Koica Program Baseline Survey 2015 Report

KOICA PROGRAM BASELINE SURVEY 2015 REPORT

Baseline Survey for KOICA Program in Uganda 2016

THE REPUBLIC OF UGANDA UGANDA BUREAU OFSTATISTICS

BASELINE SURVEY FOR KOICA PROGRAM2015

Uganda Bureau of Statistics

Colville Street, Plot 9

P.O. Box 7186, Kampala

Tel: 0414-320740, 0772 705127

Fax: 0414-237 553 August 2016 E-mail: [email protected]

Website: www.ubos.org

Baseline Survey for KOICA Program in Uganda 2016

LIST OF ACRONYMS

ANC Antenatal Care

EA Enumeration Areas

EmOC Emergency Obstetric Care

HC Health Centre

KOICA Korea International Cooperation Agency

M&E Monitoring and Evaluation

MNCH Maternal New-born and Child Health

PNC Post-natal Care

PPS Probability Proportional to Size

UBOS Uganda Bureau of Statistics

UNICEF United Nations Children’s Fund

UPHC Uganda Population and Housing Census

VHTs Village Health Teams

Baseline Survey for KOICA Program in Uganda 2016

TABLE OF CONTENTS

TABLE OF CONTENTS ...... 3 LIST OF TABLES ...... 5 EXECUTIVE SUMMARY ...... ERROR! BOOKMARK NOT DEFINED. 1 CHAPTER ONE ...... 9

INTRODUCTION ...... 9 1.1 BACKGROUND ...... 9 1.2 SURVEY OBJECTIVES ...... 10 1.3 SCOPE AND COVERAGE ...... 10 1.4 SAMPLING DESIGN ...... 10 1.4.1 Selection of Health facilities ...... 11 1.5 SURVEY ORGANIZATION ...... 11 1.5.1 Recruitment and training of fieldworkers ...... 11 1.5.2 Composition of field teams ...... 11 1.6 DATA PROCESSING ...... 12 1.7 FUNDING ...... 12 2 CHAPTER TWO ...... 13

CHARACTERISTICS OF THE HOUSEHOLD POPULATION ...... 13 2.1 INTRODUCTION ...... 13 2.2 DISTRIBUTION OF HOUSEHOLD POPULATION ...... 13 2.3 CHARACTERISTICS OF HOUSEHOLD HEADS ...... 14 2.3.1 Sex and Age-group of Household Heads ...... 14 2.3.2 Highest level of Education of Household Heads ...... 15 2.3.3 Marital status of Household Heads ...... 15 3 CHAPTER THREE ...... 17

MATERNAL AND NEW BORN CARE ...... 17 3.1 INTRODUCTION ...... 17 3.2 CHARACTERISTICS OF WOMEN AGED 15-49 YEARS ...... 17 3.2.1 Age and Marital Status ...... 17 3.2.2 Educational attainment of Women aged 15 – 49 years ...... 18 3.2.3 Age at first marriage ...... 19 3.2.4 Teenage Motherhood ...... 20 3.2.5 Children born after 2011 ...... 20 3.3 ANTENATAL CARE (ANC) ...... 22 3.3.1 Antenatal care attendance ...... 22 3.3.2 Antenatal care provider ...... Error! Bookmark not defined. 3.3.3 Number of Antenatal Care visits...... 23 3.3.4 Timing of Antenatal Care visits ...... 24 3.3.5 Intermittent Preventive Treatment of Malaria in Pregnancy ...... 25 3.3.6 Number of doses of SP Fansidar taken ...... 26 3.3.7 Attitudes towards Antenatal care ...... 27 3.4 DELIVERY ...... 27 3.4.1 Place of delivery ...... 28 3.4.2 Assistance during delivery ...... 29 3.4.3 Attitudes towards delivery in a health facility ...... 30 3

Baseline Survey for KOICA Program in Uganda 2016

3.5 POSTNATAL CARE FOR MOTHERS...... 31 3.5.1 Postnatal Care Utilization ...... Error! Bookmark not defined. 3.5.2 Timing of first postnatal check-up ...... 31 3.5.3 Postnatal Care for newborns ...... Error! Bookmark not defined. 3.5.4 Timing of first postnatal check-up for the newborn ...... 32 3.6 BREASTFEEDING ...... 33 3.6.1 Breastfeeding for Last Birth ...... Error! Bookmark not defined. 3.6.2 Initiation of Breastfeeding ...... 33 3.6.3 Feeding children using a bottle with a nipple ...... 34 3.6.4 Diarrhoeal Diseases ...... 35 3.6.5 Oral Rehydration Solutions ...... 35 4 CHAPTER FOUR...... ERROR! BOOKMARK NOT DEFINED.

HEALTH FACILITY ...... ERROR! BOOKMARK NOT DEFINED. 4.1 INTRODUCTION ...... ERROR! BOOKMARK NOT DEFINED. 4.2 GENERAL INFORMATION ABOUT HEALTH FACILITIES ...... ERROR! BOOKMARK NOT DEFINED. 4.3 WORK FORCE AVAILABILITY ...... ERROR! BOOKMARK NOT DEFINED. 4.3.1 Staff allocated to Maternity and labor ward including postnatal ward ...... Error! Bookmark not defined. 4.4 AVAILABILITY AND FUNCTIONALITY OF VILLAGE HEALTH TEAMS ...... ERROR! BOOKMARK NOT DEFINED. 4.5 FACILITY INFRASTRUCTURE AND DESIGNATED SPACE ...... ERROR! BOOKMARK NOT DEFINED. 4.5.1 Type of Facility infrastructure in HC IV ...... Error! Bookmark not defined. 4.6 SIGNAL FUNCTIONS AND OTHER ESSENTIAL SERVICES ...... ERROR! BOOKMARK NOT DEFINED. 4.7 ACTIVE MANAGEMENT OF THE THIRD STAGE OF DELIVERY ... ERROR! BOOKMARK NOT DEFINED. 4.8 STAFF TRAINED IN EMNOC (MNH PACKAGE) ...... ERROR! BOOKMARK NOT DEFINED. LIST OF REFERENCES...... ERROR! BOOKMARK NOT DEFINED. APPENDIX ...... ERROR! BOOKMARK NOT DEFINED. SAMPLE DESIGN ...... ERROR! BOOKMARK NOT DEFINED. QUESTIONNAIRES ...... ERROR! BOOKMARK NOT DEFINED.

Baseline Survey for KOICA Program in Uganda 2016

LIST OF TABLES

Table 2.1: Distribution of Households by Residence and District (%) ...... 13 Table 2.2: Distribution of households heads by Sex, Age-group and District (%) ...... 14 Table 2.3:Distribution of Household Heads Household Heads by highest level of education attended and District (%) ...... 15 Table 2.4: Distribution of Household Heads by Marital status and District (%) ...... 16 Table 3.1: Distribution of women aged 15 – 49 years by age-group, marital status and District (%) ...... 18 Table 3.2: Distribution of women age 15-49 years by highest level of education attended by district (%) ..... 19 Table 3.3: Percentage of women aged 15-49 who were first married by specific exact ages and median age at first marriage, according to age of women at time of survey ...... 20 Table 3.4: Percentage of women age 15-19 who have had a live birth in the five years preceding the survey by age and district (%) ...... 20 Table 3.5: Distribution of women age 15-49 years who had a child born after 2011 by district (%) ...... 21 Table 3.6: Distribution of women age 15-49 years who had a live birth in the five years preceding the survey by category of antenatal care (ANC) provider during pregnancy for the most recent birth by district (%) ...... 22 Table 3.7: Distribution of women age 15-49 years who had a live birth in the five years preceding the survey by number of times of antenatal care visits by district (%) ...... 23 Table 3.8: Distribution of women age 15-49 years who had a live birth in the five years preceding the survey by timing of the first ANC and district (%) ...... 24 Table 3.9: Distribution of women age 15-49 years who had a live birth in the five years preceding the survey who received SP Fansidar during the pregnancy leading to their most recent birth by source of SP Fansidar by district (%) ...... 25 Table 3.10: Distribution of women age 15-49 years who had a live birth in the five years preceding the survey who received SP Fansidar by number of times taken during the most recent pregnancy and District (%)..... 26 Table 3.11: Percentage of women age 15-49 years who had their last live birth in the last five years preceding the survey who reported “Yes” to selected attitudinal questions by district ...... 27 Table 3.12: Distribution of women age 15-49 years who had their last live birth in the last five years preceding the survey by place of delivery and district (%) ...... 28 Table 3.13: Distribution of women age 15-49 years who had their last live birth in the last five years preceding the survey by provider of assistance during delivery and district (%) ...... 29 Table 3.14: Percentage of women age 15-49 years who had their last live birth in the last five years preceding the survey who reported “Yes” to selected attitudinal questions on delivery at a health facility by district (%) 30 Table 3.15: Distribution of the mother’s first postnatal check-up for the last live birth in the last five years preceding the survey by time after delivery and district (%) ...... 32 Table 3.16: Distribution of last live births delivered in health facilities in the last five years preceding the survey by timing of first postnatal check-up after delivery by District (%) ...... 33 Table 3.17: Distribution of mothers by timing of initial breastfeeding for the last child and district (%) ...... 34 Table 3.18: Distribution of children fed from bottles with nipples during the day or night preceding the survey (%) ...... 35 Table 3.19: Distribution of children born after 2011 by whether they had diarrhoea in the last 2 weeks preceding the survey (%) ...... 35 Table 3.20: Distribution of last born children who had diarrhoea by whether they drank ORS the day preceding the survey and district (%)...... 36 Table 4.1: Number of Health facilities by Residence, Level of HF and type of facilityError! Bookmark not defined. Table 4.2: Average number of staff by cadre, level and district ...... Error! Bookmark not defined. Table 4.3: Average number of medical staff allocated to the Maternity and labor ward including the postnatal ward ...... Error! Bookmark not defined. Table 4.4: Availability and Functional (trained, attended and submitted quarterly meeting reports) VHTS by District ...... Error! Bookmark not defined. Table 4.5: Number of Hospitals by type health facility infrastructure available and districtError! Bookmark not defined. Table 4.6: Number of HC IV by of Type facility infrastructure available and districtError! Bookmark not defined. Table 4.7: Distribution of Health Facilities by the functional EmONC facilities and districtError! Bookmark not defined. Table 4.8: Distribution of the functional EmONC facilities ...... Error! Bookmark not defined. Table 4.9: Health facilities in which women received AMTSL for vaginal delivery by districtError! Bookmark not defined. 5

Baseline Survey for KOICA Program in Uganda 2016

Table 4.10: Number of Staff trained in EmNOC (MNH package) by level of health facility and district ..... Error! Bookmark not defined.

Baseline Survey for KOICA Program in Uganda 2016

EXECUTIVE SUMMARY

Introduction: In 2015, UNICEF received a four year grant (2015 to 2018) from the Korean government through KOICA to support and strengthen maternal, newborn and child health service delivery in Karamoja region in North-Eastern and part of Acholi region in Northern part of Uganda. To measure the success of the project using key implementation indicators and establish the magnitude of actual need, a baseline data on available services and uptake thereof in project areas needed to be established through a survey. The survey was conducted between March and April of 2016 The survey would also provide information to the 3 implementing agencies (UNICEF, World Vision and Save the Children) to guide areas for programmatic changes in the 12 program districts of Butaleja in the east, Kitgum, Agago& Pader in Acholi sub region, Kotido, Moroto, Nakapiripirit, Abim, Kaabong, Amudat and Napak in Karamoja sub region and Ntoroko in the West. The specific objectives of the survey were: 1. To generate information to serve as the baseline of the project indicators 2. To provide the stakeholders with information for validation of the indicator targets as a basis for project monitoring and assessment of the achievements of the interventions

Outcomes: The survey measured selected indicators under the following outcome areas: Outcome 1: Increased availability and service readiness of Essential MNCH services (EmNOC, ANC, Deliveries, PNC, iCCM) at the facility and community levels in priority districts

Outcome 2: Increased utilization of quality maternal, new-born child health services, including emergency obstetric and new-born care at the community, outreach, and Referral facility levels

Outcome 3: Increased community awareness, demand and acceptance of lifesaving interventions including innovative approaches for MNCH services

Methods: The survey was designed to produce representative estimates for the key indicators for all 12 districts separately. Each district therefore constituted a reporting domain. The survey used 2 of the 6 questionnaires employed in the last National Demographic Health Survey (DHS) i.e. the household and the facility questionnaires. The household questionnaire addressed questions on demographic characteristics of respondents, attitudes, and reproductive history of the eligible women, while the facility questionnaire addressed facility level readiness and capability to provide critical MNH services including questions on staffing, equipment and medicines & supplies. The sample size determination considered the percentage of women aged 15-49 who received a post-natal checkup in the first two days after birth and the average proportion of women attended by a skilled attendant during delivery. Using a standard formula, the effective sample size for the survey at household level with a Relative Margin of Error (RME) of 10 percent was found to be 6,646 households. This sample size was further adjusted to get an even number of villages per district for variance estimation without increasing the cost while still considering the population share. The final sample size constituted of 204 households. Households were pre-selected prior to the survey and no substitutions or changes of the pre-selected households were allowed at the implementing stage of data collection to avoid bias. To arrive at the health facilities to be surveyed; the survey employed the approach of linking after selection, where all the health facilities serving the population of the sampled villages

Baseline Survey for KOICA Program in Uganda 2016 was selected. Given that the 12 districts in the survey have few Health Centers IIIs and IVs in the districts, the survey covered all health facilities within the target districts. Results: Characteristics of the household population: Of the households surveyed, 86.4 percent live in rural areas and 13.6 percent in urban areas; four districts of Pader, Kitgum, Moroto and Butaleja had urban populations over 15 percent while Nakapiripirit, Abim and Kotido had urban populations below 5 percent. Nearly 30.9 percent of household heads were female. Overall 38 percent of household heads had never attended school; the number of households heads with no school attendance increased to 66.7 per cent in Karamoja. Over 86 percent of household heads reported being married. Seventy five point eight percent of the female respondents were between 15 and 35 years old; and 22 percent were less than 20 years old. 70.4 percent of the respondents were married with the highest numbers recorded in Amudat at 85 and Kotido at 82.5 percent. 77.4 percent of the female respondents had ever given birth with the highest numbers recorded in Amudat, Kotido, Moroto, Nakapiripirit and Butaleja. 76.4percent of the female respondents had a child under 5 years of age (born after 2011); the highest numbers of respondents with children 5 children were recorded in Kotido at 90 percent, Amudat at 83.2 percent, Abim and Nakapiripirit at 82.2 and 82.1 percent respectively. Maternal and newborn service indicators: Overall 46.9 percent of the women reported attending antenatal care (ANC) at least 4 times with the highest numbers recorded in Kitgum 63 percent, Agago 62 percent and Pader 61 percent and the worst in Ntoroko 29.9 percent and Kaabong 20.3 percent. The number of women attending ANC only once or not at all was particularly notable in Amudat 14.1 percent, Kaabong 11 percent and Ntoroko 6.5 percent. The timing of visits for the first ANC visit within the first trimester was best kept in the districts of Kotido and Nakapiripirit at 68 percent and 58 percent respectively; and worst in the districts of Amudat 22.7%, Butaleja 30.8 percent and Ntoroko 34.4 percent. Whereas 86.9 percent of the respondents reported taking fansidar as presumptive malaria treatment during pregnancy just 36.8 percent took more than 2 doses; 39.4 took 3 doses. It is to be noted that there has been a policy change on the number of doses for fansidar during pregnancy. Community knowledge and attitudes: Among women age 15-49 years who had their last live birth in the last five years preceding the survey, willingness to visit a health facility for antenatal care was nearly universal across all the districts at 98.6 percent. However, only 74 percent of the respondents were aware that women should seek antenatal care before 16 weeks of pregnancy. 78.3 percent of all the women surveyed in the focus districts reported that their husbands consider ANC to be important for all pregnant women. 67percent reported that their mothers-in-law consider ANC to be important for all pregnant women. In contrast 96.5 percent of the female respondents, 88.7 percent of husbands and 77.2 percent of mothers’ in-law were reported by the respondents to consider health facility deliveries important. Home delivery was reported at 16.1 per cent for the last under last delivery of respondents; the worst districts were Amudat with 32.6 percent home deliveries, Pader and Butaleja at 24.1 and 24.7 percent respectively. The lowest home deliveries were reported from the districts of Kotido, Abim, Kitgum and Agago with less than 8% home deliveries. Of note, were that 6.1% of the deliveries in the 12 districts and 9.1% of deliveries in Karamoja were conducted by a TBA; the highest TBA deliveries were in Pader 21.5 percent, Amudat 18.1 percent and Ntoroko 1.1 percent. Across all district 6.3 percent of mothers had no help with their last delivery; the highest numbers being reported from Nakapiripirit 17.5% and Amudat 14.9 percent. On postnatal care, 69.1 percent of mothers in all districts and 75.8 percent of all mothers in Karamoja reported receiving a post-natal check for their last delivery. However, 35.4 percent of mothers in all 12 districts, 27.8 percent in Karamoja reported having no postnatal check for their last delivery. Postnatal checks for newborn infants were reported at 55.2 percent in all

Baseline Survey for KOICA Program in Uganda 2016 districts and 63.9 percent in Karamoja; 23.7 percent of newborns did not receive any postnatal check in all districts and 18.3 percent in Karamoja. On initiation of breastfeeding at birth within the first hour, in all districts 77.2 percent of mothers reported early initiation while in Karamoja early initiation of breastfeeding was reported at 87.2 percent. Respondents reported that 35% of children under 5 in all districts and 36percent in Karamoja had had diarrhea in the 2 week preceding the survey; of these only 20.6 percent in all districts and 29.9 percent in Karamoja had received Oral rehydration salts as treatment for their diarrhea. Health facility preparedness to deliver Basic and comprehensive obstetric care: None of the hospitals or Health Centre IVs were found to provide all 9 signal functions for comprehensive EMONC and none of the health centre IIIs or IIs in all 12 districts could provide all 7 signal functions for basic EMONC. All hospitals provided all 7 BEMONC functions and just half of the HC IVs provided all 7 BEMONC functions. With regard to MNH infrastructure, only one in four hospitals had a functional newborn care unit and only 2 of the 4 hospitals had separate beds for kangaroo mother care for management of preterms. Only 1 hospital had a functioning blood bank while no HC IV had a blood bank. In assessing the technical skills of health facility staff to provide EMONC services; previously filed partographs were used to assess skills. Considering the Membranes and Liquor, the highest average number of the randomly selected cases filled in correctly were found in Amudat district (29%), Moroto district (27%) and Napak district (22%) while the lowest percentage of cases was found in Kitgum district (11%). No cases in Butaleja district were found to have been filled in correctly. Summary: The 12 program districts were selected for support based on low coverage and uptake of maternal neonatal and child health services; the baseline survey confirms that selected districts continue to perform below national targets for the key MNCH indicators. Only 46.9 percent of the women reported attending antenatal care (ANC) at least 4 times; with the worst ANC4 attendances in Ntoroko 29.9 percent and Kaabong 20.3 percent. While willingness to visit a health facility for antenatal care was nearly universal across all the districts at 98.6 percent only 74 percent of the female respondents were aware that women should seek antenatal care before 16 weeks of pregnancy. Home delivery stands at 16.1 per cent with the worst districts in Amudat with 32.6 percent, Pader and Butaleja at 24.1 24.7 percent respectively. TBA deliveries were reported as high as 21.5 percent in Pader, 18.1 percent in Amudat and 11.1 percent in Ntoroko. Nearly 24 percent of newborns did not receive any postnatal check in all districts and only 30 percent of children under 5 who had diarrhea were received ORS for treatment. Health facility capacity to deliver EMONC services remain limited with gaps in infrastructure and staff capacity. A review of programming to take into consideration the key issues highlighted by the survey and programmatic changes to address critical and varying bottlenecks across the 12 program districts is warranted.

Baseline Survey for KOICA Program in Uganda 2016

1 CHAPTER ONE

INTRODUCTION

1.1 Background United Nations Children’s Fund (UNICEF) - Uganda secured funding from KOICA to strengthen the continuum of care for maternal, new-born and child health services in the target districts of Acholi and Karamoja sub-regions. In addition, the district of Ntoroko was targeted by Save the Children while Butaleja were funded by World Vision as depicted in the Map. The baseline survey for KOICA Program was a sample survey designed to provide reference point information for Monitoring and Evaluation (M&E) of the achievements of the interventions supported under the KIOICA project in the program districts.

Baseline Survey for KOICA Program in Uganda 2016

1.2 Survey objectives The overall objective of the survey was to establish baseline indicators for care of maternal, new-born and child health services in the districts of Karamoja and Acholi sub-regions, Ntoroko and Butaleja districts against which achievements of the interventions supported under the project will be assessed. The specific objectives were:

i) To generate information to serve as the base measure of the project indicators; ii) To provide the stakeholders with information for validation of the indicator targets as a basis for project monitoring and assessment of the achievements of the interventions 1.3 Scope and coverage The baseline survey for KOICA program was conducted in i12 districts targeted by the project. The districts include; Butaleja,Kitgum, Kotido, Moroto, Nakapiripirit, Pader, Abim, Kaabong, Agago, Amudat, Napak and Ntoroko. The survey was designed to produce representative estimates for the main KOICA indicators for each district separately implying that each district constituted a reporting domain. The survey involved interviewing a randomly selected sample of households and women aged 15 to 49 years and who lived in the selected households.

The Baseline Survey for KOICA Program used two questionnaires; the Household/Individual Questionnaire and the Health Facility Questionnaire. Specifically, the household questionnaire covered topics on: the members in the household, eligible woman’s reproductive history- Antenatal Care, Delivery, Postnatal care and Breast feeding.

On the other hand, the health facility questionnaire covered topics such as: the facility workforce, training in signal functions, the functionality of Village Health Teams (VHTs), overall facility capacity and infrastructure, Pharmacy, stock management, Equipment and supplies, Signal functions and other essential services, Pantograph review, Protocols, guidelines and registers and facility case summaries on maternal and new-born outcomes.

1.4 Sampling design The sample for the survey was drawn using a two stage stratified sampling design with the 2014 Uganda Population and Housing Census (UPHC)list of Enumeration Areas (EA) used as the sampling frame. In total, 12 sampling strata were created, each representing a district. Based on the sample allocation and using Probability Proportional to Size (PPS) selection yielded a total of 216 EAs in the program districts. Following selection of the EAs, a household listing operation was undertaken in all of the selected EAs before the main survey. The household listing exercise involved generation of a comprehensive list of the names of all household heads found in the EA. The resulting list of households served as the sampling frame for the selection of households in the second stage. At the second stage of selection, a

Baseline Survey for KOICA Program in Uganda 2016 fixed number of 30 households was selected from the household listing per EA and interviewed during the survey. In order to avoid bias, no substitution of the selected households was done when the interviewers failed to secure an interview with the household. Additional details on sample design are presented in the Appendix.

1.4.1 Selection of Health facilities

With regard to selection of health facilities, after selection of the EAs, the linking approach was used whereby the nearest HCIIs serving the population in the selected EA was interviewed. In addition, the survey covered all HC IIIs and HC IVs in the districts since they are few in number.

1.5 Survey organization The planning of the survey, including designing of the sample was consultative and involved the Korea International Cooperation Agency (KOICA), UNICEF – Uganda, Save the Children and World Vision. The Uganda Bureau of Statistics (UBOS) implemented the survey.

1.5.1 Recruitment and training of fieldworkers

UBOS recruited and trained field staff to serve as field interviewers and team leaders. Candidates were centrally recruited on the basis of maturity, friendliness, language skills, education level, and willingness to work away from home. All field staff were trained for a period of five days with two days of field practice in the areas around Kampala. Training involved both classroom and practical demonstrations for a better understanding of the concepts. The trainees were taught about their roles as fieldworkers, sampling of households, how to fill the questionnaires, check for completion and handling of field returns.

1.5.2 Composition of field teams

All field staff selected to work on the survey were grouped in teams comprising a field supervisor, three interviewers, one nurse and one driver. Supervisors and interviewers were either male or female. The supervisor was responsible for the entire team, contacting local officials, selecting households to be interviewed and ensuring high quality of the work in the team.

The interviewers conducted household and women interviews while the nurse administered the health facility questionnaire. Each field supervisor was responsible for one team.

Prior to field interviews, a listing exercise was undertaken in all the sampled EAs. A total of 8 teams were formed to undertake the listing exercise. Each listing team comprised of three to four persons. 12

Baseline Survey for KOICA Program in Uganda 2016

1.6 Data processing Data entry operators were recruited and trained to handle field returns and capture the data. Two office editors were employed to support the data entry team with editing. The Directorate of Information Technology (DIT) at UBOS provided the programs for entering the data as well as training of data processing staff; while the Directorate of Socio-Economic Surveys (DSES), handled the editing, tabulation, and analysis of the survey data. Data processing began one month after the commencement of fieldwork.

1.7 Funding The Survey was implemented by UBOS with funding from by UNICEF, World Vision and Save the Children under the KOICA project.

Baseline Survey for KOICA Program in Uganda 2016

CHAPTER TWO

CHARACTERISTICS OF THE HOUSEHOLD POPULATION

2.1 Introduction This chapter presents information on characteristics of the household population covered during the survey including the sex, age group, educational attainment and marital status of household heads among others.

In the survey, a household is defined as a person or a group of persons, related or unrelated, who live together in the same house or compound, and eat together as a unit. Information was collected on all usual residents and visitors who spent the night preceding the survey in the household and who were present at the time of the interview.

2.2 Distribution of Households Table 2.1 displays the distribution of households by residence and district. Overall, 86 percent of the households were resident in rural areas while only 14 percent were in urban areas. There was a wide variation in the distribution of households by residence across the districts with Kitgum having the highest percentage of households residing in urban areas (27%) while Nakapiripirit and Abim had the lowest (3% each respectively).

Table 1.1: Distribution of Households by Residence and District (%)

District Urban Rural Total Number Butaleja 24.0 76.0 100 380 Abim 3.3 96.7 100 403 Amudat 11.7 88.3 100 330 Kaabong 8.7 91.3 100 380 Kotido 3.1 96.9 100 365 Moroto 19.5 80.5 100 385 Nakapiripirit 2.5 97.5 100 401 Napak 6.9 93.1 100 434 Agago 11.0 89.0 100 415 Pader 18.9 81.1 100 443 Kitgum 27.3 72.7 100 444 Ntoroko 5.6 94.4 100 434 All 13.6 86.4 100 4,814 Karamoja Sub-region 7.5 92.5 100 2,698

Baseline Survey for KOICA Program in Uganda 2016

2.3 Characteristics of Household Heads The head of the household is the key decision-maker, making all major decisions within the household while other members acknowledge his/her authority. It should be noted that the fact that one was the main economic provider in the household was not necessarily the most relevant criterion for identifying the household head; age was often an important factor. In this study, the household head was defined as one who takes major decisions in the household.

2.3.1 Sex and Age-group of Household Heads

Table 2.2 shows that overall, 70 percent of households were male headed while 30 percent were female headed. Butaleja had the highest percentage of male headed households (80%).while Kaabong had the highest percentage of female headed households (40%). In addition, the majority of household heads were in the age-group 25 – 44 years (60%) followed by those aged 45 years and above (29%). This pattern was observed across all districts surveyed. Kaabong had the highest percentage of household heads in the age-group 25 – 44 years (68%) compared to other districts.

Table 1.2: Distribution of households heads by Sex, Age-group and District (%)

Sex Age group Less than 25 - 44 45+ District Male Female Total 25 years years years Total Number

Butaleja 79.6 20.4 100 12.7 54.1 33.2 100 380 Abim 69.8 30.2 100 10.5 63.3 26.3 100 401 Amudat 64.5 35.5 100 16.3 64.1 19.6 100 330 Kaabong 59.6 40.4 100 7.6 67.8 24.6 100 378 Kotido 79.1 20.9 100 5.3 65.6 29.1 100 364 Moroto 69.1 30.9 100 11.0 63.2 25.8 100 385 Nakapiripirit 63.1 36.9 100 10.6 63.3 26.0 100 400 Napak 65.3 34.7 100 12.2 53.5 34.3 100 433 Agago 66.3 33.7 100 12.1 55.4 32.4 100 415 Pader 71.4 28.6 100 11.4 59.1 29.5 100 440 Kitgum 71.8 28.2 100 9.4 61.7 29.0 100 443 Ntoroko 75.2 24.8 100 14.8 56.9 28.3 100 434 All 69.9 30.1 100 10.9 60.1 29.1 100 4,803 Karamoja Sub-region 67.1 32.9 100 10 62.9 27.1 100 2,691

Baseline Survey for KOICA Program in Uganda 2016

2.3.2 Highest level of Education of Household Heads

Education is an important determinant of an individual’s attitudes and outlook on various aspects of life.Education enables individuals make informed decisions that impact their health and well-being. Table 2.3 shows the percentage distribution of household heads by highest level of education attended and district. Overall, 38 percent of household heads had no education while 43 percent had attended primary level schooling as their highest level of education. Only five percent of household heads had attended tertiary level education. The proportions of household heads with no education was highest in Amudat District (81%) followed by Kotido District (80%) and lowest in Butaleja District (7%).

Table 1.3: Distribution of Household Heads by highest level of education attended and District (%)

Education level attended No A- Don’t District education Primary O-level level Tertiary Know Total Number Butaleja 7.4 74.8 13.9 1.0 2.9 0.0 100 374 Abim 30.2 40.8 23.0 3.2 2.8 0.0 100 401 Amudat 81.1 12.1 4.6 0.6 1.0 0.6 100 324 Kaabong 73.9 19.2 4.8 0.2 1.9 0.0 100 375 Kotido 79.9 18.4 0.8 0.4 0.3 0.3 100 362 Moroto 62.9 19.7 7.2 2.0 7.6 0.5 100 383 Nakapiripirit 61.9 29.9 3.7 0.8 3.7 0.0 100 397 Napak 72.4 19.7 4.1 0.7 3.1 0.0 100 425 Agago 15.1 64.2 15.3 1.3 4.2 0.0 100 415 Pader 11.1 56.6 16.7 4.3 11.3 0.0 100 440 Kitgum 13.3 52.6 20.9 1.2 12.0 0.0 100 443 Ntoroko 17.3 58.8 18.7 1.4 3.8 0.0 100 434 Total 38.2 43.3 11.9 1.4 5.1 0.1 100 4,773 Karamoja Sub-region 66.7 22.9 6.4 1 2.9 0.2 100 2,667 Note: Education categories refer to the highest level of education attended, whether or not the level was completed.

2.3.3 Marital status of Household Heads

Marriage is a primary indication of women’s exposure to the risk of pregnancy; therefore, it is important for an understanding of fertility. .A person’s marital status indicates whether the person is married or otherwise. For purposes of the survey, the term “married” was used in its broadest context to include persons who were cohabiting as long as such persons considered themselves as “living as if married”. Table 2.4presents the percentage of household heads by marital status and district. The results show that,87 percent of all the household heads surveyed were married while nine percent were widowed. The shares vary by district with 16

Baseline Survey for KOICA Program in Uganda 2016

Amudat having the highest percentage of household heads who were married (94%) while Ntoroko had the lowest (75%). The highest percentage of widowed household heads was in Pader (15%) compared to other districts. Furthermore, one in every ten household heads (11%) in Ntoroko was divorced or separated.

Table 1.4: Distribution of Household Heads by Marital status and District (%)

Marital status Married/ Divorced/ Not District Single Cohabiting Separated Widowed stated Total Number Butaleja 1.4 92.0 3.8 2.8 0.0 100 373 Abim 0.1 89.0 0.1 10.6 0.2 100 390 Amudat 1.4 93.5 2.5 2.6 0.0 100 322 Kaabong 0.3 86.7 0.7 12.3 0.0 100 370 Kotido 1.2 93.2 0.1 5.5 0.0 100 354 Moroto 1.9 86.5 2.3 9.3 0.0 100 376 Nakapiripirit 0.6 89.1 0.8 9.6 0.0 100 392 Napak 1.4 85.1 1.2 12.3 0.0 100 418 Agago 0.0 85.0 3.2 11.8 0.0 100 412 Pader 0.0 79.8 5.7 14.5 0.0 100 437 Kitgum 0.3 86.2 3.3 10.2 0.0 100 438 Ntoroko 6.1 75.2 11.3 6.8 0.6 100 427 All 0.9 86.8 2.8 9.4 0.0 100 4,709 Karamoja Sub region 1.0 88.7 1.0 9.4 0.0 100 2,622

Baseline Survey for KOICA Program in Uganda 2016

CHAPTER THREE

MATERNAL AND NEW BORN CARE

1.1 Introduction This chapter presents the survey findings on the characteristics of female household members aged 15-49 years such as their schooling status, marital status, the highest level of education attended, the age at first marriage and her birth history among others. In addition, information on maternal and child care for women that had a birth after 2011 is included.

1.2 Characteristics of Women aged 15-49 years This section presents a profile of female respondents in each of the districts covered in the survey including their socio-demographic characteristics.

1.2.1 Age and Marital Status

Marriage is a primary indicator of women’s exposure to pregnancy and is therefore important for understanding of fertility. Populations in which women marry at a young age tend to have and early childbearing and therefore high fertility. Thus age at marriage is an important determinant of fertility levels. However, the timing of marriage also has profound consequences for women’s lives. For purposes of the survey, the term “married” was used in its broadest context to include persons who were cohabiting as long as such persons considered themselves as “living as if married”.

Table 3.1 presents the percentage distribution of women aged 15-49 years by age-group and marital status. Overall, majority of the women (54%) were in the age group 20-34 years and this was consistent across the Districts although there were variations in the proportions. The survey also collected information on the current marital status of women aged 15-49 years. The results show that overall, 70 percent of the women aged 15-49 years were married or living together with a partner at the time of the survey. The highest percentage of married/cohabiting women was in Amudat (86%) while Pader (58%) had the lowest.

Baseline Survey for KOICA Program in Uganda 2016

Table 0.1: Distribution of women aged 15-49 years by age-group, marital status and District (%)

Age Marital status 20 - 34 35-49 Married/ Not District <20 Years Years Years Total Cohabiting married Total Number Butaleja 19.9 53.7 26.4 100 73.6 26.4 100 470 Abim 17.7 50.9 31.3 100 77.0 23.0 100 489 Amudat 15.9 62.8 21.3 100 85.8 14.2 100 353 Kaabong 18.3 60.8 20.9 100 72.2 27.8 100 478 Kotido 13.5 58.9 27.6 100 82.5 17.5 100 387 Moroto 15.6 55.9 28.6 100 79.4 20.6 100 425 Nakapiripirit 17.9 61.1 21.0 100 78.6 21.4 100 451 Napak 21.7 56.3 22.0 100 71.4 28.6 100 507 Agago 25.0 45.0 29.9 100 67.0 33.0 100 505 Pader 28.1 48.8 23.1 100 58.0 42.0 100 581 Kitgum 23.0 51.5 25.5 100 62.1 37.9 100 595 Ntoroko 24.2 52.8 23.0 100 60.8 39.2 100 562 All 21.1 53.6 25.3 100 70.3 29.7 100 5,803 Karamoja Sub-region 17.5 58.1 24.4 100 77.2 22.8 100 3,090

1.2.2 Educational attainment of Women aged 15-49 years

Educational attainment is an important indicator that is also linked to reproductive behavior, use of contraception, children’s health and proper hygiene habits among others. Education provides people with the knowledge and skills that can lead to better choices and health habits leading to a better quality of life. Table3.2shows the distribution of women aged 15-49 years by highest level of education attained and district. Overall, half (50%) of the women in the reproductive age group(aged 15-49 years) had attended primary level education as their highest level of education while 36 percent had no education. The highest percentage of women in the reproductive age group whose highest level of education attended was primary level was in Kotido District (72%) while Amudat had the lowest (16%). A negligible proportions of women aged 15-49 years had attended A-level or tertiary level education.

Baseline Survey for KOICA Program in Uganda 2016

Table 0.2: Distribution of women age 15-49 years by highest level of education attended by district (%)

Highest level of education attained No District education Primary O-level A- level Tertiary Total Number

Butaleja 11.0 71.4 15.6 1.2 0.9 100 471 Abim 32.4 55.2 11.2 0.7 0.5 100 488 Amudat 78.4 16.3 5.2 0.0 0.1 100 351 Kaabong 75.3 21.0 2.7 0.2 0.8 100 468 Kotido 75.5 23.4 1.0 0.0 0.2 100 393 Moroto 61.4 27.1 4.4 1.6 5.4 100 428 Nakapiripirit 65.3 30.9 2.4 0.0 1.4 100 446 Napak 66.9 23.5 6.3 0.9 2.5 100 496 Agago 17.2 67.6 13.3 0.3 1.6 100 513 Pader 11.8 68.2 14.7 0.6 4.8 100 585 Kitgum 17.5 60.5 16.5 0.9 4.7 100 604 Ntoroko 17.7 57.1 22.6 1.0 1.7 100 562

Total 37.3 49.0 10.7 0.6 2.3 100 5,805 Karamoja Sub-region 65.4 28.0 4.5 0.5 1.5 100 3,070 Note: Education categories refer to the highest level of education attended, whether or not the level was completed.

1.2.3 Age at first marriage

In most societies, marriage marks the point in a woman’s life when childbearing first becomes socially acceptable. Women who marry early, on average, have longer exposure to pregnancy and reproductive risks and also a greater number of births in their lifetime. Information on age at first marriage was obtained by asking all women that ever-married how old they were when they started living together with their first spouse. The results in Table 3.3shows the percentage of women who are married by specific exact ages, according to current age. The minimum legal age of marriage in Uganda is 18 years. However, in Uganda, marriages among young girls do occur. Among women age 20-49 years, 11 percent were married by age 15, and 22 percent were married by age 18. Median age at first marriage across the other age groups other than the 15-19 years age group was 18 years.

Baseline Survey for KOICA Program in Uganda 2016

Table 0.3: Percentage of women aged 15-49 who were first married by specific exact ages and median age at first marriage, according to age of women at time of survey

Median age of mother at Percentage first married at exact age first Current Never marriage age 15 18 20 22 25 married Number 15 - 19 18.9 19.5 0.0 0.0 0.0 94.0 962 17.00 20 - 24 11.6 27.2 7.9 2.0 0.0 60.6 272 18.00 25 - 29 10.6 21.4 13.1 2.0 1.1 37.2 142 18.00 30 - 34 12.7 17.9 15.2 3.3 1.9 18.3 97 18.00 35 - 39 10.0 22.0 13.9 3.0 2.2 4.0 75 18.00 40 - 44 10.1 24.1 15.5 2.5 1.6 0.0 71 18.00 45 - 49 8.0 20.4 15.8 1.9 4.0 2.4 64 18.00 20 - 49 10.5 22.2 12.1 2.2 1.3 32.6 731 18.00 25 - 49 11.0 22.1 13.7 2.3 1.8 15.9 459 18.00

1.2.4 Teenage Motherhood

Teenage pregnancy and motherhood are a major health and social concern. It is associated with higher morbidity and mortality for both the mother and child. In addition to the physiological risks, there is a negative effect on the socio-economic status of the mother and hence the child in many ways.

As shown in Table 3.4, only three percent of teenage women aged 15 years had had a live birth in the last five years with the percentages increasing with increasing age. Forty eight percent of 19 year old women had had a live birth during the same period. Teenage motherhood varied by District with Ntoroko District having the highest percentage of teenage motherhood (25%) followed by Butaleja (23%). Teenage motherhood was lowest in Kaabong District (5%).

Table 0.4: Percentage of women age 15-19 who have had a live birth in the five years preceding the survey by age and district (%)

Given birth to any Characteristic Number children at age 15-19 Age (Years)

15 2.9 6 16 5.8 18 17 12.4 25 18 27.1 70 19 47.5 93 District

Butaleja 23.2 20 21

Baseline Survey for KOICA Program in Uganda 2016

Abim 13.8 13 Amudat 19.3 13 Kaabong 4.6 6 Kotido 6.9 4 Moroto 10.9 7 Nakapiripirit 12.1 12 Napak 18.2 19 Agago 19.8 24 Pader 20.4 36 Kitgum 16.4 25 Ntoroko 25.1 33 Karamoja Sub region 11.8 74

1.2.5 Children born after 2011

Women aged 15-49 years who had ever given birth were further asked whether they had Births in the last 5 years. Table 3.5 presents the distribution of women by whether they had any children born after 2011. Overall, three quarters of women (76%) had given birth to children after 2011. The highest percentage of women who had given birth to children after 2011 was in Kotido (90%) and lowest in Kitgum (69%).

Table 0.5: Distribution of women age 15-49 years by whether they had a child born after 2011 by district (%)

Had a child born after 2011

District Yes No Total Number

Butaleja 73.9 26.1 100 379 Abim 81.4 18.6 100 377 Amudat 83.5 16.5 100 303 Kaabong 69.5 30.5 100 349 Kotido 90.0 10.0 100 322 Moroto 78.6 21.4 100 351 Nakapiripirit 82.0 18.0 100 360 Napak 79.5 20.5 100 379 Agago 73.7 26.3 100 376 Pader 73.3 26.7 100 403 Kitgum 69.0 31.0 100 444 Ntoroko 70.1 29.9 100 437

All 75.8 24.2 100 4,480 Karamoja Sub region 80.1 19.9 100 2,441

Baseline Survey for KOICA Program in Uganda 2016

1.3 Antenatal Care (ANC) ANC provides an important entry point for women to the health care system. Research has shown that, women who get ANC are more likely to have a skilled birth attendant present during childbirth, and skilled birth attendance is the intervention with the greatest impact in preventing maternal and neonatal mortality. The major objective of antenatal care is to ensure optimal health outcomes for the mother and her baby. Antenatal care from a trained provider is important to monitor the pregnancy and reduce morbidity risks for the mother and child during pregnancy and delivery. Antenatal care provided by a skilled health worker enables (1) early detection of complications and prompt treatment (e.g., detection and treatment of sexually transmitted infections including HIV and syphilis), (2) prevention of diseases through immunization and micronutrient supplementation, (3) birth preparedness and complication readiness, and (4) health promotion and disease prevention through health messages and counselling for pregnant women and their partners.

1.3.1 Provider of Antenatal care

Table 3.6 shows the percent distribution of women age 15-49 years who had a live birth in the five years preceding the survey by antenatal care provider during pregnancy for the most recent birth by District. The results show that overall, 95 percent of women received antenatal care from a Nurse/Midwife with only four percent receiving antenatal care from a Medical Doctor. A very negligible percentage of mothers received antenatal care from traditional birth attendants or village health workers. Across all the Districts, Nurse/Midwife was the major provider of antenatal care with percentages ranging from 84 percent in Amudat to 97 percent each in Nakapiripirit, Napak, Pader and Kitgum districts.

Table 0.6: Distribution of women age 15-49 years who had a live birth in the five years preceding the survey by category of antenatal care (ANC) provider during pregnancy for the most recent birth by district (%)

Provider of ANC Traditional Village Medical Nurse/ birth health District None doctor midwife attendant worker Other Total Number Butaleja 1.7 1.8 96.3 0.0 0.0 0.3 100 291 Abim 0.0 3.7 96.3 0.0 0.0 0.0 100 323 Amudat 7.7 7.7 84.1 0.0 0.5 0.0 100 263 Kaabong 0.0 4.1 95.4 0.5 0.0 0.0 100 271 Kotido 0.0 11.9 87.8 0.0 0.0 0.2 100 285 Moroto 1.5 6.6 91.6 0.0 0.0 0.3 100 290 Nakapiripirit 1.3 1.7 96.7 0.0 0.0 0.4 100 304 Napak 1.1 2.1 96.8 0.0 0.0 0.0 100 299 23

Baseline Survey for KOICA Program in Uganda 2016

Agago 0.7 2.1 96.2 0.0 1.0 0.0 100 284 Pader 0.3 2.4 97.0 0.3 0.0 0.0 100 311 Kitgum 0.0 1.7 97.4 0.6 0.3 0.0 100 310 Ntoroko 1.9 5.2 91.6 0.7 0.4 0.2 100 308 All 1.0 3.7 94.8 0.2 0.2 0.1 100 3,539 Karamoja Sub region 1.3 5.3 93.2 0.1 0.0 0.1 100 2,035

1.3.2 Number of Antenatal Care visits

Antenatal care is more beneficial in preventing adverse outcomes when it is sought early in the pregnancy and is continued through to delivery. The World Health Organization (WHO) recommends that a woman without complications has at least four antenatal care visits, the first of which should take place during the first trimester (the first 13 weeks of pregnancy). Table 3.7 presents information on the number of antenatal care visits women aged 15-49 years who had a live birth in the last five years preceding the survey made during their most recent pregnancy. Almost half of the women (47%) made the recommended four antenatal care visits during the most recent pregnancy while a third (32%) made two to three antenatal care visits. About two in every ten women (18%) made five or more antenatal care visits during pregnancy. The highest percentage of women who made four antenatal care visits was in Agago district (64%) while the lowest was in Kaabong (20%). However, the highest percentage of women who made five antenatal care visits was in Kaabong district (36%).

Table 0.7: Distribution of women age 15-49 years who had a live birth in the five years preceding the survey by number of times of antenatal care visits by district (%)

Number of times of ANC visits District None Once 2-3 times 4 times 5+ times Total Number Butaleja 1.7 2.3 38.5 38.6 19.0 100 290 Kitgum 0.0 0.0 27.1 63.0 9.8 100 311 Kotido 0.0 0.5 20.7 53.0 25.8 100 284 Moroto 1.6 0.6 31.3 41.3 25.2 100 288 Nakapiripirit 1.3 0.9 40.2 32.7 24.9 100 299 Pader 0.3 0.3 31.2 62.1 6.1 100 310 Abim 0.0 0.3 34.8 48.4 16.6 100 328 Kaabong 0.0 11.5 32.0 20.3 36.3 100 244 Agago 0.7 1.8 26.5 64.1 7.0 100 284 Amudat 7.7 6.4 41.6 33.0 11.3 100 262 Napak 1.5 1.6 29.2 36.9 30.8 100 286 Ntoroko 2.0 4.5 49.4 29.9 14.2 100 296 All 1.1 2.1 32.2 46.8 17.8 100 3,482 Karamoja Sub region 1.3 2.9 32.1 38.4 25.3 100 1,991 24

Baseline Survey for KOICA Program in Uganda 2016

1.3.3 Timing of Antenatal Care visits

The WHO approach to promoting safe pregnancies recommends at least four ANC visits for women without complications. This approach, called focused antenatal care, emphasizes quality of care during each visit instead of focusing on the number of visits. The recommended schedule of visits is as follows: the first visit should occur by the end of 16 weeks of pregnancy, the second visit should be between 24 and 28 weeks of pregnancy, the third visit should occur at 32 weeks, and the fourth visit should occur at 36 weeks. Women with complications, special needs, or conditions beyond the scope of basic care may require additional visits. Early detection of problems during pregnancy leads to more timely treatment and referrals in the case of complications.

Table 3.8 presents the distribution of women age 15-49 years who had a live birth in the last five years preceding the survey by the timing of the first antenatal care. The results show that 44 percent of the women who had a live birth after 2011 made their first antenatal care visit in the first trimester (<4 months pregnant) with the highest percentage of women in Kotido (68%) and lowest in Amudat (21%). Overall, one in every ten women (9%) made their first antenatal care visit in the 6-7 month of pregnancy.

Table 0.8: Distribution of women age 15-49 years who had a live birth in the five years preceding the survey by timing of the first ANC and district (%)

Number of months pregnant at time of first ANC visit 4-5 6-7 Not District <4 months months months 8+ months stated Total Number Butaleja 28.7 43.4 25.2 1.1 1.7 100 291 Abim 44.2 50.2 5.3 0.3 0.0 100 323 Amudat 21.0 56.7 13.7 0.7 7.9 100 263 Kaabong 41.4 49.6 4.1 0.5 4.3 100 271 Kotido 67.8 31.1 0.8 0.0 0.2 100 285 Moroto 53.3 39.0 5.1 0.7 2.0 100 290 Nakapiripirit 59.2 33.3 4.9 0.0 2.5 100 304 Napak 52.3 41.2 2.6 0.2 3.7 100 299 Agago 36.3 50.5 12.2 0.4 0.7 100 284 Pader 44.9 48.6 5.9 0.4 0.3 100 311 Kitgum 44.6 48.8 5.9 0.7 0.0 100 310 Ntoroko 33.7 47.3 15.6 0.1 3.4 100 308 All 43.9 44.9 9.0 0.5 1.8 100 3,539 Karamoja Sub region 50.5 42.0 4.6 0.3 2.7 100 2,035

Baseline Survey for KOICA Program in Uganda 2016

1.3.4 Intermittent Preventive Treatment of Malaria in Pregnancy

Although malaria in pregnant women may not manifest itself as either feverish illness or severe disease, it is frequently the cause of mild to severe anemia. In addition, malaria during pregnancy can interfere with the maternal-fetal exchange that occurs at the placenta, leading to the delivery of low birth weight infants. In Uganda, Malaria in Pregnancy policy and guidelines require that pregnant women receive intermittent preventive treatment for malaria in pregnancy (IPTp). Specifically, IPTp is preventive treatment with the antimalarial combination drug SP/Fansidar given once at the beginning of the second trimester of pregnancy and once at the beginning of the third trimester. It is preferable that women receive IPTp during routine antenatal care. Pregnant women who take medicine only to treat an existing case of malaria are not considered to have received IPTp.

During the survey, women who had a live birth after 2011 (i.e. last 5 years preceding the survey) were asked whether they took Fansidar (SP) antimalarial medications for prophylaxis during the pregnancy leading to their most recent birth. Those who did were further asked the source of the SP. It should be noted that obtaining information about drugs can be difficult because some respondents did not know or remember the name of the type of drug that they received. Results in Table 3.9 show that, 87 percent of women who had a live birth after 2011 took SP Fansidar for malaria prophylaxis during the most recent pregnancy. The percentage of women who took SP Fansidar was highest in Kotido (99%) and lowest in Butaleja (73%). For the majority of women across all the districts, the source of SP Fansidar was antenatal visit from a health facility.

Table 0.9: Distribution of women age 15-49 years who had a live birth in the five years preceding the survey who received any SP Fansidar during the pregnancy leading to their most recent birthby source of SP Fansidar by district (%)

Took SP Source of SP Fansidar Fansidar Other while Antenatal facility Other District pregnant Number Visit visit source Total Number Butaleja 73.3 293 90.2 8.1 1.7 100 210 Abim 95.7 325 99.7 0.3 0.0 100 314 Amudat 84.9 262 97.2 2.8 0.0 100 220 Kaabong 95.4 271 100.0 0.0 0.0 100 257 Kotido 99.4 286 97.9 2.1 0.0 100 281 Moroto 93.9 290 99.7 0.3 0.0 100 272 Nakapiripirit 94.2 304 100.0 0.0 0.0 100 283 Napak 90.9 302 100.0 0.0 0.0 100 273 Agago 85.0 289 98.9 0.8 0.4 100 235 Pader 82.3 314 99.2 0.8 0.0 100 253 Kitgum 83.1 311 100.0 0.0 0.0 100 259 26

Baseline Survey for KOICA Program in Uganda 2016

Ntoroko 73.7 309 96.4 2.2 1.4 100 233 All 86.9 3556 98.2 1.5 0.3 100 3,090 Karamoja Sub-region 94.1 2040 99.3 0.7 0.0 100 1,900

1.3.5 Number of doses of SP Fansidar taken

It is recommended that pregnant women receive at least two doses of SP Fansidar to prevent malaria during pregnancy. Respondents who reported that they had taken SP Fansidar were also asked the number of doses they took during their most recent pregnancy. The results in Table 3.10 indicate that overall, approximately four in every ten women(39%) who had their most recent birth after 2011 took two doses of SP Fansidar during their most recent pregnancy. Variations by district range from 26 % in Napak to 58 % in Kotido.

Table 0.10: Distribution of women age 15-49 years who had a live birth in the five years preceding the survey who received SP Fansidar by number of times taken during the most recent pregnancy and District (%)

Number of doses More than 2 District One dose Two doses doses Total Number Butaleja 24.6 33.1 42.3 100 211 Abim 18.6 51.6 29.7 100 312 Amudat 25.0 36.5 38.5 100 223 Kaabong 24.0 36.9 39.1 100 256 Kotido 13.4 57.9 28.6 100 283 Moroto 18.1 56.9 25.1 100 273 Nakapiripirit 32.1 34.4 33.5 100 284 Napak 31.5 25.7 42.8 100 276 Agago 26.4 29.7 43.8 100 239 Pader 23.6 41.4 35.0 100 256 Kitgum 27.6 36.0 36.3 100 259 Ntoroko 34.4 41.0 24.6 100 233 All 24.6 39.4 36.0 100 3,105 Karamoja 23.1 43.2 33.7 100 1,907

Baseline Survey for KOICA Program in Uganda 2016

1.3.6 Attitudes towards Antenatal care

To gauge attitudes toward antenatal care, respondents were asked questions about willingness to visit a health facility for antenatal care, whether a pregnant woman should seek for antenatal care before 16 weeks of pregnancy, whether the husband and mother-in-law consider antenatal care to be important for all pregnant women and whether they would discourage attendance of antenatal care.

The results in Table 3.11show that overall, among women age 15-49 years who had their last live birth in the last five years preceding the survey, willingness to visit a health facility for antenatal care was nearly universal across all the districts. Three quarters of the women (74%) were aware that women should seek antenatal care before 16 weeks of pregnancy. However the level of awareness varied widely by District with a higher percentage of awareness among women in Kitgum (90%) compared to other districts. Seventy eight percent of all the women surveyed in the focus districts reported that their husbands consider ANC to be important for all pregnant women. Amudat district had the highest percentage of women who reported that their husbands consider ANC to be important for all pregnant women (92%) while the lowest was in Moroto (63%). Overall, only four percent of women reported that their husbands would discourage them from attending ANC. Two thirds of the women in the target districts (67%) reported that their mothers-in-law consider ANC to be important for all pregnant women. Amudat district had the highest percentage of women who reported that their mothers-in-law consider ANC to be important for all pregnant women (93%) and lowest in Moroto (46%).

Table 0.11: Percentage of women age 15-49 years who had their last live birth in the last five years preceding the survey who reported “Yes” to selected attitudinal questions by district

Aware that Mother-in- pregnant Husband law women considers Husband considers Mother-in- should ANC to be would ANC to be law would Willing to seek ANC important discourage important discourage visit health before 16 for all from for all from facility for weeks of pregnant attending pregnant attending District ANC pregnancy women ANC women ANC Butaleja 97.4 61.9 82.0 6.5 64.2 4.0 Abim 99.0 83.3 75.7 1.1 72.3 0.4 Amudat 100.0 54.8 92.3 1.8 92.5 0.5 Kaabong 99.8 70.7 84.8 1.8 73.5 0.4 Kotido 99.0 86.8 81.2 1.2 57.5 0.6 Moroto 97.1 74.2 63.1 2.1 46.1 0.3 Nakapiripirit 99.4 69.4 88.8 1.2 84.1 2.7 Napak 98.8 62.3 73.7 1.0 59.6 1.5 Agago 99.7 81.4 85.3 7.0 80.7 4.8

Baseline Survey for KOICA Program in Uganda 2016

Pader 94.4 56.9 76.8 6.2 59.2 2.6 Kitgum 98.9 89.7 71.8 7.5 57.1 1.9 Ntoroko 96.5 85.6 69.1 2.7 59.3 2.4 All 98.5 74.0 78.3 3.5 67.2 2.0 Karamoja Sub-region 98.9 71.1 81.0 2.8 68.7 1.4

1.4 Delivery Labour and delivery is the shortest and most critical period of the pregnancy-childbirth continuum because most maternal and newborn deaths arise from complications during delivery. Even with the best possible antenatal care, any delivery can become a complicated one and therefore skilled assistance is essential to safe delivery care. For numerous reasons many women do not seek skilled care even when they understand the safety reasons for doing so.

1.4.1 Place of delivery

Increasing the proportion of women who deliver in health facilities is an important factor in reducing health risks to the mother and the newborn. Proper medical attention and hygienic conditions during delivery can reduce the risks of complications and infections that can cause morbidity and mortality to either the mother or the infant. Respondents were asked to mention the place of birth for all their children born after the year 2011. Table 3.12 shows the distribution of women who had a live birth after 2011 by place of delivery and district. Overall, four in ten women (40%) delivered at a Health Centre III facility while a quarter (25%) delivered at hospitals. There were wide variations in place of delivery by district. The highest percentage of women who delivered in Hospitals was in Kaabong district (45%) while the lowest was in Amudat (3%). A notable 16 percent of all women delivered at home with the highest percentage of home deliveries in Amudat (33%) followed by Butaleja (25%).

Table 0.12: Distribution of women age 15-49 years who had their last live birth in the last five years preceding the survey by place of delivery and district (%)

Place of Delivery

Health Health Health Center Center Center District Home Hospital IV III II Other Total Number

Butaleja 24.7 19.3 20.1 30.0 3.7 2.3 100 290 Abim 7.5 24.0 2.9 55.3 10.1 0.3 100 321 Amudat 32.6 2.9 18.0 23.5 21.6 1.4 100 259 Kaabong 20.5 44.5 2.2 15.0 16.6 1.2 100 270

Baseline Survey for KOICA Program in Uganda 2016

Kotido 5.2 2.7 17.8 72.6 0.7 1.0 100 281 Moroto 18.9 32.0 1.5 41.7 4.9 1.0 100 284 Nakapiripirit 22.8 4.2 20.1 37.2 13.0 2.7 100 302 Napak 12.4 13.7 3.9 60.6 8.2 1.2 100 296 Agago 7.5 41.7 0.9 36.6 12.8 0.5 100 283 Pader 24.1 19.9 12.6 34.6 5.9 3.0 100 310 Kitgum 7.2 44.2 7.2 39.8 1.3 0.3 100 305 Ntoroko 20.1 16.7 24.0 30.7 1.2 7.3 100 310 All 16.1 24.5 10.4 39.8 7.7 1.6 100 3,511 Karamoja Sub region 16.1 18.1 9.3 45.1 10.1 1.3 100 2,013

1.4.2 Assistance during delivery

Obstetric care from a skilled provider (doctor, nurse, midwife, or physician’s assistant) during delivery is recognized as a critical element in the reduction of maternal and neonatal mortality. Birth occurring at home are usually more likely to be delivered without assistance from a skilled provider, whereas births occurring at a health facility are more likely to be attended to by a trained health professional. Table 3.13 shows the percent distribution of women age 15-49 years who had their last live birth in the last five years preceding the survey by provider of assistance during delivery. Overall, eight in every ten women aged 15-49 years (77%) who had their last live birth in the period after 2011 were assisted during delivery by a nurse or midwife. The highest percentage of women who were assisted by a nurse/midwife was in Abim district (89%) while the lowest percentage was in Amudat district (60%). Overall, a notable one in every ten women (10%) was assisted by a traditional birth attendant (TBA) during her most recent delivery.

Table 0.13: Distribution of women age 15-49 years who had their last live birth in the last five years preceding the survey by provider of assistance during delivery and district (%)

Provider of assistance during delivery

Medical/ Traditional Nurse/ Clinical Birth District Doctor midwife officer Attendant Other No one Total Number Butaleja 3.7 69.6 0.5 12.2 7.5 6.4 100 285 Abim 4.0 88.5 1.0 3.6 1.9 1.1 100 318 Amudat 3.8 60.4 0.7 18.9 14.9 1.3 100 257 Kaabong 1.2 70.4 2.7 10.8 9.1 5.9 100 253 Kotido 2.2 86.5 4.1 3.2 4.0 0.0 100 279 Moroto 5.3 71.6 0.0 12.0 10.6 0.6 100 283 Nakapiripirit 1.5 72.2 0.3 7.9 17.5 0.8 100 298

Baseline Survey for KOICA Program in Uganda 2016

Napak 1.7 83.4 0.4 5.2 8.2 1.1 100 296 Agago 3.3 80.6 4.4 7.4 2.3 2.0 100 283 Pader 6.2 68.1 0.4 21.5 1.5 2.3 100 309 Kitgum 3.1 85.6 1.3 5.3 2.0 2.7 100 299 Ntoroko 8.8 71.4 0.5 13.1 6.2 0.0 100 304 All 3.6 76.5 1.5 9.8 6.3 2.4 100 3,464 Karamoja Sub region 2.7 77.3 1.4 8.0 9.1 1.5 100 1,984 Note: “Others” includes VHT, friends, etc.

1.4.3 Attitudes towards delivery in a health facility

To establish attitudes toward delivery in a health facility, respondents were asked questions about willingness to deliver their next child in a health facility and whether the husband/partner and mother-in-law would be willing to allow the woman deliver in a health facility.

The results in Table 3.14 show that, 97 percent of women were willing to deliver their next child at a health facility. Across the target districts, the percentage of women willing to deliver their next child at a health facility ranges from 94 percent in Ntoroko to 99 percent each in Pader and Kitgum respectively. Eighty nine percent of all the women surveyed reported that their husbands would be willing to allow them deliver their next child at a health facility.Kotido and Agago districts had the highest proportion of women reporting willingness of their husbands to allow them deliver at a health facility (95%) while Kaabong had the lowest (79%). On the willingness of mothers-in-law to allow women deliver their next child at a health facility, overall, 77 percent of women surveyed reported their mothers-in-law would allow them deliver their next child at a health facility with the highest percentage in Kotido (93%) and lowest in Amudat (60%).

Table 0.14: Percentage of women age 15-49 years who had their last live birth in the last five years preceding the survey who reported “Yes” to selected attitudinal questions on delivery at a health facility by district (%)

Willingness of Willingness of mother- Willing to deliver next husband to allow in-law to allow delivery child in a health delivery of next child of next child at a health District facility at a health facility facility

Butaleja 94.8 88.5 69.0 Abim 98.1 88.1 84.3 Amudat 94.7 83.2 60.1 Kaabong 94.3 79.1 63.7 Kotido 98.1 94.8 92.5 Moroto 96.9 88.6 80.6 Nakapiripirit 95.0 87.4 71.5

Baseline Survey for KOICA Program in Uganda 2016

Napak 95.6 90.2 75.1 Agago 96.6 95.4 89.9 Pader 98.5 87.2 68.1 Kitgum 99.0 90.3 86.6 Ntoroko 93.8 84.9 73.5 All 96.5 88.7 77.2 Karamoja Sub region 96.2 87.5 76.3

1.5 Postnatal Care for Mothers Postnatal check-ups have traditionally been overlooked by both women and health care providers, but these check-ups also present an important opportunity to prevent or promptly treat morbidity and to provide family planning services. Skilled care for mothers is critical in the days after they give birth. Up to 45 percent of all maternal deaths occur within one day of delivery, and 65 percent occur within the first week. This period is also critical to newborn survival because 50 to 70 percent of life-threatening newborn illnesses occur within the first week of life (AED, the Man off Group, and USAID, 2005). A postnatal check-up within the first week of delivery is therefore an important strategy for ensuring optimal maternal and newborn health.

1.5.1 Timing of first postnatal check-up

A large proportion of maternal and neonatal deaths occur during the first 48 hours after delivery. Thus, prompt postnatal care for both the mother and the child is important to treat any complications arising from the delivery, as well as to provide the mother with important information on how to care for herself and her child. Safe motherhood programs recommend that all women receive a check of their health within two days after delivery. Women who deliver at home should go to a health facility for postnatal care services within 24 hours, and subsequent visits (including those by women who deliver in a health facility) should be made at three days, seven days, and six weeks after delivery. It is also recommended that women who deliver in a health facility should be kept for at least 48 hours (up to 72 hours depending on the capacity of the institution) so the mothers and infants may be monitored by skilled personnel.

Information was collected from women aged 15-49 years whose last live birth was in the last five years preceding the survey on how long after delivery the first postnatal checok took place. The results on timing of the first postnatal check-up are presented in Table3.15. Overall, 55 percent of women aged 15-49 years whose last live birth was in the last five years preceding the survey received the first postnatal check-up within less than 7 hours while 35 percent did not receive any postnatal care. There were variations across the districts with the highest 32

Baseline Survey for KOICA Program in Uganda 2016 percentage of mothers who received the first postnatal care within less than 7 hours in Kotido (83%) while the lowest percentage was in Kaabong (32%). Overall, about 1 in every 3 mothers (36%) did not receive postnatal care. The highest percentage of mothers who did not receive postnatal care was in Butaleja (49%) and the lowest was in Kotido (15%).

Table 0.15: Distribution of the mother’s first postnatal check-up for the last live birth in the last five years preceding the survey by time after delivery and district (%)

Received Postnatal care No Less than 7 - 23 postnatal 1 - 2 days 7 hours hours District care Total Number Butaleja 48.9 47.3 1.5 2.3 100 184 Abim 24.3 69.7 2.7 3.4 100 298 Amudat 28.2 67.9 2.3 1.5 100 164 Kaabong 40.0 32.2 6.7 21.1 100 266 Kotido 15.1 83.2 0.8 0.9 100 218 Moroto 30.2 64.7 5.1 0.0 100 235 Nakapiripirit 27.8 68.5 2.8 0.9 100 238 Napak 25.0 73.3 0.7 0.9 100 305 Agago 35.2 50.3 7.8 6.7 100 278 Pader 41.2 49.2 7.7 1.9 100 261 Kitgum 45.1 42.8 7.2 4.8 100 299 Ntoroko 46.3 44.8 5.7 3.3 100 270 All 35.4 55.2 4.8 4.7 100 3,016 Karamoja Sub region 27.8 63.9 3.2 5.2 100 1,724

1.5.2 Timing of first postnatal check-up for the newborn

The timing of the postnatal checkup for the newborns is as equally important as receiving the actual check. Similar to the mothers it is also recommended that the check is done within two days after birth. The survey collected information from mothers aged 15-49 years whose last live birth was in the last five years preceding the survey and who delivered in health facilities on how long after delivery the first postnatal check-up on the newborn took place and the results are presented in Table 3.16. Overall,69 percent of the newborns received a postnatal check-up within less than 7 hours after delivery. Two in every ten newborns (28%) did not receive any postnatal checkup. There were wide variations in the percentages by district. The highest percentage of newborns who received postnatal checkup within less than 7 hours was in Kotido (96%) while the lowest was in Kaabong and Ntoroko (48% each respectively). Overall, one in every four newborns (24%) did not receive any postnatal check-ups. The highest percentage of newborns who did not receive any postnatal checks was in Butaleja (47%). 33

Baseline Survey for KOICA Program in Uganda 2016

Table 0.16: Distribution of last live births delivered in health facilities in the last five years preceding the survey by timing of first postnatal check-up after delivery by District (%)

Timing of first Postnatal check

No health Less than 7 7 – 23 District check hours hours 1 - 2 days Total Number Butaleja 47.0 49.5 1.8 1.6 100 292 Abim 7.8 86.8 3.4 2.1 100 329 Amudat 44.5 54.3 0.4 0.7 100 262 Kaabong 24.6 49.7 5.4 20.3 100 259 Kotido 3.7 96.0 0.1 0.3 100 286 Moroto 18.6 77.3 4.1 0.0 100 290 Nakapiripirit 26.4 72.8 0.9 0.0 100 303 Napak 14.3 84.2 0.9 0.6 100 300 Agago 14.3 69.3 9.7 6.7 100 287 Pader 32.7 60.2 5.3 1.7 100 311 Kitgum 14.5 78.6 5.8 1.1 100 311 Ntoroko 44.3 48.5 4.2 3.0 100 306 All 23.7 69.1 3.9 3.3 100 3,536 Karamoja Sub region 18.3 75.8 2.2 3.7 100 2,029

1.6 Breastfeeding Breast milk contains all of the nutrients needed by children in the first six months of life and is an uncontaminated nutritional source. Biologically, breastfeeding suppresses the mother’s return to fertile status and affects the length of the birth interval as well as the level of fertility.

1.6.1 Initiation of Breastfeeding

Early initiation of breastfeeding is encouraged for a number of reasons. Mothers benefit from early suckling because it stimulates breast milk production and facilitates the release of oxytocin, which helps the contraction of the uterus and reduces post-partum blood loss. The first breast milk contains colostrum, which is highly nutritious and has antibodies that protect the newborn from diseases. Early initiation of breastfeeding also fosters bonding between mother and child. The World Health Organization recommends that healthy newborns be placed on their mothers’ bare chest immediately after birth, to keep the baby warm ( prevent hypothermia), facilitate breastfeeding and encourage bonding.

Baseline Survey for KOICA Program in Uganda 2016

Table 3.17presents the distribution of last born children in the last five years preceding the survey by initial breastfeeding and district. More than three quarters of the children (77%) had their initial breastfeeding within one hour of delivery, and only eight percent had their initial breastfeeding more than four hours after delivery. Napak and Moroto districts had the highest percentage of children whose initial breastfeeding was within the first one hour (92% each) while Pader and Agago had the least percentage (59% each respectively). Table 0.17: Distribution of lastborn children in the last five years preceding the survey by timing of initial breastfeeding and district (%)

Initiation of breastfeeding More Did not Within 1 2 to 4 than 4 District breastfeed hour hours hours Total Number

Butaleja 2.3 75.8 11.6 10.3 100 288 Abim 0.8 88.4 5.2 5.6 100 321 Amudat 1.7 73.5 21.6 3.1 100 252 Kaabong 1.6 89.9 4.5 4.1 100 259 Kotido 0.1 86.2 7.5 6.2 100 277 Moroto 0.3 92.4 4.1 3.1 100 285 Nakapiripirit 0.2 82.7 14.2 2.9 100 300 Napak 1.0 92.4 3.0 3.6 100 287 Agago 0.5 59.2 23.5 16.8 100 282 Pader 0.7 58.7 28.2 12.4 100 307 Kitgum 1.0 69.7 22.3 7.0 100 304 Ntoroko 1.8 88.1 6.1 4.0 100 304 All 1.0 77.2 14.1 7.8 100 3,466 Karamoja Sub region 0.8 87.2 7.9 4.2 100 1,981

1.6.2 Feeding children using a bottle with a nipple

Feeding children using a bottle with a nipple is discouraged among very young children, because it contributes to an increased risk of gastrointestinal infections. Women who had had their last birth the last five years preceding the survey were asked whether the last child was given anything to drink from a bottle with a nipple during the day or night preceding the survey. The findings presented in Table 3.18indicate that, overall; eight percent of the children aged under five years were fed from bottles with nipples during the day or night preceding the survey. Considering specifically the children aged less than six months, the findings show that seven percent had been given something to drink from a bottle with a nipple during the day or night preceding the survey.

Baseline Survey for KOICA Program in Uganda 2016

Table 0.18: Distribution of last births in the last five years preceding the survey by whether they were fed from bottles with nipples during the day or night preceding the survey (%)

Fed using bottle with nipple

Age of child (Months) Yes No Total Number

Less than 6 months 6.4 93.6 100 488 6 - 24 months 11.1 88.9 100 1,327 25+ months 4.6 95.4 100 1,483 All 7.5 92.5 100 3,298

1.6.3 Diarrhoeal Diseases

Dehydration caused by severe diarrhoea is a major cause of morbidity and mortality among young children in Uganda, although the condition can be easily treated with oral rehydration therapy (ORT). Exposure to diarrhoea-causing agents is frequently related to the use of contaminated water and unhygienic practices in food preparation and disposal of excreta. In the survey, mothers were asked whether any of their children under five years of age had had diarrhoea during the two weeks preceding the survey. Prevalence of diorrhoea is affected by the mother’s perception of diarrhoea as an illness and her capacity to recall the events. In interpreting the findings, it should be borne in mind that prevalence of diarrhoea varies seasonally and peaks at the end of the rainy season which coincided with the beginning of the survey. Table 3.19shows that, overall, a third of the last births in the last five years preceding the survey (35%) had suffered from diarrhea in the two weeks preceding the survey. There were variations by district with Kotido district having the highest percentage of children who suffered from diarrhea in the last two weeks preceding the survey (65%) while Ntoroko had the lowest percentage (17%).

Table 0.19: Distribution of last births in the last five years preceding the survey by whether they had diarrhea in the last 2 weeks preceding the survey (%)

Had diarrhea in last 2 weeks District Total Number Yes No Don’t know

Butaleja 38.0 62.0 0.0 100 279 Abim 28.3 70.6 1.0 100 315 Amudat 25.9 73.8 0.3 100 260 Kaabong 32.1 67.9 0.0 100 236 Kotido 65.3 34.7 0.0 100 282 Moroto 35.0 65.0 0.0 100 280 Nakapiripirit 36.2 63.8 0.0 100 297 Napak 23.5 76.5 0.0 100 283 36

Baseline Survey for KOICA Program in Uganda 2016

Agago 38.3 61.7 0.0 100 281 Pader 33.0 65.9 1.0 100 304 Kitgum 31.4 68.4 0.2 100 305 Ntoroko 16.6 82.8 0.6 100 307 All 35.0 64.7 0.2 100 3,429 Karamoja Sub region 36.4 63.4 0.2 100 1,953

1.6.4 Treatment of Diarrhea

Oral rehydration therapy (ORT), which involves giving children with diarrhea a solution prepared from oral rehydration salts (ORS) is a simple and effective remedy for the dehydration caused by diarrhea. Mothers who had children born in the last five years preceding the survey that had fallen ill with diarrhea in the last two weeks preceding the survey were asked whether the child was given ORS. Table 3.20 shows the distribution of the last born children who had diarrhea in the last two weeks preceding the survey by whether they drank ORS. Overall, one in every five children who suffered from diarrhea in the last two weeks preceding the survey (21%) drank ORS the day preceding the survey. The highest percentage who drank ORS was in Kotido, Moroto and Nakapiripirit (35% each respectively) while the lowest was in Butaleja (6%). Mothers of children who had diarrhea in the last two weeks preceding the survey were further asked whether their children drank or ate vitamin or mineral supplements or any medicines the day preceding the survey. The results show that overall, 30 percent of children had drank or eaten vitamin or mineral supplements or any medicines the day preceding the survey.

Table 0.20: Distribution of most recent children born after 2011 who had diarrhea in the last two weeks preceding the survey by whether they drank ORS drank/ate vitamin or mineral supplements or any medicines the day preceding the survey by district (%).

Drank or ate vitamin or mineral supplements or Drank ORS any medicines

District Yes No Total Number Yes No Total Number

Butaleja 6.3 93.7 100 108 45.1 54.9 100 106 Abim 23.3 76.7 100 89 23.1 76.9 100 90 Amudat 14.1 85.9 100 65 27.6 72.4 100 65 Kaabong 24.1 75.9 100 83 2.4 97.6 100 83 Kotido 35.4 64.6 100 173 32.3 67.7 100 172 Moroto 34.7 65.3 100 99 34.7 65.3 100 99 Nakapiripirit 34.8 65.2 100 111 46.6 53.4 100 111

Baseline Survey for KOICA Program in Uganda 2016

Napak 23.6 76.4 100 63 28.3 71.7 100 62 Agago 18.4 81.6 100 107 23.9 76.1 100 107 Pader 9.3 90.7 100 108 18.7 81.3 100 108 Kitgum 9.6 90.4 100 91 28.8 71.2 100 91 Ntoroko 24.1 75.9 100 50 30.8 69.2 100 49 All 20.6 79.4 100 1,147 30.0 70.0 100 1,143 Karamoja Sub region 29.9 70.1 100 683 29.8 70.2 100 682

Baseline Survey for KOICA Program in Uganda 2016

CHAPTER FOUR

HEALTH FACILITY

1.7 Introduction

The Health sector of Uganda through the Ministry of Health (MoH) aims at the delivery of curative, preventive, promotive, palliative and rehabilitative services to the people of Uganda in accordance with the Health Sector Strategic Plan (HSSP). According to the HSSP III (2010/11-2014/15), the health services are structured into National Referral (NRHs) and Regional Referral Hospitals (RRHs), general hospitals, Health Centre IV, III and IIs. The Health Centre I have no physical structure but a team of people (Village Health Teams (VHT)) who work as a link between Health Facilities and the community.

The Baseline Survey for KOICA program in Uganda survey covered all health facilities in the selected districts and solicited information on the health facility workforce, training in signal functions, functional Village Health Teams, health infrastructure, essential drugs and equipment among others.

1.8 General information about health facilities

Table 4.1 summaries the number of health facilities by location, level and type of health facility which refers to the managing authority as well as the average number of persons that had attended the outpatient department in a month. Majority of the health facilities surveyed were found in the rural areas compared to the urban areas. Pader district had the highest number of health facilities (19) in the rural areas, followed by Butaleja with 16, Kaabong and Nakapirpirit had 13 respectively and similarly Kotido and Napak districts each had 10, while Abim, Amudat and Kotido had 8 and 6 respectively. Ntoroko had the least number of health facilities in the rural areas (1). The highest number of health facilities surveyed in the urban areas was 6 and these were found in Ntoroko district.

Further disaggregation by the type of facility (managing authority) shows that, regardless of district, majority of the health facilities surveyed were managed by the Government (135/156). Of those health facilities, 23 were found in Pader district, 20 in Butaleja district, 14 in Kitgum, 13 were found in Kaabong, 12 in Nakapiripirit, 11 of the health facilities were found in Agago while less than 10 of the health facilities were found in Kotido (9), Napak (9), Abim (7), Amudat (6), Ntoroko (6), and Moroto (5). Variations can be seen when the information is further analysed by level of health facility. The highest number of HC III surveyed were found in the districts of Butaleja (11) and Kotido (8), while Ntoroko (4) and Amudat (2) had the least. 39

Baseline Survey for KOICA Program in Uganda 2016

Table 0.1: Number of Health facilities by Residence, Level of HF and type of facility

Residence Facility Type Level Government/ Urban Rural Private Hospital HC IV HC III HC II District Public Butaleja 4 16 20 2 1 0 10 9 Abim 1 8 7 2 1 0 0 6 Amudat 1 6 6 1 0 0 2 4 Kaabong 2 13 13 2 1 1 4 7 Kotido 2 10 9 3 0 1 6 2 Moroto 2 6 5 4 1 0 2 2

Nakapiripirit 1 13 12 2 0 2 5 5

Napak 1 10 9 2 0 0 5 4 Agago 0 11 11 0 0 0 5 6 Pader 2 19 23 1 0 1 7 15 Kitgum 4 9 14 1 0 0 6 8 Ntoroko 6 1 6 1 0 0 4 2 All 26 122 135 21 4 5 56 70

Karamoja Sub-region 10 66 61 16 3 4 24 30

1.9 Work force Availability

According to the 2nd National Health Policy (2010 – 2020), the Ugandan health system suffers from dual management. Urban facilities and tertiary hospitals are managed centrally by the Ministry of Health, while district hospitals and health centers II, III, and IV are managed by district governments. However, many districts lack the financial and human resources for effective management of the health system. This means that health centers are not always fully operational, sometimes lacking necessary equipment or funds to install and pay for utilities like water and electricity or for housing for health workers.

The survey sought to determine the staffing situation at the health facilities. Table 4.2 shows the average number of staff by cadre, health centre and district. Disaggregation by the level of health facility indicated that in the Hospitals for the districts of Butaleja (127), Abim (48), Napak (47), Moroto (46), Kaabong (12), Nakapiripirit (7) and, the highest number of staff reported on average were other staff in the hospital, while the majority of the medical personnel were nursing assistants with Butaleja reporting the highest number on average (50) while Nakapiripirit reported only one nursing assistant. The rest of the districts did not report having any nursing assistants.

Baseline Survey for KOICA Program in Uganda 2016

Considering the enrolled nurses, Moroto, Abim and Kaabong districts reported the highest number of enrolled nurses (22, 21, and 20 respectively) while Nakapiripirit reported only one on average. On average, Moroto district reported the highest number of registered nurses (18) as well as registered midwives (9) and medical doctors (5), Napak had the most enrolled midwives on average (12) and medical doctors (5). Only Napak and Moroto districts reported having an average of 2 and 1 Gynecologist at the hospital level respectively. Nakapiripirit generally reported the least number of staff across all the categories at the hospital level.

Table 0.2: Number of staff by cadre, level and district

District Butalej Abi Amuda Kaabon Kotid Morot Nakapiripir Napa Agag Pade Ntorok Kitgum a m t g o o it k o r o Hospital Anesthetic 0 2 - 1 - 2 ------provider Assistant nurse 50 15 - 14 - 19 ------Clinical officer 7 7 - 4 - 10 ------Enrolled midwife 10 6 - 10 - 6 ------Enrolled nurse 12 21 - 20 - 22 ------Interns 20 0 - 1 - 0 ------Medical officers 2 0 - 1 - 5 ------Registered 3 5 - 6 - 9 ------Midwife Registered Nurse 3 9 - 9 - 18 ------Specialist 0 0 - 0 - 1 ------(Obs/G) Other 127 48 - 12 - 46 ------HCIV Anesthetic - - - 1 1 1 - - 1 - - provider Assistant nurse - - - 6 6 5 - - 5 - - Clinical officer - - - 1 7 5 - - 4 - - Enrolled midwife - - - 2 2 4 - - 1 - - Enrolled nurse - - - 4 7 10 - - 6 - - Interns - - - 1 2 2 - - 1 - - Medical officers - - - 1 1 3 - - 1 - - Registered - - - 1 2 1 - - 3 - - Midwife Registered Nurse - - - 7 4 6 - - 1 - - Specialist - - - 0 0 0 - - 0 - - (Obs/G) Other - - - 11 25 35 - - 17 - - HCIII Anesthetic 0 - 0 0 0 0 0 0 0 0 0 0 provider Assistant nurse 15 - 0 7 10 3 13 16 5 10 11 8 Clinical officer 13 - 0 4 8 1 4 5 10 8 3 0 Enrolled midwife 19 - 2 6 11 4 5 11 12 8 8 0

Baseline Survey for KOICA Program in Uganda 2016

Enrolled nurse 38 - 3 4 11 10 8 9 5 13 13 0 Interns 3 - 0 0 6 1 1 0 5 0 0 0 Medical officers 0 - 0 0 0 0 0 0 0 0 0 0 Registered 0 - 0 0 0 0 0 0 0 0 0 0 Midwife Registered Nurse 0 - 0 0 0 0 0 0 0 0 0 0 Specialist 0 - 0 0 0 0 0 0 0 0 0 0 (Obs/G) Other 56 - 6 24 31 3 16 24 34 39 22 0 HCII Anesthetic 0 0 0 0 0 0 0 0 0 0 0 0 provider Assistant nurse 8 16 4 6 4 1 11 9 6 18 15 2 Clinical officer 0 0 0 0 0 0 0 0 0 0 0 0 Enrolled midwife 5 8 1 5 2 3 0 5 14 12 3 0 Enrolled nurse 17 11 2 5 2 3 2 10 8 25 12 0 Interns 0 0 0 0 0 1 2 2 11 0 0 0 Medical officers 0 0 0 0 0 0 0 0 0 0 0 0 Registered 0 0 0 0 0 0 0 0 0 0 0 0 Midwife Registered Nurse 0 0 0 0 0 0 0 0 0 0 0 0 Specialist 0 0 0 0 0 0 0 0 0 0 0 0 (Obs/G) Other 8 28 2 8 4 5 1 10 11 42 19 0 Private Health Facilities* Anesthetic 0 0 0 0 0 0 0 1 - 0 0 0 provider Assistant nurse 12 4 8 6 10 7 3 31 - 2 3 5 Clinical officer 0 1 1 0 2 1 3 5 - 1 2 0 Enrolled midwife 4 2 0 0 3 4 2 12 - 0 0 0 Enrolled nurse 3 8 1 1 12 8 5 21 - 0 4 0 Interns 0 1 0 0 2 0 1 0 - 0 0 0 Medical officers 1 0 2 0 0 0 0 5 - 0 1 0 Registered 0 0 4 1 1 0 0 2 - 0 0 0 Midwife Registered Nurse 1 2 1 1 1 4 0 7 - 0 0 0 Specialist 0 0 0 0 0 0 0 2 - 0 0 0 (Obs/G) Other 12 25 6 5 28 15 3 53 - 3 13 0 *Private Health facilities include private hospitals and clinics

1.9.1 Staff allocated to Maternity and labor ward including postnatal ward

The survey sought to find out the staffing numbers within the maternity and labor wards as well as the postnatal ward.

Table 4.3a show, that, Butaleja district reported a total of eight enrolled midwives and four assistant nurses allocated to the maternity and labor ward including the postnatal ward in

Baseline Survey for KOICA Program in Uganda 2016 hospitals, At HCIII level there were 15 enrolled midwives, three enrolled nurses and then one clinical officer, assistant nurse, registered midwife and registered nurse each. At HCII there were three assistant nurses, three enrolled midwives and two enrolled nurses allocated to the maternity and labor ward including the postnatal ward.

Kitgum district reported a total of 15 enrolled nurses, 10 assistant nurses, eight enrolled midwives, three registered midwives and three registered nurses, two clinical officers and one anesthetic provider allocated to the maternity and labor ward including the postnatal ward in HCIII.

Kotido district reported a total of three enrolled nurses, two enrolled midwives, registered midwife, and registered nurses each and assistant nurse, clinical officer, Intern, Medical officer each allocated to the maternity and labor ward including the postnatal ward in HCIV. At HCIII level there were 11 enrolled midwives, six assistant nurses, five enrolled nurses and three registered nurses allocated to the maternity and labor ward including the postnatal ward.

Moroto district reported a total of five registered nurses, 4 enrolled midwives and one medical officer and registered midwife each allocated to the maternity and labor ward including the postnatal ward in hospitals.

Nakapiripirit district reported a total of four enrolled midwives and two medical officers at HCIV level while at HCIII level the majority were the enrolled nurses (5) allocated to the maternity and labor ward including the postnatal ward.

Pader district reported a total of three registered midwives and one of all other categories of the staff except registered midwives, assistant nurse and other staff allocated to the maternity and labor ward including the postnatal ward in HCIV while at HCIII level majority were enrolled midwives, enrolled nurses and clinical officers. (8, 8, and 7 respectively).

Abim district reported a mostly enrolled nurses (6) and enrolled midwives (5) allocated to the maternity and labor ward including the postnatal ward in Hospitals.

Kaabong district reported having mostly enrolled midwives across all health centre levels (hospital – 9, HCIV – 2, HCIII – 4.

Agago district reported having mostly enrolled midwives (12), three registered nurses and one registered midwife allocated to the maternity and labor ward including the postnatal ward at HCIII.

Amudat district reported two enrolled midwives allocated to the maternity and labor ward including the postnatal ward at HCIII level.

Napak district reported a mostly enrolled midwives (10) and three registered at HC III.

Baseline Survey for KOICA Program in Uganda 2016

Ntoroko district reported mostly enrolled midwives (8), six registered midwives allocated to the maternity and labor ward including the postnatal ward at HCIV. The HC III reported 11 enrolled nurses and four assistant nurses.

Table 0.3: Number of staff allocated to the maternity and labor ward including the postnatal ward by cadre, level of health facility and district

Districts Butal Abi Amu Kaabo Koti Moro Nakapiri Nap Aga Pad Kitgu Ntoro eja m dat ng do to pirit ak go er m ko Hospital

Anesthetic 0 0 - 1 - 0 ------provider Assistant 4 0 - 0 - 0 ------nurse Clinical officer 0 0 - 0 - 0 ------Enrolled 8 5 - 9 - 4 ------midwife Enrolled nurse 0 6 - 0 - 0 ------Interns 0 0 - 1 - 0 ------Medical 0 1 - 1 - 1 ------officers Registered 0 3 - 4 - 5 ------Midwife Registered 0 0 - 1 - 0 ------Nurse Specialist 0 0 - 0 - 1 ------(Obs/G) Other 14 0 - 0 - 1 ------HCIV

Anesthetic - - - 1 0 - 1 - - 1 - - provider Assistant - - - 1 1 - 0 - - 0 - - nurse Clinical officer - - - 0 1 - 0 - - 1 - - Enrolled - - - 2 2 - 4 - - 1 - - midwife Enrolled nurse - - - 0 3 - 0 - - 1 - - Interns - - - 1 1 - 0 - - 1 - - Medical - - - 1 1 - 2 - - 1 - - officers Registered - - - 1 2 - 1 - - 3 - - Midwife Registered - - - 0 1 - 0 - - 1 - - Nurse Other - - - 0 2 - 1 - - 0 - - HCIII

Anesthetic 0 - 0 0 0 0 0 0 0 0 1 0 provider Assistant 1 - 0 1 6 0 1 1 0 5 10 4 nurse Clinical officer 1 - 0 3 3 1 0 0 0 7 2 0 Enrolled 15 - 2 4 11 3 5 10 12 8 8 0 midwife Enrolled nurse 3 - 0 1 5 0 2 0 0 8 15 11 Medical 0 - 0 0 0 2 0 0 0 0 0 0 officers 44

Baseline Survey for KOICA Program in Uganda 2016

Registered 1 - 0 0 1 4 1 3 3 3 3 0 Midwife Registered 0 - 0 2 3 1 2 0 0 3 3 0 Nurse Other 1 - 0 0 1 0 0 1 1 0 6 16 Private health facility*

Assistant 0 0 1 3 1 0 0 3 - 1 3 0 nurse Clinical officer 0 0 0 0 0 0 2 0 - 1 2 0 Enrolled 4 2 0 0 3 4 2 8 - 0 0 0 midwife Enrolled nurse 0 0 0 1 2 1 0 2 - 0 4 8 Medical 0 0 1 0 0 0 0 1 - 0 1 0 officers Registered 0 0 0 1 0 0 0 2 - 0 0 0 Midwife Registered 0 0 0 1 0 1 0 1 - 0 0 0 Nurse Specialist 0 0 0 0 0 0 0 1 - 0 0 0 (Obs/G) Other 0 0 3 0 1 0 0 2 - 0 0 6 *Private Health facilities include private hospitals and clinics

1.10 Availability and Functionality of Village Health Teams

Ministry of Health has established a network of Village Health Team (VHTs) which is facilitating health promotion, service delivery, community participation and empowerment in access to and utilization of health services. A Village Health Team are people chosen by their own community to promote the health and wellbeing of all village members. The purpose of the VHT is to improve the health of communities and to record information and help HC II plan the health services needed for the community. The survey collected information on the number of VHTs within the catchment area, the number of VHTs trained in the basic package from January to December 2015, the number of VHTs that attended quarterly meeting in the last and previous quarter as well as the number of VHTs that submitted reports for the last and previous quarter.

The findings in Table 4.4 reveal that Butaleja district has the highest number of VHTs (1,332) 1,190 of whom had trained in the VHT basic package in the last twelve months, 756 had attended quarterly meetings while 289 had submitted quarterly reports. The lowest number of VHTs was reported in Amudat district (209); of those, all had trained in the VHT basic package in the last twelve months (209); 87 had attended quarterly meetings while 48 had submitted quarterly reports.

Baseline Survey for KOICA Program in Uganda 2016

Table 0.4: Number of available and Functional (trained, attended and submitted quarterly meeting reports) VHTS by District

Total VHT VHTs number attended submitted of VHTs quarterly quarterly Total trained meetings reports number in basic (last and (last and District of VHTs package (2015) previous) previous) Butaleja 1332 1190 756 289 Abim 384 329 342 342 Amudat 209 209 87 48 Kaabong 531 531 529 531 Kotido 226 248 244 190 Moroto 262 260 262 112 Nakapiripirit 385 384 305 208 Napak 552 531 430 397 Agago 750 392 360 488 Pader 920 607 556 689 Kitgum 757 628 596 354 Ntoroko 391 370 69 66

1.11 Facility infrastructure and designated space

The survey collected information on the infrastructure available at the different health facilities. The respondents at the health facilities were asked if the facility had a room for each of the activities listed in Table 4.5.

Table 4.5 shows that, the hospitals visited in each of the districts reported having at least one operating theatres. Similarly, hospitals reported having a postpartum room with the exception of Butaleja district. Butaleja was the only district that reported having at least one neonatal care unit. In general, the findings reveal that no single hospital in any of the district had all the required infrastructure as a full package.

Table 0.5: Number of Hospitals by type health facility infrastructure available and district

Infrastructure Butaleja Abim Kaabong Moroto Labor 1 1 0 1 Delivery 0 1 0 0 Labor and delivery together 1 0 0 0 Postpartum 0 1 1 1 Laboratory services 0 1 1 1 Inpatient and postpartum together 0 1 0 1 Separate beds for Kangaroo Mother Care 1 1 0 0 46

Baseline Survey for KOICA Program in Uganda 2016

Operating theatre 1 1 1 1 Neonatal care unit 1 0 0 0 Blood bank 1 0 0 0 Blood bank and laboratory together 0 1 0 1

1.11.1 Type of Facility infrastructure in HC IV

Table 4.6 shows that two HC IVs in Nakapiripirit district reported having nearly all the anticipated infrastructure with exception of separate beds for kangaroo mother care, and the Neonatal care unit and blood bank. The HC IVs in the districts of, Kotido, Pader and Kaabong reported having Delivery rooms, postpartum rooms, rooms for Laboratory services, and an operating theatre. HC IVs in all districts surveyed reported lack of separate beds for Kangaroo mother care and neonatal care units with the exception of Kaabong.

Table 0.6: Number of HC IV health facilities by of type facility infrastructure available and district

Infrastructure Kaabong Kotido Nakapiripirit Pader Labor 1 1 1 1 Delivery 1 1 2 1 Labor and delivery together 0 0 2 1 Postpartum 1 1 2 1 Laboratory services 1 1 2 1 Inpatient and postpartum together 0 1 2 1 Separate beds for Kangaroo Mother care 0 0 0 0 Operating theatre 1 1 2 1 Neonatal Care Unit 1 0 0 0 Blood bank 0 0 0 0 Blood bank and laboratory together 0 1 2 0

Baseline Survey for KOICA Program in Uganda 2016

1.12 Signal functions and other essential services

The EmONC indicators refer to the availability and use of facilities and the performance of healthcare systems in saving the lives of women with obstetric complications1. The availability of EmONC determines the capability of the health care system to respond to obstetric and newborn complications and its contribution to the reduction in maternal and newborn mortality and morbidity. The UN has defined nine essential EmONC services termed as "Signal Functions" for the treatment and management of MNH complications. The designation of an EmONC facility depends upon round-the-clock availability of services and whether these lifesaving signal functions have been performed recently. To qualify as a Basic EmONC (BEmONC) facility, the health centers and hospitals must have performed the following seven signal functions within the past three months

a) Administered parenteral antibiotics; b) Administered parenteral anticonvulsants (magnesium sulfate) ; c) Administered Uterotonic Drugs; d) Performed manual removal of placenta; e) Performed removal of retained products (manual vacuum aspiration); f) Performed assisted vaginal delivery (with vacuum extractor or forceps); and g) Performed neonatal resuscitation with bag and mask.

For a Comprehensive EmONC (CEmONC) facility, the hospital must have performed the following two signal functions in addition to the seven above, within the past three months:

h) Blood transfusion; and

i) Obstetric Surgery (Caesarean delivery)

Table 4.7 shows the distribution of health facilitates with functional EmONC facilities that satisfied the United Nation’s minimum criteria of at least one comprehensive EmONC and four basic EmONC facilities. The findings show that, all the Hospitals that were visited in the districts of Butaleja, Abim, Kaabong and Napak were found to perform all seven signal functions met at BEmONC and the HC IVs in Ntoroko, Amudat and Kotido were performing all seven signal functions met at BEmONC while half of the HC IV’s in Nakapiripirit were providing signal functions met at BEmONC services. No HC III and HC II in any of the districts surveyed provided all the seven met at BEmONC signal functions and none of the Hospitals or the HC IVs were found to be providing all the nine functions met at EmONC.

1 WHO, UNFPA, UNICEF and AMDD., A handbook on monitoring emergency obstetric care., WHO, 2009 48

Baseline Survey for KOICA Program in Uganda 2016

Table.7: Distribution of the functional EmONC facilities by District (%)

Providing all 7 BEmONC signal functions Providing all 9 CEmONC signal functions

District Hospital (N) HC IV (N) HC III (N) HC II (N) Hospital (N) HC IV (N) Butaleja 50.0 (2) 0.0 (11) 0.0 (9) 0.0 (2) Abim 100.0 (1) 0.0 (6) 0.0 (8) 0.0 (1) Amudat 100.0 (1) 0.0 (2) 0.0 (4) 0.0 (1) Kaabong 100.0 (1) 0.0 (1) 0.0 (5) 0.0 (8) 0.0 (1) 0.0 (1) Kotido 100.0 (1) 0.0 (8) 0.0 (3) 0.0 (1) Moroto 0.0 (1) 0.0 (5) 0.0 (3) 0.0 (1) Nakapiripirit 0.0 (1) 50.0 (2) 0.0 (6) 0.0 (6) 0.0 (1) 0.0 (2) Napak 100.0 (1) 0.0 (6) 0.0 (4) 0.0 (1) Agago 0.0 (5) 0.0 (6) Pader 0.0 (1) 0.0 (7) 0.0 (16) 0.0 (1) Kitgum 0.0 (6) 0.0 (9) Ntoroko 100.0 (1) 0.0 (4) 0.0 (2) 0.0 (1)

1.13 Active management of the third stage of delivery

The management of the final stages of labor is an important phase that involves amongst others, the administration of prophylactic oxytocin before the delivery of the placenta in order to prevent post hemorrhage. It also involves key components that include:

• Administering of the uterus-contracting drug (uterotonic) within one minute after birth (oxytocin is the drug of choice). • Applying controlled cord traction and counter traction to the uterus to deliver the placenta. • Massage the uterus through the abdomen after delivery of the placenta and monitor for further signs of bleeding.

The survey collected information from the facilities on whether women received AMTSL for vaginal delivery. The findings in Table 4.8 show that, of the hospitals visited during the survey, one hospital in Moroto and Napak districts administered AMTSL to women. Only one of the HC IV’s in Amudat district and another in Nakapiripirit district administered AMTSL during delivery. In Pader district, one HC III administered AMTSL.

Table 0.8: Number of health facilities in which women received AMTSL for vaginal delivery by district

District Hospital HC IV HC III Butaleja 0 0 49

Baseline Survey for KOICA Program in Uganda 2016

Abim 0 0 Amudat 1 0 Kaabong 0 0 0 Kotido 0 0 Moroto 1 0 Nakapiripirit 0 1 0 Napak 1 0 Agago 0 Pader 0 1 Kitgum 0 Ntoroko 0 0

1.14 Staff trained in EmNOC (MNH Package)

Information regarding whether facilities trained their staff in EmNOC (MNH package) was also collected during the survey. Results in Table 4.9 show that one hospital in each of the districts of Butaleja, Nakapiripirit and Napak trained its staff in EmNOC. In addition, almost all HC IIIs had staff trained in EmNOC services with exception of those in the districts of Amudat and Agago.

Table 0.9: Number of Staff trained in EmNOC (MNH package) by level of health facility and district

District Hospital HC IV HC III Butaleja 1 1 Abim 0 1 Amudat 1 0 Kaabong 0 1 1 Kotido 0 1 Moroto 0 1 Nakapiripirit 1 1 1 Napak 1 1 Agago 0 Pader 1 1 Kitgum 1 Ntoroko 2 4

1.15 PARTOGRAPH

Labour and delivery could be very tedious because of the need to document various observations in a timely manner and in multiple registers. To avoid this tedium, partographs have been designed in such a way that on one partograph, all the observations needed for the entire process of labour and delivery can be documented.

Baseline Survey for KOICA Program in Uganda 2016

The purpose of the partograph review was to assess the use and quality of the partograph completion and labour management in the health facilities. The data team was instructed to randomly select 10 cases of completed partographs.

Partographs were reviewed with the aim of determining to what extent the tool was used in monitoring labour and delivery in the health facilities. The data team was instructed to randomly select 10 cases of completed partographs.

1.16 Fetal Condition

It is important during labour for information concerning the fetal condition rate to be recorded atleast every half hour. Table 4.10 show information recorded for the fetal heart rate, membranes and liquid as well as molding of the fetal skull bones. The finding show that, overall, 22 percent of the cases concerning the fetal heart rate were found to have been filled in correctly, 21 percent of the cases had information on the decelerations recorded correctly, 20 percent of the cases had the information on relation to contractions recorded correctly, 14 percent and three percent of the cases selected cases were found to have information on the membranes and liquor as well as on molding the fetal skull bones respectively to have been filled in correctly.

Amudat district had the highest number of correctly recorded information concerning the heart beat (54%), Moroto district had 44 percent of the cases reported correctly while health centres in Kitgum district had 19 percent of the cases filled in correctly. Butaleja District did not have any cases reported as filled in correctly.

With regards to the information recorded on decelerations, Napak district had 49 percent of the cases filled in correctly while Kitgum district had the least cases having been recorded correctly (24 %).

At least 50 percent of the cases recorded in relation to contractions in Napak district were filled in correctly while Kaabong District had averagely 26 percent of the selected cases having been filled in correctly. No cases in the districts of Butaleja, Abim, Amudat, Kotido and Agago were found to have been filled in correctly.

Considering the Membranes and Liquor, the highest average number of the randomly selected cases filled in correctly were found in Amudat district (29%), Moroto district (27%) and Napak

Baseline Survey for KOICA Program in Uganda 2016 district (22%) while the lowest percentage of cases was found in Kitgum district (11%). No cases in Butaleja district were found to have been filled in correctly.

Concerning Molding of fetal skull bones, at least 21 percent of the cases selected in Moroto district were found to have been recorded correctly while the districts of Kaabong, Kotido, and Kitgum had less than 10 percent of the cases found to have been filled in correctly.

Table 0.10: Fetal Condition- Share of cases with correctly recorded fetal condition information by district (Mean)

Fetal heart rate Membranes & Molding fetal liquor skull bones District Heart Beat Decelerations Relation to contractions Butaleja 0.000 0.000 0.000 0.000 0.000 Abim 0.256 0.244 0.000 0.122 0.097 Amudat 0.543 0.000 0.000 0.294 0.196 Kaabong 0.260 0.367 0.260 0.140 0.070 Kotido 0.225 0.000 0.000 0.115 0.067 Moroto 0.444 0.378 0.322 0.273 0.208 Nakapiripirit 0.286 0.293 0.279 0.193 0.155 Napak 0.364 0.491 0.518 0.220 0.184 Agago 0.291 0.000 0.000 0.195 0.107 Pader 0.229 0.367 0.346 0.156 0.152 Kitgum 0.193 0.240 0.320 0.105 0.065 Ntoroko 0.029 0.000 0.229 0.069 0.032 All 0.224 0.208 0.199 0.138 0.030

1.17 Progress of Labor and Maternal condition

Table 4.11 shows information regarding the progress of labour and the maternal condition. The findings show that overall, of the 10 randomly selected cases with regard to information on the monitoring of the cervical dilation, 41 percent of the cases were found to have the time recorded with Amudat district recording the highest number of cases (89%) while Kitgum was reported to have the lowest 31 percent and no case was reported in Butaleja district; three percent had the latent phase plotted with Pader having highest number of cases 18 percent of the cases and Kitgum having the lowest six percent and all the other districts having none of the selected cases being reported ; 34 percent had the alert line plotted with the highest number of cases being found in Amudat district (80%) and the lowest in Kotido district (29%); and three percent had the action line plotted with the highest number in Amudat district (14%) and the lowest in Moroto (1%).

Baseline Survey for KOICA Program in Uganda 2016

With regard to the palpate number of contractions in ten minutes and duration of each contraction in seconds, overall, 32 percent of the cases were found to have been filled in correctly and of these cases the highest number was reported in Amudat district (65%) and the lowest were reported in Kitgum district (26%). None of the cases that were selected in Butaleja district were found to have the information filled in correctly.

Considering information recorded on the Maternal condition, the findings show that of the 10 cases selected randomly, 14 percent had information on drugs, IV fluids and oxytocin recorded correctly and of these 46 percent were reported in Agago district and the lowest cases were found in Pader district (3%). Butaleja district and Kitgum district had no cases recorded correctly.

Considering the Pulse and blood pressure, the temperature and the urine volume, analysis for protein and acetone, overall 27 percent, 21 percent and six percent of the randomly selected cases were found to have been filled in correctly.

Table 0.11: Progress of Labour- Share of cases with correctly recorded information about progress of labour by district (Mean)

Progress of Labour Maternal condition Palpate Urine numbe volume, Time Latent Alert Action r of Drugs, IV Pulse, analysis for recorde phase line line contrac fluids & blood Temp protein & District d plotted plotted plotted tions oxytocin pressure . acetone Butaleja 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Abim 0.389 0.000 0.322 0.000 0.315 0.200 0.211 0.178 0.011 Amudat 0.886 0.000 0.800 0.143 0.652 0.271 0.829 0.643 0.100 Kaabong 0.400 0.000 0.353 0.067 0.311 0.233 0.220 0.207 0.107 Kotido 0.358 0.000 0.292 0.000 0.275 0.125 0.225 0.150 0.108 Moroto 0.711 0.000 0.556 0.011 0.467 0.444 0.511 0.344 0.167 Nakapiripirit 0.550 0.000 0.507 0.086 0.493 0.107 0.436 0.371 0.171 Napak 0.655 0.000 0.509 0.018 0.527 0.118 0.473 0.473 0.136 Agago 0.518 0.000 0.318 0.018 0.361 0.455 0.245 0.109 0.000 Pader 0.375 0.175 0.333 0.063 0.288 0.033 0.313 0.238 0.000 Kitgum 0.307 0.060 0.320 0.000 0.264 0.000 0.007 0.000 0.000 Ntoroko 0.429 0.000 0.343 0.014 0.310 0.057 0.200 0.029 0.000 All 0.408 0.033 0.344 0.034 0.316 0.139 0.265 0.197 0.058

Baseline Survey for KOICA Program in Uganda 2016

LIST OF REFERENCES

1. Academy for Educational Development (AED), the Manoff Group, and USAID, 2005, Maternal Survival: Improving Access to Skilled Care - A Behavior Change Approach 2. World Health Organisation (WHO), A handbook on monitoring emergency obstetric care, WHO, 2009 3. Ministry of Health Second National Health Policy, 2009

Baseline Survey for KOICA Program in Uganda 2016

APPENDIX

SAMPLE DESIGN

The sampling frame used for KOICA 2015 is the Uganda Population and Housing Census which was conducted in August 2014 (UPHC 2014), provided by the Uganda Bureau of Statistics (UBOS), the implementing agency for the KOICA 2015. The sampling frame is a complete list of census Enumeration Areas (EA) created for the census covering the whole country, consisting of 78093 EAs. An EA is a natural village in rural areas and a city block or group of residential buildings in urban areas. This is an area designated during Census mapping such that one enumerator should be able to cover it during the specified time of undertaking Census. Uganda is divided into 112 administrative districts, each districts is sub-divided into sub-counties, and each sub-county into a parish, and each parish into villages. The frame file contains the administrative components for each EA and its number of households at the time of the census. Each EA has also a designated residence type, urban or rural. The following are the definition of the study domains.

Stratum code Stratum Stratum code Stratum Stratum code Stratum Stratum code Stratum 1 BUTALEJA 4 MOROTO 7 ABIM 10 AMUDAT 2 KITGUM 5 NAKAPIRIPIRIT 8 KAABONG 11 NAPAK 3 KOTIDO 6 PADER 9 AGAGO 12 NTOROKO

Table 1 shows the distribution of the residential households by district and by type of residence. The size of the district varies from 4.0% for Ntoroko to 13.2% for Butaleja; the urban percentage of the districts varies from 4.1% for Ntoroko to 25.2% for Kitgum.

Table 1. Distribution of residential households by region and by type of residence

Households District Share Proportion of of the total urban to the households in Geo-region Rural Urban Total district the study area Butaleja 38083 6171 44254 13.9 13.2 Kitgum 29566 9952 39518 25.2 11.8 Kotido 23396 2778 26174 10.6 7.8 Moroto 18226 2954 21180 13.9 6.3 Nakapiripirit 23485 1045 24530 4.3 7.3 Pader 31413 2933 34346 8.5 10.3 Abim 15054 2790 17844 15.6 5.3 Kaabong 26748 2340 29088 8.0 8.7 Agago 37502 5704 43206 13.2 12.9 Amudat 12870 2229 15099 14.8 4.5 Napak 24878 1311 26189 5.0 7.8 Ntoroko 7994 5354 13348 40.1 4.0 Total 289215 45561 334776 100 *Source: 2014 population census frame, Uganda

Baseline Survey for KOICA Program in Uganda 2016

Table 2 shows the distribution of EAs and their average size in number of households. The average EA size is 117 households in urban areas and 84 households in rural areas, with an overall average size of 91 households per EA.

Table 2. Distribution of residential EAs and their average size by region and by type of residence

Number of EAs Average number of households per EA Geo-region Rural Urban Total Rural Urban Total Butaleja 413 62 475 92 100 93 Kitgum 507 115 622 58 87 64 Kotido 320 29 349 73 96 75 Moroto 234 31 265 78 95 80 Nakapiripirit 328 11 339 72 95 72 Pader 611 35 646 51 84 53 Abim 261 53 314 58 53 57 Kaabong 590 34 624 45 69 47 Agago 832 97 929 45 59 47 Amudat 160 21 181 80 106 83 Napak 358 15 373 69 87 70 Ntoroko 148 66 214 54 81 62 4762 569 5331 84 117 91 *Source: 2014 population census frame, Uganda

Sampling Procedure and Sample Allocation

Sample size determination

In determining the sample design for the Uganda KOICA Survey, the percentage of women aged 15-49 with a post-natal checkup in the first two days after birth (Karamoja 26.8%, North 27.8% and Western 28.8%). Karamoja includes Kotido, Moroto, Nakapiripirit, Abim, Kaabong, Amudat, and Napak; North includes Pader, Agago and Kitgum, while western includes Ntoroko. A response rate of 90% and a household size of 5 persons per household and the share of women aged 15 - 49 years per household were used. The survey considered the average proportion of women attended to by skilled person during delivery of 40 percent. In order to be able to generate estimates at domain level, the following formula was used;

4 r  (1 r) deff n  (RME *r)2  RR * HHsize Where: • n is the required sample size, expressed as number of households, for the key Indicator • 4 is a factor to achieve the 95 percent level of confidence • r is the average proportion of women attended to by skilled person to be 40% • deff is the design effect( 1.2) • RME is the margin of error to be tolerated at the 95 percent level of confidence, defined as 10 percent of r • Response rate (RR)=90%

The effective sample size for the survey at household’s level with Relative Margin of Error (RME) of 10 percent is presented in Table 3.

Baseline Survey for KOICA Program in Uganda 2016

Table 3: sample calculation

Proportion Relative margin of of Number of Effective Predicted error at target/base Average households number of value of Design 95% population household Response (Sample Cluster households indicator effect confidence in total size rate Size) size population

r deff RME pb AveSize RR n

Butaleja 0.40 1.2 0.12 0.22 5 0.9 498 30 554

Kitgum 0.40 1.2 0.12 0.22 5 0.9 498 30 554

Kotido 0.40 1.2 0.12 0.22 5 0.9 498 30 554

Moroto 0.40 1.2 0.12 0.22 5 0.9 498 30 554

Nakapiripirit 0.40 1.2 0.12 0.22 5 0.9 498 30 554

Pader 0.40 1.2 0.12 0.22 5 0.9 498 30 554

Abim 0.40 1.2 0.12 0.22 5 0.9 498 30 554

Kaabong 0.40 1.2 0.12 0.22 5 0.9 498 30 554

Agago 0.40 1.2 0.12 0.22 5 0.9 498 30 554

Amudat 0.40 1.2 0.12 0.22 5 0.9 498 30 554

Napak 0.40 1.2 0.12 0.22 5 0.9 498 30 554

Ntoroko 0.40 1.2 0.12 0.22 5 0.9 498 30 554

Total 6646 10,586

Adjusting the sample size for an even number of EAs per domain for variance estimation without increasing the cost while considering the population share, the adjusted sample is as presented in Table 4. According to the 2011 UDHS, there were 1.02 women per households on average.

Table 4. Sample allocation of households and clusters by region and by study domain

Sample allocation Number of Effective number of women age 15-49 Survey region households years EAs

Butaleja 554 565 17 Kitgum 554 565 17 Kotido 554 565 17 Moroto 554 565 17 Nakapiripirit 554 565 17 Pader 554 565 17 Abim 554 565 17 Kaabong 554 565 17 Agago 554 565 17 Amudat 554 565 17 Napak 554 565 17 Ntoroko 554 565 17 Total 6646 6779 204

Selection of EAs with PPS Systematic Sampling Procedure

The sample for KOICA 2015 was a two stage stratified sample selected from the sampling frame. In total 12 sampling strata were created; each representing a target district. Samples were selected randomly and independently from each stratum according to the sample allocation in Table 3 using probability proportional to size selection (PPS). Before the sample selection, the sampling frame was sorted within each sampling stratum first, by residence type, then by sub-county, parish, village and EA codes. Sorting coupled with the PPS sampling procedure, resulted into implicit stratification by residence type. The 57

Baseline Survey for KOICA Program in Uganda 2016 sample points were proportionally allocated to the urban and rural areas respectively. The required number of EAs was selected by probability proportional to size (PPS), using the systematic sampling as described in Hansen, Hurwitz, and Madow (1953). The measure of size (MOS) used for sample selection was the number of Households from the 2014 PHC census.

After the first stage selection, a household listing process conducted in all of the selected EAs before the main survey. The household listing operation involved visiting each of the 178 selected EAs; drawing a detailed location sketch map; and recording on household listing forms all residential households found in the EA with the address and the name of the head of household. The up to date lists of households served as the sampling frame for the selection of households in the second stage.

At the second stage, a fixed number of 30 households was selected from the newly established household listing for each selected EA. The 30 households per EA is based on previous survey undertakings such as the Demographic and Health surveys where 28-30 households are selected for health surveys. Household selection was done at the Central office prior the main survey. The survey interviewers visited and interviewed only the pre-selected households. No substitutions or changes of the pre-selected households were allowed at the implementing stage of data collection in order to avoid bias.

The 30 households were selected with equal probability from the listing for each sample EA as follows:

1. All the households listed in the sample EA were assigned a serial number from 1 to 푀ℎ푖 - the total number of households listed in the EA.

2. A sampling interval for the selection of households within the sample EA (퐼ℎ푖), was computed

by dividing 푀ℎ푖 by 30, and was maintained 2 decimal places.

3. A Random Start (푅ℎ푖) with 2 decimal places, between 0.01 and퐼ℎ푖was selected. The sampled households within the sampled EAs were identified by numbers showing the selection as: S  R I  j 1 hij hi hi , rounded up, where 푗 = 1, 2, 3... 30

The 푗 푡ℎ selected household is the one with a serial number equal to 푆ℎ푖푗 .

Selection of Health facilities

In the selection of the health facility, the survey employed the approach of linking after selection, where the health Centre II serving the population of the sampled EA was selected. Given that they are few Health Centers IIIs and IVs in the districts, the survey covered all within the target districts.

Sampling weight for household and individual survey

Due to non-proportional allocation of the sample to the different districts and study domains, sampling weights are required for any analysis using KOICA 2015 data to ensure representativeness of the sample. Since the KOICA 2015 sample is a two-stage stratified cluster sample, sampling weights were calculated based on sampling probabilities separately at each sampling stage and for each cluster. The following notations are used:

Baseline Survey for KOICA Program in Uganda 2016

th P1hi: sampling probability of the i cluster in stratum h

th P2hi: sampling probability of households within the i cluster

th Phi: overall sampling probability of households of the i cluster in stratum h

Let ah be the number of clusters selected in stratum h for theKOICA 2015, Mhi the number of households

th in the i cluster, and  M hi the total number of households in the stratum h. The probability of selecting the ith cluster in stratum h for the KOICA 2015 is calculated as follows:

ah M hi P1hi   M hi

Let Lhi be the number of households listed and ghi ( =28 for all h and i for KOICA 2015) selected in the ith cluster in stratum h. The probability for selecting a household in the ith cluster is calculated as follows:

ghi P2hi  Lhi

The overall selection probability of each household in cluster i of stratum h is therefore the production of the selection probabilities:

ah ghiM hi Phi  P1hi  P2hi  Lhi M hi The design weight for each household in cluster i of stratum h is the inverse of its overall selection probability:

W 1/ P hi hi The design weight was adjusted for household non-response and as well as for individual non-response to get the final sampling weights for households and for individual women respectively. The difference in the household sampling weights and the women individual sampling weights is introduced by individual level non-response.

Baseline Survey for KOICA Program in Uganda 2016

QUESTIONNAIRES