Ministry of Health Nutritional

MINISTRY OF HEALTH

NUTRITIONAL ANTHROPOMETRIC SURVEY CHILDREN UNDER FIVE YEARS OF AGE

INFORMAL SETTLEMENTS IN KAMPALA CITY

JUNE 29th- 18th JULY 2009

ACKNOWLEDGEMENTS

Action against Hunger – Uganda Mission would like to acknowledge the support from the following:

ª UNICEF for offering the financial support to undertake the survey;

ª Ministry of Health-Kampala, Kampala Central division, Kawempe division and Nakawa division offices for providing vital information to facilitate planning and survey implementation;

ª Action against Hunger – Uganda Mission management, administration and logistics team for their assistance in preparing and conducting the survey. Special thanks go to ACF – USA and Kutondo Edward for further broadening our understanding of SMART Methodology, coordination and ensuring training and survey objectives are met;

ª Namulumba Eva Rose, Tadria Sophie, Nakitto Peace, Oluka Samuel, Bukusuba John, Opule Nicholas, Mabingo Jonathan, Ndahura Nicholas Bari, Nabuule Elizabeth Claire, Kuziga Fiona, Agaba Edgar, Apolot Pauline, Wakou Betty, Ahimbisibwe Emmanuel, Dr. Jacinta Sabiiti, Albert K Lule, Gerald Onyango, Samalie Bananuka, Esther Wamono, Rebecca Mirembe, Muhumuza Richard, Rwegyema Twaha, Dr. Mugisha Jennifer, Mateeba Tim and Nabunya Victoria for their endurance, dedication and team spirit in ensuring quality in actualization of survey objectives;

ª The parents and caretakers for providing valuable information by patiently taking their time to be interviewed and allowing their children to be measured.

- 2 - TABLE OF CONTENTS .I. EXECUTIVE SUMMARY ...... - 4 -

.II. INTRODUCTION ...... - 7 -

.III. OBJECTIVES ...... - 7 -

.IV. METHODOLOGY ...... - 7 - .IV.1. Type of Survey and Sample Size ...... - 7 - .IV.2. Sampling Methodology ...... - 8 - .IV.3. Data Collection ...... - 9 - .IV.4. Indicators, Guidelines, and Formula Used ...... - 10 - .IV.4.1. Acute Malnutrition ...... - 10 - .IV.4.2. Mortality ...... - 11 - .IV.5. Field Work ...... - 12 - .IV.6. Data Analysis ...... - 12 -

.V. RESULTS OF THE QUALITATIVE ASSESSMENT ...... - 13 - .V.1. Socio- demographic Characteristics of the Respondents ...... - 13 - .V.2. Food Security ...... - 14 - .V.3. Health ...... - 15 - .V.4. Water and Sanitation ...... - 16 - .V.5. Child care practices ...... - 16 - .V.6. Organizations providing health and nutrition services ...... - 17 -

.VI. RESULTS OF THE ANTHROPOMETRIC SURVEY ...... - 18 - .VI.1. Distribution by Age and Sex ...... - 18 - .VI.2. Anthropometrics Analysis ...... - 19 - .VI.2.1. Acute Malnutrition defined in Weight for Height ...... - 19 - .VI.2.2. Risk of Mortality: Children’s MUAC ...... - 21 - .VI.3. Measles Vaccination Coverage ...... - 21 - .VI.4. Composition of the households ...... - 22 - .VI.5. Stunting ...... - 22 - .VI.6. Underweight ...... - 22 -

.VII. RESULTS OF THE RETROSPECTIVE MORTALITY SURVEY ...... - 22 -

.VIII. CONCLUSION ...... - 23 -

.IX. RECOMMENDATIONS ...... - 25 -

.X. APPENDIX ...... - 26 - .X.1. Sample Size and Cluster Determination ...... - 26 - .X.2. Anthropometric data collection form for children 6-59 months ...... - 27 - .X.3. Household nutrition security data form ...... - 28 - .X.4. Household enumeration data collection form for a death rate calculation survey (one sheet/household) ...... - 29 - .X.5. Enumeration data collection form for a death rate calculation survey (one sheet/cluster) ...... - 30 - .X.6. Map of surveyed informal settlements in Kampala ...... - 31 - .X.7. Prevalence of acute malnutrition by age (UDHS classification) based on WFH z- scores and/or oedema ...... - 32 -

- 3 - .I. EXECUTIVE SUMMARY

The feeding of infants and young children is crucial in determining the health, nutrition, survival, growth and development of the individual. Nutrition is a key element of the child’s right to health as stipulated in the Convention on the Rights of the Child (CRC, 1989).

According to Uganda Participatory Poverty Assessment Project, UPPAP, (2000), about 30% of Kampala’s population lives in informal settlements commonly known as slums which cover about 10% of the total area of Kampala with an average density of 14,112 people per square kilometer. Unfortunately both the number of slum dwellers and the area covered are on the increase and this is a challenge for the urban authorities.

The living conditions of slum dwellers impacts on the service availability and overall health conditions of the children under five at the household level. According to Uganda Demographic Health Survey, UDHS, (2006), stunting in Uganda was at 38%, wasting was at 6% and underweight at 16% among children under five. These rates of malnutrition contribute to over half of the high infant mortality rate of 76 deaths per 1000 live births. In Kampala district, the malnutrition rates stood at 3.7% for wasting, 8.1% stunting and 2.6% underweight based on WHO standards (2006). However, there is no consolidated data on the prevalence and infant mortality rates of children under five in informal settlements. Therefore the study was to investigate the nutritional anthropometric status of children 6-59 months in the informal settlements.

Justification Following a four day training on the National Nutritional Survey Guidelines based on SMART methodology, participants needed hands on practice to appreciate and gain experience on data collection, analysis and reporting. More still, the survey was also aimed at filling the knowledge gap on the paucity of data regarding informal settlements in Kampala.

Objectives

♦ To assess the nutritional status of children aged between 6 and 59 months. ♦ To estimate the mortality rate in the slum areas of Kampala. ♦ To determine the measles immunization coverage in children of age 9-59 months. ♦ To determine the incidence of common diseases (diarrhea, malaria, measles and ARI) among children two weeks prior to the assessment. ♦ To assess the factors influencing the nutrition situation of the community.

Methodology

Standardized Monitoring and Assessment of Relief and Transitions (SMART) methodology was utilized in the implementation of the nutritional anthropometric survey (SMART Methodology version I, October 2007). Children aged 6 - 59 months formed the target group. The planning information was obtained from

- 4 - Uganda demographic health survey (2006), World Fact Book (Uganda, 2008) and Uganda national nutrition survey guidelines (June, 2009). The majority of data was collected from Kampala division offices, UBOS, UDHS and from other organizations within the surveyed areas as indicated in Table 1.

Table 1: Survey planning data Anthropometric survey Mortality survey Population 14,8431 74,215 Estimated prevalence1 4% 0.33% ± Desired precision % 2 0.33 Design effect 1.5 1.5 Sample sizes 540 2,1972

The first samples were increased by 10% to cater for contingencies. Thirty three (33) clusters of 18 children in each cluster were used to implement the survey. In the clustered zones with approximately 250 households each, systematic random sampling method was applied to select households. A specific sampling interval for each enumeration area was calculated based on the number of households. Simple balloting or random number tables were used to determine the first household. Mortality and nutrition security questionnaires were administered to only households with children 6 – 59 months of age. Key informant interviews and observations were also used to collect data

Summary of findings Nutrition and Mortality Survey Results The final analysis included 571 children upon exclusion of 11 incoherent data sets. Global Acute Malnutrition (GAM) was 1.8% (WHO, 2006) and 1.9% (NCHS, 1977). The acute malnutrition result is below the cut off (5%) indicating a normal situation. Stunting was moderate while underweight fell within the normal range. (Refer to Table 2).

1 20% of the estimated population to cater for children under 5 years 2 The total number of persons “present now” to be included in the mortality survey - 5 - Table 2: Nutrition and Mortality Survey results

INDEX INDICATOR RESULTS3 Global Acute Malnutrition 1.8% W/H< -2 z and/or oedema (0.3 - 3.2 %)

Severe Acute Malnutrition 0.0% WHO (2006) Z- scores W/H < -3 z and/or oedema (0.0 - 0.0%) Total chronic stunting 28.5% W/H< -2 z (23.5-33.6%)

Total underweight 7.7% W/H< -2 z (5.5-9.9%)

Global Acute Malnutrition 1.9% Z-scores W/H< -2 z and/or oedema (0.6 - 3.2%) Severe Acute Malnutrition 0.0% NCHS (1977) W/H < -3 z and/or oedema (0.0 – 0.0%) Global Acute Malnutrition 0.4% % Median W/H < 80% and/or oedema (0.0– 0.8%) Severe Acute Malnutrition 0.0% W/H < 70% and/or oedema (0.0 - 0.0%)

Global Acute Malnutrition (<125 mm) 0.5% MUAC Height>65 cm Severe Acute Malnutrition (<115 mm) 0.0%

Total crude retrospective mortality (last 3 months) /10,000/day 0.19 (0.0 – 0.41 ) Under five crude retrospective mortality /10,000/day 0.17 (0.0 – 0.47 ) By card4 42.6 % Measles immunization coverage According to caretaker5 47.5 % [N= 566 children>= 9 months old] Not immunized 7.9 % Don’t know 1.7%

3 Results in bracket are at 95% confidence intervals. 4 The mass measles campaign card or the Road to health card was checked to verify measles immunization status of the child 5 When no EPI card was available for the child at the household, measles vaccination information was collected according to the caretaker - 6 - .II. INTRODUCTION

Kampala, the capital city of Uganda is situated between 0o15’N and 32o30’E and is located 45Km north of the Equator. It has a total area of 195 Km2 of which 86.7% is land. With a population size of 1.2 million, the District is divided into 5 administrative divisions of Central, Nakawa, Makindye, Kawempe and Rubaga divisions which are further sub divided into smaller administrative units.

The city is characterized by a series of low lying hills with flat hill tops which are surrounded by a network of wet valleys which are covered by papyrus swamps. Whereas the hills have been reserved for institutional purposes, many of the papyrus swamps have been reclaimed and developed to contain the central business district, informal settlements (slum dwellings) and industrial zones (Matagi, 2001).

The professional, technical and managerial occupations which require advanced skills and have higher income earning potential employ only 3% of the working women and 5% of working men from informal settlement households6. As such most people earn less and therefore are likely to be at risk of food insecurity. To build national capacity in the assessment of malnutrition, Action Against Hunger in collaboration with the Ministry of Health and other partner organizations conducted a three weeks training in Kampala. The training focused on national nutrition survey guidelines, SMART methodology and training skills. To equip participants with field experience and appreciate the robustness of the SMART methodology, an actual nutrition anthropometric assessment was conducted for children 6-59 months within the informal settlements of Kampala.

.III. OBJECTIVES

.IV. METHODOLOGY

.IV.1. Type of Survey and Sample Size

A nutrition survey was undertaken in the informal settlements of Kampala using SMART methodology. Anthropometric, nutrition security and mortality data was simultaneously collected. The study focused on

6 source: UDHS, 2006 - 7 - informal settlements in Bwaise I, II and III, Wandegeya, Mbuya and Kisenyi I, II and III, Kagugube Parishes (See appendix X:1 and X.6). The accessible population was estimated at 74,215 persons. During the survey, children aged 6-59 months formed the target group.

.IV.2. Sampling Methodology

A two-stage cluster sampling method was used:

• Cluster selection: Anthropometric and mortality sample sizes were automatically calculated in ENA for SMART Software October 2007 version after inputting the necessary information. The previous nutrition survey undertaken in the area provided necessary information for planning. The number of clusters was calculated based on the capacity of the teams per day in terms of number of children and people to survey.

For the anthropometric survey: The sample size of 540 was obtained after inputting target population (14,843), prevalence (4%), precision (2%) and design effect (1.5); and providing 10% contingency allowance. The resultant figure was then divided by 187 to obtain the total number of clusters required for the survey. 33 clusters were assigned randomly for assessment.

For the mortality survey, the total accessible population (74,215), estimated CDR prevalence (0.33), corresponding desired precision (0.3) and design effect of 1.5 were keyed into the mortality section of the planning template. The first sample was increased by 10% contingency to obtain (2,417) which was then divided by the total number of clusters (33) to obtain the required number of persons present now per cluster. Seventy four persons present now were thus targeted per cluster

• Selection of households and children

Within a cluster: In the clustered village, systematic random sampling method was applied to select households. Simple balloting or random number tables were used to determine the first household. Subsequent households were selected using a calculated interval for the location. Mortality, nutrition security and anthropometric questionnaires were administered accordingly.

Choosing children within the house: In every selected household, all children aged 6-59 months were assessed till a target of 18 was obtained. Child Health Cards and a local calendar of events were used to determine the ages of children. In cases whereby the teams only needed one child to attain the target of 18, all eligible children in the last household were measured.

Additional qualitative data was gathered through key informants, observation and secondary sources. This information was used to determine the immediate, underlying and basic causes of malnutrition within the location.

7 For ACF Uganda: The number of children that can accurately be measured per day per team. - 8 - .IV.3. Data Collection

The anthropometric questionnaire (See appendix X: 2) was administered to all eligible children till a target of 18 children per cluster was obtained. The following information was obtained:

ª Age: Recorded with the help of child health cards and a local calendar of events (See appendix X: 8).

ª Gender: Male or female

ª Weight: Targeted children were weighed using UNISCALES that were calibrated using 2kg stone.

ª Height: Children were measured on a measuring board (precision of 0.1cm). Children less than 87m were measured lying down, while those greater than or equal to 87cm were measured standing up.

ª Mid-Upper Arm Circumference: MUAC was measured at the mid-point of the left upper arm (precision of 0.1cm). ACF MUAC tapes were used.

ª Bilateral oedema: Assessed by the application of normal thumb pressure for at least 3 seconds to both feet.

ª Measles vaccination: Assessed by checking for measles vaccination on Child health cards and probing caretakers.

Households without eligible children remained a part of the “sample” that contributed zero children to the nutritional part of the survey. Children with MUAC less than 125, W/H < 80% or < -2 Z-score and > -3 Z- score were referred to Mwana-Mugimu Nutrition Unit in Mulago Hospital.

Household nutrition security data: Information was sought on livelihoods of households, diet diversity scores, as well as water, sanitation and hygiene (WASH) using a structured questionnaire (See appendix .X.3)

The mortality questionnaire (See Appendix .IX.4 and .IX.5) was administered in all households irrespective of whether they had eligible children or not. Seventy four persons present per cluster were targeted.

Retrospective morbidity of children The recall period for children’s illness including malaria, diarrhea, ARI, skin disease and other diseases was 2 weeks. Caretakers were asked questions about children’s illnesses although in some cases where the primary caretaker was not at home, any adult found in the home was interviewed.

- 9 - .IV.4. Indicators, Guidelines, and Formula Used

.IV.4.1. Acute Malnutrition

¾ Weight for Height Index

Low weight-for-height identifies wasted children. It is normally very useful when exact ages of children are difficult to determine. This index is appropriate when examining short-term effects such as seasonal changes in food supply or short-term nutritional stress brought about by illness.

Acute malnutrition rates were estimated from the weight for height (W/H) index values as well as presence of bilateral oedema. Findings were then compared to the WHO8 standards 2006 and NCHS 9 references. The result was then expressed in both Z-scores and percentage of the median.

Other than having a true statistical meaning; expression in z- score conveys malnutrition rates more precisely and allows for inter-study comparison. The percentage of the median on the other hand, estimates weight deficits more accurately and in the recent past was used in determining eligible children for targeted feeding programs

The following guidelines were thus used in expression of results in Z-score and percentage of the median. Guidelines for results expressed in Z-score: ª Severe malnutrition: - WFH < -3 SD and/or existing bilateral oedema on the child’s lower limbs. ª Moderate malnutrition: - WFH < -2 SD and ≥ -3 SD and no oedema. ª Global acute malnutrition: - WFH < -2 SD and/or existing bilateral oedema.

Guidelines for results expressed in percentage of median: ª Severe malnutrition: WFH < 70 % and/or existing bilateral oedema on the child’s lower limbs. ª Moderate malnutrition: WFH < 80 % and ≥ 70 % and no oedema. ª Global acute malnutrition: WFH <80% and/or existing bilateral oedema

Chronic malnutrition ¾ Height for age Index The height-for-age index is an indicator of linear growth retardation and cumulative growth deficits. Children whose height-for-age Z-score is below -2 z scores are considered short for their age (stunted) and are chronically malnourished. Children who are below -3 z scores are considered severely stunted. Stunting reflects failure to receive adequate nutrition over a long period of time and is also affected by recurrent and chronic illness. Height-for-age, therefore, represents the long-term effects of malnutrition in a population and is not sensitive to recent, short-term changes in dietary intake.

8 WHO Child Growth Standards: length/height-for-age, weight-for-age, weight-for-length, weight-for-height and body mass index-for-age. Methods and development. Geneva, Switzerland: World Health Organization, 2006. 9 NCHS: National Center for Health Statistics (1977) NCHS growth curves for children birth-18 years. United States. Vital Health Statistics. 165, 11-74. - 10 -

¾ Weight for age index Weight-for-age is a composite index of height-for-age and weight-for-height. It takes into account both acute and chronic malnutrition. Children whose weight-for-age is below -2 z scores are classified as underweight. Children whose weight-for-age is below -3 z scores are considered severely underweight.

¾ Children’s Mid-Upper Arm Circumference (MUAC) MUAC is a good predictor of mortality. It is a malnutrition indicator in children taller than 65 cm in some protocols, and children taller than 75cm in others. As such, MUAC measurements of the assessed children were presented in various height groups of <75cm, ≥75cm - < 90cm and ≥ 90 cm.

MUAC Guidelines

MUAC < 115mm and/or oedema severe malnutrition and high risk of mortality MUAC ≥ 115 mm and <125 mm Moderate malnutrition and risk of mortality MUAC ≥ 125 mm and <135 mm At risk of malnutrition MUAC ≥ 135 Adequate nutritional status

.IV.4.2. Mortality

Crude Mortality Rate (CMR) = 10,000/a*f/ (b+f/2-e/2+d/2-c/2), where:

a = Number of recall days (94) b = Number of current household residents c = Number of people who joined household d = Number of people who left household e = Number of births during recall f = Number of deaths during recall period

The result is expressed per 10,000 people / day. Thresholds are defined as follows10:

Total CMR: Alert level: 1/10,000 people/day Emergency level: 2/10,000 people/day

Under five CMR: Alert level: 2/10,000 people/day Emergency level: 4/10,000 people/day

10 Health and nutrition information systems among refugees and displaced persons, Workshop report on refugee’s nutrition, ACC / SCN, Nov 95. - 11 - .IV.5. Field Work

Training of enumerators and supervisors was done for 4 days by ACF on national survey guidelines, survey design, data collection techniques, signs and symptoms of malnutrition, anthropometric measurements, accurate data recording and data collection and interview skills. Four teams were formed for the pre-test and standardization exercise during training and these took measurements of the children and compared results under supervision of ACF staff. Standardization involved two repeated measurement on a set of 10 healthy children from a comparable slum that was not included in the selection of clusters in the planning phase. The field work was undertaken from 6th to 14th July 2009. Data collected was entered on a daily basis by the Action Against Hunger Program Manager. Probability statistics were generated each night in order to troubleshoot and check for errors. Teams were debriefed each morning on errors encountered and means to minimize them.

.IV.6. Data Analysis

Data entry, processing and analysis for both anthropometric and mortality data were carried out using SMART ENA Software (October 2007 version) using both NCHS (1977) and WHO (2006) references. SPSS 12.0 and Excel 2003 were used to carry out analyses on MUAC, Measles, immunization coverage, and other nutrition security related data.

- 12 - .V. RESULTS OF THE QUALITATIVE ASSESSMENT

.V.1. Socio- demographic Characteristics of the Respondents

More than 60% of Kampala’s population live in informal settlements scattered around the city where 43% of the population is not able to meet the basics of life, due to poverty (KCC, 2003).

In Uganda, 41% of the urban population lives in Kampala city with a population of 1.4 million, 54% of whom live in one- or two-roomed houses, known as muzigos .Basically, since the 1990s, the supply of low-cost housing has not kept pace with the city’s population growth resulting in, and so the spread of unplanned, informal settlements, i.e. slums, which boast a population density of over 14,000 people per square kilometre. The muzigos in the informal settlements typically lack adequate sanitation and drainage and many stand in wetlands that are prone to flooding (KCC, 2003).

Although poverty in Uganda has a “rural face” the urban poor in Kampala are much more disadvantaged, since they live in very poor and shanty housing conditions and lack access to supportive social networks (KCC 2003). According to the last Population and Housing Census, 39% of Kampala’s population lives in absolute poverty, 5.7%in abject poverty and 43% of the population is unemployed. Kampala slums developed partly as a result of rural to urban migration. Ethnically, slum dwellers constitute immigrants from neighboring countries (Rwanda, Sudan, Ethiopia, and Congo) and also from the North and Eastern regions of Uganda who have been displaced due to civil strife.

Just like in most parts of Kampala, foods consumed in informal settlements are mainly obtained by purchase from markets and shops. Figure 1 shows the distribution of sources of livelihood of the assessed households. The data indicated that 28.5% of the assessed households had permanent jobs, 18.4% had temporary jobs, 46.3% depended on small businesses, 4.2% received remittance and 2.5% responded to other options like receiving assistance from relatives and friends. Small businesses included motor garages, retail shops, milling machines, restaurants, clinics/or drug shops and airtime vending.

Others

Remittance

Small business

Temporary job

livelihood options Permanent job

0 5 10 15 20 25 30 35 40 45 50

percentage

Figure 1: Source of Livelihood

- 13 - .V.2. Food Security

According to the results presented in figure 2 below, the staple diet of people living in informal settlements of Kampala within the 24 hours preceding the interview consisted of foods made from cereals (83.9%), tubers/plantain (75.0%) and food made from legumes (63.9%). Over half of the assessed households consumed oil (52.8%), and (80.1%) consumed sugar / honey. Foods from animal sources, fruits and vegetables were least consumed; (29.6%) meat / or offal, (37.5%) milk / milk products, (23.9%) fish, (8.6%) eggs, (35%) vegetables and (15.7%) fruits. On average households consumed five food groups on a scale of 12 in the last 24 hours preceding the survey. Only 31% of the assessed households had a less diverse diet (i.e., they had fed on less than five food groups)

Fish Fruits Legumes Spices Eggs Vegetables Tubers/Plantains Milk/milk products Meat/offals Sugar/Honey Oils & fats Cereals

0 102030405060708090 Figure 2: Food groups consumed in the household in the last 24 hours

Food insecurity in Uganda results from poverty, intra-regional differences, internal displacement, gender imbalances in food allocation, intra-household food distribution and lack of knowledge (Nutritional Care and Support for People living with HIV/ AIDS in Uganda, 2006).

Despite the setbacks mentioned above, households in the informal settlements of Kampala strive to ensure availability of adequate food. 9.8% of the assessed households had not faced food scarcity. 90.2% of assessed households had ever faced food scarcity and resorted to coping mechanisms such as borrowing food (22.8%), borrowing money (5.4%), reducing amount of food per meal (24.5%), reducing number of meals (13.6%), selling assets (0.6%), and eating foods of low quality (27.7%). About 10% opted to sleeping hungry, praying to God and visiting friends and relatives.

- 14 - .V.3. Health

The health facilities in the informal settlements include public (called health centers I to IV), private facilities and local pharmacies / drug shops. Private facilities were predominant in Kawempe division. Although a number of health facilities existed in the different zones, they were inadequate in terms of medical supplies and personnel to offer quality maternal and child health and nutrition services.

Generally, the health seeking behavior was reportedly good as 48% of the households on falling sick, first sought treatment from the public health facilities, 39% from private health facilities, 9.6% from pharmacies / drug shops and 0.6% from traditional healers (Refer to figure 3). Some of the households (0.2%) sought no assistance. This could be attributed to limited access to health facilities and self medication.

Health seeking behaviour in informal settlements

Other

Private health facility

Public health facility

Pharmacy / drug shop

Traditional healer

None

0 102030405060

Percentage

Figure 3: Health seeking behavior in informal settlements

Sixty nine percent (69%) of the respondents reported illness in children under five in a recall period of two weeks. Common causes of morbidity in the informal settlement areas were Malaria (20.3%), diarrhea (10.2%), skin diseases (2.5%), Acute Respiratory Infections (ARI) - (46.6%) and others (11.6%) for example chicken pox, burns, tonsillitis and stomach upsets. Malaria cases are linked to poor and open drainage systems containing stagnant water that provides favorable breeding grounds for mosquitoes. Additionally topographical factors especially for Bwaise III (Katogo, Nakamilo, Kalimali, and Bugalanyi zones) located in a swampy area and usually affected by flooding. Diarrhea incidences could be attributed to open defecation (especially of children under five), poor waste disposal and unhygienic practices like not washing of hands after latrine use and before child feeding. The high prevalence of ARI is closely linked to unhygienic practices, poor housing structures (leading to poor ventilation), congestion within housing units and dust.

0.19 [0.00 – 0.41] /10,000/day and 0.17 [0.00 – 0.47] /10,000/day crude and under five mortality rates were obtained respectively. Analytically, both findings fall below the mortality alert and emergency levels. - 15 - Measles immunization level of 90% was verified by either child health cards or caretakers. The results were slightly below the national target of 100%. The results indicate an improvement compared to 2006 findings for Kampala which unveiled immunization coverage of 71.3%. This could be attributed to mass measles immunization and other immunization campaigns by Ministry of Health.

.V.4. Water and Sanitation

The main water sources in the surveyed locations were tap water (75.7%) from National Water and Sewerage Corporation (NWSC). The water taps were located within a short walking distance. The protected wells were also within walking distance but not within the settlements. Occasionally, some households reported purchasing water, whose source could not be ascertained by the users.

The amount of water used per day per household varied from 1 to 40 jerricans (20 liter jerrican). This varied according to household size, number of children (under five) and family water needs. Most households (97.5%) reported access to safe water.

Appropriate human waste disposal is one of disease control measures. Most households used community latrines (61.8%) where in some cases (like Busia and Kimwanyi zones) payment was required. Payment is a deterrent to latrine use as most people in these communities explained that they lacked funds for continuous and consistent use. Over 34% of assessed households had private latrines and 3.1% had VIP latrines while 1% used other methods for human waste disposal (particularly for children under five) namely garbage bins.

Most of the latrines are poorly constructed and maintained. The communities explained that this was due to lack of funds. Additionally, the response elicited by the communities on fecal matter disposal clearly indicated that they were somehow aware of the negative repercussion of poor waste disposal. It is thus important to strengthen health education in the assessed areas while looking into more sustainable and feasible modalities of constructing latrines in the areas. This will greatly encourage latrine use especially in those areas where payment is required.

Soap was available in almost every household assessed (99.2%) and was used mostly to wash clothes (96.9%), wash utensils (77.1%), bathing (52.2%) and washing of hands before eating (29.3%). A few households used soap to clean hands before feeding young children (17.2%) or after defecation / soiling (27%).

.V.5. Child care practices

Infant and young child feeding (IYCF) practices include timely initiation of feeding solid / semisolid foods from age 6 months and increasing the amount and variety of foods and frequency of feeding as the child gets older, while maintaining frequent breastfeeding. The guidelines were established with respect to IYCF practices for children age 6-23 months (PAHO/WHO, 2003 and WHO, 2009).

- 16 - Less than 50% of the households reported to feed children below five years more than three meals per day, 18.7% fed three meals per day, 11.2% fed two meals per day and 2.9% fed one meal per day (figure 4). Breastfed children are more likely than non-breastfed children to meet the recommendations for both diversity in food groups and frequency of feeding. Among the assessed households (58.9 %%) fed children below five years and who were no longer breastfeeding on cow’s milk in the last 24 hours preceding the survey. In some cases children below 6 months were breastfed as well as fed on foods like soy porridge, fruit juice, Irish potatoes and fruits.

Greater than 3 meals per day

3 meal per day

2 meal per day Number of meals

1 meal per day

0 5 10 15 20 25 30 35 40 45 Percentage

Figure 4: Number of meals children below five years ate in a day during the last 24 hours

It was observed that majority of the children were dirty and clothed in dirty garments although households indicated bathing and washing hands and clothes. More so, it was common to see young children defecating not very far from their homesteads and in areas used as play grounds and rubbish littered around the compound.

.V.6. Organizations providing health and nutrition services

The organizations providing health and nutrition services in the informal settlements of Kisenyi, Nakawa, Bwaise, Kagugube and Wandegeya include Non Government Organisations (NGOs), Community Based Organisations (CBOs) and Faith Based Organisations (FBOs) some of which include AIDS Information centre, Water and Sanitation Foundation (WATSAN), Straight Talk Foundation, Joint Clinical Research Centre, African Medical and Research Foundation (AMREF), God Helps Uganda, Child Family Protection Unit, Jafari Orphanage Centre, St. Matia Mulumba Youth Group, Uganda Australian Christian Outreach, Voice of the Disadvantaged People (VODAP) and Plan International. Services provided range from food security and nutrition counseling, food supply, HIV / AIDS counseling to water and sanitation.

- 17 - .VI. RESULTS OF THE ANTHROPOMETRIC SURVEY

.VI.1. Distribution by Age and Sex

Table 3: Distribution by Age and Sex AGE BOYS GIRLS TOTAL Sex Ratio ( In months) N % N % N % Boy: Girl 6-17 88 54.7 73 45.3 161 28.2 1.2 18-29 75 49.7 76 50.3 151 26.4 1.0 30-41 71 50.7 69 49.3 140 24.5 1.0 42-53 51 59.3 35 40.7 86 15.1 1.5 54-59 16 48.5 17 51.5 33 5.8 0.9 Total 301 52.7 270 47.3 571 100.0 1.1

An overall sex ratio of 1.1 falls within the acceptable range of 0.8 – 1.2. Slight imbalances were noted in the age group 42- 53 months. This is attributed to use of a local calendar of events which is prone to recall bias.

54-59

42-53

30-41

Age Boys 18-29 Girls "6-17

-60% -40% -20% 0% 20% 40% 60%

Percentage

Figure 5: Distribution by Age and Sex

- 18 - .VI.2. Anthropometrics Analysis

.VI.2.1. Acute Malnutrition defined in Weight for Height

¾ Distribution of Acute Malnutrition in Z-Scores

Table 4: Weight for Height distribution by Age in Z - scores and / or oedema (WHO Reference) Moderate Normal Age (months) Total no. Severe wasting wasting (> = -2 z Oedema (<-3 z-score) (>= -3 and <-2 z- score) score ) No. % No. % No. % No. % 6-17 161 0 0.0 5 3.1 156 96.9 0 0.0 18-29 151 0 0.0 1 0.7 150 99.3 0 0.0 30-41 140 0 0.0 0 0.0 140 100.0 0 0.0 42-53 86 0 0.0 2 2.3 84 97.7 0 0.0 54-59 33 0 0.0 2 6.1 31 93.9 0 0.0 Total 571 0 0.0 10 1.8 561 98.2 0 0.0

Table 5: Weight for Height distribution by Age in Z - scores and / or oedema (NCHS Reference) Moderate Normal Age (months) Total no. Severe wasting wasting (> = -2 z Oedema (<-3 z-score) (>= -3 and <-2 z- score) score ) No. % No. % No. % No. % 6-17 161 0 0.0 6 3.7 155 96.3 0 0.0 18-29 151 0 0.0 3 2.0 148 98.0 0 0.0 30-41 140 0 0.0 0 0.0 140 100.0 0 0.0 42-53 86 0 0.0 1 1.2 85 98.8 0 0.0 54-59 33 0 0.0 1 3.0 32 97.0 0 0.0 Total 571 0 0.0 11 1.9 560 98.1 0 0.0

Table 6: Weight for Height Vs Oedema in Z - scores (WHO and NCHS Reference) WEIGHT FOR HEIGHT WHO 2006 NCHS 1977 <-3 SD ≥ -3 SD <-3 SD ≥ -3 SD OEDEMA YES Marasmic Marasmic Kwashiorkor Kwashiorkor kwashiorkor kwashiorkor 0 (0.0 %) 0 (0.0%) 0 (0.0 %) 0 (0.0 %) NO Marasmic Normal Marasmic Normal 0 (0.0%) 571 (100.0%) 0 (0.0 %) 571 (100.0 %)

- 19 - A standard deviation of 0.99 was unveiled as shown in the graph below. This fell within the acceptable range (0.8-1.2) indicating that the sample is representative.

Figure 6: Weight-for-Height z-scores based on WHO standards

¾ Distribution of Acute Malnutrition in Percentage of the Median

Table 7: Prevalence of malnutrition by age, based on weight-for-height percentage of the median and oedema (NCHS reference) Severe Moderate Normal Oedema wasting wasting (> =80% median) (<70% (>=70% and median) <80% median) Age Total No. % No. % No. % No. % (months) no. 6-17 161 0 0.0 2 1.2 159 98.8 0 0.0 18-29 151 0 0.0 0 0.0 151 100.0 0 0.0 30-41 140 0 0.0 0 0.0 140 100.0 0 0.0 42-53 86 0 0.0 0 0.0 86 100.0 0 0.0 54-59 33 0 0.0 0 0.0 33 100.0 0 0.0 Total 571 0 0.0 2 0.4 569 99.6 0 0.0

- 20 - Table 8: Prevalence of acute malnutrition based on the percentage of the median and/or oedema n = 571 Prevalence of global acute malnutrition (2) 0.4 % (<80% and/or oedema) (0.0 - 0.8 95%) Prevalence of moderate acute malnutrition (2) 0.4 % (<80% and >= 70%, no oedema) (0.0 - 0.8 95%) Prevalence of severe acute malnutrition (0) 0.0 % (<70% and/or oedema) (0.0 - 0.0 95%)

Table 9: Global and Severe Acute malnutrition in NCHS references in percentage of the median 0.4% Global Acute Malnutrition (0.0% - 0.8%) 0.0% Severe Acute Malnutrition (0.0% - 0.0%)

.VI.2.2. Risk of Mortality: Children’s MUAC

Table 10: MUAC Distribution >=75 – < 90 CM < 75 cm height ≥ 90 cm height Total MUAC (mm) height N % N % N % N % < 115 0 0 0 0 0 0 0 0 ≥115 MUAC 1 0.7 2 0.8 0 0 3 0.5 <125 ≥125 MUAC 18 13.1 3 1.2 2 1.1 23 4.1 <135 MUAC ≥ 135 118 86.1 238 98.0 179 98.9 535 95.4 TOTAL 137 24.4 243 43.3 181 32.3 561 100

According to MUAC, 0.5% children were moderately malnourished. MUAC data for 10 children was not collected due to an oversight by one team.

.VI.3. Measles Vaccination Coverage

Table 11: Measles Vaccination Coverage* Measles vaccination N % Proved by Card 226 42.6 According to the mother/caretaker 252 47.5 Not immunized 42 7.9 Don’t know 9 1.7 Total 531 99.7

* 2 data sets had wrong answers (code 4) which was applicable for children less than 9 months.

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From the above results, 90.1% children were immunized against measles while 7.9% were not immunized.

.VI.4. Composition of the households

A total of 531 households were assessed during the mortality survey

Table 12: Household composition Average per Age group N % household Under 5 years 646 24.5 1.2 Adults 1993 75.5 3.8 Total 2639 100.0 5.0

.VI.5. Stunting

Table 13: Chronic malnutrition based on Height-for-Age in z-scores Nutritional status Height for age index Z Result score

Moderate chronic malnutrition ≥ - 3.0 but <-2.0 21.0% (17.2%-24.9%)

Severe chronic malnutrition/Severely <-3 Z scores 7.5% stunted (5.0%-10.0%)

Total chronic malnutrition/Total stunted <-2 Z score 28.5% (moderate + severe) (23.5%-33.6%)

Total chronic malnutrition of 28.5% falls within the moderate category and is slightly below the national average of 38%.

.VI.6. Underweight

Table 14: Underweight based on Weight-for-Age in z-scores Description of Nutritional Status Weight for Age Index Z Result scores Severe Underweight <-3 Z scores 0.7% (-0.1- 1.5 C.I.) Moderately Underweight ≥ - 3.0 but <-2.0 7.0% (5.0- 9.1 C.I.) Total Underweight (moderate plus <-2 Z score 7.7% (5.5- 9.9 C.I.) severe)

The underweight rate of 7.7% is less than 10% cut off point for normal weight for age category.

.VII. RESULTS OF THE RETROSPECTIVE MORTALITY SURVEY

A 94 days recall period was utilized during data collection.

- 22 - As at the time of the survey, a total of 2639 were present in the 531 households assessed; 646 of them being children under five years of age. The demographic data below was also gathered from these households. 42 people had joined the households, 28 of them being children under five years of age 288 persons had left the households, 20 of them being children below 5 years of age 43 births 5 deaths were reported; 1 being a child below five years of age

0.19 [0.00– 0.41] /10,000/day and 0.17[0.00–0.47] /10,000/day crude and under five mortality rates were unveiled respectively. Analytically, both findings fall below the mortality alert and emergency levels.

.VIII. CONCLUSION

The current GAM findings of 1.8% (0.3%-3.2%) indicates a normal situation and is lower than national average for wasting of 6% (UDHS, 2006). Stunting was moderate while underweight fell within the normal range. Stunting rate of 21% despite being below the national average of 38% indicates that there is need to address causes of chronic malnutrition. The anthropometric nutritional results could be attributed to the following factors:

Disease prevalence and access to health facilities: Although the health seeking behavior was good, some of the health facilities were located far from the informal settlements compromising access to health services. Common causes of morbidity in the surveyed location such as malaria, diarrhea and acute respiratory infections (flu and cough) predisposed the community to malnutrition as explained by the synergistic cycle of malnutrition. Disease prevalence could be worsened by unhygienic practices, inadequate drugs and personnel at health facilities and distance to health facilities. Measles immunization coverage had improved to 90% and campaigns are required to reach the national target of 100%.

Food intake and food insecurity: Most households relied on purchasing food. In view of the recent increase in commodity prices and high unemployment levels (43%), food security could be compromised. Most households resorted to coping mechanisms such as borrowing food, borrowing money, reducing amount of food per meal, reducing number of meals, selling assets and eating foods of low quality. Majority of the households had no food stocks prompted by increased prices of food items, large household sizes, and low education level that affect their income earning potential.

Water and sanitation situation: Potable water is generally available in the informal settlements. However some water sources are not close to the communities. Additionally there were open and poorly constructed drainage systems and litter scattered all over the place in most informal settlements. Residents didn’t have proper garbage bins / pits. Availability and use of latrines was wanting. Many households shared one latrine while in some cases payment was required prior to latrine use.

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Child care practices: Though there is knowledge about balanced diets and hygiene, it is not always practiced. Children were also not fed frequently (1-3 meals per day) and often left at home under care of younger siblings. Mothers were often engaged in small scale business which is a major source of livelihood in the location surveyed. Complementary feeds were introduced late by some households with most diets lacking in diversity. These indicators suggest that child feeding practices are contributing to the prevalence of malnutrition, poor growth, and risk to infection which can lead to or aggravate malnutrition. Knowledge concerning the signs and symptoms of malnutrition appears to be high. Though the communities can identify whether a child is ill or suffering from malnutrition, knowledge about the prevention and treatment of malnutrition appears to be low.

- 24 - .IX. RECOMMENDATIONS

Health and Nutrition • Training of nutrition and health workers at Mulago nutrition unit and health centres on application of new WHO standards in detection and treatment of malnourished children. • Introduction of nutrition and health education sessions at community level, with an emphasis on breastfeeding, weaning, complementary foods, balanced diets and prevention of malaria, Acute Respiratory infections and diarrhoea. • Introduction of nutrition units at local health facilities (particularly government facilities) in the area so as to meet the increased demand for health and nutrition services. • Continue EPI services and monitoring trends through appropriate assessment techniques to unveil specific areas requiring attention. • Improve the availability and access to drugs in the health facilities. • Enforce regulations related to housing construction, space, playing grounds and provision of basic facilities within residential areas.

Food security There is need to support growth of small scale businesses and creation of employment opportunities to increase income of the households. The incomes derived from these activities could then enable the households to purchase food and non food items.

Water and sanitation

• Continue with sanitation programs such as water protection, safe human waste and garbage disposal. There is need to enforce regulations pertaining to latrine construction standards and waste disposal in the informal settlements.

- 25 - .X. APPENDIX

.X.1. Sample Size and Cluster Determination

Geographical unit Population size Assigned cluster KIVULU 1 800 1 KIVULU11 600 KAGUGUBE 800 INDUSTRIAL AREA 1500 2 KITAMANYANGAMBA 480 BUSIA 650 3 KIMWANYI 5000 4,5 SOWETO 500 MUZAANA ZONE 889 BLUE ROOM 675 6 CENTRAL ZONE 468 BUWANIKA 1112 KIGANDA 1010 7 MARKET VIEW 595 SCHOOL VIEW 569 MBIRO 685 8 KASAATO 1000 LUBIRI TRIANGLE 984 9 KIBWA 601 KAKAJJO 851 CHURCH ZONE 798 10 MENGO HILL 774 KAWEMPE 871 NOOK 1000 11 LUZIGE 1010 KIGULI 1125 12 SAPOBA 998 BISHOP MUKWAYA 1665 13 BUBAJWE 2019 14 INDUSTRIAL AREA 1038 KISENYI 3027 15,16 KIYAGA 1278 KIYINDI 2515 17 KULUMBA 2398 18 LULE 999 19 SEMPA 1133 NAKAMILO 4000 20,21 LUFULA 1300 22 JAMBULA 1600 MUKALAZI 1600 23 TEBUYOLEKA 4175 24,25 KATALE 250 NABUKALU 4000 26,27 MUGOWA 1000 KALIMALI 1300 28 BOKASA 1260 BUGALANYI 1800 29 St. FRANCIS 800 30 KATOOGO 3112 31 KAWAALA ROAD 1600 32 KINAWATAKA 4000 33

- 26 - .X.2. Anthropometric data collection form for children 6-59 months Anthropometric data collection form for children 6-59 months

Village/zone: ______Date: ______Cluster number: ______Team number: ______

11 Weight Height/ Length 12 Illness in the Child HH. Sex Age in Oedema MUAC Measles 13 (kg) (cm) last 2 weeks no. no. (F/M) months (Y/N) (mm) Vaccination ±0.1 kg ±0.1cm 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

Case definition: Diarrhea = Any episode of more than three stools per day; Bloody diarrhea = Any episode of more than three stools with blood stains per day; ARI = Any episode with associated fever and cough and at least one of the following signs: sputum, thoracic pain, dyspnoea, wheezing; Fever = Elevated body temperature (confirm if test was done).

11 Height measurement standing when child is ≥24 months( height proxy ≥87 cm) 12 1 = Yes (with card); 2= Yes (without card); 3= No; 4= Not applicable for children below 9 months. 13 1= No illness; 2= malaria; 3= diarrhea; 4= ARI; 5= skin disease; 6=other(specify) - 27 - .X.3. Household nutrition security data form

- 28 - .X.4. Household enumeration data collection form for a death rate calculation survey (one sheet/household)

Survey district: Village: Cluster number:

HH number: Date: Team number:

1 2 3 4 5 6 7 Present at beginning of recall Date of Born during Died during HH Present ID (include those not present now and Sex birth/or age recall the recall member now indicate which members were not present at the start of the recall period ) in years period? period 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Tally (these data are entered into ENA for each household):

Current HH members – total Current HH members - < 5 Current HH members who arrived during recall (exclude

births) Current HH members who arrived during recall - <5 Past HH members who left during recall (exclude deaths) Past HH members who left during recall - < 5 Births during recall14 Total deaths Deaths < 5

14 If the child subsequently died during the recall period tally up as death ONLY - 29 - .X.5. Enumeration data collection form for a death rate calculation survey (one sheet/cluster)

Survey Payam: Village: Cluster number:

HH number: Date: Team number: Current HH Past HH members Current HH members who who left during Births Deaths during recall N member arrived during recall recall during (exclude births) (exclude deaths) recall Total < 5 Total <5 Total < 5 Total < 5 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

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.X.6. Map of surveyed informal settlements in Kampala

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.X.7. Prevalence of acute malnutrition by age (UDHS classification) based on WFH z- scores and/or oedema

Severe wasting Moderate Normal Oedema wasting (> = -2 z score) (<-3 z-score) (>= -3 and <-2 z- score ) Age Total No. % No. % No. % No. % (mths) no. 6-11 85 0 0.0 2 2.4 83 97.6 0 0.0 12-23 164 0 0.0 4 2.4 160 97.6 0 0.0 24-35 128 0 0.0 0 0.0 128 100.0 0 0.0 36-47 120 0 0.0 0 0.0 120 100.0 0 0.0 48-59 74 0 0.0 4 5.4 70 94.6 0 0.0 Total 571 0 0.0 10 1.8 561 98.2 0 0.0

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.X.8. Local calendar of events, Kampala District June 2009

Annual Events 2004 2005 2006 2007 2008 2009 .I.5. Swearing in for .I. .I.2. New Year’s Multiparty Presidential Feast of National President .I.3. 54 42 30 .I.4. 18 6 an Day elections Unity Barrack Obama Cleaning the field, Fire outbreak in St. opening of schools, Feb 53 41 29 17 Balikuddembe 5 Beginning of rainy (Owino) market season Church roof collapsed killed 27 people in Women’s day, Sea- Beginning of rainy Beginning of rainy Mar 52 Kampala town 40 28 16 4 nut season season season (Kalerwe), National LC 3 & LC5 elections Easter, White-aunt season, April fool’s Fire outbreak at Buddo April 51 39 27 15 day, 13th Kabaka’s Junior Primary School birth day 3 Labour day, Mango National Child health May 50 38 26 14 2 Season days 3rd Martyrs day, Graduated Tax June 49 37 25 13 1 9th heroes day scrapped Harvest of Millet, July 48 36 24 Harvesting period 0 5th Ekyigunda 12 Uganda and LRA rebels signed a truce Plane crash killed 72 Aug .I.6. Ascension Day 59 John Garang died 47 35 23 11 to end the bitter war, soldiers Peace talks in Juba Flooding washed Weeding of 2nd Sept 58 46 9th Independence Day 34 away towns and lives 22 10 session in Teso region Death of former 9th Independence Museveni meets LRA Oct 57 President Milton 45 33 21 9 Day rebels Obote (10th Oct)

Election day for Dr. Kizza Besigye CHOGM hosted in Nov 56 44 32 20 President Barrack 8 arrested, Muloki’s wife Uganda Obama lady Alice died Peace talk failed and Sadam Hussein Presidential elections Dec .I.7. Christmas Museveni declared 55 43 31 19 7 executed in Kenya war

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