BASELINE SURVEY: A REPORT ON THE PROFILE OF LOCAL COMMUNITIES AND HOUSEHOLDS IN MBITA AND SUBA DISTRICTS

BASELINE SURVEY: A REPORT ON THE PROFILE OFLOCAL COMMUNITIES AND HOUSEHOLDS INMBITA AND SUBA DISTRICTS INTRODUCTION1.1 

BackgroundBaseline studies are critical since they help to lay the foundation upon which anyfuture studies can be measured. Baseline studies serve as forerunners of impactevaluations especially in cases where interventions are intended. Unless one issufficiently knowledgeable about the conditions prevailing in an area – whethersocial, economic, cultural or otherwise, it will be difficult to appreciate any changesthat are later introduced.The survey we are reporting on aimed at establishing the prevailing conditions inselected parts of Suba and Mbita Districts. This background will serve as a benchmarkfor assessing the effects (impacts) of future activities that may be planned by theClient in introducing and implementing interventions whose purpose would be toameliorate any challenges experienced by the communities that inhabit the twoDistricts.The report whose details are narrated hereunder is divided into seven parts: Part 1 -Introduction, Part 2 - Methodology and Implementation, Part 3 - Results ofCommunity Mapping, Part 4 - Results of Household Interviews, Part 5 - Constraintsand Problems, Part 6 - Summary and Review of Survey Results and Part 7-Conclusions.1.2 LocationThe study was carried out in three locations – Mbita, Sindo and Nyandiwa - falling intwo districts of Nyanza Province in Kenya namely: Mbita and Suba. Until recentlythese two formed one administrative district – Suba District.The study area (here referring to the old Suba District) is located to the South-West ofKisumu City. Suba District is one of the twelve districts in Nyanza Province. It islocated in the south-western part of Kenya along Lake Victoria. It borders BondoDistrict to the North across the lake, Homa Bay District to the East, Migori District tothe South and Lake Victoria to the West. It is located between longitude 34°E and34°”E and latitudes 0°20”S and 0°52”S. The District covers an area of 1,056 km²exclusive of water surface. The water mass covers an area of 1,190 km². The Districtis also made up of 16 islands the biggest of which are Mfangano, Rusinga, Kibwogiand Takawiri. In total the mainland and the islands cover a total of 1,055,400 km².Water surface accounts for 11.3 percent of the District’s total area.The selection of the location was deliberate. There are three existing Water andEnergy hubs, commonly referred to as WE!Hubs, in the location one each at Mbita,Sindo and Nyandiwa. Under the WE!Hub project which is a joint project of SiemensStiftung, the Global Nature Fund (GNF), OSRAM AG, and Thames Electricals Ltdand funded by the European Commission, five new WE!Hubs will be established:three at Lake Victoria, one in a slum in the Industrial Area of Nairobi and another one2in the country in the initial phase. The three existing WE!Hubs will be refurbishedwith up-to-date technology and extended with internet cafés. The GNF is coordinatingthe project. OSRAM, which has already implemented three pilot kiosks at LakeVictoria in cooperation with the GNF, is supporting the joint project as a technologypartner and is consulting on technical and conceptual issues. Thames Electricals, aKenyan company, is critical to the successful local implementation and founded thesocial enterprise Light for Life, which is likewise based in Kenya. Light for Lifeoperates the WE!Hubs, conducts local trainings, and offers a platform for additionalprojects in the area. Siemens Stiftung carries out social projects in the area that gobeyond the WE!Hub project to empower the community as a whole.1.3 InterviewsTwo instruments were used to collect critical information required from respondentsdrawn from the two districts: Mbita and Suba. The first, an interview schedule, wasused for community mapping while the second, a questionnaire, was used to elicit andcapture information and data from individual households.1.4 General Information About the ParticipantsMbita and Suba are districts in South Nyanza. The large majority of members of localcommunities are Suba. The Suba who inhabit the islands were (and some would arguestill are) Bantu speakers. However, because of the overwhelming presence andinfluence of the dholuo speaking Nilotic group, the Suba have largely beenassimilated within the predominant Luo culture. 81% of the respondents spokeDholuo, the language of the Luo community, 5 % spoke Kiswahili, 4 % spoke Suba, 4% spoke Dholuo and Suba, 3 % spoke Dholuo and Kiswahili, 3% English, Dholuoand Kiswahili, 1 % English and Dholuo. 1% of the respondents did not provide ananswer to the question on language.Table 1: Language spoken by respondentsLanguage Spoken Frequency PercentDholuo 91 81Kiswahili 6 5Suba 4 4English and Dholuo 1 1Dholuo and Kiswahili 3 3Dholuo and Suba 4 4English and Dholuo and Kiswahili 3 3Missing 1 1Total 113 100Participants in both the community mapping and household interviews were adults:men and women, living and/or working in either Mbita or Suba District. The majorityof the respondents were representatives of the local communities. However, a3significant number of the key officers, especially in Government offices, did not comefrom the local community.

 2. METHODOLOGY AND IMPLEMENTATION2.1 

Survey DesignThe method adopted and used in this study was the descriptive survey design. Aspointed out in the preceding section, this was applied through interviewing of selectedkey informants. The community mapping tool (Appendix 1) was administered onrespondents by the Research Officer and research assistants. Both primary andsecondary data was collected during the survey.2.2 Selecting Key Players in the CommunityThe respondents for community mapping were selected using purposive samplingtechnique. To a large extent, persons in strategic positions of responsibility weretargeted for interview. Key informants included District Development Officers,District Education Officers, Water Operation and Maintenance Officers, DistrictPublic Health Officers, religious leaders, and the provincial administration (chiefs andassistant chiefs).2.3 Selecting Households for the SurveyInterviews were carried out with two distinct groups: members of the localcommunities, selected respondents – 113 of them (25 from Sindo, 25 from Nyandiwaand 63 from Mbita). 22 percent of the respondents were from Sindo and Nyandiwarespectively and 56 percent from Mbita. This does not in any way significantlydeviate from the Siemens Stiftung team’s requirement to ensure that 60 percent of therespondents were from Mbita and 40 percent from Sindo and Nyandiwa combined.The rationale for requiring 60 per cent of the respondents to be drawn from Mbita wasbecause Mbita town is much bigger than Sindo and Nyandiwa. It is important to notethat while the Siemens Stiftung team had recommended that a total of 100respondents be interviewed, eventually a total of 113 respondents were interviewedand their responses have been taken into account in the preparation of this report. Thedeviation is insignificant and does not significantly affect the end result obtained inthis case.Households were randomly selected to represent a cross-section of the population inboth Mbita and Suba Districts on the basis of livelihood support systems i.e.categorization according to employment status. Based on the findings of communitymapping it was established that about 65% of the respondents were employed in theinformal sector (self-employed) while the rest were either employed in the formalsector or unemployed. The survey distributed the sample in such a way that 65% wasdrawn from the self-employed category, 21% from employees in the formal sector,and 13% from the unemployed category. This data is presented in Table 1 below.4Table 2: Distribution of Household Sample According to Employment StatusResponse Frequency PercentageEmployed 24 21%Self-Employed 74 65%Unemployed 15 13% 113 100%Source Survey Data, 2012In the following parts is a presentation of the results obtained and discussion of theemerging patterns and trends.53. RESULTS OF COMMUNITY MAPPING3.1 OverviewAs pointed out in the overview, this study was carried out in two districts: Mbita andSuba. An analysis is provided of a range of socio-economic parameters which help toshed more light on the socio-economic characteristics of the communities in these twodistricts. The attributes examined include population, education, access to water,access to health services, sources and uses of energy and livelihood systems.3.2 Population ProfileTable 3 shows the latest population statistics for the two districts: Mbita and Suba. Asit may be observed, the population in the two districts has been disaggregated atdivisional level (three –Mbita, Mfangano and Lambwe for Mbita and two - Gwasi andSuba Central for Suba).Table 3: Population Data for respective divisions in Mbita and SubaDistrict Division Population HouseholdMbita Mbita 62,974 13,789Mfangano 26,120 5,573Lambwe 22,315 4,542Sub-Total 111,409 23,904Suba Gwasi 65,161 13,351Suba Central 37,893 8,065Sub-Total 103,054 21,416Total 214,463 45,320Source: District Development Office, Mbita District (2012)3.3 Education:Education and the institutions related to it play an important function in ruraldevelopment. Education is needed virtually in every sector of the economy – inbusiness, health, agriculture, natural resource management, etc. Indeed, educationserves as an important barometer for gauging the process of development.In the community mapping survey it was, therefore, deemed necessary to identify andmap institutions of learning located within the community. A description is made ofvarious levels of education provisioning – primary, secondary, tertiary and universityin terms of the pupil/student enrolment, as well as the number of teachers at therespective levels.63.3.1 Primary Schools in Mbita and Suba DistrictsAccording to the Mbita District Education Office, as at 23rd February 2012, therewere five (5) educational zones in Mbita District, namely: Mfangano, Rusinga, MbitaWest, Mbita East and Lambwe. There were 13, 266 boys and 12, 803 girls totalling to26,069 pupils. Inexplicably official data obtained from Mbita District EducationOffice gives the total as 25, 895. There were 719 teachers in the District. Thistranslates to a teacher-pupil ratio of 1: 37. (See table in Appendix 3 and 4)In Suba District, there were four (4) educational zones; namely Kigoto, Nyagwethe,Central and Kiyabuya. There were a total of 13,755 pupils and 545 teachers (407 maleteachers and 138 female teachers). Inexplicably official data obtained from SubaDistrict Education Office gives the total number of teachers as 547. This translates toa teacher-pupil ratio of 1: 19. Details of the total enrolment per division by gender aswell as the total number of teachers, also by gender, are provided in Appendix 3.3.3.2 Secondary Schools in Mbita and Suba DistrictsThere were a total of 22 secondary schools with a total enrolment of 5, 395 students.Of these, 3,716 were boys and 1, 679 girls. The teaching force was made up of a totalnumber of 165 teachers, 129 of whom were male and 36 female (Appendix 4).Two observations may be made about these statistics. One is that the number ofsecondary schools in the study areas is quite low as compared with that of primaryschools. Two, is the gender pattern. While in the primary school system, there wasnear gender parity between boy and girl pupils, at secondary school there is a sharpdecline in the number of girls. This pattern is repeated with respect to genderdistribution between male and female teachers: of the total 129 teachers, only 36 arefemales.These statistics have serious implications on socio-economic development of thecommunities in the study areas. In 2003, the Government of Kenya initiated FreePrimary Education. Accordingly, all children of eligible age (5 years) are expected toattend school. The data presented here suggests that not all children within the schoolgoing age are taking advantage of this programme which is free. This is mainly due tohigh pupil drop out, which according to the Suba District Development Plan, is 21%for females and 8% for males in primary school, while in secondary schools itdecreases to 8% and 6% for male and female pupils respectively. The Suba DistrictEducation for All Plan of Action 2002 – 2015 estimates that “11% of primary schoolgoing children are not in school”.This study’s findings corroborate the findings of an earlier assessment conducted inthe District in 2005 by Concern Kenya and The CRADLE – The Children’sFoundation where data obtained from 338 households in Gwassi Division showed that255 of the eligible 1151 (22%) were out of school.7Box 1: Concern Kenya and CRADLEA Rights-based Community Participatory Assessment of Out of School Childrenand the Right to Free Primary Education in Suba District by Concern Kenya andCRADLE, in 2005 revealed as follows:• The introduction of FPE led to a 17 % increase in enrolments in SubaDistrict, this means that only two years ago at least 17% of children in Subawere marginalised from Primary Education;• Data from Gwassi Division showed that 255 of the eligible 1151 (22%) wereout of school, an indication that there are locations in the District wherechildren have no access to primary education;• Absenteeism for boys (62.7%) and girls (58%) is higher during rainyseasons and most boys (70%) and girls (67%) attend school less regularly inthe afternoon sessions than the morning ones. Attendance is less regular onmarket days and poor during the first three weeks of the term and at the endof the month. These figures reveal children who though in school, do not getthe full benefit of Rights holders.• Overall, more girls dropped out of school than boys in all these schoolsexcept for schools near the lake;• The average drop-out rates in Suba District were higher than the nationalaverage which stands at 4.9 % (girls 4.8 %) and the provincial average of 5.8% (6.2 % for girls)Source: Concern Kenya and CRADLE, 20058While this is still the trend, interviews with key stakeholders reveal that the situationis worsening. Leading factors hindering the achievement of the goals of Free PrimaryEducation (FPE) could include poverty which prevents parents from buying uniformsand raising money for other “fees” which are payable under a free education system.Moreover, the difference between boys’ and girls’ enrolment and subsequenttransition from primary to secondary school suggests a higher drop-out rate for girlsthan is the case for boys. Cultural factors assumedly play an important influence here.It is possible, for instance, that the girls are dropping out of school to get into earlymarriages to meet cultural expectations. The converse of this is that the boys areretained in school longer than girls because of cultural norms which accord boys morevisibility in society at the expense of girls. This cultural norm is corroborated by themale-female teacher ratio.The allure of making quick money from fish trade was cited as one of the possiblecauses of low girls’ enrolment in schools. The effects of the parental responsibilitiesyoung girls have to assume as a result of deaths of parents due to the HIV/AIDSscourge were also cited as a contributing factor.3.3.3 Tertiary InstitutionsInformation relating to tertiary institutions in the survey area was not readily availablein government offices. Nevertheless, through observation in the course of the study,the research team located four polytechnics, one community resource centre and oneyouth empowerment centre:1) Community Learning Resource Centre2) Kakrigu / Wakiaga Polytechnic on Rusinga Island3) Sindo Youth Polytechnic.4) Wanyama Technical Institute located at Kamasingiri - “Rusinga”5) Waondo Polytechnic, Waondo, Lambwe6) Youth Empowerment Centre – KisuiThese may not be the only ones existing in the study area. For purposes of initiatingnew interventions, a further study may have to be conducted in future to establishtheir enrolment, what the institutions teach, how they teach, and the qualifications ofthe teachers or their gender composition. It is also noted that as yet, there are nouniversities or Constituent Colleges in the two districts of Mbita and Suba.3.4 Health Facilities in the Study AreasThe survey results show that, there are 27 registered health facilities in Mbita Districtand 18 registered health facilities in Suba District. The health facilities in MbitaDistrict may be divided into hierarchical categories as follows:Hospitals 02Health Centres 06Dispensaries 14Clinics/ Family Planning 059According to Mbita District’s Deputy Public Health Officer, Mr. Henry Ojwang, therewere 217 health workers in Mbita and Suba Districts combined. A quick observationof the information in Appendix 3 reveals that the study areas are underserved in termsof provision of health services. This is evident especially when the number ofhospitals is considered against lower ranked health facilities. Indeed, except forhospitals, lower order health centres offer very limited health support. This suggeststhat access to higher quality health services in Mbita and Suba Districts may be achallenge. Appendix 5 Provides details of the health facilities located in MbitaDistrict.How does this situation compare with that of Suba district? The following healthfacilities are located in Suba District (See Appendix 4 for details):Hospitals 02Health Centres 05Dispensaries 11Clinics 00The situation in Suba District is similar to that prevailing in Mbita District wherethere are very few higher order health facilities and a fairly large number of lowerorder health facilities. As in the case of Mbita District, it may be stated that residentsof Suba District lack access to adequate health services.3.5 Social Centres in the Study AreaSocial centres play an important role in the socio-economic lives of communities.They serve as entertainment centres/points (beaches, bars and restaurants, footballplaying or watching).Markets serve as collecting, bulk-breaking and selling points. They are centres thatfacilitate exchange of goods and services. Information is also exchanged andinnovations passed on from one person to another.Plate 1: Research Officer,Mr. Toboso, talking to MbitaDistrict’s Deputy Public.Health Officer, Mr. HenryOjwang at Mbita DistrictHospital during theCommunity MappingExercisePhoto: Courtesy of ResearchTeam10Churches and mosques are other forms of social places, where people gather to prayand worship.All these services are important for wholesome growth of local communities, andwithout them society cannot function efficiently and smoothly. We sought to find outwhat social centres and facilities exist in the study areas. The main places where localpeople gather for social events in the study areas include:1. Beaches, where fishermen and women gather to prepare and sort the silvercyprinid, Rastrineobola argentea locally known as Omena and Tilapia andNile Perch. The beaches are also used as drying points of Omena.2. Churches: There are churches in all the locations of the survey area. The mainchurches in the area are the Catholic Church, the Seventh Day Adventist andthe Anglican Church. Others include Chrisco Church and Deliverance Church.3. There are also bars / clubs / disco halls4. Residents occasionally gather at Onundo Football Stadium, named after thefounder but owned by the County Council, to play and watch football.5. Markets: there are two big markets – one at Mbita and another at Sindo whichserve locals.3.6 The Energy Supply Situation in the Study AreaEnergy is a major determinant of development everywhere in the world. Indeed,energy consumption provides a good measure of the level of development. Sinceindependence the Government of Kenya has emphasized the importance of extendingelectricity to rural areas in an effort to boost development through a programmepopularly called “rural electrification”. It is, therefore, important to determine theextent of this programme’s reach in Mbita and Suba Districts by determining thenumber of community members connected to the national grid.There are 23,904 and 21,416 households in Mbita and Suba respectively. Accordingto the results obtained from the community mapping 797 households (3.3%) wereconnected to the national grid in Mbita and Sindo area, while 621 households (2.8%)were connected to the national grid in Suba, making a total of 1, 418 in the area.Notice also that in Mbita District, access to electricity is fairly restricted to Mbitapoint while for Suba District access is limited to Sindo and Magunga areas. There isno connection in Nyandiwa. The number of households connected to the national gridis less than 10 percent of the total number of households in the two districts.3.6.1 Alternative Energy SourcesThe shortfall in connectivity to the national grid is made up by alternative sources.Information on leading alternative sources of energy in order of extent of use in bothdistricts was provided by among others: District Development Officers, DistrictEducation Officers, Religious leaders (Father Walter of the Catholic Church andPastor Nyangiya of the Seventh Day Adventist Church) (See Table 4)11Table 4: Alternative Energy Sources and Use in Mbita and Suba DistrictsEnergysourceType ofpopulationSourceFirewood Urban Firewood vendors / hawkers, market placeRural In the bushes / thicketsCharcoal Rural & Urban Local charcoal vendorsKerosene Rural & Urban Petrol stations, Fuel pumps, shopsSolar Rural & Urban Purchased from solar panel suppliers in Kisumuand other major towns across the country3.6.2 Energy Supply IndicatorsAs explained by Government officials and key informants, the current energy supplysituation can be described as inadequate with the following indicators:i. Local communities do not have access to adequate supplies. As indicated, onlya few have access to electricity.ii. Even for those who are connected to the national grid, there is frequentrationing of electricity supply.iii. Alternative sources of energy are similarly unreliable and unpredictable : e.g.solar batteriesiv. Energy costs are escalating, the price of kerosene has for the last few yearsbeen on an upward trend. The same is true for charcoal and increasingly woodfuel. For those who use car batteries, the cost of re-charging has alsoincreased.v. Moreover, the distance to the nearest town/market for purposes of re-chargingthe batteries is long and time consuming for those living deep in the hinterlandof such markets/towns.vi. Solar-based energy equipment and installation costs have remained expensiveand therefore out of reach for most members of the community who arelargely poor.vii. In addition, logistical support such as technical back-up is largely absent inmany rural areas to the extent that households who have ventured intoinstallation of solar-powered energy systems find it challenging to maintainthem in working order all the time.3.7 The Water Supply Situation in Mbita and Suba DistrictsWater is linked to virtually every sector in any community, both in the developed anddeveloping countries, rural and urban areas. Water sustains all living things – human,animals and plants. It is often said that “water is life”. The central investigativequestion in examination of the water situation in the study areas was: What is thestatus with regard to access to safe piped water by members of the communities livingin Mbita and Suba districts?12According to Mbita District’s Water Operation and Maintenance Officer, Mr. PaulAlele, there were 380 connections of piped water supply of which 120 were dormant.All the 380 connections were in Mbita District and were shared among householdsespecially in Mbita town. The active 260 connections experienced regular waterrationing due to shortage in supply as opposed to demand. Compared to thegeographical area and the total number of households in the survey area, it is safe toconclude that there is lack of access to piped water. A discussion with the SubaDistrict Water Officer, Mr. Kassim Mohamed confirmed that there was not even asingle water connection in Suba District.3.7.1 Access to Alternative Water Supply in Mbita and Suba districtsAccording to Mbita District’s Water Operation and Maintenance Officer, Mr. Alele,there were 8 water kiosks serving the area; out of which 2 were dormant (Table 5).Table 5: Water Kiosks in MbitaNo. Name of Water KioskOperatorLocation ConnectionNumberStatus1 Joshua Ogal Mlimani 28 Active2 Collins Olweny Mlimani 26 Active3 Lukiu Ogada Mlimani 64 Active4 Ziporah Achieng Mlimani 73 Active5 John Odera Owala Mbita Town 182 Active6 Peter Oketch Mbita Town 6 Active7 Agnes Onundo Mlimani 12 Dormant8 Florence Okoth Atieno Mlimani 172 DormantSource: Survey Data, March 2012Given the inadequacies in access to piped water, and community-based water kiosks,majority of the members of the community in Mbita District are compelled to accesswater supplies from alternative sources as indicated below:i. Bore holes (mainly in Lambwe Valley)ii. Lake Victoriaiii. Ponds and damsiv. Purchase from water vendorsv. Rain harvesting (roof catchment)vi. Streamsvii. WellsLake Victoria has plenty of water, and theoretically should be able to satisfy the waterrequirements for all the communities in the study areas. According to interviewees,however, the quality of the lake water is poor. The lake water contains impuritiesincluding silt, chemicals and fertilizers washed down into the Lake from largercatchment agricultural practices as well as from human activities. The lake water alsocontains heavy metals, some from urban sewerage and run-off from nearby urban13centres. It is worth noting that the water drawn from the lake is hardly treated beforeuse.Water from ponds and dams is equally poor in quality. Many local communities havelittle choice but to use it in the forms available. Our observations revealed that waterin ponds and dams served multiple purposes. Local community members use it fordrinking, cooking, washing clothes, bathing, watering animals as well as irrigation.Just like the water from the lake, there is hardly any effort to have the water obtainedfrom ponds and dams treated before use (especially for cooking and drinking).According to Suba District’s Water Officer, Mr. Kasim Mohamed, the main sourcesof water include; the lake, wells, boreholes, springs and dams. For instance, theresidents of Olando area in Suba obtained and used spring water from Mirare Hill.Households also obtain their water supplies from communal water supply points(water kiosks) for which they are charged a fee. There are three such water points –one at Magunga area (Gwasi Central), another next to the District Commissioner’sOffice, and the third next to Magunga Health Centre (Plate 2 shows a typical waterkiosk). In spite of these sources, access to safe drinking water is still a majorchallenge in Suba district since the water being sold at the kiosks is pumped directlyfrom the Lake.A clear indicator of the challenge faced by the local community in accessing portablewater is the long distances they travel to fetch this important commodity. To mitigatethis, local communities rely on a variety of means including the use of donkeys(Plates 4 & 5), human transport (carrying water on their heads), bicycles, motor cyclesand pickups.Plate 2: Water Kiosk atSindo built by CISP, anItalian NGOPhoto: Courtesy ofResearch Team14With support from NGOs, local community members have initiated additional watersupply points, including boreholes. However, these have not been successful. One ofthe reasons for the failure of development projects is the manner in which they areconceived and executed. Usually the local communities are not involved in the design,planning, and implementation. Moreover, the local people do not directly andsignificantly contribute towards the running of initiated projects. To a large extent,therefore, projects lack sustainability and fold or “die” at the close of donor funding.Plate 5 shows an example of such a failed project.Boreholes were another source of water mainly in Gwasi East Location, Suba District,which is over 50 kilometres away from the Lake. According to the Chief of theLocation, there were boreholes in Remakanga, Kigoto, God Keyo, Seka, Gendo,Olando, Ugoro, Misore and Nyagina villages. However, the boreholes at Kigotovillage and God Keyo were dormant.Important to note also is that the WE!Hubs at Mbita, Sindo and Nyandiwa are asource of wholesome water for the local community.Plate 5: A failed /dormant wind-poweredwater pump project inNyadendo, GwasiCentral LocationPhoto: Courtesy ofResearch Team.Plate 4: Donkeys headed to a water kiosk Plate 3: Transporting water using a cartdrawn by donkeys153.7.2 Link between Water Supply/Quality, and Water Borne Diseases in theCommunityAn attempt has been made to characterize the water supply situation in both Mbitaand Suba Districts in the previous section. It is apparent from this description thatbesides the quantity, water quality in both districts is poor. It is, therefore, importantto examine the link between water quantity and quality, on the one hand, and theprevalence of waterborne diseases, on the other.According to the Deputy District Public Health Officer, Mr. Henry Ojwang, 27% ofthe patients who visited Mbita District Hospital in 2011 were diagnosed with waterborne diseases, especially diarrhoea and typhoid. It was further established frominterviews with Government officers – District Development Officer (DDO), DistrictEducation Officer (DEO), District Director of Education (DDE), and church elders,that, water-borne diseases are not only prevalent, but the rate of infections is high.Part of the problem is lack of awareness about water-borne diseases. Father Walter ofMbita Catholic Church concerned by the problem, advised that people should besensitized about the causes of water-borne diseases through deliberately plannedhealth education programmes. According to him, the educated are more likely to linklimited access to clean water and the prevalence of water-related diseases. PastorNyangiya of the SDA Church adds that the rate of infection of water borne-diseases isespecially high during dry seasons (the period when water scarcity is highest). Thedisease challenge in the area is compounded by poor waste disposal mechanisms.According to Mr. Ojwang 58% of the population does not exercise proper wastedisposal. Although the link between the quality of water and water-borne diseases isclear, a number of the respondents think otherwise. For instance, Chief Mboya Owourof Rusinga East Location explained that people under his jurisdiction see nothingwrong with using untreated water from the Lake.3.8 Livelihood Support Systems in Mbita and Suba DistrictsThe District Development Officer, religious leaders and members of the provincialadministration (chiefs and assistant chiefs) revealed the following sources ofhousehold livelihoods, in order of importance.i. Small scale businessesii. Fishingiii. Formal Employmentiv. Farmingv. Livestock keepingvi. Sand harvesting (from the lake, especially at Mbita point)163.8.1 Main Employers in the Communityi. Non-Governmental Organization (NGOs) and Community BasedOrganizations (CBOs)ii. Government of Kenyaiii. Faith-based organizationsiv. Entrepreneurs and other well-to-do individualsv. Private Institutions such as schools and colleges, banks (e.g. Equity andCooperative Bank)3.8.2 Farming as a LivelihoodFood crops grown in the area include sorghum, millet, cassava, maize and sweetpotatoes. According to the Mbita District Development Officer, due to a number offactors including: limited exposure, lack of role-models and unfavourable climaticconditions, a large proportion of the districts’ productive population, especially theyouth, have developed a negative attitude towards farming to the extent that they donot regard it as a source of livelihood. The situation is exacerbated by the HIV/AIDSscourge as well as the role of competing alternatives such as fishing and off-farmbusiness enterprises which many local people perceive to offer quick returns.Plate 7: Poultry farming at arespondent’s household onRusinga East Location. Thehouse is powered by solarenergyPhoto: Courtesy of ResearchTeamPlate 6: Livestockfarming in SubaDistrictPhoto: Courtesy ofResearch Team.173.8.3 The Status of Employment in Mbita and Suba DistrictsMbita District experiences unemployment. According to the Suba DistrictDevelopment Plan unemployment stands at 65 percent. According to the MbitaDistrict Development Officer, Mr. Owilla, of the 35 percent employed majority areself-employed. According to him urban self-employment stands at 7% while ruralself-employment is at 45%. These sentiments about unemployment are corroboratedby other leaders in the area. Pastor Nyangiya of SDA Church stated that the rate ofunemployment in the area is high and estimated it to be around 65% of theemployable population.An estimated 50% of the people employed in Government Offices come from outsideMbita and Suba Districts while a much higher percentage (90%) of those employed inthe local NGOs and CBOs come from outside Mbita and Suba Districts. This suggeststhat requisite skills may not be found within local communities.Plate 8: A fishermanpreparing to go fishingPhoto: Courtesy ofResearch TeamPlate 9: Vegetablefarming by the lakeshoresupported by irrigationPhoto: Courtesy ofResearch Team183.8 Community Based Organizations/Non-Governmental Organizations andBusiness Organizations Working in Different Sectors in Mbita and Suba districtsThe description given of the various sectors within the study areas suggests thaturgent interventions should be put in place to address the challenges identified. It isnoted at the same time that a number of organizations (e.g. NGOs and CBOs) arealready involved in the implementation of various interventions with the aim ofmitigating some of these challenges. Any future interventions should seek to establishhow much has been achieved by such initiatives not only to avoid duplication but alsoto build on what has been accomplished so far.The District Development Officer, District Education Officer, Religious leaders(Father Walter of the Catholic Church and Pastor Nyangiya of the Seventh DayAdventist Church), local administrators identified a number of non-state actors activein the areas of Agriculture, Environment, Health, Education, Energy and Water. Table4 provides details of these actors, their mandate and involvement in various activitiesin the study areas and/or areas contiguous to them.19Table 6: Non-Governmental Organizations, Community Based Organizations andBusiness Organizations Working in Different Sectors in Mbita and Suba DistrictsNGOs, CBOs andBusinessOrganizationsSector ObjectivesCare Kenya –SWASH – Water• Water The main objective is to promotecommunity’s access to clean waterWorld Vision • Food Security• HealthSustainable Agriculture and FoodSecurityQuality of life – healthCEFA – EuropeanCommittee forTraining andAgriculture• Food Security Enhancing food security throughsustainable agricultureOSRAM • Energy Provision of renewable energyEquity Bank • Finance Provision of micro credit to groupsand individualsAdok Timo • Finance Provision of finance to crop farmersand fishermenCoop Bank • Finance Provision of finance to crop farmersand fishermenGreen Forest SocialInvestment Ltd –Environment• Environment• Food SecurityEnvironmental protection andsustainable agricultureSuba EnvironmentalEducation of Kenya• Environment• Food SecurityEnvironmental protection andsustainable AgricultureICIPE • Health• SustainabledevelopmentResearch on health and AgricultureDevelopmentKnowledge LinkAfrica (DEVLINK)• Povertyalleviation• human rights• healthPromotion of human rights for womenand children with special emphasis onpoverty, health and socio-culturalfactors that lead to gender disparities.3.8.1 Other Community Development Related Projects In Mbita and SubaDistricts.Besides the projects summarized in Table 5 above, there are also a number of ongoing community development projects in part covering the study areas. Two of theseare summarized in Boxes 1 & 2 below.20Box 2: Southern Nyanza Community Development ProjectThis is an IFAD-funded project that covers six districts – Homa Bay, Kuria, Migori,Nyamira, Rachuonyo and Suba. The districts are characterized by strong sociocultural traditions, high levels of poverty, and weak institutional and policyinfrastructure. The HIV/AIDS prevalence rate in the districts is higher than thenational average.The project focuses on empowering rural communities by:• strengthening local institutions and community-driven developmentactivities;• improving access to health-care services, safe water, and improvingenvironmental sanitation and hygiene practices;• increasing on-farm labour productivity and strengthening human capacitythrough improved food security and nutrition;• Increasing community awareness of social behaviour and their consequences.• Engaging communities to articulate their needs and priorities through acommunity action planning process.•• Encouraging communities to implement their development activities e.g.health-care centres, water points and latrines through self-help groups.Box 3: WASEH A component of CARE Kenya’s Nyanza Household LivelihoodProgram (Dak Achana).The Nyanza Household Livelihood Security Program is a multi-sectoral set ofprojects, targeting mainly food, health and nutrition securities. The program isdesigned based on a livelihood security assessment conducted by CARE-Kenya in1996 and 1999. These assessments found constraints to livelihood security,including 34% access to safe drinking water, 47% incidence of diarrhea amongchildren, poor sanitation, poor nutritional standards, high prevalence ofSTD/HIV/AIDs, low food production and lack of credit facilities.The project targets communities located in Western Kenya around Lake Victoria, inthe three districts of Rachuonyo, Homa Bay and Suba in Nyanza province. Thedistricts have an estimated population of 575,294 with an annual growth rate of3.0%. The main livelihood systems are subsistence farming, petty trading,agricultural wage labor and small-scale commercial fishing.Rural-to-urban migration, along with the break-up of households due to deaths anddivorce, has resulted in approximately 35% of rural households being headed bywomen. These female-headed households constitute (53%) of all households livingin absolute poverty, nationally. In two of the districts, the target population is ofrural-rural migrants, whose settlements dates back as far as 1950s.214. RESULTS OF HOUSEHOLD INTERVIEWS4.1 OVERVIEWAn overview of the socio-economic profile of the participants in the survey conductedin Mbita and Sindo districts for a period of one month (March 2012) is provided inthis part. The overview focuses on gender, age, education and related characteristicsof the participants.4.2 RESULTS (DATA AND FIGURES)Females formed the majority of the respondents, making up 65% of the totalinterviewees. Further, all ages were well represented, with the youth (18-29 years)making up the largest age category (41.6%). The lower number of men in this regionis attributed to the HIV/AIDS scourge. According to the Suba District StrategicDevelopment Plan, 2005 Suba District’s HIV/AIDS prevalence is of great concernand that men are highly vulnerable to the scourge which has already claimed many ofthem. In the year 2002, the HIV/AIDS prevalence rate was reported to be 34% andincreasing. This makes it one of the highest prevalence rates in Nyanza Province.Results show that literacy levels were high with 97.3% of the respondents reported tohave attended formal education. However, when this group is broken down, it isobserved that majority (57.7%) had primary education as the highest attained level ofeducation, those with secondary education were 27.9%, while 9.9% and 3.6% hadtertiary and university level education respectively. Examined from the viewpoint ofthe three study areas, it is evident that respondents in Mbita had attained higher levelsof education in comparison to the other two: Sindo and Nyandiwa. This is furtherconfirmed by the observation that Mbita had the lowest percentage of respondentswith primary education. At the same time, it was the only area where somerespondents reported to have tertiary/university level education. In the other twoareas, majority of the respondents reported their highest level of education as beingprimary, and with hardly any respondents having attained tertiary or university leveleducation (Table 7).The explanation for this is that Mbita enjoys access to better education infrastructureas well as other amenities to attract an educated population in comparison toNyandiwa or Sindo.224.2.1 Level of Education of the respondentsTable 7: Respondents’ Highest level of EducationResearch area Frequency PercentValidPercentCumulativePercentNyandiwa Valid Primary 18 72.0 75.0 75.0Secondary 6 24.0 25.0 100.0Total 24 96.0 100.0Missing .00 1 4.0Total 25 100.0Mbita Valid Primary 29 46.0 46.8 46.8Secondary 18 28.6 29.0 75.8Tertiary 11 17.5 17.7 93.5University 4 6.3 6.5 100.0Total 62 98.4 100.0Missing .00 1 1.6Total 63 100.0Sindo Valid Primary 17 68.0 68.0 68.0Secondary 7 28.0 28.0 96.0None 1 4.0 4.0 100.0Total 25 100.0 100.0Source: Survey Data, March 20124. 2.2 Communities’ Priority NeedsEvery community experiences certain challenges which in essence are influenced bysome unmet needs. Some of these arise out of geo-physical challenges prevalent in thelocal area, while others are inherent socio-economic characteristics of the localcommunities themselves and the social environments within which they live. Indeed,it is only when these needs are analysed and understood that correct and appropriateinterventions can be initiated to help raise the standard of living of the people in thearea.Pursuant to the above, local communities through carefully-selected respondents werepresented with a list containing 11 of what were considered basic needs and requestedto have them ranked in the order of importance, starting with the most pressing needs.A frequency distribution was generated showing the needs ranked depending on thepercentage of respondents who reported on them. The results indicate that the higherthe percentage the higher the need was perceived to be important. The results from the23ranking by respondents show that the majority ranked food as the mostimportant/pressing need. This was followed by income, better access to education andenergy, in that order. Of all the eleven needs identified and presented to therespondents for ranking, only access to Information and Communication Technology(ICT) was not perceived as an important/pressing need. The priority needs of thecommunities living in the three study areas of Mbita, Nyandiwa and Sindo arepresented in Table 8.Table 8: Perceived Priority Needs Among Communities in Mbita, Nyandiwa andSindo Needs Frequency Valid Percent RankFood 46 41 1Income/employment 15 13 2Better access to school education 12 11 3Energy 9 8 4Health services 8 7 5Safe portable water 8 7 5Information on health, environment 6 5 6Sanitation/Toilets/Latrines 6 5 6Entrepreneurship/vocational training 1 1 7Waste management 1 1 7Missing 1 1Total 113 100Source: Survey Data (March 2012)The needs perceived as most pressing by the respondents were further analysed acrossthe three study areas. The aim for such comparison was to verify whether or not theyvaried across the three geographical areas.Results from such analysis show that, the most important need in each of the threeareas was food reported by 72% of the respondents in Sindo, 40% in Nyandiwa and28.6% in Mbita. The second most important need was employment and the relatedincome, reported by 24% of the respondents in Nyandiwa. However, for Mbita thepriority perceived second in importance was better access to school education,reported by 15.9% of the respondents. Access to education was ranked the secondmost important need in Sindo as well albeit by fewer respondents - only 8% of therespondents. Energy was ranked number three in Nyandiwa (16%), number five inMbita (7.9%) but did not feature among the needs listed by respondents in Sindo.(Table 9, Figures 2, 3 and 4 below).24Table 9: Comparative Perceived Priority Needs: Mbita, Nyandiwa and SindoResearch area Need Frequency Percent RankNyandiwaFood 10 40 1Income/employment 6 24 2Energy 4 16 3Health services 3 12 4Sanitation/Latrines 2 8 5Total 25 100MbitaFood 18 28.6 1Better access to school education 10 15.9 2Safe potable water 8 12.7 3Income/employment 7 11.1 4Energy 5 7.9 5Health services 5 7.9 6Information on health,environment 4 6.3 7Sanitation/Latrines 4 6.3 8Entrepreneurial ship/vocationaltraining 1 1.6 9Waste management 1 1.6 10Total 63 100SindoFood 18 72 1Better access to school education 2 8 2Employment/income 2 8 3Information on health,environment 2 8 4Total 24 96Missing (0) 1 4Total 25 100Source: Survey Data, March 2012This brief comparison, therefore, confirms that although food is regarded as a priorityneed across the three study areas; there is some difference when it comes to the otherneeds. It is, however, evident that respondents in Nyandiwa and Mbita similarly ratehighly the importance of access to education.25Figure 1: Perceived Priority Needs, NyandiwaFigure 2: Perceived Priority Needs, Mbita26Figure 3: Perceived Priority Needs, Sindo4.2.2.1 Understanding the Relative Importance of Food, Employment/Incomesand Better Access to School Education as perceived by respondents in thethree study areas.In the course of this study, it became evident that poverty is widespread throughoutthe region. For instance, according to the Suba District Strategic Plan, 2005 half of theDistrict’s population is in some state of poverty. The Plan identifies the causes ofpoverty as including the following: low farm yields; poor infrastructure especiallyroads; lack of access to credit facilities; high rate of deaths due to HIV/AIDS; lack ofaccess to electric power; and cultural beliefs and practices. Consequently, this level ofpoverty has implications on the District’s development initiatives since no meaningfuldevelopment can take place with half of the population still unable to meet their basicneeds.There is a close relationship between the identified poverty trends and unmet foodneeds leading a majority of the respondents to perceive food to be one of the mostimportant needs in the District. Agro-ecological conditions as well as the socioeconomic environment prevailing in the study area are the main reasons why food is amajor problem in the area. In both Suba and Mbita Districts, soil and climaticconditions such as rainfall are not conducive for sustainable agricultural production.In some parts members of the local community practice irrigation farming.27The causes of poverty identified also directly and indirectly influence food productionlevels in the study areas.Table 10: Socio-Economic Indicators, 2002Total number of Households 33,987Average Households size 4.6Absolute Poverty (Rural & Urban) 40.03% (47,219)Income from Agriculture 51%Income from Rural Self-employment 1%Wage employment 5%Urban self-employment 3%Fishing 40%Number of unemployed 3,088Source: Suba District Strategic Plan (2005-2011)The table shows that despite food being a major problem in the study areas,agriculture is still the predominant source of livelihood for the majority of thepopulation - 51 percent of the income received by the local communities is attributedto agriculture. The second most important source of livelihood is fishing whichaccounts for 40 percent of the total income. This is followed distantly by wageemployment (5%) and urban self-employment (3%).The data also explains why the respondents perceive employment and incomes as achallenge. Besides farming and fishing, wage employment takes care of a very smallfraction of the incomes in the study areas. This is partly explained by the fact thatmajority of the employment positions are held by employees from outside the localareas. In itself this could be the result of lack of requisite skills among the localcommunities. The results of the study are presented against this background.Plate 10: A horticulturalirrigation projectsponsored by Value GirlsProgram through JiinueHoldings (K) Ltd nearKaugege Beach in MbitaDistrictPhoto: Courtesy ofResearch Team284.2.2.2 Other Needs in the Study Area.A further discussion of the top four priority needs is undertaken in this part. Besidesfood these needs are: energy, housing, water and education.4.2.3 EnergyIn Nyandiwa, 23 of the 25 respondents thought the most important end uses forenergy were lighting and cooking. In Mbita and Sindo, the same end uses were rankedhigher than any other. This shows clearly that among the respondents, cooking andlighting were rated at the top among energy end uses. Table 11 presents details of theend uses considered important in the three study areas.Table 11: Energy Needs by their End UsesResearch area Energy needs Frequency Percent Valid Percent RankNyandiwa LightingCooking121148.044.052.247.812Total 23 92.0 100.0Missing (0) 2 8.0Total 25 100.0Mbita Batteries 2 3.2 3.2 3Cooling 1 1.6 1.6 4Cooking 33 52.4 52.4 1Lighting 26 41.3 41.3 2Mobile phonecharging1 1.6 1.6 4Total 63 100.0 100.0Sindo Cooking 6 24.0 24.0 2Lighting 17 68.0 68.0 1Mobile phonecharging2 8.0 8.0 3Total 25 100.0 100.0Source: Survey Data, (2012)In addition to the end uses, it was deemed important to find out how the lighting,cooking and other end uses were made possible. An outline of the sources of energyin each case is presented below.294.2.3.1 LightingLighting is an important end use in the study areas as it is elsewhere. Anoverwhelming majority of the respondents (82.3%) used kerosene as the source ofenergy for lighting purposes. Electricity and solar energy were the next mostimportant source of energy reported but as it may be observed by a much lowerpercentage of the respondents: 9.7% and 6.2% respectively.Table 12: Lighting as End Use of EnergySource Frequency Percent Cumulative PercentCandle 2 1.8 1.8Kerosene 92 81.4 83.2Electric light 11 9.7 92.9Solar 7 6.2 99.1Kerosene/ Solar 1 .9 100.0Total 113 100.0 Source: Survey Data, (2012)Kerosene was the most widely used source for lighting in all areas. Electricity wasused most in Mbita (15.9%) and in Sindo (4%) but was absent in Nyandiwa (Table13). The data shows that solar was also used but by a small percentage of therespondents.Table 13: Lighting SourcesResearcharea Source Frequency PercentCumulativePercentNyandiwa Candle 1 4.0 4.0Kerosene 23 92.0 96.0Solar 1 4.0 100.0Total 25 100.0Mbita Candle 1 1.6 1.6Kerosene 45 71.4 73.0Electric light 10 15.9 88.9Solar 6 9.5 98.4Kerosene/Solar1 1.6 100.0Total 63 100.0Sindo Kerosene 24 96.0 96.0Electric light 1 4.0 100.0Total 25 100.0Source: Survey Data, 201230Kerosene lighting devices were used by the majority who comprised 80.5% of therespondents (65.5% used kerosene lamp and 15% tin lamps). Additionally, 1.8% usedkerosene lamps together with electricity and solar devices.Table 14: Lighting devices UsedLighting device Frequency Valid Percent Cumulative PercentElectric bulb 10 8.8 8.8Kerosene lamp 74 65.5 74.3Solar lamp 8 7.1 81.4Tin lamp 17 15.0 96.5Safari lamp 2 1.8 98.2Electric/ Kerosene 1 .9 99.1Kerosene/ Solar 1 .9 100.0Total 113 100.0Source: Survey Data, 2012The lighting devices for each area were in tandem with the source of light. Forinstance, in Nyandiwa virtually all respondents used kerosene devices apart from 4%who used solar devices. In Mbita 15.9% of the respondents used an electric bulb.Table 15: Lighting device per areaResearch area Device Frequency Percent Cumulative PercentNyandiwa Kerosene 19 76.0 76.0Solar lamp 1 4.0 80.0Tin lamp 5 20.0 100.0Total 25 100.0Mbita Electric bulb 10 15.9 15.9Kerosene 41 65.1 81.0Solar lamp 6 9.5 90.5Tin lamp 4 6.3 96.8Electric/Kerosene1 1.6 98.4Kerosene/Solar1 1.6 100.0Total 63 100.0Sindo Kerosene 14 56.0 56.0Solar lamp 1 4.0 60.0Tin lamp 8 32.0 92.0Safari lamp 2 8.0 100.0Total 25 100.0Source: Survey Data, 2012314.2.3.2 CookingSources of energy for cookingFirewood was the most widely used energy source for cooking. Firewood only wasused by 44.2% of the respondents. Additionally, a further 33.7% of the respondentsused firewood in combination with other energy sources. This makes 78.8% therespondents who used firewood. Charcoal was the second most common source ofenergy for cooking as noted in 51.3% of the respondents. Other energy sources wereused as shown in Table 16.Table 16: Energy sources for cookingEnergy for cooking Frequency Percent Cow dung 1 0.9 Crop leftovers 0 0.0 Gas 9 8.0 Electricity 1 0.9 Kerosene 16 14.2 Firewood 89 78.8 Charcoal 58 51.3N (for each source) = 113Analysis for each area reveals that Mbita and Sindo have more diverse sources ofenergy than Nyandiwa where firewood and charcoal are the only sources of energyfor cooking. (Table 17).Table 17: Sources of energy for cooking by area Nyandiwa Mbita Sindo Energy source Frequency Percent Frequency Percent Frequency Percent Cow dung 0 .0 0 .0 1 4.0 Crop leftovers 0 .0 0 .0 0 .0 Gas 0 .0 7 11.1 2 8.0 Electricity 0 .0 1 1.6 0 .0 Kerosene 0 .0 13 20.6 3 12.0 Firewood 21 84.0 46 73.0 22 88.0 Charcoal 8 32.0 39 61.9 11 44.032Cooking devicesThe three stone fire place dominates as it was used by 70.8% of the respondents whoeither used it alone or in combination with other cooking devices. The ordinarycharcoal stove (jiko) was also fairly common and was used by 40.7% of therespondents. The cooking devices used in the study areas are as shown in Table 18.Table 18: Devices used in cookingDevice Frequency Percent3-stone 80 70.8Electric cooker 1 .9Gas cooker 10 8.8Improved charcoal stove (jiko) 10 8.8Ordinary charcoal stove (jiko) 46 40.7Kerosene stove 1 .9Source: Survey Data 2012Although the 3-stone fire-place was used in all areas by the majority, in Sindo it wasused by the largest percentage of the respondents (88%) as compared to Mbita(65.1%) and Nyandiwa (68%). In all areas the ordinary charcoal stove (jiko) was usedby more people than the improved one.Table 19: Devices used in cooking by Study AreaNyandiwa Mbita SindoDeviceFrequency Percent Frequency Percent Frequency Percent3-Stone FirePlace17 68.0 41 65.1 22 88.0Electric cooker 0 .0 1 1.6 0 .0Gas cooker 3 12.0 6 9.5 1 4.0Improved jiko 1 4.0 9 14.3 0 .0Ordinary jiko 7 28.0 29 46.0 10 40.0Kerosene stove 1 4 0 .0 0 .0Source: Survey Data 2012Firewood CollectionMost of the people collect firewood from within a distance of 1 kilometre (54.4%)from their homes. About 20% collect it from within a distance of 2 kilometres and23.3% collect firewood from a distance greater than 2 km from their homes (see Table20).33Table 20: Distance Travelled to Collect FirewoodDistance Frequency Percent Valid Percent Cumulative PercentLess than 1 km 49 43.4 54.4 54.41-2 Km 20 17.7 22.2 76.72-4 Km 8 7.1 8.9 85.64-6 Km 9 8.0 10.0 95.6Above 6 Km 4 3.5 4.4 100.0Total 90 79.6 100.0Missing 23 20.4Total 113 100.0Source: Survey Data, 2012Residents of Sindo collected their firewood from within a shorter distance from theirhomes than in other study areas. In Sindo the cost of a bundle of firewood was alsothe lowest (KES 70 approx. $0.84) as compared to Mbita (KES 99 approx. $1.19) andNyandiwa (KES 145 approx. $1.68– Central Bank Exchange rate: $1=KES 83 TheDaily Nation, Friday April 20, 2012). The people of Nyandiwa, despite buyingfirewood at the highest price used the largest amount.4.2.4 HousingAs shown in the table below, 63.7% of the respondents occupied semi-permanenthouses while 21.2% of the respondents occupied Permanent houses.Table 21: Kind of HouseType Frequency Percent Cumulative PercentPermanent 24 21.2 21.2Semi-permanent 72 63.7 85.0Temporary 17 15.0 100.0Total 113 100.0Source: Survey Data, 2012Mbita had the highest number of respondents living in permanent houses (31.7%) ascompared to 8% of the respondents in Sindo and Nyandiwa. Most of the respondentslived in semi-permanent houses, 72% in Nyandiwa and Sindo and 57.1% in Mbita.34Table 22: Type of House per Research AreaResearch area Type Frequency Percent Cumulative PercentNyandiwa Permanent 2 8.0 8.0Semi-permanent 18 72.0 80.0Temporary 5 20.0 100.0Total 25 100.0Mbita Permanent 20 31.7 31.7Semi-permanent 36 57.1 88.9Temporary 7 11.1 100.0Total 63 100.0Sindo Permanent 2 8.0 8.0Semi-permanent 18 72.0 80.0Temporary 5 20.0 100.0Total 25 100.0Source: Survey Data, 2012Majority of the respondents lived in their own houses (62.8%) while the rest (37.2%)rented the house in which they lived (See Table 23 below).Table 23: House Ownership or RentOwnership Frequency Percent Cumulative PercentRent 42 37.2 37.2Own 71 62.8 100.0Total 113 100.0Source: Survey Data, 2012Renting of houses was highest in Nyandiwa (52%), followed by Mbita (36.5%) andSindo (28%) (See Table 24).Table 24: Rent/Ownership of House per Study AreaResearch Area Ownership Frequency Percent Cumulative PercentNyandiwa Rent 12 48.0 48.0Own 13 52.0 100.0Total 25 100.0Mbita Rent 23 36.5 36.5Own 40 63.5 100.0Total 63 100.0Sindo Rent 7 28.0 28.0Own 18 72.0 100.0Total 25 100.0Source: Survey Data, 201235Majority of the households had a total number of members ranging between 4 and 6.38% had 5 or 6 members, 16% had 4 members, 19% less than 4 members 8 % 28%had more than 6 members.Table 25: Household sizeNumber of people perhousehold Frequency Percent1 8 7%2 4 4%3 9 8%4 18 16%5 21 19%6 22 19%7 5 4%8 7 6%9 5 4%10 3 3%11 3 3%12 4 4%13 4 4%Total 113 100%Source: Survey Data, 20124.2.5 Water UseExclusively for drinking purposes tap water was used by 14.2%, water from watervendors at kiosks by 0.9%, lake water by 1.8% of the respondents as well as wellwater. Water kiosks and wells were the least common sources of water serving only6.2% of the population each. Tap water was used by 27.4% of the respondents, waterfrom water vendors at kiosks by 6.2%, lake water by 78.8%, and water from wells by6.2%. It is important to note that while 1.8% of the respondents use Lake Waterexclusively for drinking, 61.9% use Lake Water both for drinking and other purposes.Therefore, 63.7% of the respondents use Lake Water for drinking as shown in theTable 26 below.36Table 26: Water uses according to sourcesTap water Kiosk water Lake water Well waterUse of water F % F % F % F %Drinking 16 14.2 1 .9 2 1.8 2 1.8Non-drinking 2 1.8 4 3.5 17 15.0 1 .9Both 13 11.5 2 1.8 70 61.9 4 3.5Total 31 27.4 7 6.2 89 78.8 7 6.2Missing 82 72.6 106 93.8 24 21.2 106 93.8Total 113 100.0 113 100.0 113 100.0 113 100.0Source: Survey Data, 2012A majority of the respondents (81.4%) reported that they are able to access theamount of water that they require for drinking.Table 27: Access to amount needed for drinking Frequency Percent ValidPercentCumulativePercentValid Access 92 81.4 82.1 82.1No Access 20 17.7 17.9 100.0Total 112 99.1 100.0Missing .00 1 .9 Total 113 100.0Source: Survey Data, 2012Of the 17.7% who had limited access to amounts of water for drinking, 14.3% dugboreholes, 23.8 purchased water while 38.1 used chemicals to treat water. 23.8% didnot indicate their coping mechanism.Table 28: Coping with limited amounts of wholesome drinking water Frequency Percent Cumulative PercentValid Digging borehole 3 14.3 14.3Purchase 5 23.8 38.1Chemical treatment 8 38.1 76.2Missing .00 5 23.8 100 Total 21 100.0Source: Survey Data, 2012374.2.6 LatrinesTable 29 shows that 36.3% of respondents reported not having latrines.Table 29: Presence of latrine/toiletPresence Frequency Percent Cumulative PercentYes 72 63.7 63.7No 41 36.3 100.0Total 113 100.0Source: Survey Data, 2012Table 30 shows that 68% of residents in Nyandiwa did not have latrines. This wasfollowed by Sindo (28%) and Mbita (27%) (Table 29). Observation results show thatmajority of the households visited did not have toilets, but instead had pit latrines.Table 30: Presence of latrines in each research areaResearch area Presence Frequency Percent Cumulative PercentNyandiwa Have 8 32.0 32.0None 17 68.0 100.0Total 25 100.0Mbita Have 46 73.0 73.0None 17 27.0 100.0Total 63 100.0Sindo Have 18 72.0 72.0None 7 28.0 100.0Total 25 100.0Source: Survey Data, 2012Of those who had latrines, 11.4% had improved latrines and the rest (88.6%) hadordinary ones. The findings showed that most of the households in Mbita town hadlatrines compared to Nyandiwa and Sindo.Table 31: Kind of latrineType Frequency Percent Valid Percent Cumulative PercentOrdinary 62 54.9 88.6 88.6Improved 8 7.1 11.4 100.0Total 70 61.9 100.0Missing 43 38.1Total 113 100.0Source: Survey Data, 2012All the respondents who reported to have latrines in Nyandiwa reported them as beingordinary.38Table 32: Kind of latrine used within the three study areasResearch area Type Frequency Percent Valid Percent Cumulative PercentNyandiwa Ordinary 8 32.0 100.0 100.0Missing 17 68.0Total 25 100.0Mbita Ordinary 38 60.3 86.4 86.4Improved 6 9.5 13.6 100.0Total 44 69.8 100.0Missing 19 30.2Total 63 100.0Sindo Ordinary 16 64.0 88.9 88.9Improved 2 8.0 11.1 100.0Total 18 72.0 100.0Missing 7 28.0Total 25 100.0Ordinary latrines were improved by cementing them, improving walls, roofing,ventilation (see Table 32).76% of the respondents did not have their own latrines and either shared withneighbours or relieve themselves in the bushes.Table 33: Ways of improving ordinary latrinesWay of Improving Frequency Percent ValidPercentCumulativePercentCemented andpermanent24 21.2 64.9 64.9Roofing 2 1.8 5.4 70.3Provide water in toilet 2 1.8 5.4 75.7Drain the waste 1 .9 2.7 78.4Proper ventilation 2 1.8 5.4 83.8Improve walls 6 5.3 16.2 100.0Total 37 32.7 100.0Missing 76 67.3Total 113 100.0Source: Survey Data, 2012394.2.7 Waste disposalLiquid wasteLiquid wastes were mainly disposed of by throwing them away. Virtually all therespondents 97.3% used this method to dispose their liquid waste (see Table 34).Table 34: Ways of disposing liquid wasteMethod Frequency Percent Valid Percent Cumulative PercentThrow away 109 96.5 97.3 97.3Dust bin 1 .9 .9 98.2Bury 1 .9 .9 99.1Burn/ Recycle 1 .9 .9 100.0Total 112 99.1 100.0Missing 1 .9Total 113 100.0Source: Survey Data, 2012Solid waste66.4% of the respondents disposed solid waste by burning while 28% buried thewaste. (Table 35).Table 35: Disposing solid wasteMethod Frequency PercentageThrowing away 5 4.4Use of dust bins 7 6.2Burying 32 28.3Burning 75 66.4Recycling 10 8.8Compost Pit 2 1.8Source: Survey Data, 2012404.2.8 EmploymentThe self-employed were the majority (65.5%) as compared to the employed (21.2%)and the unemployed (8%) for all the three areas.Table 36: Employment statusStatus Frequency Percent Valid Percent Cumulative PercentEmployed 24 21.2 22.4 22.4Self employed 74 65.5 69.2 91.6None 9 8.0 8.4 100.0Total 107 94.7 100.0Missing 6 5.3Total 113 100.0Source: Survey Data, 2012In Sindo all respondents were self-employed, whereas the self-employed were 68% inNyandiwa and 50.8% in Mbita. Mbita had the highest number of employed persons(Table 37).Table 37: Employment status in the three areasResearch area Status F % Valid Percent Cumulative PercentNyandiwa Employed 3 12.0 13.0 13.0Self employed 17 68.0 73.9 87.0None 3 12.0 13.0 100.0Total 23 92.0 100.0.00 Missing 2 8.0Total 25 100.0Mbita Employed 21 33.3 35.6 35.6Self employed 32 50.8 54.2 89.8None 6 9.5 10.2 100.0Total 59 93.7 100.0Missing 4 6.3Total 63 100.0Sindo Self employed 25 100.0 100.0 100.041The occupations of the respondents are as shown in Table 38Table 38: Household occupationFishing Agriculture Retail/salesConstruction Manufacturing(bakery)Services Govt. & PublicservicesEducation UnemployedPerson F % F % F % F % F % F % F % F % F %Husband 19 16.8 11 9.7 4 3.5 2 1.8 0 0 8 7.1 3 2.7 4 3.5 5 4.4Wife 6 5.3 31 27.4 14 12.4 0 0 1 .9 7 6.2 4 3.5 1 .9 9 8.0Both 4 3.5 5 4.4 1 .9 0 0 0 0 0 0 2 1.8 0 0 0 0Total 29 25.7 47 41.6 19 16.8 2 1.8 1 1.9 15 13.3 9 8.0 5 4.4 14 12.4Missing(None)84 74.3 66 58.4 94 83.2 111 98.2 112 99.1 98 86.7 104 92.0 108 95.6 99 87.6Total 113 100.0 113 100.0 113 100.0 113 100.0 113 100.0 113 100.0 113 100.0 113 100.0 113 100.0Source: Survey Data, 20124.2.9 Use of Computers/Information Communication TechnologyUse of computers in daily work73% of the households indicated that they did not use computers in their daily work while27% did. This was mainly because of poverty, low computer literacy levels in the area,lack of access to electricity and the fact that most of the households were engaged inoccupations such as fishing and small and micro-enterprises that did not require computeruse. It was also established that there were four internet cyber cafes in the three areas ofSindo, Mbita and Nyandiwa (2 in Mbita Town - one with 6 computers and the other with5 computers, 2 in Sindo - one with three computers and the other with four computers,and none in Nyandiwa). It is clear from the number of available computers that the cybercafes had limited capacity to serve the area population.Figure 4: Use of computer in daily workSource: Survey Data, 2012Computer uses12.4% of the respondents indicated that computers assisted them in data processing /report writing, 8.8% used computers for record keeping/ data storage, 2.7% usedcomputers for communication, while 2.7% used computers for Internet browsing. (Table39)43Table 39: Computer UsesFrequency PercentValidPercentCumulativePercentValid Record keeping/ Data storage 10 8.8 33.3 33.3Data processing/Report writing 14 12.4 46.7 80.0Communication 3 2.7 10.0 90.0Internet browsing 3 2.7 10.0 100.0Total 30 26.5 100.0Missing .00 83* 73.5Total 113 100.0*Not applicableSource: Survey Data, 2012Use of computers sometimes even if daily work does not require computer Use41 respondents i.e. 36% of the respondents used computers other than for carrying outdaily work, while 72 respondents i.e. 64% did not. 36% is inclusive of respondents whouse computers in the course of their work.This is indicative of the fact that most people inthe three communities of Mbita, Sindo and Nyandiwa were not computer literate, a mostlikely reason why they were not using computers.Figure 5: Use of computer sometimes even if daily work does not require computeruseSource: Survey Data, 201244Exact use of computersComputers are used as follows: communication (12.4%); internet browsing (6.2%); reportmaking / computer work (4.4%); record keeping (2.7%); Computer work/ Internet(0.9%); Entertainment / Communication (0.9%); and Entertainment (0.9%).Table 40: Exact use of computerFrequency PercentValidPercentCumulativePercentValid Entertainment 1 .9 3.1 3.1Communication 14 12.4 43.8 46.9Record keeping 3 2.7 9.4 56.3Report making/ computer work 5 4.4 15.6 71.9Internet browsing 7 6.2 21.9 93.8Entertainment/ Communication 1 .9 3.1 96.9Computer work/ Internet 1 .9 3.1 100.0Total 32 28.3 100.0Missing .00 81* 71.7Total 113 100.0*Not applicableSource: Survey Data, 2012Ways of access to computer servicesThe findings show that 15% of the households accessed computer services mainly atinternet cafes; 5.3% accessed computers at work; 3.5% accessed the services both atwork and in internet cafes; 2.7% accessed computers in other locations; 0.9% at homeand 0.9% accessed the services both at home and at work.45Table 41: Ways of access to computer servicesFrequency PercentValidPercentCumulativePercentValid Computer at home 1 .9 2.0 2.0At work 6 5.3 12.0 14.0At internet cafe 17 15.0 34.0 48.0Other location 3 2.7 6.0 54.0Home/ Work 1 .9 2.0 56.0Work/Internet cafe 4 3.5 8.0 64.0None 18 15.9 36.0 100.0Total 50 44.2 100.0Missing .00 63 55.8Total 113 100.0Source: Survey Data, 2012Access to internetThe findings show that 66% of the households did not have access to internet services,while only 34% had access. Most people in the survey areas had not yet appreciated thebenefits associated with internet use and this was mainly due to challenges that can belinked with unfavourable infrastructural conditions existing in the area.Figure 6: Access to internetSource: Survey Data, 201246Devices and locations to access internetThe devices used in accessing internet services include computers at internet cafés (usedby 9.7% of the respondents); mobile phones (used by 8% of the respondents); combineduse of mobile phone / internet café (3.5% of the respondents); combined use of homecomputer, workplace computer and internet café (3.5%); combined mobile phone andhome computer (1.8%); exclusively workplace compute (1.8%); combined workplacecomputer and internet café (0.9%); while 3.5% of the respondents indicated that theyaccessed internet café in other locations (this could include friends’ computers).Table 42: Devices and location to access internetDevice Frequency Percent ValidPercentCumulativePercentValid Mobile phone 9 8.0 25.7 25.7Computer at work 2 1.8 5.7 31.4Computer at internet cafe 11 9.7 31.4 62.9Mobile phone/ Homecomputer2 1.8 5.7 68.6Mobile phone / Internet cafe 4 3.5 11.4 80.0Work computer/ Internetcafe1 .9 2.9 82.9Home computer/ Workcomputer/ Internet cafe2 1.8 5.7 88.6Other location 4 3.5 11.4 100.0Total 35 31.0 100.0Missing .00 78 69.0Total 113 100.0Source: Survey Data, 2012Ownership of mobile phoneOn whether or not they owned a mobile phone, 73% of the respondents (households)owned mobile phones, 9% shared with friends or relations, while 18% had none.However, it became apparent that most of these phones were not internet enabled.Moreover, if they had features for internet browsing, the phone owners lacked thetechnical knowhow on how to use them to access internet services.47Figure 7: Ownership of mobile phoneSource: Survey Data, 20124.2.10 Information NeedsOn whether or not respondents felt a need for more information in six selectedinformation needs areas, the need for more information in entrepreneurship emerged thehighest at 57.5%. The rest were as follows: need for more information on hygiene(41.6%); need for more information on health (38.1%); need for more information oncomputer skills (31.9%); need for more information on life-skills (18.6%); and need formore information on environment (9.7%).Table 43: Information NeedsInformation needs % Yes % No Total%Need for more information in health 38.1 61.9 100Need for more information in hygiene 41.6 58.4 100Need for more information onenvironment9.7 90.3 100Need for more information in computerskills31.9 68.1 100Need for more information inentrepreneurship57.5 42.5 100Need for more information in life-skills 18.6 81.4 100Source: Survey Data, 2012484.2.11 Attendance to Course of Instruction (Training)On whether or not they had ever attended a course of instruction in topical areas ofMarketing, Book-keeping and accounts, Sales, Business Plan Development, ComputerLiteracy and Life skills (CV writing, presentation skills, communication skills), only 29%had ever attended such a course of instruction. However, other courses taken arepresented in Table 44Table 44: Attendance to Course of InstructionCourseAttendedNo. ofRespondentsPercent Place ofTrainingDuration Nature/Level ofTrainingCertifying /Awarding BodyMarketing 6 5% Moi University,StrathmoreUniversity,Kenya Instituteof ManagementCertificate(6 months)Diploma 1YearCertificate,DiplomaSame Institute,Kenya NationalExaminationsCouncilBook keeping &Accounts4 4% Moi University,Strathmoreuniversity,KenyaPolytechnic12 months Certificate,DiplomaKASNEB,ACCA, KenyaNationalExaminationsCouncilSales 3 3% Kenya Instituteof Management12 months Diploma Kenya NationalExaminationsCouncilBusiness planDevelopment7 6% LocalPolytechnic3 months NocertificateInternalexaminationComputerLiteracy8 7% University ofNairobi, KenyaPolytechnic,Overseas collegeCanada (1)3 months CollegeCertificateInternalexaminationLife skills (CVwriting,presentationskills,communicationskills)5 4% USAID 2 Weeks -workshopNocertificateNo examinationTotal 33 29%Source: Survey Data, 201249Training in other coursesOther trainings taken were in the areas of community and family health (8.8%), tailoring(6.2%), teaching (3.5%), community development (0.9%), hygiene (0.9%), Nursing(1.8%), Hair dressing (0.9%), Mechanics (1.8%), Masonry (0.9%), Personnelmanagement (0.9%), Welding and fabrication (0.9%), Veterinary (0.9%), Counselling(0.9%), Photography (0.9%), Early Childhood Development (0.9%), and Leatherwork(0.9%) as shown below.Table 45: Training in other coursesFrequency Percent ValidPercentCumulativePercentValid Community/Family health 10 8.8 27.8 27.8Community development 1 .9 2.8 30.6Hygiene 1 .9 2.8 33.3Nursing 2 1.8 5.6 38.9Teaching 4 3.5 11.1 50.0Tailoring 7 6.2 19.4 69.4Hair dressing 1 .9 2.8 72.2Mechanic 2 1.8 5.6 77.8Masonry 1 .9 2.8 80.6Personnel management 1 .9 2.8 83.3Welding and fabrication 1 .9 2.8 86.1Veterinary 1 .9 2.8 88.9Counselling 1 .9 2.8 91.7Photography 1 .9 2.8 94.4Early ChildhoodDevelopment1 .9 2.8 97.2Leatherwork 1 .9 2.8 100.0Total 36 31.9 100.0Missing .00 77 68.1Total 113 100.0Source: Survey Data, 2012Apart from courses such as Community Development, Community and Family Health,Nursing and Teaching which lasted for a period of between 24 months and 48 months,the other courses lasted for between one week and 12 months.50Place of training in other coursesThe places of training for the other courses were identified as: Nairobi UniversityCollege, Muran’ga Teachers’ Training College, Kenya Medical Training College(KMTC) – Kisii, Rift Valley Institute of Science and Technology (RVIST), KabeteTechnical Training Institute, Kapswanga Hospital, Tom Mboya Health Center and St.Josephs Kitale Technical Training Institute. (See Table 46 below).Table 46: Place of training in other coursesFrequency PercentValidPercentCumulativePercentValid Nairobi University 2 1.8 10.0 10.0College 10 8.8 50.0 60.0Muran’ga TTC 1 .9 5.0 65.0Kisii MTC 1 .9 5.0 70.0RVIST 1 .9 5.0 75.0Kabete 1 .9 5.0 80.0Kapswanga Hospital 2 1.8 10.0 90.0Tom Mboya HealthCenter1 .9 5.0 95.0St. Joseph’s, KTTI 1 .9 5.0 100.0Total 20 17.7 100.0Missing .00 93* 82.3Total 113 100.0*Not ApplicableSource: Survey Data, 2012Impact of training on householdsOn whether or not the training helped the respondents 41.6% (47 out of 56) trained invarious areas indicated that the training had benefited them, while 58.4% (9 out of 56)did not derive any benefits from the training. See Table 47.51Table 47: Impact of training on householdsFrequency PercentValidPercentCumulativePercentValid Yes 47 41.6 83.9 83.9No 9 8.0 16.1 100.0Total 56 49.6 100.0Missing .00 57 50.4Total 113 100.0Source: Survey Data, 2012The respondents further indicated that training had helped them to: earn income (9.7%),get employed (4.4%), Mid-wifing (2.7%), Home building (2.7%), Handling customers(1.8%), Working with computers (1.8%), Develop business skills (1.8%), Bettercommunication and reporting (1.8%), Personal development skills (1.8%), Personalhealth/ hygiene improvement (0.9%), Marketing skills (0.9%) and Peace building (0.9%).See Table 48.Table 48: Specific benefits from trainingBenefitFrequency PercentValidPercentCumulativePercentProfit and loss calculation 1 .9 2.6 2.6Earn income 11 9.7 28.2 30.8Employment 5 4.4 12.8 43.6Handling customers 2 1.8 5.1 48.7Working with computers 2 1.8 5.1 53.8Develop business skills 2 1.8 5.1 59.0Better communication andreporting2 1.8 5.1 64.1Personal development skills 2 1.8 5.1 69.2Personal health/ hygieneimprovement1 .9 2.6 71.8Education 2 1.8 5.1 76.9Marketing skills 1 .9 2.6 79.5First aid skills 1 .9 2.6 82.1Midwifery 3 2.7 7.7 89.7Peace building 1 .9 2.6 92.3Home building 3 2.7 7.7 100.0Total 39 34.5 100.0Missing.00 74 65.5Total 113 100.0Source: Survey Data, 201252The type of certification issued to the respondents after training included certificate(25.7%), Diploma (6.2%) and degree (0.9%). Nine (9) respondents, that is 8%, were notissued with any form of certification after training (See Table 49).Table 49: Type of certification issued to the respondentsFrequency PercentValidPercentCumulativePercentValid Certificate 29 25.7 63.0 63.0Diploma 7 6.2 15.2 78.3Degree 1 .9 2.2 80.4None 9 8.0 19.6 100.0Total 46 40.7 100.0Missing .00 67 59.3Total 113 100.0Source: Survey Data, 20124.2.12 Respondents’ (Households’) EarningsIt proved difficult for most of the respondents, especially the salaried persons, to indicatehow much they earned per day or per week because of the irregularity of the earnings.Those engaged in business indicated seasonality as a factor making precision difficult inwhich case they were asked to give an estimate as accurately as they could. Wage-earnerswere able to indicate the income per day, per week as well as per month. The averageincome earned per day for the entire group was Kenya shillings 476.35, the averageearning per week for the group was Kenya shillings 2007.70 ($24.18), while the averageearnings per month was Kenya shillings 7963.11($95.94) ($5.73 Central Bank ExchangeRate 1$=KES 83, Daily Nation, Friday April 20 2012) (See Table 50).Table 50: Earnings per day / week or monthN Minimum Maximum Mean Std. DeviationAmount of money earned per day 88 20.00 8000.00 476.3295 988.38674Amount of money earned per week 48 100.00 15000.00 2007.7083 2989.76828Amount of money earned permonth78 300.00 60000.00 7963.1154 10830.01452N=the number of respondents who responded to the particular questionSource: Survey Data, 201253Regularity of Income EarnedOn whether or not respondents earned regular income, it was established that 58% of therespondents earned regular income, while 42% indicated that they did not (See Table 51).Table 51: Regularity of Income EarnedFrequency PercentValidPercentCumulativePercentValid Yes 66 58 58 58No 47 42 100 100.0Total 113 100 100.0Source: Survey Data, 20124.2.12 Respondents’ (Households’) ExpendituresThe respondents’ expenditures on selected expenditure line items is presented hereunder.Average amount of money spent on foodHouseholds spent on average 288.96 ($3.48), 2688.57 ($32.39), and 6, 520.94($78.56)Kenya shillings on food per day, week and month respectively. (See Table 52).Table 52: Average amount of money spent on foodN Minimum Maximum MeanStd.DeviationAmount of money spent on food perday75 70.00 700.00 288.9600 147.96068Amount of money spent on food perweek14 490.00 4900.00 2688.5714 1239.87504Amount of money spent on food permonth53 150.00 30000.00 6520.9434 6175.84602Source: Survey Data, 2012Average amount of money spent on shelterHouseholds spent on average 119.26 ($1.43), 835.00 ($10.06), 1718.48($20.70) Kenyashillings on shelter per day, week and month respectively. (See Table 53).54Table 53: Average amount of money spent on shelterN MinimumMaximum MeanStd.DeviationAmount of money spent onshelter per day9 21.00 429.00 119.2667 125.97972Amount of money spent onshelter per week9 150.00 3000.00 835.0000 880.33729Amount of money spent onshelter per month33 200.00 12000.00 1718.48482227.99535Source: Survey Data, 2012Average amount of money spent on clothesHouseholds spent on average 65.59 ($0.79), 445.83 ($5.37), and 1392.85($16.78) Kenyashillings on clothes per day, week and month respectively. (See Table 54).Table 54: Average amount of money spent on clothesN Minimum Maximum MeanStd.DeviationAmount of money spent on cloth perday11 7.10 107.00 65.5909 36.38757Amount of money spent on cloth perweek12 50.00 750.00 445.8333 247.90791Amount of money spent on cloth permonth49 200.00 4000.00 1392.8571 967.76159Source: Survey Data, 2012Average amount of money spent on energyHouseholds spent on average 47.86 ($0.57), 507.64 ($6.11) and 1473.75($17.75) Kenyashillings on energy per day, week and month respectively. (See Table 55).Table 55: Average amount of money spent on energyN Minimum Maximum Mean Std. DeviationAmount of money spenton energy per day58 8.50 286.00 47.8621 51.56557Amount of money spenton energy per week17 40.00 2000.00 507.6471 531.94254Amount of money spenton energy per month58 95.00 12000.00 1473.7586 1984.24229Source: Survey Data, 201255Average money spent on waterHouseholds spent on average 49.68 ($0.59), 415.80 ($5.00) and 928.57 ($11.18) Kenyashillings on water per day, week and month respectively. (See Table 56).Table 56: Average amount of money spent on waterN Minimum Maximum Average Std.DeviationAmount of money spenton water per day22 5.00 300.00 49.6864 67.01716Amount of money spenton water per week13 35.00 2100.00 415.8077 602.33240Amount of money spenton water per month35 10.00 8400.00 928.5714 1637.92039Source: Survey Data, 2012Average money spent on educationHouseholds spent on average 450.05 ($5.42), 3149.25 ($37.94) and 3396.53($40.92)Kenya shillings on education per day, week and month respectively. (See Table 57).Table 57: Average amount of money spent on educationN Minimum Maximum Average Std.DeviationAmount of money spenton education per day11 17.00 1809.50 450.0545 637.07854Amount of money spenton education per week11 120.00 12667.00 3149.2455 4460.86657Amount of money spenton education per month83 100.00 50667.00 3396.5301 7898.52423Source: Survey Data, 201256Average money spent on healthHouseholds spent on average 42.17 ($0.51), 300 ($3.61) and 1006.94($12.13) Kenyashillings on health per day, week and month respectively (See Table 58).Table 58: Average amount of money spent on healthN Minimum Maximum Average Std.DeviationAmount of money spenton health per day10 10.00 71.40 42.1700 22.06798Amount of money spenton health per week10 125.00 500.00 300.0000 146.72347Amount of money spenton health per month59 50.00 5000.00 1006.9492 1191.79704Source: Survey Data, 20124.2.13 Saving of money90.3% of the respondents indicated that they had embraced the practice of saving while9.7% had not. (See Table 59). The saving culture has been promoted by banks andmicrofinance institutions operating in the area such Adok Timo, Jiinue Holdings (K) Ltd,Kenya Women Finance Trust, Cooperative Bank and Equity Bank who have made theopening and maintenance of an operational account a prerequisite for credit financing.Table 59: Saving of moneyFrequency PercentValidPercentCumulativePercentValid Yes 102 90.3 90.3 90.3No 11 9.7 9.7 100.0Total 113 100.0 100.0Source: Survey Data, 2012Money Saving Places34.5% of the respondents saved money with banks, 30.1% with groups, 8.8% both withbanks and groups, 7.1% kept their money at home, 6.2% saved in their phones (mostlycapitalizing on the M-Pesa, Orange Money and Zap options), 1.8% saved with groupsand at home, 0.9% saved both with banks and mobile phones while 9.7% did not save atall. M-Pesa and Zap are mobile money transfer services provided by mobile phone57service providers: Safaricom, Orange and Airtel that allow subscribers to deposit andwithdraw money from their mobile phone accounts at their convenience.Table 60: Money Saving PlacesFrequency PercentValidPercentCumulativePercentValid Bank 39 34.5 38.2 38.2Group 34 30.1 33.3 71.6Home 8 7.1 7.8 79.4Mobile phone 7 6.2 6.9 86.3Bank/ Group 10 8.8 9.8 96.1Group/ Home 2 1.8 2.0 99.0Bank/ Mobilephone1 .9 1.0 100.0Total 102 90.3 100.0Missing .00 11 9.7Total 113 100.0Source: Survey Data, 2012585. CONSTRAINTS AND PROBLEMS5.1 Availability of DataAs was outlined at the beginning, baseline surveys serve to provide critical informationon various indicators including socio-economic and governance in study areas. Theinformation provides a basis for measuring impacts of intervention measuressubsequently planned and implemented to address particular issues adversely affect localcommunities. The success of such interventions, therefore, highly depends upon theaccuracy of information collected. This in itself depends on a number of factors,including: how the survey was conceived and designed, availability of data in therequired forms, ability of the research team to collect the requisite data, andexecution/implementation of the entire project.Having stated the above, there were some constraints experienced in the process ofexecuting the baseline survey in the study areas. First, the research team was not quitesatisfied with the quality and adequacy of available secondary data. While critical datawas missing, available data seemed to be outdated and, therefore, unreliable.Stakeholders in strategic leadership positions in the community including area chiefs andassistant chiefs, church leaders were identified and interviewed to provide information tofill the identified gaps in order to overcome this constraint.Second, most documented (secondary) information is only available and accessible fromMbita, the current headquarters of the old district. This renders project planning andexecution slow and unnecessarily cumbersome. Though it was time consuming, it was asuccessful approach. To accurately record the information, the research team employedobservation techniques backed up with photography.Third, Most of the respondents scheduled for interviews, who were government officersin charge of various departments, were not available on Thursdays and Fridays. This waspartly the result of many of them residing far away from their work stations, neglect ofduty, or simply taking undue advantage of the remoteness of Suba and Mbita Districts.Following this understanding, the research team used the links available at thegovernment offices at Mbita to trace the whereabouts of various government officers andrescheduled interviews with them at times convenient to them.Fourth, the local community was not enthusiastic about the survey at the beginning. Theresearch team was alive to the fact that once the community had approved of the project itwould offer the necessary support in ensuring collection of quality data. Therefore, toovercome this constraint, the research team first explained the importance of the surveyto the community leaders who having understood and endorsed the survey were able toinfluence the local community to take part. The research assistants were familiar with the59area and were personally known to most of the informants. Thus it was easy to secureendorsement for the project and its design.There was indecisiveness as to when the commissioning of the survey would be done onthe part of Light for Life. Indeed, the commissioning was done when the research teamand the Siemens team from Germany were already through with the pilot phase!The Terms of Reference (ToRs) for the survey were delivered to the research team longafter the survey had been conducted and when data analysis was underway. This furtherdelayed the finalization of the report.4.3 Data Reliability and RepresentativenessData reliability is highly dependent upon the instruments used in obtaining that data. If aninstrument is well designed, it should elicit the same type of answers every time it is usedon the same or even a different set of population sample. It is, therefore, important thatresearchers ensure that they have properly designed instruments to facilitate thecollection of data in an accurate and reliable manner.In the case of this project, the two instruments which were used to collect the requireddata were carefully designed and tested prior to being used. The instruments were firstdesigned by the Siemens Stiftung team. In the course of consultations, the twoinstruments – for community mapping and household survey - were extensively edited,expanded and re-structured to improve their clarity and focus. In this sense, both theSiemens Stiftung team and the research team had opportunity to fully collaborate in thedesign of the instruments. The instruments were pre-tested prior to being used. Theparticipation of the Siemens Stiftung team during the pre-testing phase was usefulbecause several inadequacies were identified and rectified before the actual data wascollected.Besides the above, research assistants who had experience in collecting data using similarinstruments were engaged and utilized. The research assistants were further put through acomprehensive one day training to ensure they were well-acquainted with the content andformat of the data collection tools.Prior to data collection there was a preparatory visit to the Mbita We!Hub operated byOsram - a multinational lighting manufacturer, headquartered in Munich, Germany, and awholly-owned subsidiary of Siemens. This was followed by a preparatory meetingbetween the research team (led by Kennedy Toboso) and Siemen Stiftung team composedof Weyrich and Koptisch on 15th February 2012 at ICIPE in Mbita.605. SUMMARY AND REVIEW OF THE SURVEYRESULTSThe objective of this survey (baseline) was to collect information and data consideredimportant in laying the foundation for more detailed research in the two districts of Subaand Mbita and introduction of further interventions. The survey was done in two parts:community mapping and household survey. The two have served to complement andenrich each other in terms of the information required and eventually obtained.Arising from the information obtained from the survey, it can be stated that Mbita andSuba districts do experience development challenges in various sectors. It would appearthat although the region relies mainly on the agricultural sector, agricultural production islow to the extent that the region has a food deficit. In the three areas where communitymapping was done and where household interviews were conducted, food is listed as anumber one priority need. Other problems experienced in the study areas include pooraccess to education, access to portable water, access to employment and incomes, andaccess to more reliable energy sources. Attempts seem to have been made towardsmitigating these challenges. For instance, the research team witnessed irrigationagriculture initiatives. But these are far between or being operated/implemented in anunsatisfactory manner to make significant impact. A preliminary observation indicatesthat some of the initiatives have not been successful: stalled water projects are but anexample.616. CONCLUSIONSArising from this study, it can be concluded that Suba and Mbita Districts experiencedevelopments needs that are not being met with the current development efforts from thecentral and local governments. Despite various initiatives by various NGOs and CBOsfocusing on the South Nyanza region (of which Mbita and Suba are part) there are stillmany unmet needs. The situation is compounded by an increasing population, lowliteracy levels, climate change, environmental degradation, unemployment, waterscarcity, lack of access to electricity, lack of access to health services, HIV/AIDS andMalaria prevalence, and “proximity syndrome” - isolation from the main markets, amongothers.62REFERENCESRepublic of Kenya (2009) Suba District Development Plan -2008 -2012. Government Printer: NairobiRepublic of Kenya (2005) Suba District Strategic Development Plan. Government Printer: NairobiRepublic of Kenya (2008) Mbita District Development Plan. Government Printer: Nairobi.http://www.ifad.org/operations/projects/regions/pf/factsheets/kenya.pdf. Accessedon 14th April, 2012.63APPENDICESAppendix 1 – Questionnaire: Community ProfileCommunity (official statistics, if available)1. Other than government administration, what other forms of governance exist?2. CommunityNumber of people in total _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _Number of households _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _3. Geographical location of the Community (use administrative/natural boundary)4. Education: Which institutions of learning are located in the community? (Please give name,exact location and numbers of students)Name of PrimarySchoolNo ofpupilsNo. of Teachers byGenderLocation SponsorshipMale Female12345. Secondary schoolsName ofSchoolNo ofpupilsNo. of Teachers byGenderLocation Sponsorship (private orpublic)Male Female12346. Tertiary (Universities)Name ofInstituteNo ofpupilsNo. of Teachers byGenderLocation Sponsorship (private orpublic)Male Female1234647. Vocational training institutesName ofInstituteNo ofpupilsNo. of Teachers byGenderLocation Sponsorship (private orpublic)Male Female12348. Other training institutions (governmental and/or private)a.b.c.d.9. Health: Which health centres / hospitals are located in the community? (please give nameand exact location) For each indicate sponsora.b.c.d.10. Community: How centres are located in the community? (please give name and exactlocation) For each indicate sponsora.b.c.d.11. Energy: How many members of the community are connected to the electric grid?_____________________12. What are the leading sources of energy in this community?a.b.c.d.13. Comment on the energy supply situation and indicators?14. Water: How many members of the community are connected to piped water?6515. How else does the community access water?16. Are water borne diseases common in the community?Yes No17. What do most people do to earn a living? List and ask community to list in order ofimportance18. a. Who are the main employers in the community? (if there are any)19. What is the Unemployment situation in the community?20. Indicators of unemployment21. Which organizations (CBOs/NGOs and Business Organizations) would you recommend to talkto with regard to community work? 1. Agriculture 2. Environment 3. Health 4.Education 5. Energy 6. Water etc. (please give the names and objectives/targets of theorganization)a.b.c.d.66Appendix 2: - Questionnaire at Household LevelThis Questionnaire is designed to learn more about the situation and needs in the local communities,where a WE! Hub is planned or already exists. To preserve your confidentiality please do not put yourname on the survey. We appreciate your help!Tell me about yourself1. Were you born in this area (Mbita District?Yes NoIf No, where do you come from? _______________________________________________Where do you live?Location __________________ Division ________________ District ___________________2. How did you come to live in Mbita (to be filled out by interviewer)Bought land Home land Employment other (pleasespecify)________________3. Gender (to be filled out by interviewer)Male Female4. How old are you? 17 and below 18-29 30-39 40-49 50 and above5. Have you ever attended school?Yes NoIf No, What factors prevented you from doing so?……………………………………………………………………………………………………………….6. If yes, what is the highest school level that you achieved?67Primary Secondary Tertiary (College, Apprenticeship, VocationalTraining) University None7. Which of the following languages do you normally speak at home?English Dholuo Kiswahili Suba other (please specify)________________8. Please rank the following needs / demands in your community using the scale 1 for mostpressing and 10 for lease pressing demand or need)1. Access to energy: 2. Access to health services3. Access to information and communication technology (e.g. computer, internet)4. Better access to school education5. Food6. Income / Employment7. More information on health, hygiene and environmentalissues8. Safe potable water9. Sanitation / Toilets10. Training measures on Entrepreneurship / Vocational training11. Waste Management / Dumping12. Other (please specify)__________________________________9. Please rank the following energy needs / demands in your community using the scale 1 formost pressing and 7 for lease pressing demand or need)a)batteriesb) coolingc) cooking devicesd) heatinge) lightingf) mobile phone chargingg) other:_______________________________________68Profile of Housing10. What kind of house do you live in? Permanent Semi- Permanent Temporary11. Do you rent or own your house?rent own12. How many people do you live with, in your household? – please circle number(Definition “household”: number of people living together in a house)1 2 3 4 5 6 7 8 9 10 11 12 more than 1213. What kind of lighting source do you use in your house?Candle Kerosene Electric light other (pleasespecify)__________________14. What device do you use for lighting in your house? Electric Bulb Kerosene Lamp Gas Light Pressure Lamp Solar Lampother (please specify)__________________15. What form of energy sources do you use for cooking? Cow dung Crop leftovers Gas Electricity Kerosene Firewood Charcoal Other, specify ____________________________16. What devices / Equipment do you use for cooking per day? 3 stone Electric cooker Gas cooker Improved Jiko Ordinary Jikoother (please specify)__________________17. How far does your household go to collect firewood?69Less than 1km 1 – 2 km 2-4km 4-6 km Above 6km18. How many bundles / heads of firewood do you use for cooking per day?19. How much money do you spend on firewood per day or per bundle / 8-10 kg?20. How would you describe the water situation?Source Water purpose / use Numberof 20LitreJericansusedPriceper 20litreJericanDistancetravelledto accesswaterDrinkingwaterNondrinkingwaterBothtap/pipewater kiosklake/riverwater wellother (pleasespecify)___________________21. How much water in 20 litre jerry can do you need in a day for:Cooking? ____________House cleaning? ____________Washing? ____________Animals ____________Other (Specify) ____________________________________________22. Do you have access to the amount of drinking water you need?Yes NoIf No, how do you ensure you get the right amount?_______________________________________________________23. Do you have toilets / latrines around your house?70Yes No24. What kind of toilets / latrines are they? Ordinary ImprovedIf ordinary, in what ways should the toilet / latrine be improved?________________________________________25. How do you dispose your domestic waste?Liquid SolidThrow awayDust bins / plastic cansBuryBurnRecycleOther, please specifyProfile of Daily Activities26. Are you an employed or self-employed person?Employed Self-employed None27. Which of the following best describes your household’s occupation?Husband WifeFishingAgriculture, please specify………………………………………..Retail / SalesConstructionMiningManufacturing71Services (Private), pleasespecify_____________________________Finance, Real Estate, InsuranceGovernment and Public ServicesEducationStudentOther Occupation (please specify)________________________Unemployed7228. a). Do you need to use a computer in your daily work? Yes No b). If yes, how does the use of a computer assist you?__________________________________________ c). Even if your work does not require use of computer, do you sometimes use it? Yes Nod). What exactly do you use the computer for?__________________________________________ e). How do you access the computer?computer at home at work at internet café other location none29. Do you access the internet? Yes NoIf yes, which of the following helps you to? Mobile phone home computer Computer at work at internet café other location30. Do you have a mobile phone?Yes, have my own Yes, but share with several others Have none31. Do you feel a need for more information in the following areas?Healthcare Yes No If Yes, Specify__________________________________Hygiene Yes No If Yes, Specify__________________________________EnvironmentalProtection Yes No If Yes, Specify__________________________________Computer73skills Yes No If Yes, Specify__________________________________Entrepreneurialskills Yes No If Yes, Specify__________________________________Life skills Yes No If Yes, Specify__________________________________Other (please specify)______________________________________________________________32. Have you ever attended a course of instruction in one or more of the following topics(school education, trainings, etc.)?Course attended Where(Institution)Length Nature oftrainingCertifying /Awarding BodyMarketingBook keepingSalesBusiness planDevelopmentComputer literacyLife skills (CV writing,presentation skills,communication skills)Other, please specify33. Has the training helped you?Yes No Don´t knowIf yes, in which way ____________________________________________________7434. What form of certification were you awarded if any? Certificate Diploma Degree None Any other specify35. How much money are you able to make per day?_____________________per day?_____________________per week?_____________________per month?36. Do you have regular income?Yes No37. How much of your income do you spent on:Per day Per week Per monthFood?Shelter /Housing?Clothing?Energy (fuel)?Water?Education?Health?38. Do save any of your income?Yes NoIf yes, where? Bank Group Home Any Other (specify)______________75Appendix 3: Enrolment in Primary Schools and Number of teachers in Mbita.S/No Name of School Enrolment No of Teachers TotalBoys Girls Total M FMfangano Zone/Division1 Wasamo 155 142 297 6 2 82 Uozi 89 83 172 4 3 73 Ramba 180 187 367 6 1 74 Kakiimba 89 79 168 3 3 65 Masisi 127 129 256 4 2 66 Remba 109 118 227 5 0 57 Wamai 59 53 112 5 3 88 Nyahera 46 48 94 6 0 69 Wakula 196 187 383 5 3 810 Kagungu 71 68 139 5 2 711 Misori 126 161 287 2 5 712 Takawiri 134 136 270 4 4 813 Sena 147 130 277 5 1 614 Nyakweri 162 146 308 6 2 815 Wakiangata 87 80 167 3 5 816 Kitenyi 56 65 121 3 3 617 Soklo 84 62 146 6 1 718 Kiwari 85 81 166 8 0 819 Gulwe 66 61 127 6 1 720 Ugina 125 102 227 4 3 721 Mauta 80 84 164 5 1 622 Rinya 76 76 152 3 0 323 Ringiti 67 73 140 5 1 624 Kakrigu Mfangano 45 42 87 1 1 2Total: Mfangano Zone 2461 2393 4767 110 47 155Rusinga Zone1 Kamasengre 159 163 322 6 2 82 Wanyama 197 216 413 4 5 93 Wasaria 155 179 334 4 6 104 Utajo 145 138 283 7 1 85 Lianda 141 106 247 7 1 86 Kamayoge 112 123 235 6 2 87 Dr. Williams 256 245 501 7 3 108 Uya 181 183 364 8 1 99 Agiro 184 176 360 6 2 810 Wakondo 134 124 258 6 3 911 Kamgere 171 212 383 4 6 1012 Kakrigu 122 109 231 4 4 87613 Nyamuga Special School For Ph 26 16 42 2 3 514 Oguta Mbare 68 52 120 3 2 515 Waregi 118 120 238 3 6 916 Temo 117 130 247 6 3 917 Kaswanga 172 165 337 6 2 818 Nyamuga 199 183 382 3 5 819 Ngodhe SDA 80 98 178 7 0 720 Wamwanga 16 24 40 2 0 221 Eddy Memorial 31 33 64 2 0 2Total: Rusinga Zone 2784 2795 5579 103 57 160.Mbita West Zone1 Ponge 46 47 93 3 5 82 Kirambo 120 104 224 4 3 73 Kirindo 123 140 263 4 3 74 Nyamanga 159 133 292 3 4 75 Mbita 148 181 329 0 7 76 Obalwanda 166 140 306 3 3 67 M.P.I.S 260 252 512 5 5 108 Wanga 157 148 305 2 6 89 Olweya 58 45 103 3 3 610 Nyasumbi 71 65 136 6 1 711 Chamakowa 72 82 154 6 1 712 Usare 332 272 604 2 9 1113 Kisui 147 121 268 3 5 814 Kombe 142 168 310 3 5 815Obalwanda Special School ForMh 33 18 51 3 0 316 Osodo 196 162 358 4 2 617 God Awendo 153 120 273 6 1 718 Nyamasare 163 142 305 5 4 919 Nyadenga 57 55 112 1 2 320 Lwanda Oloo 26 29 55 1 0 1Total: Mbita West Zone 2629 2424 5053 67 69 136Mbita East Zone1 Usungu 135 155 290 6 1 72 Waondo 139 98 237 4 3 73 Uwi 134 126 260 6 1 74 Kamsama 136 132 268 4 4 85 Hope Special School For Mh 22 16 38 1 2 36 Nyawiya 239 235 474 4 3 77 Powo 106 109 215 3 2 58 Obambo 142 130 272 4 3 7779 Oseno 64 73 137 1 2 310 Ngodhe Dsc 204 172 376 4 2 611 Kuge 84 72 156 2 0 212 Genge 190 210 400 3 3 613 Usao 197 193 390 5 2 714 Rambim 43 36 79 0 1 115 Kitare 44 49 93 0 1 116 Alero 68 54 122 2 0 2Total: Mbita East Zone 1947 1860 3807 49 30 79Total: Mbita Division 7192 7048 14153 262 134 394Lambwe Zone/ Division1 Ndhuru 145 136 281 6 1 72 Got Rateng 153 142 295 7 1 83 Sikri Jerusalem 106 92 198 5 1 64 Nyamaji 131 140 271 5 0 55 Kisaka 132 120 252 5 1 66 Waiga 206 153 359 5 2 77 Aringo 207 198 405 6 1 78 Wandiji 229 206 435 6 2 89 Ochieng Odiere 126 126 252 5 2 710 Owich 147 144 291 6 1 711 Urianda 215 210 425 6 2 812 Nyakayiemba 147 111 258 3 5 813 Paga 85 67 152 6 0 614 God Jope 169 156 325 5 2 715 Nyasanja 100 79 179 3 3 616 Rapora 149 157 306 4 4 817 Got Kopolo 101 100 201 4 3 718 Kamato 147 146 293 7 0 719 Sulwe 115 122 237 1 6 720 Lambwe 184 191 375 2 5 721 Ogando 172 156 328 6 0 622 Waringa 167 143 310 4 2 623 Got Nyasumbi 134 115 249 5 1 624 Lambwe Special School 40 48 88 3 5 825 Bedie 63 68 131 3 1 426 Soko-Abala 43 36 79 1 1Total: Lambwe Zone 3613 3362 6975 119 51 170Grand Total: Mbita District 13266 12803 25895 491 232 719Source: District Education Office, Mbita District78Primary schools in Suba DistrictS/No School EnrolmentTeachers Employed ShortfallKigoto Male Female Total1 Mumisa 121 3 4 7 12 Kithereka 126 3 0 3 33 Seka 252 6 1 7 24 Sanjweru 134 5 1 6 25 Kumbatha 133 3 0 3 46 Tonga 155 5 4 9 07 Nyabwacheche 70 2 0 2 38 Nyasoti 138 6 1 7 19 Mumisa 121 3 4 7 110 Nyawacha 90 1 2 3 411 Nyamadede 260 6 1 7 212 Gendo 155 5 2 7 113 Oma 221 5 1 6 214 Mwiregwa 168 5 1 6 215 Miriya 66 3 0 3 316 Koga 188 7 0 7 117 Kichare 152 7 0 7 118 Wiga 190 6 1 7 719 Kibura 200 6 1 7 220 Kiembe 152 6 0 6 221 Ramula 95 4 2 6 222 Magunga 225 5 2 7 323 Koigoto 234 5 2 7 324 Olando 328 4 3 7 9NyagwetheB M F T25 Uterere 110 4 1 6 226 Mwiyoyo 129 3 2 5 327 Nyakasera 171 4 1 5 328 Obanga 128 7 0 7 129 Koyombe 159 5 1 6 230 Kirambo 160 6 1 7 131 Osiri 188 5 0 5 332 Kisaku 223 4 2 6 233 Kitawa 105 4 2 6 234 Malongo 224 2 0 2 735 Nyagwethe 66 4 2 6 236 Mwiraria 139 5 1 6 237 Kisegi 212 5 1 6 238 Kumuinda 56 4 2 6 279Central Male Female Total39 Nyalkimba 142 2 2 4 440 Gingo 263 4 3 7 741 Gotkombuto 148 4 0 4 442 Kisiambi 112 4 1 5 343 Kinyasaga 162 4 3 7 144 Manyala 130 3 4 7 145 Msare 140 4 2 6 246 Kasinga 122 5 0 5 347 Onywera 262 5 2 7 348 Sagarume 50 0 2 2 249 St.Joseph Mikiundu 96 6 6 0 250 Matunga 32 2 0 2 251 Mwirendia 171 6 0 6 252 Nyabera 170 6 1 7 153 Kingenyo 196 6 0 6 254 Sindo 290 6 7 13 355 Rowo 203 4 3 7 256 Roo Doh 224 3 4 7 157 Ngayo 98 4 4 8 058 Nyakiya 11 5 1 6 259 Nyandenda 131 3 2 5 260 Nyabomo 142 4 2 6 361 Yongo 141 5 1 6 262 Sumba 101 5 2 7 163 Victor Nsoga 56 3 3 6 264 Ngeri 212 6 1 7 765 Ragwe 177 6 1 7 166 Mukende 79 5 1 6 667 Nyatoto 182 4 4 8 268 Kigbuogi 50 4 0 4 369 Wira 70 1 0 1 2Kiabuya70 God Bura 220 5 2 7 171 Sokoni 107 5 2 7 172 Mukuyu 130 5 2 7 173 God Oloo 185 5 2 7 474 Kiwa 197 5 2 7 175 Pundo 205 6 2 8 176 Nyenga 172 5 2 8 177 Nyatambe 214 5 3 8 678 Ongongo 80 7 0 7 179 Lwanda 126 4 3 7 180 Kimange 170 5 3 8 181 Miramba 159 6 2 8 18082 Soko 170 5 1 6 283 Kikubi 247 8 0 8 184 Nyandiwa 291 6 2 8 685 Kiabuya 171 6 2 8 186 Kimoro 162 4 2 6 287 Ligongo 143 7 0 7 188 Ogaka 99 6 1 7 1 13755 407 138 547 20381Appendix 4: Secondary SchoolsS/No Name of SchoolEnrolmentTeachersBoys Girls Total Male Female Total1 Tom Mboya 372 0 372 11 3 142St.WilliamsOsodo 155 108 263 5 1 63 Wandiji 136 101 237 4 1 54 Nyamasare Girls 0 183 183 2 4 65 Waondo 339 157 496 13 4 176 Ogongo 303 179 482 6 3 97 Waware 188 140 328 7 2 98 Mbita High 844 0 844 21 6 279 Uozi 169 70 239 9 0 910 Lambwe 250 74 324 11 4 1511 Kakiimba 213 133 346 11 3 1412 Ngodhe 120 66 186 3 2 513 Mauta 43 31 74 6 0 614 Sena 63 57 120 2 1 315 Kamasengre 127 83 210 3 0 316 Kirindo 115 67 182 2 1 317 Usao 61 36 97 1 1 218 Nyakweri 29 43 72 2 0 219 Prof. Karega 57 43 100 4 0 420Hon.OtienoKajwang 30 25 55 1 0 121 Kamato Sec 27 11 38 3 0 322 Rapora 75 72 147 2 0 2Total: PublicSchools 3716 1679 5395 129 36 165Source: District Education Office, Mbita82Appendix 5: Health Facilities by Location Against the backdrop of CatchmentPopulationNoName & type of HealthFacility LocationTotal CatchmentPopulation1 Tom Mboya Health centre Rusinga 5,8202 Ngodhe Dispensary Ngodhe (Gembe East) 9743 Kamasengere Dispensary Kamasengere West 3,4404 Waware Dispensary Rusinga 3,3775 Mbita District Hospital Mbita Township 12,9366 St. Jude Health Centre Kasgunga Central 1,6367 St. Mary Dispensary Mbita Town (Gembe West) 2,3068 Angiya Dispensary Gembe West 2,3429 Obalwanda Dispensary Gembe West 3,51010 Ponge Dispensary Kamreri West (Gembe central) 6,48611 Kitare Health Centre Kayanja (Gembe East) 5,50912 Usao Dispensary Usao 5,06213 Young Generation Centre Gembe East 4,79214 Vianjenco Clinic Gembe East 1,73515Kageno(Plasse Family HealthClinic) Gembe East 29916 New Mbita Clinic Gembe East 81917 Humanist Rusinga Islanda Rusinga 4,63418 Ogongo Sub District Hosp. Ogongo (Lambwe East) 9,97919 Lambwe Dispensary Lambwe East 6,23920 Ndhuru Dispensary Lambwe East 7,05421 Sena Health Centre Mfangano East 6,39622 St Lukes Health Centre Mfangano East 1,82923 Yokia Dispensary Mfangano East 3,92624 Takawiri Dispensary Takawiri 3,09625 Ugina Health Centre Ugina 4,98826 Wakula Dispensary Mfangano North 4,23627 Soklo Dispensary Soklo North (Mfangano) 2,769116,189Source: Office of District Medical Officer, Mbita83Appendix 6: Health Facilities in Suba DistrictNo. Name & type of HealthFacilityLocation Total CatchmentPopulation1 Suba District Hospital Sindo (Kaksingiri West) 19,1392 Nyadenda Dispensary Ruma 1,9013 Nyatoto Health Centre Nyatoto 6,9304 NYS Dispensary Ruma 2,0845 Nyamrisra Dispensary Nyamsisra 2,7586 Roo Dispensary Roo 2,7807 Msare Health Centre Kaksingiri West 3,9268 Kisegi Sub District Hospital Kisegi (Gwasi North) 6,9659 Nyagwethe Dispensary Nyagwethe (Gwasi North) 2,61710 Kisaku Dispensary Kisaku 1,98711 Kigwa Dispensary Kigwa (Gwasi East) 7,95612 Magunga Health centre Magunga (Gwasi Central) 18,22713 God Bura Dispensary Lambwe West 1,94914 Lwanda Gwassi Dispensary Gwasi Central 6,95615 Seka Health Centre Gwasi Central 9,08416 Tonga Health Centre Gwasi West 2,63417 Nyandiwa Dispensary Gwasi West 8,04618 Kiwa Island Dispensary Gwasi West 1,53684Appendix 7: Photo Gallery (Plates 1-18)1. Enumerator Violet Akinyi administering ahousehold questionnaire at the pilot stage onRusinga Island2. Research Officer, Kennedy Alaly during aninterview with Chief Nyakiya of Gwasi EastLocation3. Household Questionnaire administration inprogress at Mbita shopping centre.4. Research Assistant, Mr. Fred Musambiinterviewing the Assistant Chief of Rusinga EastSub-Location5. Group Discussion between Researchers andFather Walter of Mbita Catholic Church6. Enumeration work at Shiro beach on RusingaIsland.857. Water irrigation near Kaugege beach in Mbita Districton a horticultural project sponsored by Value GirlsProgram through Jiinue Holdings (K) Ltd8. Omena fish spread to dry in the sun along ShiroBeach on Rusinga Island9. Temporary human settlement for a fishingcommunity at Shiro beach, Rusinga Island10. Community members queuing for relief food(beans) for orphans and vulnerable children atthe Chiefs’ camp on Rusinga Island11. A poultry house in one of the households onRusinga East Location. The house is powered bysolar energy12.A traditional Suba cereal storage facility8613.Researcher Officer, Kennedy Alaly, engaged in aconsultation session with Christine Weyrich(middle) and Christine Koptisch (right) of SiemensStiftung, Germany on Rusinga Island14. Enumerator Violet Akinyi administering ahousehold questionnaire in Rusinga East15.Enumerator Violet Akinyi during a householdsurvey at one of the small scale businesses (shop) atMbita Township16. A dormant borehole /water pump in RusingaEast Sub-Location17.A We!Hub at Nyandiwa 18.A We!Hub at Sindo87Appendix 8: Key InformantsName Title Phone NumberKelly Owilla Deputy DevelopmentOfficer, Mbita0722 682 754Joseph Nyakwama Deputy Public Health Officer Mbita0722 545 517Father Walter Bishop Catholic Cathedral Mbita0723 064 826Daniel Alango In charge of Mbita Energy HubOSRAM0720 797 518Paul Alele Water Scheme ManagerGibanga-Gwasi Location0712 631 570Joseph Ogutu Operations & MaintenanceMbita District0712 631 570Mary Onyango Mbita District Office 0710 311 277Kassim Mohamed District Water Officer(Suba District)0760 865 096Henry Ojwang Deputy District PublicHealth Officer0728 309 493Samson Obura Head Teacher – God Bura PrimarySchool0726 588 617Jarred Owour Human Resource Officer, DistrictEducation Office Mbita District0721 604 356Aloyce Nyakiya Chief-Gwasi East Location 0710 244 630Joseph Oyuko Otieno Assistant Chief, Mbita Township 0710 296 765Daniel Mboya Owuor Chief Rusinga, East Location 0720 748 11988Appendix 9: Location, Administrative Areas and Population Density pattern

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