manafwa district’s proximity to Mbale town which provides a market for

agricultural produce and livestock for Manafwa farmers. Even though markets are not

quite accessible and available in Kapchorwa, more than 80% of households considered the

markets usable at any given time (Table 51). In both sites, the markets were reachable and

most farmers either walked or used boda boda. Only 37% and 21% of farmers in

Kapchorwa and Manafwa accessed agrovets. The high percent of farmers using boda boda

to reach the nearest agrovet indicates longer distance to agrovets.

64

Table 51: Market and inputs infrastrucre

Manafwa Kapchorwa Manafwa Kapchorwa Manafwa Kapchorwa Availability of market

for crops Availability of market for livestock

availability of Agrovet

No 62 84 58 87 63 79 Yes 38 16 42 13 37 21 Usability (%)

No 19 7 20 6 14 6 Yes 81 93 80 94 86 94 Commonest way of reaching markets (%)

Walking 33 37 35 28 18 45 Taxi (car) 0 6 0 19 6 3 Boda-boda 59 55 57 50 69 51

Bus/minibus 0 0 1 0 0 0

Motorcycle 5 1 6 0 5 1

Bicycle 2 0 2 0 1 0 If unusable, Why (%)

Bad weather 5 2 5 4 4 3

Bad terrain 7 3 8 1 6 2

Potholes 2 0 2 0 1 0 Poor drainage

5 0 6 0 3 0

Bushy roads 0 1 0 0 0 0

Other (specify)

0 1 0 1 0 0

The distance in km, covered by farmers from the homestead to the market for crops was

longer in Manafwa than in Kapchorwa and therefore more time was used in reaching these

markets. The time taken and distance covered to reach the crops market was significantly

different between the two sites. Farmers covered an average of 8km in Manafwa while

Kapchorwa farmers cover an average of 6km (Table 52). Distance and time covered by

farmers to reach available livestock markets was not significantly different between the

two sites, the distance to the livestock market was 8.5km on average in both sites.

As earlier indicated few farmers accessed agrovets in their communities and were more

likely to use boda boda to access them. The average distance to access the nearest agrovet

was 5km in Kapchorwa compared to 11km in Manafwa. The long distance covered

especially in Manafwa could discourage farmers from applying herbicides and pesticides to

their crops and livestock leading to low productivity.

65

TABLE 52: DISTANCE AND TIME TO DIFFERENT MARKETS

Distance and time to different markets District Mean SE

Time in minutes taken to travel to the

nearest market for crops

Manafwa 41.44 2.31


Distance in km from homestead to the

nearest market for crops

Manafwa 8.41 0.42

Kapchorwa 6.06 0.32


nearest market for livestock

Manafwa 44.83 2.41



nearest market for livestock

Manafwa 8.56 0.38

Kapchorwa 8.55 0.59


nearest agrovet shop using the most

convenient route

Manafwa 47.42 2.61



nearest agrovet shop

Manafwa 11.31 0.53

Kapchorwa 4.29 0.26

4.0 CONCLUSION AND RECOMMENDATIONS

This study sought to analyze the livelihoods of communities living in Manafwa and

Kapchorwa with the aim of developing strategies that will improve household incomes and

food security. Data collected was on demographic characteristics of households, education,

land ownership, crop enterprises, household assets, income, institutions, agricultural and

livestock production with a focus on coffee, dairy and bee keeping. The findings of the

livelihood analysis of households in Manafwa and Kapchorwa disctrict has shown that

households are engaged in different livelihood strategies in order to meet their basic needs.

A majority of households are engaged in farming as their main livelihood strategy with a

few involved in casual work and small scale business. Among the crop enterprises, maize,

beans, bananas and coffee were high on the list. Among the livestock enterprises, local

chicken, dairy cattle and goats were kept by many farmers. In their endeavor to meet basic

needs, households face a number of challenges which if addressed will improve their

livelihood prospects. This section will discuss production, institutional, marketing and

infrastructural challenges faced in relation to coffee, dairy and honey value chains and

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propose interventions/strategies that if put in place will improve the livelihoods of

communities living in the two districts

Coffee value chain

Uganda accounts for 2.5% of global coffee production. It is also the country’s most

important export crop. About 80% of the coffee grown is Robusta which is indigenous to

Uganda while the rest in Arabica (GAIN, 2015). The crop is grown by smallholder farmers

and this study has shown that the area allocated to coffee is small; 0.09 ha for Manafwa and

0.13 ha for Kapchorwa accounting for 18 % and 23% of the total land under cultivation

2015/2016 agricultural season in Manafwa and Kapchorwa respectively. Coffee yields

range from 1556 Kg/ha in Kapchorwa to 1776 kg/ha in Manafwa. The data indicate that

the average yields are below the potential average of 2000kg/ha for Arabica coffee under

good management practices. The findings from this study have shown that farmers are

facing several challenges which have led to low production. High incidence of diseases and

pests and low productivity are the two most important challenges mentioned by coffee

farmers. The high incidence of pests and diseases could be attributed to a number of factors

such as farmers not having resources to purchase pesticides (7.4% and 16.2%) of farmers

used pesticides in Manafwa and Kapchorwa respectively), not following the right

agronomic practices and limited access to extension services as mentioned by a few

farmers. The results also show that few farmers accessed agrovets in their communities

and were more likely to use boda boda to access nearest agrovet. The average distance to

access the nearest agrovet was 5km in Kapchorwa compared to 11 km in Manafwa. The

long distance covered especially in Manafwa could discourage farmers from using

herbicides and pesticides leading to low productivity. Low productivity on the other hand

is due to a number of factors such as the coffee wilt disease, limited use of fertilizers (5.8%

and 3.1 % of farmers in Manafwa and Kapchorwa respectively) and limited access to

extension services. Increasing production of coffee goes beyond teaching farmers on better

agronomic practices. It requires the joint effort of leading stakeholders such as BCU, UCDA,

MAAF, the private sector, NGOs and farmers in the coffee industry to come together in

multi-stakeholder platforms to address the challenges being faced and develop strategies

for improving productivity of coffee. Some of the strategies may include (i)adopting low

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cost extension approaches such as the use farmer-to-farmer extension to fill the gap of the

dysfunctional extension system occasioned by the dissolution of NAADS, ii) Encourage

farmers to grow specialty coffee by providing incentives which will motivate them to

increase production

The Dairy value chain

Uganda milk production is largely dominated by small scale farmers who own 1-2 dairy

cows. This study has shown that on average farmers keep at least one dairy cow in

Manafwa and two in Kapchorwa, but the type of dairy cow kept varies by the various

landscapes .More farmers keep improved (crossbred) cows in Kapchorwa than those in

Manafwa. Livestock is kept both for subsistence and cash. Production of milk is however

low. Milk yields range from 3.42 litres per day in Manafwa to 4.14 litres per day in

Kapchorwa. Few farmers are however using improved feeds and feeding practices such as

the use of herbaceous legumes and fodder shrubs. Reasons for not growing fodder include

lack of enough land, unavailability of seeds/planting material for the preferred fodder

species and limited information on fodder production due to the vacuum created in the

extension system following the dissolution of the NAADs programme. There is potential to

increase production through the use of improved feeds and breeding services. A strategy to

address the scarcity of land is to grow fodder on contours and farm boundaries. Farmers

need to be made aware of the different niches of growing fodder that do not take up a lot of

land. Creating awareness can be done through low cost extension methods such as farmer-

to-farmer extension. Issues of unavailability of seed can be addressed through developing

mechanisms that are community based to ensure a reliable supply of fodder

seeds/seedlings. A strategy to improve breeds is to encourage farmers to use the services

of AI. This study has shown that farmers are making an effort to improve their breeds by

paying for services rendered from shared bulls in the village.

The honey value chain

In Uganda, it is estimated that about 1.5 million households derive their income from bee

keeping from which they harvest various hive products such as honey, propolis, and bee

wax, among others. Findings from this study show that honey production is undertaken by

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very few farmers in the two districts, Manafwa (4%) and Kapchorwa (13%). The findings

also showed that 1% of bee keepers harvested honey in Manafwa compared to 39% in

Kapchorwa. Bee hives in the two districts were mostly sited in the national park, a tedious

process that requires a permit from UWA, which explains the small number of producers

engaging in the enterprise. Given the subsistence nature of honey production, only 39% of

the producers sold honey in Kapchorwa. The results therefore suggest that more efforts

need to be put in promoting honey production in order to increase production. On average,

farmers in Kapchorwa have 18 hives per year while in Manafwa they have three hives per

year. Amount of honey produced per hive is relatively low. This could be attributed to the

fact that most farmers still use traditional bee hives. Another challenge is the overreliance

on the National park for siting bee hives. Farmers also mentioned that they do not have a

reliable market. Improving bee keeping practices will involve modern training, combined

with improved commercial bee stocks and a focus on increased agricultural production

through pollination of food crops. But on the wider scale of things, farmers could also be

encouraged to site their hives on their farmers. This requires awareness creation. The

sector, which has a high employment potential for especially youth and women, could do

even better with local institutional strengthening so that farmers can market their honey

collectively. This study has shown that very few farmers belong to groups. Reasons given

include lack of commitment, lack of trust, benefits not visible among other reasons.

Institutional strengthening should therefore involve strategies that include awareness

creation of the benefits of joining groups, training on group dynamics, governance and

building trust among group members. Farmers need to be made aware that by working in

groups, they stand a higher chance of accessing credit from financial institutions and also

the fact that they will have a higher bargaining power. Training communities in modern

apiary management and considering involving more youths can also improve the sector.

Packaging and branding will also improve marketing of honey.

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5.0 REFERENCES

DE SATGE, R., HOLLOWAY, A., MULLINS, D., NCHABALENG, L. & WARD, P. 2002. Learning about livelihoods: Insights from Southern Africa, South Africa, Oxfam GB

Practical Action Publishing. DFID. 2000. Sustainable livelihoods guidance sheets [Online]. UK: Department for International

Development. Available: http://www.ennonline.net/dfidsustainableliving [Accessed 17-07-2017 2017].

DONOVAN, J. & STOIAN, D. 2012. 5Capitals: A Tool for Assessing the Poverty Impacts of Value Chain Development. In: SHECK, R. (ed.) Rural Enterprise Development Collection. Turrialba, CR,

CATIE,: ICRAF. FILMER, D. & PRITCHETT, L. H. 2001. Estimating Wealth Effects Without Expenditure Data—Or

Tears: An Application To Educational Enrollments In States Of India. Demography, 38, 115-132.

GAIN 2015. Assessments of commodity and trade issues. In: SERVICES, U. F. A. (ed.) Global Agricultural Information Network. Nairobi: USDA.

MCKENZIE, D. J. 2005. Measuring Inequality with Asset Indicators. Journal of Population Economics, 18, 229-260.

SMITS, J. & STEENDIJK, R. 2014. The international wealth Index (IWI). Social Indicators Research 122.

UBOS. 2014. Uganda Bureau of statistcis (UBOS), Kapchorwa population preliminary data [Online]. Available: http://www.ubos.org/2014/11/28/national-population-and-housing-census-2014-provisional-results/

http://www.ennonline.net/dfidsustainableliving

http://www.ubos.org/2014/11/28/national-population-and-housing-census-2014-provisional-results/

http://www.ubos.org/2014/11/28/national-population-and-housing-census-2014-provisional-results/

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