Analysis of the Baseline Surveys for the REAP CohortFunded through the Bill & Melinda Gates Foundation

August 2016

TABLE OF CONTENTSOverview........................................................................................................................................2

Background................................................................................................................................ 2

The Rural Entrepreneur Access Program (REAP)........................................................................3

Purpose of the Report................................................................................................................... 3

Survey analysis:..............................................................................................................................3

Survey Information:................................................................................................................... 3

Area Information:.......................................................................................................................4

Demographic Profile:................................................................................................................. 4

Household Income:....................................................................................................................6

Livestock Ownership:.................................................................................................................7

Household Expenditure:.............................................................................................................8

PRIORITY AREAS OF THE RESULTS FRAMEWORK.........................................................................10

Household decision making.....................................................................................................10

Access and usage of financial services.....................................................................................11

Savings..................................................................................................................................12

Loans.................................................................................................................................... 12

Education opportunities for girls..............................................................................................13

Household food security..........................................................................................................14

Food Consumption...............................................................................................................15

Use of healthcare.....................................................................................................................16

Graduation at Baseline:............................................................................................................... 17

Conclusion:.................................................................................................................................. 19

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OVERVIEW

BackgroundThe BOMA Project works in the arid and semi-arid lands (ASALs) of Africa where residents suffer from some of the highest poverty rates in the world. BOMA’s target area represents the true last mile of extreme poverty and economic isolation. The region’s low population density and lack of infrastructure mean there are no large employers, making livelihood choices minimal. Many of the villages where BOMA works are miles from the nearest trading post, paved road, public transportation, school, health center or financial institution. Low population density, geographic remoteness and transportation challenges have left residents largely forgotten by their own government, with only a few NGOs willing to make meaningful investment beyond food aid or short-term humanitarian relief.

BOMA’s current work area, Northern Kenya, is defined by its geographic, economic and political seclusion. As the Kenyan Ministry of State describes in Vision 2030: Development Strategy for Northern Kenya and Other Arid Lands report, “The defining feature of Northern Kenya is its separation from the rest of the country, which manifests itself in both physical and psychological ways… isolation, insecurity, weak economic integration, limited political leverage, and a challenging natural environment combine to produce high levels of risk and vulnerability.”1

According to a 2011 report by the Kenyan Ministry of State, taken together, the seven districts of Northern Kenya had a UNDP Human Development Index lower than that of Sierra Leone, the lowest-ranked country in the world.2 According to data from the Grameen Foundation’s Progress out of Poverty Index, 92% of people live in poverty in Marsabit and Samburu districts and the reported number of people living in extreme poverty is as high as 82%.

Livestock remains the traditional source of food and income, and as the severity of droughts escalate, herding has become an increasingly unsustainable livelihood. In 2011, the worst drought in 60 years triggered a hunger crisis in East Africa, impacting more than 13 million people and leaving in its wake 50,000 to 100,000 dead. The United Nations estimated the cost of humanitarian response at $1.5 billion.

In the severe cycle of drought and famine, women and children are particularly vulnerable. Left in the villages, without food or income, for as long as six months while men travel with the herds in search of increasingly scarce water and grazing lands, women must survive by subsisting on food aid, begging for credit from shopkeepers, or scraping together small incomes from menial labor like gathering firewood or collecting water.

Historically, pastoral nomadic communities of Northern Kenya share a patriarchal social system, in which men have greater authority in household decision-making and control financial resources and assets, mostly livestock and land. Women are typically not allowed to own livestock, save for few animals in the homestead. In recent years, women have become further marginalized and disempowered by the ripple effect of climate change and dependence on humanitarian aid. Women suffer doubly in geographic isolation with a lack of opportunities for income-generating activities and

1 Ministry of State, “Vision 2030: Development Strategy for Northern Kenya and Other Arid Lands” Republic of Kenya, August 2011.2

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discrimination within a patriarchal society. And for the few women who have managed to cultivate a source of income, their lack of access to formal financial institutions makes it difficult to keep, transfer and save money safely.

The Rural Entrepreneur Access Program (REAP)The Rural Entrepreneur Access Program is an innovative, gender focused, two-year poverty graduation model developed to meet the needs of women in the drylands of Africa that addresses all of the problems described above. BOMA provides seed capital, training and two years of mentoring, supporting a business group of three women to start a small business and establish a sustainable income and savings. BOMA’s holistic program helps ultra-poor women to build a pathway out of extreme poverty by addressing the three interrelated elements that contribute to the cycle of poverty: low incomes, inconsistent cash flows and inadequate financial services. Profits from each REAP business provide a new and diversified income for participants, while personal and business savings training help women manage cash for daily needs. BOMA savings groups help women plan for future expenses like school fees and healthcare and respond to shocks (drought or emergencies).

To date, BOMA has helped 10,557 women, supporting more than 52,630 children find pathways out of extreme poverty by establishing 3,343 businesses and 607 savings groups across Marsabit and Samburu districts in Northern Kenya. Our goal is to lift more than 100,000 women and children out of extreme poverty by 2018 and reach one million women and children in the next five years.

PURPOSE OF THE REPORTIn October 2015, the BOMA Project received funding from the Bill & Melinda Gates Foundation Putting Women and Girls at the Center of Development Global Grand Challenge to enroll 750 ultra-poor women from the drylands of Northern Kenya in BOMA’s REAP program. With the goal of helping women establish their own income and savings, and to assess any changes in household decision-making resulting from economic empowerment, BOMA conducted this baseline survey to measure conditions before the intervention.

The purpose of this report is to present the characteristics of REAP participants in the Gates cohort at baseline. Outcomes of interest, including household income, expenditures, assets, household decision making, healthcare use and food security, are reported and will be used to draw comparisons after one year and at the end of two year REAP program. Data from the baseline report will also be used to inform areas where attention is needed by staff in the field.

SURVEY ANALYSIS

Survey Information:In April 2016, baseline surveys were conducted with the 750 participants who enrolled in REAP supported by funding from the Bill and Melinda Gates Foundation. Baseline data was collected between April 14, 2016 to May 1, 2016, with follow-up surveys conducted through May 8, 2016 for participants that were missed due to travel or illness. Surveys were conducted by three teams of enumerators, each consisting of one survey supervisor and five trained, independent enumerators. Baseline surveys were completed by all (100%) participants.

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Selection of enumerators was a competitive process, with seven enumerators brought into the training for each team but only five were selected. All enumerators were University students or graduates from Marsabit or Samburu County to ensure a high level of maturity and seriousness. Upon completion of the training, enumerators were scored on a scale from 0-100, which was used to select the enumerators who would be on the survey teams. Seventy percent of the score was from accuracy of responses entered during a challenging enumerator interview (post-test). The remaining 30% of the score was from a rating of each enumerator by the respective Field Officer and Survey Supervisor on the enumerator’s language skills, participation in training, how well they act with participants, their attitude, whether they ask questions when they are unsure, and how well they represent BOMA. All survey teams consisted of at least two female enumerators for gender balance.

Area Information:Data was collected from 14 locations in Samburu and Marsabit counties. These locations are home to both semi-nomadic communities (people living usually in portable or temporary dwellings and practicing seasonal migration) or settled communities with more permanent buildings and services. A small percent of households were internally displaced, coming from communities impacted by ethnic conflict.

Badasa

Dhirib Gombo

Dukana

Illaut

Kalach

aKarg

iKorr

Maikona

Merille

Ndonyo Uasi

n

Ngilai

West

Nguru

nit

Saga

nte

South

Horr0

10

20

30

40

50

60

70

80

Figure 1. Location and Area Type of REAP Participants

Other

Semi-Nomadic

Settled

Location

Perc

ent

Demographic Profile:The average age of REAP participants surveyed is 37 years, based on the date of birth on the participant’s ID. 64% of participants are between 21 - 40 years and 29% are 41 - 60 years (Figure 2). It is important to note that the majority of participants do not know their age and the age on the participant’s ID card is likely an estimation.

Nearly all participants belong to Rendille (27.9%), Samburu (26.4%), Borana (21.8%) or Gabbra (20.6%)

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18-20 21-40 41-60 61-80 81-900%

10%

20%

30%

40%

50%

60%

70%

2%

64%

29%

5%0%

Figure 2. Age of REAP Participants

Age Group

ethnic groups (Figure 3). Samburu is the language spoken by the most participants (31.4%), followed by Gabbra (23.4%), Borana (22.7%), and Rendille (22.3%).

Of the 750 participants surveyed, 72.6% reported they are married (Figure 4), and of the married participants, 30.7% are co-wives, meaning that their husband has at least one other wife. Participants have an average of three children under 18 in their household and the average household had two adults aged 18 and above; although about 23% of adults are at satellite camps or away from home at least six months of the year.

The majority of the participants (88.9%) have no formal education (Figure 5) and only 14% speak Kiswahili, one of the national languages of Kenya (the other is English). Although only 8% and 7% of participants can read and write in any language, respectively, 93% can do addition, subtraction,

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Rendille; 27.9

Samburu; 26.4

Borana; 21.8

Gabra; 20.6

Watta; 2.5 Burji; 0.4 Somali; 0.3 Konso; 0.1

Figure 3. Tribe of REAP Participants

None Some primary

Completed Primary

Completed Secondary

More than Secondary

Completed adult lit..

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

100%

Figure 5. Level of Education of REAP Partic-ipants

Other Semi-Nomadic SettledCan speak Kiswahili

Can read

Can write

Can add/subtract

Can multiply/divide

14%

8%

7%

95%

93%

Figure 6. Literacy, Numeracy and Language Skills

Divorced/Separated; 7.6%

In a relation-ship (but not

married); 0.4%

Married; 72.6%

Single (never married);

1.1%

Widowed (husband is

dead); 18.3%

Figure 4. Marital Status of REAP Participants

multiplication and division, determined by the ability to solve contextual math problems (e.g. If you sell two cups of milk a day for seven days, how many cups of milk in total would you sell in a week?) (Figure 6).

Of all the participants, 40.6% have their own mobile phone and 34.5% use MPESA or another mobile money service.

When asked what they do during the day (prior to REAP, represented in Figure 7), the majority of participants reported that they engage in household domestic work (91.5%), collect firewood (58.0%) and fetch water (57.9%). Other less frequent activities reported by participants were herding (17.1%), burning charcoal (6.2%), selling goods (5.2%) doing day labor for others (4.7%) and selling livestock (2.3%).

Household Income:For questions pertaining to income, participants were asked about their household income, as opposed to their individual income, in order to capture the financial situation of the household. Most participants report having one and two income sources for their household (Figure 8).

0

1

2

3

4

5

6

7

0% 5% 10% 15% 20% 25% 30% 35% 40%

4%

30%

35%

19%

8%

2%

1%

0%

Figure 8. Number of Income Sources for Participants' Households

The most common sources of income reported are selling livestock (62.7%) and casual labor (36.9%) (Table 1). Although participants report that their household has multiple sources of income, they may not receive income from each source every month (e.g. selling livestock) and some sources may contribute very little (e.g. selling firewood, selling milk, fetching water).

Table 1: Income sources for REAP households and the amount earned from each source in the past 30 days.

Variable Percent of participants Average income in the Average income in the

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House/Domestic WorkCollecting Firewood

Fetching WaterHerding

OtherDay Labour For Others (e.g. digging)

Burning CharcoalSelling Goods (non-BOMA)

Selling LivestockSalaried Labour for Others

Selling Hides or Skins

90.9%57.6%57.5%

16.9%12.3%

7.3%6.1%

2.9%2.3%

0.3%0.1%

Figure 7. Daily Activities of Participants Before Joining REAP

whose household receives income from this source

past 30 days for participants reporting income (KES)

past 30 days across all participants (KES)

Selling Livestock 63% 1961 1229Casual Labor 37% 1807 667Firewood 23% 1138 264Own Business 22% 2361 519Remittances 16% 940 150Other 11% 863 97Fetching Water 11% 898 101Charcoal 10% 1942 199Selling Meat 10% 1057 103Selling Milk 9% 576 51Selling Crops 6% 1317 74Selling Hides & Skins 5% 51 2Household Shop 3% 2539 74Formal Employment and Salaried Labor 2% 5687 114Tourism 1% 93 1Pension 0.3% 2500 7

Table 1 shows the number and percent of participants reporting each source of income in addition to the average income reported for the past 30 days from each source. The value in the third column models the average income reported by participants that received income from that source in the past 30 days. The value in the fourth column is the average income reported by all 750 participants in the past 30 days. Although only 2.9% of the participants reported earnings from employment and salaried labor, it had highest amount of average income of KES 5,867. While 22% of participants reported having income from their own business, this refers to any regular activity of buying and selling goods, not necessarily indicating a business or shop.

In total, 44% of participants reported that their household was registered for Kenya’s cash transfer program for vulnerable households, the Hunger Safety Net Programme (HSNP), while only 37% reported receiving HSNP benefits in the past month. The average monthly HSNP payment was equivalent to 2,430 KES/month for households receiving benefits. 5% of participants reported receiving income from another cash transfer, equivalent to an average of 3,892 per month.

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Overall, the majority of participants’ households (91%) own some kind of livestock. The average number of types of livestock owned by participants is two out of a possible five kinds of livestock, including camels, cattle, donkeys and goats and sheep - commonly combined and referred to as shoats (Figure 9).

The most commonly owned livestock are female and male shoats (86% and 69% of households, respectively). Female shoats are the livestock that participants themselves own and control the most.

Table 2 models the number and percentage of households owning each kind of livestock, the average number of each livestock their household owns, and the average number of livestock the participants themselves own or control.

Table 2: Livestock ownership by REAP households

Livestock Type Percentage of households who own this livestock

Average number owned by the household

Average number owned or controlled by the participant

Female Cattle 35% 2.4 1.0Male Cattle 20% 1.5 0.5Male Camels 16% 1.7 0.2Female Camels 26% 2.3 0.4Female Shoats 86% 7.9 2.9Male Shoats 69% 3.7 1.3Donkeys 30% 1.4 0.4Female Chickens 15% 3.4 3.0Male Chickens 10% 1.9 1.7

Tropical Livestock Units are livestock numbers converted to a common unit. Conversion factors are: camels = 1, cattle = 0.7, donkeys = 0.5, sheep/goats = 0.1 and chickens = 0.01. The average number of

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0 1 2 3 4 50%5%

10%15%20%25%30%35%

Figure 9. Livestock Ownership by REAP Households

Number of Types of Livestock OwnedPe

rcen

t of H

ouse

hold

s

total livestock that participants’ household owns is 2.8 TLUs, and the average number of total livestock under participant control is 0.9 TLUs.

Household Expenditure:In this portion of the survey, participants are asked about household expenditure spent on school fees, medical care, food, clothes and household items. Participants were asked to report the amount their household spent in the past month, excluding school fees and medical expenses which were reported for the past year. Table 3 shows the number and percent of participants who reported having each type of expenditure and the amount they paid in cash and credit. The values for school fees and medical expenses are the amounts spent over the past year.

Table 3: Monthly household expenditure for REAP participants

The expenditure with highest amount spent (KES 3,314) was food with 98.1% of the participants reported spending on food. Sixty-seven percent of the participant’s households reported spending related to school fees or school expenses in the past year and 56.5% of households reported medical expenditures in the past year.

Of the households that paid school fees or school expenses, 12.5% reported receiving money from sources outside of the household, including sponsorship, county government funds, constituency development funds (CDF), ministry funds, other family members, and clan bursary for school fees (Table 4). The average amount of school fees that covered by these sources was KES 2,742. A greater percentage (66%) of participants reported that their household paid school fees, with an average of KES 5,986.

Expense Percent of Participants who made this expense (last 30 days)

Average amount spent by Participants who made this expense (last 30 days)

Average amount Paid with Cash byParticipants who made this expense

Average amount Paid with Credit by Participants who made this expense

Average amount spent across all participants(last 30 days)

Food 98% 3377 2261 1116 3314Livestock 1% 2315 2315 0 31

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Expense Percentage of participants who reported this expense (last 1 Year)

Average amount spent for participants reporting the expense (KES) (last 1 Year)

Average amount spent across all Participants (KES) (last 1 Year)

School fees and school expenses paid by the household

66% 5,986 3,991

School fees and school expenses paid by a source other than the household

13% 4,113 2,742

Medical expenses 51% 2,659 1,351

Home Improvements 1% 633 597 37 8Travel 7% 618 603 15 44Clothes for Others 21% 538 457 80 112Clothes for self 17% 522 445 77 86Beads 3% 434 399 35 12Livestock Related 30% 366 299 67 109Special Events 33% 294 260 33 97Home Items 9% 208 193 15 18Cosmetics 38% 159 133 26 61Sweets, miraa, alcohol, tobacco 65% 156 150 7 101

Table 4: Average amount spent on school fees and medical expenses over the past year

For the 50.8% participants who reported having medical expenses, the average medical expenditure over the past year was KES 2,659. It is important to note that in most local government facilities, healthcare services are now offered at no cost making the primary expenses transportation and medicine.

PRIORITY AREAS OF RESULTS FRAMEWORKThis section describes the baseline specific priority areas of interest from the Gates Results Framework. These outcomes will be tracked over the two years at mid-line and exit and compared to baseline data to determine impact.

Household decision makingOne of the primary outcomes of interest for this grant is the change in household decision making in REAP participants’ homes. We hypothesize that married women will have a greater role in household decision making upon exiting REAP as a result of having her own income and savings. In this section we look at the degree to which the participants are involved with decisions at baseline in eight subject areas: purchasing food, purchasing household items, paying for children’s education, deciding which children to send to school, paying for children’s medical expenses, purchasing livestock for the household, purchasing livestock for herself and selling her own livestock.

For each of the eight subject areas, participants were first asked about the extent they are involved in making decisions in each of the eight subject areas: Fully she makes the decisions; Mostly - she usually makes decisions or has a major say in decisions; Somewhat she makes some decisions or has a say in some decisions; Little she is rarely consulted or her opinion usually doesn't count; and None she has no say and is not consulted.

Participants were then asked to quantify their relative contribution to decisions by herself and her husband on a scale of 1 to 10; a score of 10 means that the participant has complete control over the decision and does not need to consult her husband before making a decision. A score of 5 indicates that the participant and her husband undertake the decision making jointly and discuss the matter before making the final decision together. A score of 2 indicates that the husband has most of the

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say in the decision although the participant is informed. A score of 1 indicates that the husband has complete control over the decision and he does not consult the participant at all.

The following analysis includes only the participants who reported they were married at the time of the baseline survey.

Data from the baseline survey indicate that participants play a major role in making decisions about buying food for the household and buying household items. 66% of married participants reported they fully or mostly make decisions about purchasing foods while 92% of the participants reported they fully or mostly make decisions about purchasing household items (Table 5).

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Table 5. Extent REAP participants are involved in making decisions at baseline

Fully Mostly Somewhat Little NoneBuying household items 78% 14% 3% 3% 3%

Buying food for HH 40% 26% 24% 9% 1%

Buying livestock for self 9% 11% 22% 31% 28%Paying for children’s school fees 7% 6% 44% 28% 15%Paying for children’s medical expenses 5% 9% 48% 25% 13%

Which children to send to school 4% 3% 53% 18% 22%Buying livestock for HH 4% 1% 12% 35% 49%

Selling own livestock 3% 5% 22% 33% 37%

Women have much less input in decisions about their children’s education and medical expenses. Only 12.9% and 7.0% of women surveyed, said they make decisions fully or mostly by themselves regarding paying for children’s school fees and which children to send to school. The average score for decisions regarding school was a 3.6, compared with a score of 7.5 and 9.5 for buying food and household items, respectively (Table 6).

Table 6: Household decision making score by REAP participants at baseline

Type of decision ScoreBuying food for the household 7.5Paying for children’s school fees 3.6Deciding which children to send to school 3.6Paying for children’s medical expenses 4.1Buying livestock for the household 1.9Buying livestock for self 2.9Selling own livestock 2.5Buying household items 9.5

Most participants reported that they have little say when it comes to decisions regarding purchasing or selling livestock for themselves or for the household. The average scores for decision making about buying livestock for the household and participant was 1.9 and 2.9 respectively, meaning that the participant’s husband make the final decision.

Access and usage of financial servicesThe second area of interest is access and usage of financial services. As part of the baseline survey, participants were asked about how much savings they have in different locations and what loans they have taken from various sources. This information will be compared with the midline and end line survey data to see how access and usage of financial services change as a result of participating in REAP.

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SavingsApproximately one third (30%) of participants reported some sort of savings. The most common was savings groups (12.0% of all participants) and cash savings (11.1% of all participants) (Figure 10). The average amount of total savings is KES 3,186 for those who have reported any savings and KES 997 for all the participants.

The number of REAP participants with savings at baseline has risen over time as savings groups and ROSCAs become more common, and there is a greater knowledge of the importance of savings. Participants who were in a ROSCA were nearly all from Badasa (30%) and Sagante (49%). Similarly, 30% of participants in Sagante reported being in a savings group as well as 8-12% of participants in Badasa, Dhirib Gombo, Dukana, Kalacha, Korr and Merille.

Table 7: Locations and average amounts of personal savings

Location of Savings Percent of participants with savings

Average amount saved for those who have reported any savings (KES)

Average amount saved across all participants (KES)

Savings group 12% 2146 255Personal savings 11% 1272 141ROSCA 8% 2744 216With other people 7% 2615 188Non-BOMA business 3% 1783 62Bank* 1% 13600 109M-pesa 0% 400 1

* The average amount of savings in a bank is inflated due to one participant recently receiving a large HSNP payment and thus having 50,000 KES in her bank account.

Loans Approximately 22%, 167 participants, reported taking a loan in the past year, this includes informal, personal loans taken from family members. Of those who took a loan, the average value of loans taken in the past year was KES 6,700; the average is 1,492 KES over all participants. At 9.9% of all participants, family and friends are the most commonly accessed source for loans. Loans from savings groups are the second most accessed source with 8.6% of participants reporting loans. Loans from moneylenders was third with 4.4% of the participants reporting have taken a loan from this source (Figure 11). No participants reported accessing loans from banks.

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Savings group

Personal savings

Rosca

Savings with other people

Non-BOMA business

Bank

m-pesa

12.0%

11.1%

7.9%

7.2%

3.5%

0.8%

0.1%

F i g u r e 1 0 . S a v i n g s b y R E A P p a r ti c -i p a n t s

Family

Savings group

Money lender

MFI

Bank

0.0% 2.0% 4.0% 6.0% 8.0% 10.0% 12.0%

9.9%

8.6%

4.4%

0.5%

0.0%

Figure 11. Percent of participants taking loans from various sources in the past year

As shown in Table 8, of the participants who have taken loans during the past year, all of them still have a large outstanding balance. This may be because participants reported on recently taken loans.

Table 8: Sources and amounts of loans and outstanding balance

Loans Number of participants who took a loan from this source in the past year

Average amount of loan taken for those who’ve reported taking loan (KES)

Average amount of loan taken for all participants (KES)

Average loan balance for those who reported taking a loan (KES)

Average loan balance for all participants (KES)

Family 10% 3550 350 2782 274Savings Group 9% 7162 611 6200 529Money Lender 4% 7976 351 7406 32MFIs 1% 33650 179 26175 140Bank 0% 0 0 0 0

Education opportunities for girls A primary outcome for this cohort is girls’ school enrollment as BOMA is committed to putting women and girls at the center of development in the most remote and impoverished dryland regions of Africa.

In total, 58.9% of participants have primary school age girls (6 to 14 years). The average number of girls’ aged 6-14 years is 1.53. Of all primary school age girls, 66.5 are enrolled in school and of all primary school age boys 65.0% are enrolled in school. Figure 12 shows the percentage of girls and

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boys enrolled in primary and secondary school respectively.3 It is encouraging that these numbers are similar considering the large number of boys involved in herding.

The enrollment rate for all primary school age girls is 83.3% in settled villages (n=235) and 48.3% in semi-nomadic villages (n=201). This is due to the greater availability of schools and also lower likelihood that a child will be involved in herding. The breakdown of enrolment rates by location appears later on in “Graduation at Baseline” section.

As a way to gauge the impact of income from a BOMA business on girl’s education, we will look at the change in spending on girl’s education over the two years. At baseline on average, households with primary and secondary school age girls spent an average of 2,484 KES in the past year on school fees and school expenses for girls.

Household food securityFood security is a priority area of interest because it indicates if REAP participants can meet the basic needs of their family.

Although 79.9% of participants reported to have two or more meals per day over the past week, over half of participants (57.2%) reported that there was at least one night when children in their household went to bed without an evening meal in the past week (Figure 13). It is likely that this

3 Primary-aged children are defined as between the ages of 6 and 14. Secondary-aged children are defined as between the ages of 15 and 18.

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1 2 3 4 5 6 7 Did Not Go

Hungry

0%5%

10%15%20%25%30%35%40%45%50%

14.7%

27.9%

9.7%

3.2%0.3% 0.1% 0.9%

43.2%

Figure 13. Number of Times Children Went to Bed Without an Evening Meal in the Past Week

Primary Seconday All0.0

10.020.030.040.050.060.070.080.0

F i g u r e 1 2 . E n r o l l m e n t R a t e O f B o y s A n d G i r l s O f R E A P P a r ti c i p a n t s

Girls Boys

number over reports the level of food security because women will often spare their own food in order for their children to eat.

Looking at other indicators of food security, 100% of participants reported worrying that their household would not have enough food to eat in the past month and 100% of participants’ reported their household did not have enough food or enough money to buy food for all its members at least once in the past month (Figure 14).

89.4% of participants reported restricting their own consumption to allow their children to eat and

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Miss meals due to lack of food

Worry about having enough food

Restrict consumption so kids can eat

Not enough food or money for food

0 10 20 30 40 50 60 70 80 90 100

0

4

1

0

19

24

20

31

39

46

40

51

28

26

29

18

14

0

11

0

Figure 14. Food Security Reported by REAP Participants

Always (every day) Pretty often (3-6 times a week)Once in a while (1-2 times/week) Rarely (<1 time/week)Never

Percent of households

86.3% of participants missed a meal because they did not have enough food. 76.6% of participants had to take credit or borrow money in the last 30 days so their children did not have to go to bed hungry.

Food ConsumptionAs described earlier, food is the largest monthly household expense. On average the participants spend KES 3,314 on food of which KES 2,219 is paid in cash and KES 1,095 is paid on credit. Table 9 shows the frequency of consumption of various foods by REAP participants in the past month. To calculate the average frequency of consumption for each food, the responses for this question (every day, once per week, etc.) were coded from 0-4, with 0 being that the participant never ate the food in the past month, and 4 being the participant ate the food almost every day. The average was then calculated across for the whole cohort.

Table 9: Food consumption

Variable Percent of households that eat this item

Frequency of Consumption in the past 30 days(Almost every day = 42-3 times per week = 3Once per week = 21-3 times per month = 1Never = 0)

Rice 87% 2.0Wheat 56% 1.0Maize Floor 99% 3.2Beans 98% 3.3Meat 87% 0.8Fish 0.1% 0.0Milk 97% 3.7Vegetables (greens) 46% 0.8Pasta 38% 0.4Potatoes 60% 1.2Eggs 16% 0.3

Use of healthcare

The final priority area of interest is the impact of REAP on use of healthcare services.

At baseline, 56.7% of the participants reported that their household incurred medical expenses in the past year, which includes expenses for medicine and transport to a health center. The average amount for medical expenses in the past year was KES 2,382 for those who incurred the cost and KES 1,351 across all participating households. It is important to note that many local clinics provide healthcare for free, so this value may not accurately reflect the true cost of health care services.

Of the surveyed participants, 24.7% had given birth during the past year. Of them 88.1% reported making at least one antenatal visit and 11.9% did not make any antenatal visits.

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In the health section the participants were also asked about if they had certain other illnesses in the past year, how many times they had sought care for each ailment and the location they sought treatment.

Table 10 shows the percent of participants who suffered from each ailment over the past year and the percent who sought medical help either from traditional healer / herbalist, dispensary, health center, community health worker, mobile clinic or other location at least once.

Table 10: Health conditions and percent of participants who sought care

Health Condition Percent of participants who suffered from the condition in the past year

Percent of participants who sought care at least once for the condition

Malaria 40% 97%Stomach Illness 22% 94%Respiratory infection 33% 96%Eye Problems 11% 89%Injury 7% 96%

Table 11 shows the location where participants having malaria, stomach illness, respiratory infection, eye problems and or injuries went for treatment. Overall, dispensaries were the most common location visited for treatment, followed by health centers and traditional healers/herbalists.

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Table 11. Locations that REAP participants sought medical treatment for various health conditions

Malaria Stomach Illness Respiratory Infection

Eye Problems

Injury

Dispensary 71% 63% 59% 65% 63%Health center 18% 21% 18% 16% 34%Mobile clinic 1% 2% <1% 3% 0%Traditional healer/herbalist

11% 15% 20% 15% 20%

Other 6% 10% 8% 6% 7%

GRADUATION AT BASELINE:

The BOMA graduation criteria are used to determine the percentage of REAP participants that graduate from extreme poverty after the two years in the program. In order to graduate, BOMA requires that participants satisfy six unique criteria in four categories- food security, sustainable livelihoods, shock preparedness, and human capital investment.

The following six mandatory criteria, in four categories, will be used at endline to assess whether REAP participants have graduated out of extreme poverty:

Food Security

1. No child going to bed hungry in the last month

2. Household members eat at least two meals a day in the past week4

Sustainable Livelihoods

3. The value of the BOMA business is 25% higher than the total conditional cash transfer

4. Participant can access more than one source of income5

Shock Preparedness

5. Participant is a member of a savings group (with formal constitution and credit and loan protocols), has access to credit, and has a minimum of KES 8,000 in savings

Human Capital Investment

6. All eligible girl children are attending primary school6

It is also useful to determine the percentage of participants meeting each criteria at baseline to understand where the participants are before entering REAP. Since Criteria 3 requires the value of

4 Household members refer only to the participant and her children for this criteria. Other adult household members may not be permanent residents of the home, and so we cannot expect the REAP program to influence the number of meals that they consume.5 Sources of income include any type of income that the household receives, either through the participant or through other household members, excluding HSNP. 6 Primary school-aged girls are defined as being between the ages of 6 and 14. If the participant does not have any eligible primary school-aged girls, she is excluded from this criteria.

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the BOMA business and is not applicable at baseline, it was excluded from the current analysis and the baseline graduation rate was calculated using only the remaining five criteria.

In Table 12 below, graduation rates are given for each graduation criteria for the entire cohort as well as for participants living in semi-nomadic villages versus settled villages.

Table 12: Graduation criteria and passing rates

Category Overall Graduation Rate %

Semi-Nomadic Graduation Rate %

Settled Village Graduation Rate %

Food Security1. No child going to bed hungry in the last month

42.8 29.4 53.8

2. Household members eat two meals a day in the past week

79.1 89.8 70.4

Sustainable Livelihoods3. Value of business is 25% higher than total conditional cash transfer

N/A N/A N/A

4. Participant can access more than one source of income

65.5 64.6 66.1

Shock Preparedness5. Participant is a member of a savings group, has access to credit, and has a minimum of KES 8,000 in savings

2.0 0.0 3.7

Human Capital Investment6. All eligible girl children are attending primary school *

57.0 32.3 77.5

Overall Graduation Rate 1.5

*Includes only participants who have at least one primary-age girl (n=439)

Overall, the criteria in which most participants graduated at baseline is “household members eat two meals a day in the past week” in the food security category, with 79.1% participants passing that criteria. The category with the lowest graduation rate is shock preparedness with 2% of participants passing at baseline. 14 out of 15 (93%) participants who pass this criteria report being members of a ROSCA. The 11 participants who graduated in all five criteria come from Badasa (2), Dhirib Gombo (1), and Sagante (8) in settled villages.

As table 11 shows, there are some differences between graduation rates in semi-nomadic and settled villages. For human capital investment, the difference is quite stark with 77.5% of families in settled villages having all eligible girl children in primary school, while only 32.3% of families in semi-nomadic villages fulfilling this criteria. In addition, 89.8% participants in semi-nomadic village graduate in the eating at least two meals criteria, but only 70.4% in settled village met the criteria.

The different graduation rates in semi-nomadic and settled villages partially explains why graduation rates of each criteria vary by location. Table 13 shows the percent of participants meeting each graduation criteria by location.

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Table 13: Graduation rates by location

Location Number of Participants from the Location

1. No child going to bed hungry in the last week

2. Household members eat two meals a day in the past week

4. Participant can access more than one source of income

5. Participant is a member of a savings group, has access to credit, and has a minimum of KES 8,000 in savings

6. All eligible girl children are attending primary school

Overall

Badasa 60 71% 88% 56% 3% 93% 3%Dhirib Gombo

60 60% 70% 75% 2% 94% 2%

Dukana 60 27% 54% 68% 0% 55% 0%Illaut 30 23% 100% 30% 0% 6% 0%Kalacha 60 60% 52% 78% 0% 60% 0%Kargi 60 20% 87% 82% 0% 62% 0%Korr 75 21% 93% 73% 0% 41% 0%Maikona 45 60% 67% 62% 0% 88% 0%Merille 60 47% 81% 60% 0% 24% 0%Ndonyo Uasin

60 28% 87% 62% 0% 27% 0%

Ngilai West 45 34% 95% 69% 0% 36% 0%Ngurunit 30 23% 93% 43% 0% 39% 0%Sagante 60 80% 68% 62% 20% 97% 10%South Horr 45 29% 89% 71% 0% 44% 0%

CONCLUSION:The BOMA Project, by design, is a gender-focused organization that seeks to impact health and development for women in the forgotten and marginalized drylands of Africa. The focus of our work is to determine the effects of REAP on gender-sensitive priorities including economic empowerment (defined by changes in household decision making and income/savings measures, education of girls, access and usage of financial services), financial inclusion, household food security, and healthcare access. This baseline report provides the starting point upon which these outcomes will be assessed at the program end of two years.

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