KARAGWE DC CWIQ 2006

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PMO-RALG

KARAGWE DC CWIQSurvey on Poverty, Welfare and Services

In Karagwe DC

SEPTEMBER 2006

Implemented by:EDI (Economic Development Initiatives)PO Box 393, BukobaTanzania

Telephone and Fax: +255-(0)28-2220059Email:[email protected]


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ACKNOWLEDGEMENTS

This research was commissioned by the Prime Ministers Office RegionalAdministration and Local Governance (PMO-RALG) and implemented by EDI(Economic Development Initiatives). It is part of an effort to conduct CWIQ surveys in

34 districts across Tanzania. The project Director is Joachim De Weerdt. Field work operations are being co-coordinated by Respichius Mitti and Francis Moyo. Fieldsupervision was in the hands of Matovu Davies, Wilson Kabito, Henry Kilapilo, HenryLugakingira, Josephine Lugomora, George Musikula, and Neema Mwampeta. Thelisting team was formed by Felix Kapinga and Benjamin Kamukulu. Interviewers wereDativa Balige, Geofrey Bakari, Rukia Charles, Abbanova Gabba, George Gabriel,Jamary Idrissa, Felix James, Batista John, Gloria Joseph, Placidia Josephat, JustinaKatoke, Makarius Kiyonga, Faustine Misinde, Jesca Nkonjerwa, Kamugisha Robert,Resti Simon, Pius Sosthenes, Aissa Soud, Adella Theobald, and Honoratha Wyclife.The data processing software was written by Jim Otto and Neil Chalmers. The dataentry team consisted of Marystella Andrew and Alieth Mutungi, and was supervised by

Thaddaeus Rweyemamu. Formatting the final document layout was in the hands of Amina Suedi. The data analysis and report writing were undertaken by Luis Barron,Ngasuma Kanyeka, Mujobu Moyo, and Teddy Neema, under the supervision of ManuelBarron. Assistance from Charles Citinka and Howard Clegg from PMO-RALG isacknowledged.


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DEFINITIONS

General

Accessible Village Within a district, accessible villages are villages

located closer to the district capital, all-weatherroads, and public transport.

Remote Village Within a district, remote villages are villageslocated farther from the district capital, all-weatherroads, and public transport.

Socio-economic Group The socio-economic group of the household isdetermined by the type of work of the mainincome earner.

Poverty Predictors Variables that can be used to determine householdconsumption expenditure levels in non-expenditure surveys.

Basic Needs Poverty Line Defined as what a household, using the foodbasket of the poorest 50 percent of the population,needs to consume to satisfy its basic food needs toattain 2,200 Kcal/day per adult equivalent. Theshare of non-food expenditures of the poorest 25percent of households is then added. The BasicNeeds Poverty Line is set at TZS 7,253 per 28days per adult equivalent unit in 2000/1 prices;households consuming less than this are assumedto be unable to satisfy their basic food and non-food needs.

Education

Literacy Rate The proportion of respondents aged 15 years orolder, who identify themselves as being able toread and write in at least one language.

Primary School Age 7 to 13 years of age

Secondary School Age 14 to 19 years of age

Satisfaction with Education No problems cited with school attended.


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Gross Enrolment Rate The ratio of all individuals attending school,

irrespective of their age, to the population of children of school age.

Net Enrolment Rate The ratio of children of school age currentlyenrolled at school to the population of children of school age.

Non-Attendance Rate The percentage of individuals of secondary school-age who had attended school at some point andwere not attending school at the time of the survey.

Health

Need for Health Facilities An individual is classed as having experiencedneed for a health facility if he/she had sufferedfrom a self-diagnosed illness in the four weekspreceding the survey.

Use of Health Facilities An individual is classed as having used a healthfacility if he/she had consulted a healthprofessional in the four weeks preceding thesurvey.

Satisfaction with HealthFacilities

No problems cited with health facility used in thefour weeks preceding the survey.

Vaccinations BCG: Anti-tuberculosisDPT: Diphtheria, Pertussis3, TetanusOPV: Oral Polio Vaccination

Stunting Occurs when an individuals height is substantiallybelow the average height in his/her age-group.

Wasting Occurs when an individuals weight issubstantially below the average weight for his/herheight category.

Orphan A child is considered an orphan when he/she haslost at least one parent and is under 18 years.

Foster child A child is considered foster if neither his/herparents reside in the household


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Employment

Working Individual An individual who had been engaged in any typeof work in the 4 weeks preceding the survey.

Underemployed Individual An individual who was ready to take on more

work at the time of the survey.

Non-working Individual An individual who had not been involved in anytype of work in the 4 weeks preceding the survey.

Unemployed Individual An individual who had not been engaged in anytype of work in the 4 weeks prior to the survey buthad been actively looking for it.

Economically InactiveIndividual

An individual who had not been engaged in anytype of work in the 4 weeks prior to the survey due

to reasons unrelated to availability of work (e.g.Illness, old age, disability).

Household duties Household tasks (cleaning, cooking, fetchingfirewood, water, etc.) that do not entail payment

Household worker A household worker performs household dutiesbut received payment.

Household as employer A person is said to be employed by his/herhousehold if he/she does domestic/household work for the household they live in (e.g. a housewife ora child that works on his/her parents fields orshop). It does not include people whose main job wasdomestic work for other households (private sector) .

Welfare

Access to Facilities A household is considered to have access tofacilities if it is located within 30 minutes of travelfrom the respective facilities.


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TABLE OF CONTENTS

1. INTRODUCTION 11.1 The Karagwe District CWIQ.. 11.2 Sampling 11.3 Constructed Variables to Disaggregate Tables..... 11.3.1 Poverty Status. 21.3.2 Cluster Location. 31.3.3 Socio-economic Group 4

2 VILLAGE, POPULATION AND HOUSEHOLDS CHARACTERISTICS 72.1 Introduction 72.2 Main Population Characteristics 72.3 Main Household Characteristics 92.4 Main Characteristics of the Heads of Household.. 112.5 Orphan and Foster Status... 14

3 EDUCATION... 173.1 Overview of Education Indicators 173.1.1 Literacy... 173.1.2 Primary School Access Enrolment and Satisfaction.. 173.1.3 Secondary School Access, Enrolment and Satisfaction. 203.2 Dissatisfaction 213.3 Non-Attendance. 223.4 Enrolment and Drop Out Rates..... 233.5 Literacy...... 24

4 HEALTH... 274.1 Health Indicators 27

4.2 Reasons for Dissatisfaction 284.3 Reasons for Not Consulting When III 314.4 Type of Illness 314.5 Health Provider...... 314.6 Child Deliveries. 324.7 Child Nutrition... 33

5 EMPLOYMENT... 395.1 Employment Status of Total Adult Population.. 395.1.1 Work Status..... 395.1.2 Employment of Household Heads... 405.1.3 Youth Employment 40

5.2 Working Population 415.3 Underemployment Population 435.4 Unemployed and Inactive Population 455.5 Household Tasks 465.6 Child Labour 47

6 PERCEPTIONS ON WELFARE ANDCHANGES WITHIN COMMUNITIES 496.1 Economic Situation 496.1.1 Perception of Change in the Economic Situation of the Community 49


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6.1.2 Perception of Change in the economic Situation of the Household... 506.2 Self- reported Difficulties in Satisfying Household Needs... 526.2.1 Food Needs. 526.2.2 Paying School Fees. 546.2.3 Paying House Rent. 566.2.4 Paying Utility Bills........ 576.2.5 Paying for Healthcare. 576.3 Assets and Household Occupancy Status.. 586.3.1 Assets Ownership... 586.3.2 Occupancy Documentation 596.4 Agriculture. 606.4.1 Agriculture Inputs... 606.4.2 Landholding 616.4.3 Cattle Ownership 626.5 Perception of Crime and Security in the Community 636.6 Household Income Contribution 646.7 Other House Items. 64

7 HOUESHOLD AMENITIES... 677.1 Housing Materials and Typing of housing Unit 677.2 Water and Sanitation.. 717.3 Type of Fuel... 727.4 Distance to Facilities.. 747.5 Anti -Malaria Measures. 75

8 GOVERNANCE... 798.1 Attendance at Meeting... 798.2 Satisfaction with Leaders... 798.3 Public Spending................. ............... ............. 80

9 CHANGES BETWEEN 2003 AND 2006 839.1 Household Characteristics. 849.2 Education....... 849.3 Health. 849.4 Household Assets and Perception of Welfare.... 86


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LIST OF TABLES

Table 1.1 Variables Used to Predict Consumption Expenditure.......... 1Table 1.2 Predicted vs. Actual Poverty, Kagera Rural, 2000/01 ......... 2Table 1.3 Cluster Location .. 3Table 1.4 Socio-economic Group......... 4Table 1.5 Socio-economic Group and gender of Household ... 4Table 1.6 Socio-economic Group and Main Economic Activity................ ................ .............. ............... ............. 5Table 2 1 Percent distribution of Total Population by Gender and Age.. 7Table 2.2 Dependency Ratio .... 8Table 2.3 Percent Distribution of Households by Number of Household Members 8Table 2.4 Percent distribution of total population by relation to head of household 9Table 2.5 Percent distribution of the total population age 12 and above by marital status.. 10Table 2.6 Percent distribution of the total population age 5 and above by socio-economic group.. 11Table 2.7 Percent distribution of the total population age 5 and above by highest level of education............ 11Table 2.8 Percent distribution of heads of households by marital status.. 12Table 2.9 Percent distribution of heads of households by socio-economic group.... 13

Table 2.10 Percent distribution of heads of household by highest level of education . 13Table 2.11 Percent distribution of children under 18 years old who have lost their mother and /or father. 14Table 2.12 Percent distribution of children less than 18 years old living without mother and/or father 15Table 3.1 Education Indicators. 19Table 3.2 Percent distribution of students currently enrolled in school with reasons for dissatisfaction............. 21Table 3.3 Percent distribution of children 7-9 years who ever attended school by reasons not currentlyattending.............................................................. 22Table 3.4 Primary School enrolment and drop out rates by age and gender.... 23Table 3.5 Secondary school enrolment and drop out rates by age and gender.... 23Table 3.6 Adult literacy rates by age and gender (persons age 15 and above)..... 24Table 3.7 Youth literacy rates by age and gender (persons age 15-24).... 24Table 4.1 Health Indicators... 27Table 4.2 Percent distribution of persons who consulted a health provider in the 4 weeks proceeding thesurvey and were not satisfied, and the reasons for dissatisfaction.. 28Table 4.3 Percent distribution of persons who did not consulted a health provider in the 4 weeks preceding thesurvey and the reasons for not consulting.................. ............... ............... ............... ................ .............. ....... 29Table 4.4 Percent distribution of population sick or injured in the 4 weeks preceding the survey, and those sick or injured the percentage by type of sickness/injury.......................... .............. .............. .............. ............... 30Table 4.5 Percent distribution of health consultation in past 4 weeks by type of health provider consulted... 30Table 4.6 Percent distribution of women aged 12-49 who had a live birth in the year proceeding the survey byage of he mother and the percentage of those births where the mother received pre-natal care 32Table 4.7 Percent distribution of births in the five years preceding the survey by place of birth 33Table 4.8 Percent distribution of births in the five years preceding the survey by person who assisted indelivery of child.................................................................................................................................................. 34Table 4.9 Percent distribution of children by nutrition status indicators and program participating rates... 35Table 4.10 Percent distribution of children vaccination by type of vaccination received.... 36Table 4.11 Percent distribution of children vaccinated by source of information.............. . 37Table 5.1 Percent distribution of the population by working status (age 15 and above).. 39Table 5.2 Principal labour force indicators (persons age 15 and above).. 40Table 5.3 Percent distribution of the population by work status (age 15 -24).............. 41Table 5.4 Percent distribution of the working population by type of payment in main job. 41Table 5.5 Percent distribution of the working population by employer................... 42Table 5.6 Percent distribution of the working population by activity.......... 42Table 5.7 Percent distribution of the working population by employer, sex and activity............ 43


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Table 5.8 Percent distribution of the underemployed population by employment status............... 43Table 5.9 Percent distribution of the underemployed population by employer.. 44Table 5.10 Percent distribution of the underemployed population by activity... 44Table 5.11Percent distribution of the unemployed population by reason.. 45Table 5.12 Percent distribution of the economically inactive population by reason.. 46Table 5.13Activities normally undertaken in the household (age 15 and over)..... 47Table 5.14 Activities normally undertaken in the household (age 5 to 14).. 48Table 5.15 Child Labour (age 5 to 14)............ 50Table 6.1 Percent distribution of household by the percentage of the economic situation of the communitycompared to the year before the survey.. 51Table 6.2 Percent distribution of households by the percentage of the economic situation of the householdto the year before the survey.......... 51Table 6.3 Percent distribution of Households by the difficulty in satisfying the food needs of the household 53during the year before the survey....... 53Table 6.4 Percent distribution of households but the difficulty in paying during the year before the survey 54Table 6.5 Percent distribution of households by the difficulty in paying house rent during the year before thesurvey... 55Table 6.6 Percent distribution of households by the difficulty in paying utility bills during the year before the

survey.. 56Table 6.7 Percent distribution of households by the difficulty in paying for healthcare during the year beforethe survey................ ............. ............... .............. ............... .............. .............. ............... .............. ............... ............. .. 58Table 6.8 Percentage of households owning certain assets.................... ............. ............... ............... .............. ....... 59Table 6.9 Percent distribution of households by occupancy status................. .............. .............. .............. ............. 59Table 6.10 Percent distribution of households by type of occupancy documentation....................... .............. ...... 60Table 6.11 Percent distribution of households using agricultural inputs and the percentage using certaininputs....................................................................................................................................................................... 60Table 6.12 Percent distribution of households using agricultural inputs by the main source of the inputs....... 61Table 6.13 Percent distribution of households by the area of land owned by the household................. .............. . 62Table 6.14 Percent distribution of households by the number of cattle owned by the household.................. ....... 63Table 6.15 Percent distribution of households by the perception of the crime and security situation of theCommunity compared to the year before the survey................. .............. .............. .............. ............... ............. ....... 64Table 6.16 Percent distribution of households by principal contributor to household income.................... .......... 65Table 6.17 Percent distribution of households owning selected household items.................... ............... .............. . 65Table 7.1 Percent distribution of households by material used for roof of the house............... ............... ............. 67Table 7.2 Percent distribution of household by material used for walls of the house................ ............... ............. 68Table 7.3 Percent distribution of households by material used for floors of the house................ ............... .......... 68Table 7.4 Percent distribution of households by type of housing unit............... ............... .............. ............... ........ 69Table 7.5 Percent distribution of households by main source of drinking water................ .............. ............... ...... 70Table 7.6 Percent distribution of households by main type of toilet................... ............... ............... ................ ..... 70Table 7.7 Percent distribution of households by fuel used for cooking............... ............... .............. ................ ..... 71Table 7.8 Percent distribution of households by fuel used for lighting.................... ............... ............. ............... ... 72Table 7.9 Percent distribution of households by time (in minutes) to reach nearest drinking water supply andhealth facility.... 73

Table 7.10 Percent distribution of households by time (in minutes) to reach the nearest primary and secondaryschool...................................................................................................................................................................... 75Table 7.11 Percent distribution of household by time (in minutes) to reach nearest food market and publictransportation........................................................................................................................................................... 76Table 7.12 Percent distribution of households taking anti-malaria measures and percentage taking specificmeasures.................................................................................................................................................................. 77Table 8.1 Percent distribution of attendance of meetings (any household members within past 12 months) 79Table 8.2 Distribution of leaders' satisfaction ratings and reasons for dissatisfaction.......................... ................ . 80Table 8.3 Percent distribution of households who received financial information in the past 12 month............... 81


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Table 8.4 Satisfaction with public spending and reasons for dissatisfaction........................ ............... ................ ... 82Table 9.1 Household Characteristics.......................... .............. .............. .............. ............... ............. ............... ....... 83Table 9.2 Education................... ............... .............. ............... ............. ............... .............. ............... .............. .......... 84Table 9.3 Health.............. ............. ............... .............. ............... ............... ............. ................ .............. .............. ....... 85Table 9.4 Household Assets and Perception of Welfare................. ............... .............. ............... ................. .......... 86


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Generic Core Welfare Indicators (2006)

Total Margin of

error* Accessible Remote Poor Non-poor Household characteristics

Dependency ratio 1.1 0.0 1.1 1.2 1.4 1.0Head is male 85.4 1.7 83.8 86.9 84.1 85.8

Head is female 14.6 1.8 16.2 13.1 15.9 14.2Head is monagamous 57.2 2.1 58.7 55.8 61.3 56.1Head is polygamous 24.4 2.1 21.2 27.4 21.2 25.2Head is not married 18.4 1.9 20.2 16.8 17.5 18.7

Household welfare

Worse now 43.4 2.7 41.1 45.5 50.7 41.4Better now 27.0 2.5 31.1 23.1 20.5 28.8

Worse now 11.1 2.5 11.6 10.7 12.1 10.9Better now 39.2 5.1 35.1 43.0 39.1 39.2

Food 58.1 3.5 52.8 63.2 82.6 51.3School fees 2.0 0.8 2.2 1.8 2.9 1.8House rent 0.7 0.5 0.0 1.4 0.0 0.9Utility bills 1.4 0.7 2.3 0.6 1.3 1.4Health care 31.2 2.9 24.3 37.8 43.2 27.9

Agriculture

Less now 2.7 0.8 3.4 2.0 1.9 2.9More now 5.5 0.7 5.3 5.7 11.7 3.7

Less now 22.7 2.9 24.6 20.9 22.7 22.7More now 11.0 2.1 10.7 11.2 9.4 11.4

Yes 76.2 3.9 72.4 79.9 74.7 76.7Fertilizers 49.5 4.6 54.5 45.2 54.8 48.1

Improved seedlings 65.1 4.4 60.3 69.2 45.9 70.3Fingerlings 0.0 0.0 0.0 0.0 0.0 0.0

Hooks and nets 0.0 0.0 0.0 0.0 0.0 0.0Insecticides 58.3 4.0 48.2 66.9 53.7 59.5

Other 0.0 0.0 0.0 0.0 0.0 0.0Household infrastructure

Secure housing tenure 1.5 0.9 2.8 0.3 0.0 1.9Access to water 59.6 6.1 66.5 53.1 49.0 62.6

Safe water source 18.4 4.9 29.0 8.4 14.5 19.5Safe sanitation 1.4 1.2 2.3 0.6 0.0 1.8Improved waste disposal 26.0 5.3 26.2 25.8 21.3 27.3

Non-wood fuel used for cooking 0.5 0.5 1.1 0.0 0.0 0.7Ownership of IT/Telecommunications Equipment

Fixed line phone 0.2 0.2 0.5 0.0 0.0 0.3Mobile phone 10.0 2.0 14.2 6.0 3.4 11.8

Radio set 49.4 3.7 56.3 42.9 19.7 57.7Television set 2.0 1.1 2.7 1.2 0.0 2.5

Household economic situation compared to one year ago

Difficulty satisfying household needs

Use of agricultural inputs

Neighborhood crime/security situation compared to one year ago

Land owned compared to one year ago

Cattle owned compared to one year ago


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Total Margin of

error* Accessible Remote Poor Non-poor EmploymentEmployer in the main job

Civil service 0.8 0.3 0.7 0.9 0.0 1.1Other public serve 0.2 0.1 0.3 0.0 0.3 0.1Parastatal 0.0 0.0 0.0 0.0 0.0 0.0

NGO 0.0 0.0 0.0 0.0 0.0 0.0Private sector formal 0.6 0.4 1.2 0.0 0.0 0.8

Private sector informal 33.0 1.2 31.8 34.2 25.3 35.9Household 60.8 1.2 62.0 59.7 68.1 58.1

Activity in the main jobAgriculture 69.2 2.7 64.4 74.0 74.8 67.2

Mining/quarrying 0.6 0.3 1.0 0.2 0.3 0.7Manufacturing 0.0 0.0 0.0 0.0 0.0 0.0

Services 0.8 0.3 0.9 0.7 0.0 1.1

Employment Status in last 7 daysUnemployed (age 15-24) 0.0 0.0 0.0 0.0 0.0 0.0Male 0.0 0.0 0.0 0.0 0.0 0.0

Female 0.0 0.0 0.0 0.0 0.0 0.0Unemployed (age 15 and above)) 0.0 0.0 0.0 0.0 0.0 0.0

Male 0.0 0.0 0.0 0.0 0.0 0.0Female 0.0 0.0 0.0 0.0 0.0 0.0

Underemployed (age 15 and above) 22.2 1.6 20.6 23.7 22.7 22.0Male 30.0 2.3 27.3 32.5 30.7 29.7

Female 14.6 1.8 14.2 15.0 15.6 14.2EducationAdult literacy rate

Total 62.0 2.4 69.2 54.9 54.4 64.8Male 71.7 3.0 82.5 61.2 63.7 74.4Female 52.4 2.4 56.2 48.7 46.3 54.9

Youth literacy rate (age 15-24)Total 82.5 2.7 86.6 77.7 77.8 84.5Male 83.3 2.9 89.6 76.2 77.0 86.3

Female 81.5 3.4 83.4 79.3 78.9 82.6Primary school

Access to School 60.8 6.6 72.0 50.1 55.0 64.1Primary Gross Enrollment 102.1 2.9 106.8 97.7 98.4 104.3

Male 100.0 4.2 107.8 93.0 101.6 99.2Female 104.2 4.1 105.8 102.5 95.7 109.6

Primary Net Enrollment 78.4 2.2 83.9 73.2 69.8 83.4Male 73.7 2.8 80.3 67.7 66.7 77.3

Female 83.0 3.0 87.1 78.8 72.4 89.7Satisfaction 39.6 3.4 41.6 37.4 41.9 38.3

Primary completion rate 19.6 2.2 24.2 15.2 12.7 23.6


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Total Margin of

error* Accessible Remote Poor Non-poor Secondary school

Access to School 14.2 5.2 20.1 7.1 6.8 18.3Secondary Gross Enrollment 10.6 2.2 11.7 9.3 7.7 12.2Male 10.9 2.5 14.7 6.7 8.7 12.1

Female 10.2 3.2 8.2 12.7 6.5 12.3Secondary Net Enrollment 9.0 1.8 9.6 8.2 7.7 9.7

Male 8.9 1.9 10.8 6.7 8.7 8.9Female 9.1 2.7 8.2 10.2 6.5 10.6

Satisfaction 48.5 9.9 56.4 36.4 70.2 40.8Secondary completion rate 0.5 0.4 0.2 0.8 0.0 0.7

Medical servicesHealth access 36.4 5.8 50.7 22.8 29.5 39.6

Need 19.7 1.1 19.9 19.6 16.2 21.3

Use 23.9 1.1 25.1 22.7 21.8 24.8Satisfaction 71.8 2.3 75.3 68.2 57.9 77.4Consulted traditional healer 9.8 2.1 9.0 10.6 13.0 8.5

Pre-natal care 100.0 0.0 100.0 100.0 100.0 100.0Anti-malaria measures used 75.3 2.3 79.2 71.5 61.3 79.1

Person has physical/mental challenge 0.2 0.1 0.3 0.1 0.3 0.1Child welfare and healthOrphanhood (children under 18)

Both parents dead 1.4 0.4 1.5 1.3 2.4 0.9Father only 3.0 0.5 2.8 3.2 3.3 2.8Mother only 1.8 0.4 2.1 1.4 0.7 2.3

Fostering (children under 18)

Both parents absent 13.0 1.4 11.3 14.7 13.4 12.8Father only absent 11.7 1.7 9.9 13.5 16.1 9.3Mother only absent 4.0 1.0 5.5 2.6 2.3 5.0

Children under 5Delivery by health professionals 72.2 3.1 75.4 69.2 64.3 76.0

Measles immunization 66.9 2.5 69.3 64.7 63.8 68.4Fully vaccinated 32.0 3.4 34.4 29.8 22.0 36.9Not vaccinated 13.0 2.1 14.6 11.5 13.5 12.7

Stunted 18.5 2.1 19.5 17.5 22.0 16.8Wasted 1.4 0.5 1.2 1.6 1.5 1.3

Underweight 10.6 1.8 10.6 10.5 13.0 9.4* 1.96 standard deviations


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Estimate SE Signif.

Net Enrolment RatePrimary School 75.3 79.2 3.9 3.4 -2.8 10.6

Secondary School 15.7 11.8 -3.9 2.6 *** 4.7 15.2

ate oDissatisfaction withSchool 39.0 51.2 12.2 5.8 ** 1.1 24.4Reasons for Dissatisfaction

Books/Supplies 52.4 20.0 -32.4 9.5 *** -52.3 -14.4Poor Teaching 7.0 11.4 4.4 4.5 -4.7 13.4

Lack of Teachers 74.3 48.2 -26.1 7.3 *** -42.0 -12.9d Condition of Facilities 54.9 48.7 -6.2 9.6 -12.2 26.2

Overcrowding 19.0 28.9 9.9 7.2 -4.5 24.3Health FacilityConsulted

Private hospital 3.5 3.7 0.2 1.7 -3.2 3.7Government hospital 58.7 51.9 -6.8 6.2 -19.4 5.5Traditional healer 4.4 3.8 -0.6 1.8 -4.2 3.1

Pharmacy 10.2 32.8 22.6 3.4 *** 15.7 29.2ate o

Dissatisfaction withHealth Facilities 24.3 32.3 8.0 5.3 -2.3 18.9Reasons for Dissatisfaction

Long wait 32.3 45.6 13.3 10.5 -10.2 31.9of trained professionals 21.0 15.3 -5.7 6.4 -20.9 4.8

Cost 27.0 46.6 19.6 10.8 * -2.2 41.2No drugs available 38.1 6.6 -31.5 7.3 *** -46.2 -16.9

nsuccessful treatment 40.7 3.8 -36.9 13.1 *** -64.7 -12.0

Child DeliveryHospital or Maternity 28.7 28.8 0.1 5.9 -11.3 12.2

Delivery AssistanceDoctor/Nurse/Midwife 28.4 29.0 0.6 6.3 -12.8 12.2TBA 65.1 43.3 -21.8 5.5 *** -32.0 -9.9Self-assistance 6.5 27.3 20.8 4.4 *** 12.0 29.5

Child NutritionStunted 49.5 38.0 -11.5 4.2 *** -22.1 -5.4

Severely Stunted 21.3 15.4 -5.9 3.3 * -12.9 0.4Wasted 6.0 4.0 -2.0 1.7 ** -6.7 0.0

Severely Wasted 2.3 0.7 -1.7 0.8 ** -3.2 -0.1

2003 2006 Change

95% Confidence Interval


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1 INTRODUCTION1.1 The Karagwe District

CWIQThis report presents district level analysisof data collected in the Karagwe DistrictCore Welfare Indicators Survey using theCore Welfare Indicators Questionnaireinstrument (CWIQ).

The survey was commissioned by thePrime Ministers Office RegionalAdministration and Local Governanceand implemented by EDI (EconomicDevelopment Initiatives), a Tanzanianresearch and consultancy company. The

report is aimed at national, regional anddistrict level policy makers, as well asthe research and policy community atlarge.

CWIQ is an off-the-shelf survey packagedeveloped by the World Bank to producestandardised monitoring indicators of welfare. The questionnaire is purposivelyconcise and is designed to collectinformation on household demographics,employment, education, health andnutrition, as well as utilisation of andsatisfaction with social services. An extrasection on governance and satisfactionwith people in public office was addedspecifically for this survey.

The standardised nature of thequestionnaire allows comparisonbetween districts and regions within andacross countries, as well as monitoringchange in a district or region over time.

Karagwe District CWIQ was the secondof its kind to be administered in KaragweDistrict, the first one having beenadministered in 2003. Chapter 9 of thisreport analyses changes between the twosurveys.

Although beyond the purpose of thisreport, the results of Karagwe CWIQcould also be set against those of otherCWIQ surveys that have are beingimplemented at the time of writing inother districts in Tanzania: Bariadi DC,Bukoba DC, Bukombe DC, Bunda DC,Dodoma DC, Dodoma MC, Hanang DC,Kasulu DC, Kibondo DC, Kigoma DC,

Kilosa DC, Kishapu DC, Kongwa DC,Kyela DC, Ludewa DC, Makete DC,Maswa DC, Meatu DC, Kahama DC,

Mbulu DC, Morogoro DC, MpwapwaDC, Muheza DC, Musoma DC, NgaraDC, Ngorongoro DC, Njombe DC, RufijiDC, Shinyanga MC, Singida DC, SongeaDC, Sumbawanga DC, Tanga MC,Temeke MC. Other African countriesthat have implemented nationallyrepresentative CWIQ surveys includeMalawi, Ghana and Nigeria.

1.2 Sampling

The Karagwe District CWIQ wassampled to be representative at districtlevel. Data from the 2002 Census wasused to put together a list of all villagesin the district. In the first stage of thesampling process villages were chosenproportional to their population size. In asecond stage the sub-village (kitongoji)was chosen within the village throughsimple random sampling. In the selectedsub-village (also referred to as cluster orenumeration area in this report), allhouseholds were listed and 15households were randomly selected. Intotal 450 households in 30 clusters were

visited. All households were givenstatistical weights reflecting the numberof households that they represent.

A 10-page interview was conducted ineach of the sampled households by anexperienced interviewer trained by EDI.

Age of household head Wall material

Household size Floor material

Education of household head Radio, radio cassette, music system

Iron, electric or charcoalTotal land

Number of days the household had meat

Number of meals per day

People per bedroom

Use of toothpaste

Source: CWIQ 2006 Karagwe DC

Proportion of households with a memberhaving a bank account

Household Assets

Household AmenitiesProportion of households with access to a safesource of drinking water

Table 1.1 Variables Used to Predict Consumption Expenditure

Basic Variables

Food Security

Village level variables


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1 Introduction

The respondent was the most informedperson in the household, as identified bythe members of the household. A weightand height measurement was taken bythe interviewers for each individualunder the age of 5 (60 months) in thesurveyed households.

Finally, the data entry was done byscanning the questionnaires, to minimisedata-entry errors and thus guarantee thequality of the data.

1.3 Constructed variablesto disaggregate tables

The statistics in most tables in this reportwill be disaggregated by certaincategories of individuals or households.Some of these variables have beenconstructed by the analysts and, in thelight of their prominence in the report,deserve more explanation. This chapterdiscusses some of the most important of these variables: poverty status, clusterlocation and socio-economic group.

1.3.1 Poverty Status

The poverty status of a household isobtained by measuring its consumptionexpenditures and comparing it to apoverty line. It is, however, difficult,expensive and time consuming to collectreliable household consumptionexpenditure data. One reason for this isthat consumption modules are typicallyvery lengthy. In addition, household

consumption patterns differ acrossdistricts, regions and seasons; hencemultiple visits have to be made to thehousehold for consumption data to bereliable.

However, household consumptionexpenditure data allows more extensiveand useful analysis of patterns observedin survey data and renders surveyoutcomes more useful in policydetermination. Because of this, theTanzanian government has become

increasingly interested in developingways of using non-expenditure data topredict household consumption and, fromthis, poverty measures.

Table 1.2 : Predicted and Observed Poverty

Rates, Kagera Rural, 2000/01

Non-Poor Poor Total

Non-Poor 60.9 10.9 71.8

Poor 7.9 20.3 28.2

Total 68.8 31.3 100.0Source: HBS 2000/01

ObservedPredicted

There is a core set of variables that areincorporated in the majority of surveys.These variables inform on householdassets and amenities, level of educationof the household head, amount of landowned by the household and others. Byobserving the relation between thesevariables and consumption expenditureof the household in an expendituresurvey, a relationship can be calculated.

These variables are called povertypredictors and can be used to determinehousehold expenditure levels in non-expenditure surveys such as CWIQ. Thismeans that, for instance, a household thatis headed by an individual who has postsecondary school education, with everymember in a separate bedroom and thathas a flush toilet is more likely to be non-poor than one where the household headhas no education, a pit latrine is used andthere are four people per bedroom. Thisis, of course, a very simplified example;however, these are some of the variablesused to calculate the relationship between

such information and the consumptionexpenditure of the household.

For the purpose of this report, the datacollected in the Household Budget Survey 2000/01 (HBS) was used to selectthe poverty predictors and determine thequantitative relationship between theseand household consumption. The five-year gap is far from ideal, but the dataitself is reliable and is the most recentsource of information available. Work was then done to investigate the specificcharacteristics of Karagwe in order toensure that the model developedaccurately represents this particulardistrict.

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Karagwe DC CWIQ 2006

Table 1.3: Cluster Location

District

Capital

All-Weather

Road

Public

Transport

Cluster Location

Accessible 10 6 120 9.1 44,355

Remote 90 60 240 31.7 47,040


Median Time (in minutes) to:

Poverty RateEstimatedNumber of Households

Some caveats are in order whentabulating variables used as povertypredictors on poverty status. Povertystatus is defined as a weighted average of the poverty predictors; hence it shouldcome as no surprise that povertypredictors are correlated to them. Forinstance, education of the householdhead is one of the variables included inthe equation used to calculate householdconsumption. The relationship is set as apositive one, consequently whenobserving the patterns in the data thisrelationship may be positive byconstruction. Table 1.1 lists the variablesthat have been used to calculate predictedhousehold consumption expenditure. Theactual quantitative relationship betweenthese and consumption expenditure ispresented in Table B1 in Annex 2.

Once the consumption level of ahousehold has been predicted, it iscompared to the Basic Needs PovertyLine set by National Bureau of Statistics

(NBS) on the basis of the 2000/01 HBS.The Basic Needs Poverty Line is definedby what a household, using the foodbasket of the poorest 50 percent of thepopulation, needs to consume to satisfyits basic food needs to attain 2,200Kcal/day per adult equivalent. The shareof non-food expenditures of the poorest25 percent of households is then added.With this procedure, the Basic NeedsPoverty Line is set at TZS 7,253 per 28days per adult equivalent unit in 2000/01prices. Households consuming less thanthis are assumed to be unable to s atisfytheir basic food and non-food needs 1 .

The Karagwe CWIQ uses povertypredictors to classify households as pooror non-poor, i.e. to determine whether ahouseholds monthly consumption per

1 The exact procedure by which this linehas been set is described in detail in the2000/01 HBS report: National Bureau of Statistics, 2002, 2000/2001 Tanzania

Household Budget Survey .

adult equivalent unit is below or abovethe Basic Needs Poverty Line. Thisbinary approach generates two types of mistakes associated with the prediction:

1. A poor household ispredicted to be non-poor

2. A non-poor household ispredicted to be poor

One way of determining the accuracy of the poverty predictors is to see how manymistakes of each type the model makes.To do this the poverty predictor model isapplied to the actual consumptionexpenditure data. Results of this exerciseare presented in Table 1.2. The modelwrongly predicts a non-poor householdto be poor in 7.9 percent of the cases, andvice versa in 10.9 percent of thehouseholds. This gives an overallpercentage of correct predictions of 81.2percent.

When the model is applied to the CWIQ

data for Karagwe 2006, the estimatedpopulation living in poverty is 21percent, very much consistent with the 23percent estimated with HBS for KageraRural.

However, it must be kept in mind that theaim of the model is not estimatingpoverty rates, but to determine thecharacteristics of the poor population.Hence, the accuracy of the model doesnot hinge on the closeness between theestimated and actual poverty rate; but onthe percentage of correct predictions asindicated in Table 1.2.

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1 Introduction

Expenditure surveys, such as the2000/2001 Household Budget Survey,are much better suited for informing onpoverty rates. However, such large scalesurveys have insufficient number of observations to inform on district-leveltrends. The Karagwe CWIQ, on the otherhand, is sufficiently large to allowdetailed district-level analysis. Theaccuracy with which households can beclassified by poverty status using theCWIQ gives credence to the use of predicted poverty level as a variablethroughout this report.

1.3.2 Cluster Location

Cluster Location is constructed on thebasis of self-reported travel time of thehousehold to three different locations: thenearest place to get public transport, thenearest all-weather road and the district

capital. Travel time is probed for by thehouseholds most commonly used formof transport. For each household, theaverage travel time is taken across thesethree locations. For each cluster, themedian of the 15 means is calculated. Allclusters are then ranked according to thismedian. The 15 clusters with the lowestmedian are labelled as accessible and the15 clusters with the highest median arelabelled as remote. Table 1.3 shows themedian of each of the variables used toconstruct the cluster location.

Table 1.3 shows that the poverty ratesdiffer substantially by cluster location:households in remote villages are morelikely to be poor than households inaccessible villages. Whereas the povertyrate in accessible villages is 9 percent,the figure for remote villages is more

than three times higher, at 32 percent.

Table 1.4: Socio-economic Group, Poverty Rate, and L ocation

Remote ClustersAccessibleClusters

Socio-Economic Group

Employees 7.3 43.1 56.9

Self-Employed Agriculture 22.3 54.3 45.7Self-Employed Other 7.5 28.2 71.8

Other 20.3 42.7 57.3


Percentage Living in

Poverty Rate

1.3.3 Socio-economicGroup

The socio-economic group that ahousehold belongs to depends on theemployment of the household head.Throughout the report heads employed inthe private sectors, formally orinformally, as well as Government andParastatal employees are categorised as

Employed. Self-employed individualsare divided into two groups, dependingon whether they work in agriculture(Self-employed agriculture) or in trade orprofessional sectors (Self-employed other).Finally, those who worked in other activitiesor who had not been working for the 4 weekspreceding the survey are classed as other.

Table 1.4 shows that the poverty rate ishighest for households headed by anindividual in the self-employedagriculture or other category andlowest for households where the head isan employee or is self-employed in non-agricultural activities. Households in thecategories employee and self-employed other are more likely to belocated in accessible villages, whereasthe categories self-employedagriculture and other are associatedwith households located in remotevillages .

The gender composition of the socioeconomic group is shown in Table 1.5.Roughly, 4 out of 5 households areheaded by a male. Heads working asemployees and self-employed in non-agricultural activities areoverwhelmingly males. Femalehousehold heads are mostly self-employed in agriculture or in the othercategory.

Table 1.5: Socio-economic Group and Gender of

the household headMale Female Total

Socio-economic Group

Employees 87.4 12.6 100.0

Self-Employed Agriculture 80.8 19.2 100.0

Self-Employed Other 100.0 0.0 100.0

Other 54.4 45.6 100.0

Total 80.6 19.4 100.0


Table 1.6 shows the breakdown of socioeconomic groups by main activity of thehousehold heads. As expected, the maineconomic activity in the district isagriculture, to which 88 percent of household heads are dedicated.

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Employees are mostly dedicated tomining, manufacturing, energy orconstruction, with a share of 76 percent;though an important share of them (24percent) is dedicated to agriculture. Theself-employed in non-agriculturalactivities are mostly dedicated to services

(93 percent). The other category ismostly divided between agriculture (61percent) and household duties (32percent).

Table 1.6: Socio-economic Group and Main Economic Activity

AgricultureMining

ManufacturingEnergy Construction

Private andPublic Services

HouseholdDuties

Other Total

Socio-economic GroupEmployees 23.8 76.2 0.0 0.0 0.0 100.0

Self-Employed Agriculture 98.1 0.4 1.5 0.0 0.0 100.0Self-Employed Other 3.7 3.7 92.6 0.0 0.0 100.0Other 60.6 0.0 0.0 31.7 7.7 100.0Total 87.5 3.5 7.5 1.2 0.3 100.0Source: CWIQ 2006 Karagwe DC

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1 Introduction

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2 VILLAGE, POPULATION ANDHOUSEHOLD CHARACTERISTICS

This chapter provides an overview of theKaragwe DC households and populationcharacteristics. The main populationcharacteristics are presented in sectiontwo. Section three presents the maincharacteristics of the households, such asarea of residence, poverty status, numberof members, and dependency ratio. Thesame analysis is then conducted for thehousehold heads in section four. Anexamination of orphan and foster status inthe district concludes the chapter.

2.1 Main PopulationCharacteristics

Table 2.1 shows the percent distribution of the population by cluster location andpoverty status, by gender and age. Overall,the districts population is young. Forinstance, 5 percent of the population isover 60 years old, whereas 50 percent isunder 15 years old. The remaining 45percent is between 15 and 59 years old.The location of the household does notseem to show strong correlation with theage of the population. However, poverty

status does seem to be correlated with age.People from non-poor households seem tobe slightly older than the poor.

The dependency ratio of the districtshouseholds is shown in Table 2.2. Thedependency ratio is the number of household members under 15 and over 64years old (the dependant population) over

the number of household members agedbetween 15 and 64 (the working agepopulation). The result is the averagenumber of people each adult at workingage takes care of.

The mean dependency ratio is 1.2,meaning that one adult has to take care of more than 1 person. There seems to be nostrong correlation between cluster locationand the dependency ratio. However, onaverage poor households present a higherdependency ratio (1.5) than non-poorhouseholds (1.1).

The dependency ratio increases with thenumber of household members, from 0.6for households with 1 or 2 members, to1.5 for households with 7 or moremembers. The breakdown by socio-economic group of household shows theother group has the highest dependencyratio (1.4), whereas the self-employed innon-agricultural activities has the lowest(0.9). There are no strong differences bygender of the household head.

Table 2.3 shows the percent distribution of households by number of householdmembers. The mean household size is 4.9individuals. Households with at most twoindividuals only represent 15 percent of allhouseholds in the district. Householdswith 3 to 6 members represent 60 percentof the total.

Table 2.1: Percent distribution of to tal population by gender and age

0-14 15-59 60+ Total 0-14 15-59 60+ Total 0-14 15-59 60+ TotalTotal 26.6 20.7 2.3 49.6 23.9 23.7 2.8 50.4 50.5 44.3 5.1 100.0

Cluster LocationAccessible 26.6 20.9 2.6 50.1 23.0 24.0 2.9 49.9 49.5 44.9 5.5 100.0Remote 26.7 20.4 2.0 49.1 24.8 23.4 2.7 50.9 51.5 43.8 4.8 100.0

Poverty StatusPoor 34.5 16.0 0.7 51.2 25.2 22.3 1.4 48.8 59.7 38.3 2.1 100.0Non-poor 23.6 22.4 3.0 48.9 23.5 24.2 3.4 51.1 47.0 46.6 6.3 100.0

Source:CWIQ 2006 Karagwe DC

Male Female Total


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2 Village, Population and household characteristics

Table 2.2: Dependency ratio

0-4 years 5-14 years 0-14 years 15-64 years 65+ years TotalDependency

ratioTotal 1.0 1.5 2.5 2.3 0.2 4.9 1.2Cluster Location

Accessible 0.9 1.5 2.4 2.2 0.2 4.9 1.2Remote 1.1 1.5 2.6 2.3 0.1 5.0 1.2

Poverty StatusPoor 1.7 2.2 3.9 2.6 0.1 6.5 1.5Non-poor 0.8 1.3 2.1 2.2 0.2 4.5 1.1

Household size1-2 0.0 0.1 0.2 1.0 0.4 1.6 0.63-4 0.9 0.5 1.4 1.9 0.2 3.5 0.85-6 1.2 1.7 2.9 2.4 0.2 5.4 1.37+ 1.5 3.4 4.9 3.3 0.1 8.3 1.5

Socio-economic GroupEmployee 0.9 1.9 2.8 2.8 0.0 5.6 1.0Self-employed - agric 1.0 1.5 2.5 2.2 0.2 4.9 1.2Self-employed - other 1.0 1.3 2.2 2.5 0.0 4.8 0.9

Other 0.8 1.9 2.7 2.3 0.5 5.4 1.4Gender of Household Head

Male 1.1 1.5 2.7 2.4 0.2 5.2 1.2Female 0.6 1.3 1.8 1.7 0.3 3.9 1.2


Table 2.3: Percent distribution of households by number of household members

1-2 persons 3-4 persons 5-6 persons 7+ persons Totalhousehold

sizeTotal 14.8 30.4 31.4 23.4 100.0 4.9Cluster Location

Accessible 14.2 33.3 30.6 21.9 100.0 4.9Remote 15.4 27.6 32.1 24.9 100.0 5.0

Poverty StatusPoor 0.0 19.2 36.6 44.2 100.0 6.5Non-poor 18.8 33.5 29.9 17.8 100.0 4.5

Socio-economic GroupEmployed 0.0 39.6 24.5 35.9 100.0 5.6Self-employed - agriculture 15.9 29.8 30.1 24.3 100.0 4.9Self-employed - other 9.6 36.7 38.2 15.4 100.0 4.8

Other 14.0 27.6 45.7 12.8 100.0 5.4Gender of Household Head

Male 12.1 28.3 32.5 27.1 100.0 5.2Female 26.2 39.5 26.4 7.9 100.0 3.9


The breakdown by cluster location showsno strong differences in mean householdsize. However, the breakdown by povertystatus shows that poor households aresignificantly bigger than non-poor. Over40 percent of them have 7 or moremembers, compared to just 15 percent of non-poor, with mean household sizes of 6.5 and 4.5 members, respectively.

Regarding socio-economic groups, theemployees and other have the higher

holds headed by males arerger than female headed households: the

mean household size, 5.6 and 5.4, than theself-employed groups, at 4.9 and 4.8,respectively.

Finally, houselaformer have 5.2 members in average,whereas the latter have only 3.9 members.This difference partly owes to the factthat, as shown in Section 2.4, femalehousehold heads rarely have a spouse.

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2.2 Main HouseholdCharacteristics

Table 2.4: Percent distribution of total populatio

Table 2.4 shows the percent distribution of total population by relationship to the head

f household.

or poverty status. Whennalysing by age-groups, it is clear that the

ld heads thanmales, with shares of 33 and 7 percent,

above byarital status. Overall, 35 percent of the

an 1ercent being officially divorced, up to 5

separated. Informal unions constitute only5 percent of the population and 6 percent

poor households are morekely to be in informal unions, whereas

tolygamous-married category peaks at the

the men have nevereen married, but for women the figure is

nhousehold

Other NotHead Spouse Child Parents relative related Total

Total 20.3 15.7 54.9 0.7 8.2 0.2 100.0Cluster Location

Accessible 20.5 16.6 54.4 0.3 8.1 0.2 100.0

Remote 20.1 14.9 55.4 1.1 8.3 0.3 100.0Poverty Status

Poor 15.3 13.2 61.8 0.6 8.9 0.2 100.0Non-poor 22.2 16.7 52.2 0.7 8.0 0.2 100.0

Age0- 9 0.0 0.0 89.6 0.0 10.3 0.2 100.0

10-19 1.0 2.7 81.1 0.0 14.6 0.5 100.020-29 28.5 43.9 21.4 0.0 5.9 0.3 100.030-39 50.3 45.7 3.8 0.0 0.3 0.0 100.040-49 65.9 29.5 2.1 2.5 0.0 0.0 100.050-59 65.8 29.4 1.6 3.2 0.0 0.0 100.060 and above 73.3 15.1 0.0 8.0 3.6 0.0 100.0GenderMale 33.3 0.1 58.3 0.1 7.8 0.3 100.0Female 7.4 31.1 51.5 1.2 8.6 0.2 100.0Source:CWIQ 2006 Karagwe DC

o No particular trends emerge by analysingby remotenessa

category other relatives is mostlycomprised by children under 19 years old.This highlights the importance of theanalysis of fostering and orphan status.After 30, most of the population is eitherhead of their own household or spouse tothe head of the household.

The gender split-up shows that males aremore likely to be househoferespectively. In turn, spouses and parentsare overwhelmingly females.

Table 2.5 shows the percent distribution of

the population age 12 andmpopulation has never been married. Inaddition, 40 percent is married and

Monogamous and 10 percent is marriedand polygamous. Despite less thppercent of the population is unofficially

is widowed.

Members of

by relationship to head of

linon-poor households are more likely to bein a monogamous marriage. But there areno strong differences by cluster location.

The age breakdown shows thap50-59 group, with almost one-third of theindividuals in that age-group being in apolygamous marriage. For the populationafter 20 years old, married-monogamousis the most common category, except forthe population aged 60 and over, where widowed is the most common category.Divorce does not show a trend but, aswould be expected, the categoriesseparated and widowed both increasewith age. Never married also showscorrelation with age, decreasing as thepopulation gets older.

Around 40 percent of bonly 30 percent. While 11 percent of women are widowed, only 1 percent of men are in this category. Furthermore,females tend to be separated morecommonly than men, who are morecommonly married.

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Table 2.5: Percent distribution of the total population age 12 an above by marital status

Never Married Married Informal,married monogamous polygamous loose union Divorced Separated Widowed Total

Total 34.7 39.8 9.5 4.9 0.1 4.6 6.3 100.0Cluster Location

Accessible 34.8 40.3 10.3 4.8 0.0 4.3 5.4 100.0

Remote 34.7 39.4 8.8 5.0 0.2 4.8 7.2 100.0Poverty Status

Poor 36.2 33.8 9.7 9.2 0.0 5.9 5.3 100.0Non-poor 34.1 41.7 9.6 3.6 0.1 4.2 6.7 100.0

Age12-14 100.0 0.0 0.0 0.0 0.0 0.0 0.0 100.015-19 91.1 6.8 0.7 1.0 0.0 0.4 0.0 100.020-24 38.5 53.2 1.2 3.0 0.0 3.1 1.0 100.025-29 7.0 62.7 11.4 11.9 0.0 6.4 0.5 100.030-39 1.9 68.1 12.9 9.4 0.0 5.9 1.8 100.040-49 0.7 50.5 23.2 7.5 0.0 6.5 11.6 100.050-59 0.0 35.1 31.8 1.6 0.0 6.2 25.3 100.060 and above 0.4 41.5 9.3 1.5 1.2 12.5 33.7 100.0GenderMale 40.3 41.8 9.1 5.1 0.0 2.3 1.4 100.0Female 29.7 38.1 9.9 4.7 0.2 6.7 10.8 100.0Source:CWIQ 2006 Karagwe DC

Table 2.6: Percent distribution of the to tal population age 5 and above bysocio-economic group

Self-employed Self-employedEmployed Agriculture Other Other Total

Total 1.2 26.0 2.4 70.4 100.0Cluster Location

Accessible 1.9 24.2 3.6 70.3 100.0Remote 0.5 27.7 1.2 70.5 100.0

Poverty Status

Poor 0.0 24.3 0.5 75.2 100.0Non-poor 1.5 26.7 3.1 68.7 100.0

Age5- 9 0.0 0.0 0.0 100.0 100.0

10-14 0.0 0.0 0.0 100.0 100.015-19 0.0 5.4 0.0 94.6 100.020-29 0.9 32.7 6.3 60.0 100.030-39 3.6 50.2 5.1 41.1 100.040-49 5.2 68.9 3.3 22.5 100.050-59 2.9 66.7 4.4 26.1 100.060 and above 0.0 61.2 1.2 37.6 100.0GenderMale 1.9 36.9 4.0 57.2 100.0Female 0.6 15.5 0.8 83.1 100.0


Table 2.6 shows the percent distribution of the population age 5 and above by socio-economic group. Overall, roughly onequarter of the population is self-employedin agriculture, with 70 percent in otheractivities. Individuals living in remotevillages seem to be somewhat more likelyto be self-employed in agriculture, as non-poor households. Members of non-poor

households are also more likely beemployees than poor households, whohave a higher share in the other category.

The analysis of the age-groups isparticularly interesting. The share of self-employed in agriculture increases withage, peaking at 69 percent for the 40 to 49group. The category other decreases

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Table 2.9: Percent distribution of heads of household by socio-economic group

Employed Self-employed Self-employed OtherAgriculture Other Total

Total 3.5 83.8 6.5 6.2 100.0Cluster Location

Accessible 4.4 79.5 10.0 6.1 100.0Remote 2.6 88.0 3.0 6.3 100.0

Poverty StatusPoor 1.2 91.6 2.4 4.8 100.0Non-poor 3.8 82.0 7.6 6.6 100.0

Age15-19 0.0 100.0 0.0 0.0 100.020-29 2.6 82.2 14.1 1.2 100.030-39 4.6 84.6 7.6 3.1 100.040-49 6.0 84.3 4.0 5.7 100.050-59 4.4 85.6 4.4 5.5 100.060 and above 0.0 81.7 1.4 16.9 100.0GenderMale 4.0 83.3 7.7 5.0 100.0

Female 1.4 85.7 1.4 11.4 100.0Source:CWIQ 2006 Karagwe DC

Table 2.10: Percent distribution of heads of household by highest level of education

Some Completed Some Completed PostNone primary primary secondary secondary secondary Total

Total 33.4 21.8 40.3 1.6 0.0 2.8 100.0Cluster Location

Accessible 23.1 20.2 50.1 1.7 0.0 4.9 100.0Remote 43.5 23.5 30.7 1.6 0.0 0.8 100.0

Poverty StatusPoor 65.5 9.6 24.9 0.0 0.0 0.0 100.0Non-poor 25.0 25.1 44.6 2.1 0.0 3.2 100.0

Age15-19 24.5 75.5 0.0 0.0 0.0 0.0 100.020-29 33.5 11.6 54.9 0.0 0.0 0.0 100.030-39 20.2 12.1 62.7 1.6 0.0 3.5 100.040-49 30.8 18.9 45.6 3.0 0.0 1.5 100.050-59 34.4 39.3 17.8 0.5 0.0 8.0 100.060 and above 54.4 35.5 4.2 2.7 0.0 3.2 100.0GenderMale 24.3 23.3 47.1 1.8 0.0 3.5 100.0Female 71.0 16.0 12.0 1.0 0.0 0.0 100.0Source:CWIQ 2006 Karagwe DC

important category, representing at least 4out of 5 household heads in each age-

group. The employee category peaks at 6percent for the group aged from 40 to 49.The self-employed other categorystarts at 14 percent for the 20-29 groupand then decreases steadily down to 1percent for the cohort aged 60 and above.The other category gains importance inthe latter group, with a share 17 percent,as it includes the economically inactivepopulation.

The breakdown by gender of thehousehold head shows that in male-headed

households, the main income earner ismore likely to be an employee or self-employed in non-agricultural activitiesthan in female-headed households. In thelatter, the main income earner is morelikely to be from the other category.

Table 2.10 shows the percent distributionof the heads of household by highest levelof education. Overall, around only 5percent of the household heads has any

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education after primary. One third of thehousehold heads has no education, 22percent some primary and 40 percent havecompleted primary.

The breakdown by cluster location showsthat, as would be expected, householdheads in remote villages are more likely tohave no education than the ones fromaccessible villages, with shares of 44 and23 percent, respectively. Furthermore,household heads in accessible villages are

more likely to have post-primaryeducation, with a share of 7 percentagainst 3 percent of household heads inremote villages.

Poverty status is strongly correlated withthe education of the household heads. Thisshould be no surprise, since education of the household head is one of the povertypredictors used to define poverty status.However, the difference is still important:while 66 percent of heads of poorhouseholds has no education, the share fornon-poor is 25 percent. In the otherextreme, whereas 5 percent of non-poor

household heads has post-secondarystudies, the share for poor householdheads is virtually null.

The age breakdown shows that 54 percentof household heads aged 60 or over has noeducation, and a further 35 percent justsome primary. Completed primaryrepresents around 55 percent for thegroups between 20 and 49; but only 18

percent in the 50-59, where someprimary gains importance.

Table 2.11 - Orphan status of children under 18 years old

Children who lostmother only

Children wholost father only

Children wholost both father &

motherTotal 2.0 6.6 1.4Cluster Location

Accessible 1.7 6.2 1.2Remote 2.4 6.8 1.5

Poverty StatusPoor 1.6 8.5 1.8Non-poor 2.3 5.7 1.2

Age0-4 0.7 1.1 0.05-9 1.7 4.6 2.210-14 4.4 10.4 1.815-17 1.5 21.0 2.8GenderMale 1.9 6.1 1.1

Female 2.2 7.1 1.7Source:CWIQ 2006 Karagwe DC

The analysis by gender shows that femalehousehold heads are more likely to haveno education than males, with rates of 24and 71 percent, respectively. Half the malehousehold heads has completed primary,

against 12 percent of females.

2.4 Orphan and FosterStatus

Table 2.11 shows the percent distributionof children under 18 years old who havelost at least one parent. Overall, about 1percent of children under 18 lost bothparents, 2 percent lost only their motherand 7 percent lost only their father. Thisamounts to 10 percent of all childrenunder 18 who lost at least one parent at thetime of the survey.

The age breakdown shows that orphanstatus is correlated with age: as can beexpected older children are more likely tobe orphans than younger children. Around26 percent of the children between 15 and17 years lost a parent, and 24 of thechildren in that age-group lost their father.There does not seem to be a gender trendin orphan status.

The percent distribution of children under18 years old by foster status is shown inTable 2.12. A child is defined as living ina nuclear household when both parentslive in the household and as living in anon-nuclear household when at least oneparent is absent from the household. Notethat this makes it a variable defined at thelevel of the child, rather than thehousehold (a household may be nuclearwith respect to one child, but not withrespect to another). The table shows that40 percent of children under 18 wereliving in non-nuclear households at thetime of the survey.

Overall, 43 percent the children fromremote clusters live in non-nuclear

households. There is no strong relationbetween cluster location and foster status,but children from poor households tend tobe fostered more often than children fromnon-poor households (with shares of 10and 6 percents, respectively).

The analysis of age-groups shows that theshare of children living in non-nuclearhouseholds increases with age, but is

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3 EDUCATIONThis chapter examines selected educationindicators in Karagwe district. Theseinclude literacy rate, access to schools,satisfaction rate, dissatisfaction rate andenrolment.

The first section presents an overview onselected education indicators. The secondsection provides information ondissatisfaction and non-attendance alongwith the reasons behind them. Schoolenrolment and drop-out rates are presentedin the fourth section. These give a pictureon the enrolment patterns according to theage of pupils. The final section of thechapter gives information on adult andyouth literacy status within the district.

3.1 Overview of theEducation indicators

3.1.1 Literacy

Table 3.1 shows the main educationindicators for the district. Literacy isdefined as the ability to read and write inany language, as reported by therespondent. Individuals who are able toread but cannot write are considered

illiterate.Overall, about two thirds (66 percent) of all adults in this survey are literate.However, there is a large gap in literacybetween accessible and remote villages aswell as non-poor and poor households.The adult literacy rate in accessiblevillages is about 16 percentage pointshigher than that of those from remotevillages at 74 and 58 percent respectively.Similarly, literacy rate among individualsliving in non-poor households is at 70percent while individuals living in poorhouseholds have a literacy rate of 53

percent.

Data collected for this district furthershows that the proportion of literate adultsin households headed by an employee issignificantly higher than that of adultsfrom households headed by individuals inthe other social economic group (whichconsists of unemployed, inactive orindividuals involved in domestic work).Literacy rate is highest among adultsliving in households headed by employees

at 95 percent, followed by those adultsliving in households headed by individualswho are self-employed in agriculture at 84percent, self-employed in non-agriculturesector at 64 percent and the lowest literacyrate is observed in households whose headis from the other category at 57 percent.

Furthermore, literacy rates differ betweenmen and women. The literacy rate amongmen is about 16 percentage points higherthan that of women at 75 and 59 percentrespectively.

3.1.2 Primary School Access, Enrolmentand Satisfaction

Access

Primary school access is defined as theproportion of primary school-age children(7 to 13 years) reporting to live within 30minutes of travel from the nearest primarySchool.

Just above half (51 percent) of primaryschool-age children live within 30 minutestravel from a primary school. Primaryschool access is significantly higher inaccessible clusters than in remote clusters.Data shows that primary school accessamong accessible clusters is more thantwice as high as that among remoteclusters at 68 and 33 percent respectively.Furthermore, children living in non-poorhouseholds have a better access to primaryschools compared to children living inpoor households at 53 and 46 percentrespectively. Primary school access ishighest among children living inhouseholds headed by an individual whois self-employed in agriculture 90 percent,followed by those from households headedby employees (69 percent), othercategory and lowest among householdsheaded by an individual who is self-employed in non-agriculture sector at 47percent. However, there is a minimaldifference in primary school access amongthe children living in male and female


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3 Education

headed households at 52 and 49 percentrespectively.

Enrolment

There are two measures of Enrolment: theGross Enrolment Rate (GER) and the NetEnrolment Rate (NER). Both of thesemeasurements are examined in thissection.

Gross Enrolment Rate is defined as theratio of all individuals attending school,irrespective of their age, to the populationof children of school-age. If there are alarge proportion of non-school-ageindividuals attending school, the GrossEnrolment Rate may exceed 100 percent.Primary school Gross Enrolment Rate

informs on the ratio of all individuals inprimary school-age (7 to 13 years) in thedistrict.

Net Enrolment Rate is defined as the ratioof children of school-age currently

enrolled at school to the population of children of school-age. Therefore, primaryschool Net Enrolment Rate is the ratio of children between the ages of 7 and 13years currently in primary school to thepopulation of children in this age-group inthe district.

The Net Enrolment Rate provides moreinformation for analysis than the GrossEnrolment Rate. While trends in actualparticipation of school-age children informal education are in part captured bythe Net Enrolment Rate, the GrossEnrolment Rate, at best, provides a broad

Table 3.1: Education indicators

Literacy gross net gross netrate access enrollment enrollment satisfaction access enrollment enrollment satisfaction

Total 66.8 51.8 109.6 79.2 46.5 4.6 14.2 11.8 46.9Cluster Location

Accessible 74.4 69.5 112.0 82.9 51.8 8.8 22.8 20.3 45.8Remote 59.2 34.5 107.3 75.6 41.2 0.7 6.2 3.8 50.9

Poverty StatusPoor 53.6 45.9 94.3 73.8 43.5 0.0 11.6 8.5 65.9Non-poor 70.5 54.0 116.8 81.8 48.0 6.0 14.0 11.8 42.0

Socio-economic Group

Employee 92.4 62.4 113.6 70.6 71.4 15.7 48.7 32.3 68.8Self-Employee - agric 64.6 48.2 110.3 79.9 44.1 2.7 10.7 10.1 40.1Self-Employee - other 85.1 90.4 114.1 90.7 70.0 28.5 22.7 15.6 100.0Other 59.3 60.3 97.9 71.1 41.8 0.0 24.4 14.1 10.6

GenderMale 75.2 52.7 110.1 79.7 47.7 5.0 13.5 10.8 27.3Female 59.5 50.9 109.1 78.7 45.2 4.2 14.8 12.7 62.8

Orphan statusOrphaned 84.5 54.4 119.5 70.6 44.1 1.8 5.3 5.3 0.0Not-orphaned 84.0 51.5 107.4 80.7 46.6 5.2 12.5 12.5 55.8

Foster statusFostered 72.9 53.5 95.8 80.0 55.1 11.5 6.9 6.9 0.0Not-fostered 86.4 51.0 111.5 79.9 44.8 3.5 11.0 11.0 55.2


1. Literacy is defined for persons age 15 and above.2. Primary school:

Access is defined for children of primary school age (7-13) in households less than 30 minutes from a primary school.

Enrollment (gross) is defined for all persons currently in primary school (Kindergarden, Grade 1 to Grade 8) regardless of age.

Enrollment (net) is defined for children of primary school age (7-13) currently in primary school (Kindergarden, Grade 1 to Grade 8).

Satisfaction is defined for all persons currently in primary school who cited no problems with school.

3. Secondary school:

Access is defined for children of secondary school age (14-19) in households less than 30 minutes from a secondary school.

Enrollment (gross) is defined for all persons currently in secondary school (Form 1 to Form 5) regardless of age.

Enrollment (net) is defined for children of secondary school age (14-19) currently in secondary school (Form 1 to Form 5).

Satisfaction is defined for all persons currently in secondary school who cited no problems with school.

Primary Secondary

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indication of the general participation ineducation and of the capacity of theschools. The Gross Enrolment Rate givesno precise information regarding theproportion of individuals of school andnon-school-ages at school, nor does it

convey any information on the capacity of the schools in terms of quality of education provided.The primary school Gross Enrolment Ratein the district is currently at 113 percent.This figure indicates that all individualswho are at primary school constitute 113percent of all children of primary school-age in the district. The Net EnrolmentRate further shows that 80 percent of allprimary school-age children are currentlyattending school. The Gross EnrolmentRate is almost the same for clusterslocated in remote and those located inaccessible areas. However, Net EnrolmentRate is higher among clusters located inaccessible areas than that of clusterslocated in remote areas at 83 and 77percent respectively.

Disaggregation of the enrolment data byselected household characteristics showsthat primary school enrolment rates varysignificantly by poverty status and socio-economic status. Both Gross EnrolmentRate and Net Enrolment Rate are higheramong people living in non-poor thanpoor households are. While the GrossEnrolment Rate is significantly higheramong people living in non-poorhouseholds than that of those living inpoor households, at 121 and 96 percentrespectively, the Net Enrolment Rateamong non-poor households is about 8percentage points higher than that amongpoor households at 83 and 75 percentrespectively.

Whereas, Gross Enrolment Rate is highestamong people living in households headedby employees and Net Enrolment Rate ishighest among households where the headis employed in agriculture sector, in bothcases, Gross Enrolment rate and Net

enrolment Rate are lowest amonghouseholds headed by an individualbelonging to the other socio-economicgroup.

Satisfaction

The satisfaction rate informs on theproportion of primary school pupils whocited no problems with their schools.

Information on satisfaction was obtainedby asking respondents to identifyproblems they faced with their schools.

46 percent of all primary school pupils aresatisfied with the schools they are

attending. Pupils living in householdslocated in accessible clusters seem to bemore satisfied than those living in remoteclusters at 51 and 40 percent respectively.Similarly, pupils living in non-poorhouseholds are more satisfied with theschools they attend compared to thoseliving in poor households at 48 and 42percent respectively. Respondents livingin households headed by non-agricultureself-employed individuals tend to be leastsatisfied with their primary schools at 42percent, while households headed byemployees, have the highest satisfactionrate (71percent). Lastly, it is observed thatthe difference in satisfaction between maleand female headed households is minimalat 48 and 44 percent respectively.

3.1.3 Secondary School Access, Enrolmentand Satisfaction

Access

Secondary school access rate is defined asthe proportion of secondary school-agechildren (14 to 19 years) reporting to livewithin 30 minutes of travel from thenearest secondary school.

Only 5 percent of all pupils in secondaryschool live within 30 minutes travel to thenearest secondary school. This is a verysmall percentage compared to that of primary school (51 percent).

Data shows that location and povertystatus of the household are correlated tosecondary school access rate. Secondary

school access rate is higher in accessibleclusters than in remote clusters at 9 and 1percent respectively. Similarly, whereasnon of the pupils in secondary schoolliving in poor households live within 30minutes travel to the nearest secondaryschool, the access rate for individualsliving in non-poor households is at 6percent.

It is observed that members living inhouseholds whose head is self-employed

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3 Education

in agriculture have the highest access rateto secondary school of 29 percentfollowed by those living in householdsheaded by employees (16 percent) self employed in non-agriculture (3 percent)and non of the members living in

households whose head belongs to theother socio-economic group live within30 minutes travel to the nearest secondaryschool.

Enrolment

As explained elsewhere before, GrossEnrolment Rate is defined as the ratio of all individuals attending school,irrespective of their age, to the populationof children of school-age while the NetEnrolment Rate is defined as the ratio of children of school-age currently enrolledat the school to the population of childrenof school-age. The secondary schoolGross Enrolment and Net Enrolment Rateis calculated using population of the age-group 14 to 19 years.

The Gross Enrolment Rate and NetEnrolment Rate at secondary school arevery low compared to primary schoollevel. Only 12 percent of children of secondary school-age are currentlyenrolled in secondary school. There is anadditional 2 percent of the populationenrolled in secondary school but their ageis outside the identified secondary school-age range. This is a very small percentagecompared to that of primary school.

It is observed that the difference in GrossEnrolment Rate and Net Enrolment Ratebetween people living in accessibleclusters is about 4 times as high as that of people living in remote clusters. Povertystatus of the household shows to beslightly correlated with the GrossEnrolment Rate as poor households have aGross Enrolment Rate of 10 percent whilenon-poor households have a 14 percent

Gross Enrolment Rate. Furthermore, datashows that the difference in secondaryschool Net Enrolment Rate between poorand non-poor households and that betweenmales and females is only about 2 percent.

Individuals living in households headed byemployees have the highest Net EnrolmentRate and Gross Enrolment Rate of 32 and49 percent respectively, while those livingin households headed by self-employed innon-agriculture have the lowest secondaryschool Net Enrolment rate and GrossEnrolment Rate of about 10 percent.

Satisfaction

About half (49 percent) of the totalpopulation enrolled in secondary schoolare satisfied with their schools. Thissatisfaction rate is slightly higher than inprimary schools (46 percent). Thesatisfaction rate for people living inaccessible clusters is significantly lowerthan that of those living in remote clustersat 46 and 61 percent respectively.

It is observed that secondary schoolsatisfaction rate for people living in poorhouseholds are nearly double that of thoseliving in non-poor households at 82 and 42percent respectively. Whereas allrespondents living in households wherethe head is self-employed in agricultureare satisfied with their schools, peopleliving in households where the head isfrom the other category have the lowestsatisfaction rate of 16 percent, followed byindividuals from households whose headis self-employed in non-agriculture sectorat 40 percent.

Among individuals currently enrolled insecondary school, females are moresatisfied with their schools than males.The satisfaction rate for females is morethan twice as high as that of males at 67and 27 percent respectively.

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Table 3.2: Percentage of students currently enrolled in school by reasons for dissatisfaction

Total 51.2 20.0 11.4 48.2 4.6 28.9 48.7 8.0 3.7Cluster Location

Accessible 45.6 27.8 14.4 54.6 5.5 31.1 42.0 9.3 3.9Remote 57.7 12.8 8.6 42.3 3.7 26.9 54.8 6.8 3.6

Poverty StatusPoor 54.5 20.6 15.8 45.0 7.1 22.1 56.4 8.0 1.1Non-poor 49.9 18.6 7.9 48.3 3.7 30.0 46.8 8.2 4.8

Socio-economic GroupEmployee 26.4 44.3 49.2 62.4 7.4 49.2 43.4 0.0 0.0Self-employed - agric 53.8 18.4 10.9 48.1 3.4 28.4 51.5 7.7 4.0Self-employed - other 26.6 71.9 12.5 12.5 7.6 45.5 31.9 10.4 10.4Other 60.6 10.2 3.8 55.0 13.4 21.5 30.3 13.1 0.0

GenderMale 51.2 20.1 11.2 43.1 4.1 33.2 50.2 9.7 4.6Female 51.2 19.9 11.7 53.6 5.1 24.3 47.1 6.2 2.8

Type of schoolPrimary 53.2 19.9 10.9 49.8 3.9 30.8 51.2 4.3 3.4

Government 54.5 20.0 11.0 50.2 3.9 30.6 51.2 4.0 3.5Private 7.1 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0Other 32.9 0.0 0.0 0.0 0.0 100.0 100.0 0.0 0.0

Secondary 53.1 29.8 22.9 38.6 15.0 31.7 27.0 32.0 5.2Government 54.8 44.6 33.5 50.9 26.5 44.0 35.5 0.0 0.0Private 49.5 13.2 11.4 28.2 0.0 19.7 19.7 67.1 15.0Other 57.9 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0

Other 40.7 16.1 9.5 41.9 4.2 15.6 42.6 21.0 4.9Government 40.8 13.9 7.0 41.6 6.1 20.0 51.9 11.0 3.5Private 43.0 37.1 26.2 64.6 0.0 0.0 27.2 21.8 13.6Other 37.7 0.0 0.0 13.6 0.0 13.6 15.8 70.6 0.0

Source:CWIQ 2006 Karagwe DCGender is B1, Age is B4, Rural is UrbRur = 1, Urban is UrbRur = 2

Other

Reasons for dissatisfaction

Percentdissatisfied

Books/ supplies

PoorTeaching

Lack of teachers

in badcondition

Highfees

Teachersabsent

Lack of space

3.2 Dissatisfaction

One of the aims of the survey is to informon perceptions of quality of servicesreceived among individuals for whomthese services are provided. To obtain theinformation, primary and secondaryschool students who were not satisfiedwith the schools they were attending at thetime of the survey were asked to providereasons for their dissatisfaction.

Complaints regarding lack of books andother resources were allocated into theBooks/Supplies category, while thoserelating to quality of teaching and teachershortages were grouped into theTeaching category. The Facilitiescategory incorporates complaintsregarding overcrowding and badconditions of facilities. The questionnaireallowed a good collection of dissatisfaction data as there were eight

options for dissatisfaction including theothers category.

Just above half (51 percent) of studentsenrolled in primary or secondary schoolreported dissatisfaction with the schoolsthey were attending. Out of the dissatisfyindividuals, 51 percent reported to bedissatisfied due to facilities in badcondition (Table 3.2), 49 percent reporteddissatisfaction because of lack of teachersand 31 percent of all students reporteddissatisfaction with their schools becauseof lack of space.

People living in accessible clusters seemto be less dissatisfied than those living inremote clusters. The dissatisfaction ratefor people living in accessible clusters is12 percentage points less than that of people living in remote clusters at 46 and58 percent respectively. However, thedifference in dissatisfaction rates betweenpoor and non-poor households appear to

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3 Education

Table 3.3: Percentage of children 6-17 years who ever attended school by reason not currently attending

Percent notattending

Completedschool Distance Cost Work Illness Pregnancy

Gotmarried

Useless/ uninteresting

Failedexam

Awaitsadmission Dismissed

Total 10.8 27.8 1.9 25.4 7.2 8.2 1.7 7.8 9.1 16.1 4.8 0.0Cluster Location

Accessible 7.8 30.2 0.0 21.4 8.6 2.9 4.8 5.9 0.0 11.5 9.6 0.0Remote 13.9 26.3 3.0 27.7 6.3 11.2 0.0 8.9 14.4 18.8 2.0 0.0

Poverty StatusPoor 12.6 7.9 5.9 22.1 7.9 10.6 5.5 2.0 14.1 10.9 0.0 0.0Non-poor 10.3 36.9 0.0 26.9 6.8 7.1 0.0 10.5 6.9 18.5 7.0 0.0

Socio-economic GroupEmployed 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0Self-emp - agric 11.7 29.7 2.1 27.4 8.1 7.0 2.0 8.8 10.3 12.7 5.4 0.0Self-emp - other 9.5 33.4 0.0 26.3 0.0 0.0 0.0 0.0 0.0 40.3 0.0 0.0Other 9.6 0.0 0.0 0.0 0.0 28.3 0.0 0.0 0.0 44.4 0.0 0.0

GenderMale 8.7 14.1 4.6 38.6 6.1 6.5 0.0 6.1 12.9 19.1 8.5 0.0Female 12.9 37.3 0.0 16.2 7.9 9.4 3.0 9.0 6.5 14.0 2.2 0.0

Age7-13 1.6 0.0 0.0 0.0 0.0 11.5 0.0 0.0 11.7 0.0 0.0 0.014-19 26.7 30.6 2.1 28.0 7.9 7.9 1.9 8.6 8.9 17.7 5.3 0.0

Source:CWIQ 2006 Karagwe DCGender is B1, Age is B4, Rural is UrbRur = 1, Urban is UrbRur = 2

Reasons not currently attending

be minimal at 54 and 50 percentrespectively.

Furthermore, data shows that whereasmore than half (55 percent) of peopleliving in households where the head isself-employed in non-agriculture are

dissatisfied with the schools they attend,only 19 percent of those living inhouseholds where the head is self-employed in agriculture report the same.The most prominent reason fordissatisfaction among the pupils living inhouseholds headed by employees andthose in the other category is lack of teachers, while pupils living in householdswhere the head is self-employed inagriculture are mainly dissatisfied due tolack of books and supplies, and those fromhouseholds headed by self-employed innon-agriculture are mainly dissatisfied dueto facilities in bad condition.

Reasons for dissatisfaction with schoolsslightly differ depending on whether theperson is in primary or secondary school.Those attending primary school report tobe most dissatisfied due to facilities in badcondition (53 percent) followed by lack of teachers (50 percent), while thoseattending secondary school reportdissatisfaction due to lack of teachers (42percent) followed by lack of space (34percent).

Whereas 4 percent of individuals attendinggovernment primary schools raisedcomplaints about high fees, none of theindividuals attending governmentsecondary schools reported dissatisfactiondue to high fees. On the other hand, all

individuals attending private primaryschools complained about high feescompared to 59 percent of those attendingprivate secondary schools.

3.3 Non-attendance

Table 3.3 shows the percentage of individuals of primary or secondaryschool-age (7 to 19 years) currently notattending school and the reasons for notattending. The non-attendance rate isdefined as the proportion of individuals of school-age who previously participated informal education and had stoppedattending school by the time of the survey.

The district has about 11 percent of 7 to 19year olds who are currently not attendingschool. More than a quarter (29 percent)of this population does not attend schoolbecause they have completed standardseven, O-level or A-level. 25 percent of respondents of this population reportednon-attendance due to high expenses,while 16 percent were not attending

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school because they failed standard four,seven or form four exams. Only about 2percent of the respondents reported non-attendance due to pregnancy and distanceto schools.

Data collected shows that the non-attendance percentage rate of respondentsliving in remote clusters is nearly doublethat of those living in accessible clusters at15 and 8 percent respectively.

There is no difference in the non-attendance rates among children living inpoor and non-poor households. However,differences appear when the two groupsare broken down by reasons for notattending school. The major reasons fornon-attendance for individuals living inpoor households is high expenses (24percent) followed by being uninterested(12 percent). Individuals living in non-poor households report completing school(38 percent) followed by high expenses(26 percent). The percentage rate of respondents from non-poor households notattending school because they havecompleted standard seven, O-level and A-level is about 4 times as high as that of those from poor households at 38 and 9percent respectively. While 6 percent of the respondents from poor households arenot attending school due to pregnancynone of those from non-poor householdsreported the same.

Whereas non of the respondents living inhouseholds whose head is an employeereported to be out of school, about 10percent of those from the other socio-economic groups reported not to beattending school.

Nearly all the primary school-agedchildren attend school, as their non-attendance rate is only 2 percent. On theother hand, 74 percent of secondary schoolaged individuals attend school. 32 percentof secondary school-aged individualsclaim that it is because they have

completed school (standard seven, O-levelor A-level) while 28 percent say it isbecause of high expenses.

3.4 Enrolment and Drop-out rates

This section takes a closer look at theprimary and secondary school enrolmentand drop-out rates. Rather than looking atprimary or secondary school-aged children

as a whole, data will be categorized by ageand gender. Drop-out rates are calculatedby dividing the number of children wholeft school in the current year by the totalnumber of children enrolled this year plusthose that dropped out (children who left

school/ (children currently enrolled+children who dropped out).

Primary School

The drop-out rates at primary level aregenerally very low. The primary schooldrop-out rate at the time of the survey wasonly 1 percent. Therefore, only enrolmentrates will be analysed.

Overall, 80 percent of primary school-aged children are currently enrolled, out of those within the primary school-age range(7 to 13 years) 79 percent all femalechildren and 81 percent of all malechildren are enrolled. The required age atwhich children should start standard one is7 years. However, data on primary schoolenrolment shows that at the time of thesurvey, only 37 percent of all seven yearolds were enrolled. Most children arelikely to be in school by the age of 11where the Net Enrolment Rate is at 98percent.

Table 3.4: Primary school enrollment and drop out rates by gender

Male Female Total Male Female TotalTotal 79.7 78.7 79.2 0.8 0.6 0.7

7 41.9 36.0 39.5 0.0 0.0 0.08 64.2 75.0 70.1 0.0 0.0 0.09 86.0 81.1 83.3 0.0 0.0 0.0

10 90.7 92.8 91.6 2.4 0.0 1.411 100.0 88.6 94.3 0.0 0.0 0.012 90.2 83.1 86.7 0.0 3.9 1.913 92.7 90.6 91.7 2.3 0.0 1.2


Base for table is primary school age population (age 7-13)

Drop out ratesNet enrollment rates

Table 3.5: Secondary school enrollment and drop out rates by gender

Male Female Total Male Female TotalTotal 10.8 12.7 11.8 5.1 7.9 6.6

14 0.0 0.0 0.0 0.0 3.3 1.515 2.8 4.9 3.8 0.0 9.0 4.616 12.9 19.8 16.5 12.7 5.9 9.217 17.9 21.5 20.2 6.0 15.7 12.218 20.0 25.2 23.0 8.0 15.7 12.519 34.8 9.8 20.2 9.7 0.0 4.0


Net enrollment rates Drop out rates

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3 Education

Secondary School

Secondary school enrolment rates aremuch lower than those at primary level.Only 12 percent of secondary school

children are currently enrol compared to80 percent in primary school. For a personfollowing a normal school curriculum i.e.started standard one with 7 years of age,he/she is expected to start form one at age14. Table 3.5 shows secondary netenrolment patterns by age. From this tablewe see that net enrolment rates increasegradually by age up to the age of 18.However, the biggest difference inenrolment rate is observed between age 15and 16, which suggests that many children

join secondary school at the age of 16lagging 2 years from a person who followsa normal school curriculum. Furthermore,less than a fifth (17 percent) of 16 yearolds report to be enrolled by the time of the survey. We also observe that there isno student enrolled in secondary school bythe age of 14.

Secondary school drop-out rates amongindividuals of secondary school-age (14 to19 years) are substantially highercompared to those of primary school. 7percent of children of secondary school-age had dropped out of school in the yearprior to the survey (table 3.5). In general,

the highest drop-out rate is observedamong 18 year olds. The highest drop-outrate among males is at the age of 16 whi

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KARAGWE DC CWIQ 2006