NUTRITIONAL ANTHROPOMETRIC SURVEY

FINAL REPORT

IDP CAMPS AND RESETTLEMENT AREAS OF APAC & OYAM DISTRICTS, NORTHERN UGANDA

APRIL-MAY 2008

Funded by:

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ACKNOWLEDGEMENTS

ACF would like to express its deep gratitude to all partners and people who participated in the nutritional survey, ensuring its quality and success:

‐ Apac and Oyam DHO staff who have shown high commitment during the survey ‐ ACF logistic and administrative teams in Lira and Kampala who worked hard on daily basis to make the

survey possible ‐ ACF nutrition teams from Lira office and nutritional centres in Lira, Apac and Oyam who were the pillars

of this survey ‐ Apac and Oyam surveyors who participated actively in the survey teams ‐ Village authorities who voluntarily helped the teams in their daily field work ‐ Mothers and fathers who willingly allowed the teams to measure their children and patiently participated

in the interviews sharing valuable information without which the survey would not have been possible.

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Table of content

I EXECUTIVE SUMMARY .................................................................................................................................. 4 II INTRODUCTION .............................................................................................................................................. 7 III OBJECTIVES .............................................................................................................................................. 7 IV METHODOLOGY ........................................................................................................................................ 8

IV.1 Type of Survey and Sample Size .............................................................................................................. 8 IV.2 Data Collection .......................................................................................................................................... 8 IV.3 Indicators, Guidelines, and Formula’s Used ............................................................................................. 9

IV.3.1 Acute Malnutrition .............................................................................................................................. 9 IV.3.2 Mortality ............................................................................................................................................ 10

IV.4 Field Work ............................................................................................................................................... 10 IV.5 Data Analysis .......................................................................................................................................... 10

V RESULTS OF THE ANTHROPOMETRIC SURVEY ..................................................................................... 10 V.1 Distribution by Age and Gender .............................................................................................................. 10 V.2 Anthropometric Analysis ......................................................................................................................... 11

V.2.1 Distribution of Acute Malnutrition in Z-scores .................................................................................. 11 V.2.2 Distribution of Acute Malnutrition in Weight-for-height percentage of median ................................ 13 V.2.3 Risk of Mortality: Mid-Upper Arm Circumference (MUAC) .............................................................. 13 V.2.4 Measles Vaccination Coverage ....................................................................................................... 14

V.3 Retrospective Mortality Survey ............................................................................................................... 14 V.4 Additional Household Information ........................................................................................................... 15

V.4.1 Household characteristics ................................................................................................................ 15 V.4.2 Food security .................................................................................................................................... 15

V.5 Water and Sanitation ............................................................................................................................... 16 VI DISCUSSION ............................................................................................................................................. 17 VII RECOMMENDATIONS ............................................................................................................................. 19 VIII ANNEXES .................................................................................................................................................. 20

VIII.1 Annex I. Assignment of Clusters, Apac and Oyam districts ................................................................ 20 VIII.2 Annex II:. Selected villages, Apac and Oyam districts ........................................................................ 22 VIII.3 Annex III: Household Selection ........................................................................................................... 23 VIII.4 Annex IV: Anthropometric survey questionnaire ................................................................................. 24 VIII.5 Annex IV: Calendar of Events in Apac/Oyam Districts ........................................................................ 25 VIII.6 Annex VI: Household enumeration data collection form for a death rate calculation survey (one sheet/household) ................................................................................................................................................ 26 VIII.7 Annex VII: Household Questionnaire .................................................................................................. 27

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I Executive summary

Apac and Oyam districts are located in the Lango sub-region of northern Uganda. The northern region of Uganda has witnessed a tragic armed conflict for almost two decades, conflict perpetrated by the Lord's Resistance Army (LRA) led by Joseph Kony against the Government of Uganda. First displacements occurred in the early 90’s in the districts of Gulu, Amuru, Kitgum and Pader. In 2002/2003, insecurity reached the districts of Apac, Oyam and Lira leading to massive displacements. Later, with the initiation of peace talks in 2006 there were reduced threats of LRA attacks and since the beginning of 2007 many IDPs began returning to their places of origin (i.e. their home villages or parish of origin). By the time the surveys were carried in the three districts: Oyam, Apac and Lira, all the former IDPS had returned to their places of origin, and all the IDP camps in these districts were closed by the Government. Since 1981 Action Against Hunger (ACF-USA) has been present in the North of Uganda to assist the vulnerable population with first intervention in Karamoja region. ACF started to support Northern Uganda war-affected populations in 1997. ACF works in the following sectors:

• Nutrition: 5 SFC and 5 OTP in Acokara, Ajaga, Ngai, Otwal and Alito. Moreover, a community approach activity started in 2007 carrying out training of the community on how to detect and refer acutely malnourished children less than 5.

• Food security: seed distribution, seed security training, seed multiplication, animal traction training, oxen distribution and income generating activities.

• Water and sanitation: hygiene promotion, latrines and borehole construction and rehabilitation. The last nutritional survey conducted in Apac and Oyam districts by ACF in May 2007 indicated rates of global and severe acute malnutrition of 4.6% (CI: 3-6.3%) and 0.9% (CI: 0.0-1.9%) respectively (results presented in WH Z-scores with a confidence interval 95%, NCHS reference table). An anthropometric nutrition survey was implemented in Apac / Oyam districts from April 23rd to May 3rd 2008. This survey is part of the of nutritional surveillance program of ACF.

OBJECTIVES

- To evaluate the nutritional status of children aged 6 to 59 months. - To estimate measles immunization coverage of children aged 9 to 59 months. - To estimate crude mortality rates through a retrospective mortality survey.

METHODOLOGY

Two-stage cluster sampling using SMART methodology was applied to randomly identify clusters with the probability of being selected proportional to the population size in each cluster. At the cluster level, households were randomly selected and surveyed using the EPI method. A household was defined as all the inhabitants using the same cooking pot. All children aged between 6 and 59 months of the same family, were included in the survey for anthropometric measurements. A retrospective mortality survey over the past three months and a half was undertaken alongside the anthropometric survey, using SMART methodology.

Anthropometric and mortality data were analyzed using Nutrisurvey version October 2007 software.

FIELD WORK

The survey was carried out by four teams; each team comprising four to five members (one team leader, two measurers and one surveyor for food security and water and sanitation components) completed the data collection. The nutritional survey teams comprised ACF field staff (working in nutrition feeding centers) and DDHS staff. All surveyors participated in four days of training including training on the standardization of

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anthropometric measurements and two days in the field for pilot survey. The supervision of the survey was conducted by the 2 Nutrition Program Managers and the Medical and Nutrition Coordinator.

The surveys were carried out from April 23rd to May 3rd 2008.

RESULTS

873 children were measured during the assessment. The data of 7 of them were not used for the analysis, as they did not meet eligibility criteria or were incorrect or incomplete. The following analysis is therefore done on the data of 866 children.

INDEX INDICATORS RESULTS (n=866)

NCHS

Z- scores

Global Acute Malnutrition W/H< -2 z and/or oedema

5.9% [4.1% - 7.7 %]

Severe Acute Malnutrition W/H < -3 z and/or oedema

0.3% [0.0% - 0.7%]

% Median

Global Acute Malnutrition W/H < 80% and/or oedema

3.3% [1.8% - 4.8%]

Severe Acute Malnutrition W/H < 70% and/or oedema

0.0% [0.0% - 0.0%]

WHO Z-scores

Global Acute Malnutrition W/H< -2 z and/or oedema

7.2% [5.2% - 9.1%]

Severe Acute Malnutrition W/H < -3 z and/or oedema

0.7% [0.2% - 1.2%]

MUAC Height> 65 cm

Global Acute Malnutrition MUAC (<120) 5.7%

Severe Acute Malnutrition MUAC (<110) 0.6%

Total crude retrospective mortality (last 3 months) /10,000/day Under five crude retrospective mortality /10,000/day

0.71 [0.43-0.99] 1.75 [0.89-2.61]

Measles immunization coverage (N=803 children ≥ 9months old)

By card According to caretaker1 Not immunized

37.8% 45.8% 16.3%

Table 1: Results summary, Apac and Oyam Districts, May 2008

The results of the previous nutritional surveys allows for an analysis of the evolution of the nutritional situation in Apac and Oyam districts:

Feb-05 (n=956)

Apr-06 (n=900)

Apr/May-07 (n=669)

Apr/May-08 (n=866)

Global Acute Malnutrition (W / H <-2 Z-scores and/or edema)

4.4% (2.8%-6.8%)

4.7% (2.9% - 7.2%)

4.6% (3.0 – 6.3%)

5.9% (4.1 – 7.7%)

Severe Acute Malnutrition (W / H <-3 Z-scores and/or edema)

1.4% (0.5%-3.0%)

0.8% (0.2% - 2.3%)

0.9% (0.0% - 1.9%)

0.3% (0.0% - 0.7%)

Measles vaccination coverage

Confirmed by card 27% 54% 30% 38%

Not confirmed

73% 33% 56% 46%

Table 2: Evolution of acute malnutrition rates, Apac and Oyam Districts, 2005 to 2008 (NCHS Reference, z-scores)

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The results of the 2008 survey show a slight though not significant increase in the prevalence of acute malnutrition as compared to the rates found in the previous years Although the rates of malnutrition are low, there are a number of factors that need to be taken into consideration:

Health Access: Anemia is widely prevalent. Malaria, diarrhea and respiratory tract infections are among the main types of diseases reported among children in both districts. HIV/AIDS is also another major factor. The district often has a shortage of drugs, further intensifying infections and also discouraging the population from seeking health services.

Water and Sanitation: Nearly half of the survey respondents reported collecting water from

unprotected water points. Access to clean and safe water can contribute to the reduction of morbidity due to water-borne diseases, which can reduce susceptibility to malnutrition in a vulnerable population. Hand washing practices need to be strengthened, particularly after latrine use.

Food Security: People reported low food stocks. Some reported getting food on credit, which indicates

that some households could be more vulnerable than others. Moreover, when food is inadequate, people tend to buy less expensive food, reduce the number of meals per day or tend to reduce portion size, which is likely to affect dietary quantity and quality.

Nutrition and Health Education: Children were also not fed frequently. They were most likely to be

left under the care of slightly older siblings. They were also more likely to be fed only at the same time as the adults (1-2 times a day). These suggest that the children feeding practices combined with poor child care and hygiene practices increase the risk of infection among children which can lead to or aggravate malnutrition.

RECOMMENDATIONS

The global acute malnutrition rate is below the critical level. A more global approach to managing malnutrition is necessary: Health and Nutrition:

- To continue the treatment of severely and moderately malnourished children under 5 years old in therapeutic and outpatient centers.

- To reinforce the capacity of MOH staff (hospital and health center staff) in the management of acute malnutrition. The health staff at all levels including district hospitals and health centers (including HCII, HCIII and HC IV) need to be trained on detection and management of acute malnutrition.

- To strengthen the capacity of communities by training VHTs/community volunteers on how to detect and refer acutely malnourished children less than 5 years to enable early detection and referral

- To monitor the nutritional status of the population on an annual basis. - To conduct nutrition surveillance and to train MoH staff in nutrition surveillance to better monitor the

nutritional status and the factors contributing to malnutrition - To continue conducting EPI campaigns whenever necessary with systematic routine immunization

activities to ensure all children are vaccinated against childhood diseases - To promote nutrition and healthy behaviors in the communities and health centers, with an emphasis on

breastfeeding, weaning, complementary foods, and balanced diets Food Security:

- To continue with programs devoted to the generation of incomes at household level Water and Sanitation:

- To emphasize on the promotion of adequate hygiene practices - To improve the access to safe drinking water at communities level

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II INTRODUCTION

Apac and Oyam districts belong to the Lango sub-region of Northern Uganda. Oyam district was created in 2006 from the north of Apac district. The native inhabitants of Apac and Oyam are Langi and are the main ethnic group of the region.

Northern Uganda witnessed war for more than twenty years. Initially rooted in a popular rebellion against President Yoweri Museveni’s National Resistance Movement (NRM) government, the conflict was transformed by Joseph Kony’s Lord’s Resistance Army (LRA) into a brutally violent war in which civilians from northern districts were the main victims. There were displacements with the first displacements occurring in the early 90’s in the Northern districts of Gulu, Amuru, Kitgum and Pader. In 2002/2003, insecurity reached the districts of Apac, Oyam and Lira, leading again to massive displacements. Urban areas and trading centres were soon surrounded by huge IDP camps. Trading centres and health facilities were quickly overloaded. Access to safe water and sanitation facilities deteriorated as existing facilities were not sufficient for such an increased population. In addition, most IDP’s lost access to cultivation or remained with a very limited access to fields. Some of the distinct features of displacement in Apac and Oyam include:

‐ In terms of geography, the area affected by displacement is small. IDP camps were settled closer to people’s areas of origin compared to other affected districts

‐ There were 18 camps in Apac and Oyam districts with the majority located in Oyam district ‐ Humanitarian assistance was provided at a much lower level than for IDP’s in other districts; no general

food distribution ever occurred, similarly basic health facilities, infrastructures, water and sanitation programs and food security activities never reached the level noticed in other surrounding districts with similar displacement problems.

Beginning of 2007, IDP’s from Apac and Oyam camps started returning to their villages of origin following a significant improvement of the security situation and the recommendations from Ugandan authorities. All the IDP camps in Apac and Oyam are officially closed2. The agricultural and commercial activities have gradually resumed in the region since the beginning of the returning process.

ACF has been implementing nutrition programs in Apac and Oyam districts since 2004. Initially 5 Supplementary Feeding Centres (SFC) were opened. 3 Outpatient Therapeutic Program (OTP) centres were opened in mid-2006 to ensure the access to treatment for severely malnourished children. Currently there are 5 SFCs and 5 OTPs functioning in Apac and Oyam districts to manage acute malnourished children. These centres are located in the district health facilities in order to facilitate future handover and to ensure access to health care for beneficiaries. In April 2007, a Therapeutic Feeding Centre (TFC) was opened in Aboke Health Centre IV in Apac district to provide in-patient treatment for severely acute malnourished children. So far, compared with Gulu, Amuru and Lira districts, nutritional centres in Apac and Oyam have consistently shown much higher levels of admissions since 2004.

ACF also implements water and sanitation and food security programs in these districts.

Nutrition surveys have been conducted in Apac and Oyam districts since 2005 in order to monitor the evolution of the nutrition situation. The present survey took place when all camps were officially closed and people have returned to their village of origin. As the nutritional status of people in Apac and Oyam districts could be assumed to be similar and also in order to be able to compare nutritional data with those collected during the previous years, the current survey was conducted jointly for both districts.

III OBJECTIVES

The specific objectives of the nutritional survey were: ‐ To evaluate the nutritional status of children aged 6 to 59 months ‐ To estimate the measles immunization coverage of children aged 9 to 59 months ‐ To estimate the crude mortality rate through a retrospective survey

2 IASC Working Group. Population Movement_IDP, June 2008

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IV METHODOLOGY

IV.1 Type of Survey and Sample Size

A two-stage cluster sampling method was used. The anthropometric survey targeted children aged between 6 months and 59 months utilizing the SMART survey methodology. The survey was conducted from April 23rd to May 3rd, 2008. Selection of villages was done using data provided by district (DDHS) authorities. In addition, data were collected from local leaders. The geographical units and their respective population were then input into the SMART ENA software for planning the survey:

1. Cluster election: At the first stage, the sample size was determined by inputting necessary information in the ENA software for both anthropometric and mortality surveys. This information included estimated population sizes, estimated prevalence rates of mortality and malnutrition, the desired precision and design effect. Global malnutrition prevalence was expected at 10% with 3% precision and design effect of 2. Hence the required sample size was 765. Clusters were randomly selected with the chance of a cluster being selected being proportional to the size of the population. Population figures were available at the parish level. Villages within the parishes were the clusters then randomly selected. The number of clusters was calculated based on the capacity of the teams being able to reach the number of children and people to survey per day. Considering that each team could survey 20 children per day and in order to ensure a sufficient number of children, 40 clusters were selected with margin of safety to take care of unexpected drawbacks. List of selected clusters is available in Appendix 1 (Appendix 1a, 1b).

2. Children selection: In each cluster, households were randomly selected and surveyed using the EPI method. The survey team identified the centre of the village with the assistance of the leader. A pen was spun and the team walked in the direction of the pen, using reference points to maintain a straight line to the border of the village. At the border, the team spun the pen again and followed the direction of the pen to the opposite border. As they walked, each house was numbered that was on the line. In villages where the distance between houses was vast, the team drew a map of the houses and numbered them on the paper. Upon reaching the opposite border of the location, the team used a random number table to blindly select a number in the range of houses counted. The number selected indicated the first house to be sampled. From this house, the team continued moving right for the next house to be sampled. When the houses in the village were widely spread out, if there were no more houses on the right, then the next closest house either on the right or left was selected (Appendix II, household selection methodology).

All children in the selected household between the ages of 6 and 59 months were included in the survey. A household was defined as all inhabitants using the same cooking pot. The selected households were interviewed for the retrospective mortality questionnaire whether or not they had eligible children for the anthropometric survey.

IV.2 Data Collection

For each selected child, information was collected during the anthropometric survey using an anthropometric questionnaire (Appendix III):

Age: recorded with the help of local calendar of events (Appendix IV) Gender: male or female Weight: children were weighed without clothes with a Salter balance of 25 kg (precision of 100g)

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Height: children were measured on a measuring board (precision of 0.1 cm). Children less than 85 cm were measured lying down while those greater than or equal to 85 cm were measured standing up

Mid-Upper Arm Circumference: MUAC was measured at mid-point of left upper arm for measured children (precision of 0.1 cm)

Bilateral edema: assessed by the application of normal thumb pressure for at least 3 second on both feet

In addition, a retrospective mortality survey (Appendix V) and household questionnaire (Appendix VI) assessments were conducted. Measles vaccination was assessed by checking for measles vaccination on health cards and asking caretakers.

IV.3 Indicators, Guidelines, and Formula’s Used

IV.3.1 Acute Malnutrition

Weight for Height Index

Acute malnutrition rates are estimated from the weight for height (WFH) index values combined with the presence of edema. The WFH indices are expressed in both Z-scores and percentage of the median, according to both NCHS3 and WHO references4. The complete analysis is done with the NCHS reference. The expression in Z-scores has mainly statistical meaning, and allows inter-study comparison. The percentage of the median, on the other hand, is used for the identification criteria of acute malnutrition in nutrition programs. Guidelines for the results expressed in Z-scores: • Severe malnutrition is defined by WFH < -3 SD and/or existing bilateral Edemas on the lower limbs

Moderate malnutrition is defined by WFH < -2 SD and ≥ -3 SD and no Edemas. • Global acute malnutrition is defined by WFH < -2 SD and/or existing bilateral Edemas. Guidelines for the results expressed in percentage of median: • Severe malnutrition is defined by WFH < 70 % and/or existing bilateral edemas on the lower limbs • Moderate malnutrition is defined by WFH < 80 % and ≥ 70 % and no edemas. • Global acute malnutrition is defined by WFH <80% and/or existing bilateral edemas

Mid-Upper Arm Circumference (MUAC)

The weight for height index is the most appropriate index to quantify wasting in a population in emergency situations where acute forms of malnutrition are the predominant pattern. However, the mid-upper arm circumference (MUAC) is a useful tool for rapid screening of children at a higher risk of mortality. MUAC measurements are significant for children with a height of 65 cm or one year and above. The guidelines are as follows: MUAC < 110 mm severe malnutrition and high risk of mortality MUAC ≥ 110 mm and <120 mm moderate malnutrition and moderate risk of mortality MUAC ≥ 120 mm and <125 mm high risk of malnutrition MUAC ≥ 125 mm and <135 mm moderate risk of malnutrition MUAC ≥ 135 mm adequate’ nutritional status

3 NCHS: National Center for Health Statistics (1977) NCHS growth curves for children birth-18 years. United States. Vital Health Statistics. 165, 11-74. 4 WHO reference, 2005

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IV.3.2 Mortality

Mortality data was collected using Standardized Monitoring and Assessment of Relief mortality questionnaire. The crude mortality rate (CMR) is determined for the entire population surveyed for a given period. The CMR is calculated using Nutrisurvey for SMART software for Emergency Nutrition Assessment. The formula below is applied: Crude Mortality Rate (CMR) = 10,000/a*f/ (b+f/2-e/2+d/2-c/2), Where: a = Number of recall days 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. The thresholds are defined as follows5: 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

IV.4 Field Work

Four teams comprising two measurers, one anthropometric data recorder and one mortality surveyor conducted the surveys. The teams were composed of ACF staff (nutrition and food security) and DDHS staff from Apac and Oyam. All surveyors have participated in four days of training including theoretical and practical training on the standardization of anthropometric measurements and pilot survey in the field. The supervision of the survey was conducted by the 2 Nutrition Program Managers and the Medical and Nutrition Coordinator of ACF. As people were busy in the gardens, it could have been difficult to find many caretakers in the villages. However, proper announcement and active participation of the local leaders in each selected cluster reduced this problem, although survey teams sometimes waited for people to be back home from the gardens.

IV.5 Data Analysis

Data processing and analysis for both anthropometric and mortality were carried out using Nutrisurvey (ENA) for SMART (October 2007 version) using both NCHS and WHO references. Excel was used to carry out analysis on MUAC, measles immunization coverage and household questionnaire.

V RESULTS OF THE ANTHROPOMETRIC SURVEY

V.1 Distribution by Age and Gender

873 children between 6 and 59 months were measured during the survey. The data of 7 of them were excluded from the analysis due to incoherence. The following analysis is based on the data of 866 children.

5 Health and nutrition information systems among refugees and displaced persons, Workshop report on refugee’s nutrition, ACC / SCN, Nov 95.

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Age groups Boys Girls Total Ratio

no. % no. % no. % Boy / girl6-17 months 138 54.8 114 45.2 252 29.1 1.2 18-29 months 111 48.5 118 51.5 229 26.4 0.9 30-41 months 88 55.0 72 45.0 160 18.5 1.2 42-53 months 80 49.7 81 50.3 161 18.6 1.0 54-59 months 36 56.3 28 43.8 64 7.4 1.3

Total 453 52.3 413 47.7 866 100.0 1.1

Table 3: Distribution by age and sex, Apac and Oyam districts

The age ratio between 6-29m to 30-59m is 1.24, indicating that there are slightly younger children compared to older children. As all caretakers did not have health cards, there is a possibility of caretakers not being able to recall the exact date of birth. The overall sex ratio (male to female ratio) is 1.09 and is acceptable.

Figure 1: Distribution by age and gender, Apac and Oyam, survey April-May 2008

V.2 Anthropometric Analysis

V.2.1 Distribution of Acute Malnutrition in Z-scores

The Global Acute Malnutrition (GAM) rate as assessed by weight for height z-score was 5.9% while the Severe Acute Malnutrition (SAM) was 0.3% for children aged 6 to 59 months. Although the GAM rate for boys is higher than that for girls, it is not significantly different.

Alln = 866

Boysn = 453

Girlsn = 413

Prevalence of global malnutrition (<-2 z-score and/or oedema)

(51) 5.9 % (4.1% - 7.7%)

(36) 7.9 % (5.5% - 10.4%)

(15) 3.6 % (1.6% - 5.6%)

Prevalence of moderate malnutrition (<-2 z-score and >=-3 z-score, no oedema)

(48) 5.5 % (3.7% - 7.3%)

(34) 7.5 % (5.1 - 9.9%)

(14) 3.4 % (1.4% - 5.4%)

Prevalence of severe malnutrition (<-3 z-score and/or oedema)

(3) 0.3 % (0.0% - 0.7%)

(2) 0.4 % (0.0% - 1.2%)

(1) 0.2 % (0.0% - 0.8%)

Table 4: Prevalence of acute malnutrition based on weight-for-height z-scores (and/or oedema) by sex

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Figure 2: Z-scores distribution, Weight for Height, Z-scores, Apac and Oyam, April-May 2008

Children aged 6 to 29 months were noticed as more likely to be malnourished compared to older children aged 30 to 59 months. Severe

wasting (<-3 z-score)

Moderate wasting (>= -3 and <-2 z-

score ) Normal

(> = -2 z score) Oedema

Age (mths)

Total no. No. % No. % No. % No. %

6-17 252 0 0.0 29 11.5 223 88.5 0 0.0 18-29 229 3 1.3 13 5.7 213 93.0 0 0.0 30-41 160 0 0.0 4 2.5 156 97.5 0 0.0 42-53 161 0 0.0 2 1.2 159 98.8 0 0.0 54-59 64 0 0.0 0 0.0 64 100.0 0 0.0 Total 866 3 0.3 48 5.5 815 94.1 0 0.0

Table 5: Weight for height distribution by age in z-scores and/or oedema, Apac and Oyam (NCHS Reference)

<-3 z-score >=-3 z-score

Oedema present Marasmic kwashiorkor 0 (0.0 %)

Kwashiorkor 0 (0.0 %)

Oedema absent Marasmic 3 (0.3 %)

Normal 863 (99.7 %)

Table 6: Distribution of acute malnutrition and oedema based on weight-for-height z-scores

NCHS Reference WHO Reference

Global acute malnutrition 5.9% (4.1%-7.7%)

7.1% (5.2% - 9.1%)

Severe acute malnutrition 0.3% (0.0%-0.7%)

0.7% (0.2 - 1.2%)

Table 7: Global and Severe Acute Malnutrition in Z-scores

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V.2.2 Distribution of Acute Malnutrition in Weight-for-height percentage of median

The GAM rate as assessed by weight for height percentage of median was 3.3% for children aged 6 to 59 months and was mainly associated with moderate acute malnutrition. There were no children severely malnourished screened. The GAM rate indicates acceptable level according to WHO thresholds. Children between 6 to 29 months are more likely to be malnourished than the older children. Severe wasting

(<70% median) Moderate wasting (>=70% and <80%

median) Normal

(>=80% median) Oedema

Age (mths)

Total no. No. % No. % No. % No. %

6-17 252 0 0.0 15 6.0 237 94.0 0 0.0 18-29 229 0 0.0 12 5.2 217 94.8 0 0.0 30-41 160 0 0.0 2 1.3 158 98.8 0 0.0 42-53 161 0 0.0 0 0.0 161 100.0 0 0.0 54-59 64 0 0.0 0 0.0 64 100.0 0 0.0 Total 866 0 0.0 29 3.3 837 96.7 0 0.0

Table 8: Distribution of acute malnutrition based on the percentage of the median and/or oedema, Apac and Oyam districts, April-May 2008 (NCHS Reference)

<80% >=80%

Edema present Marasmic kwashiorkor 0 (0.0 %)

Kwashiorkor 0 (0.0 %)

Edema absent Marasmic 29 (3.3%)

Normal 837 (96.7%)

Table 9: Weight for height vs. Oedema in Lira District in percentage of the median (NCHS Reference)

n = 866Prevalence of global acute malnutrition (<80% and/or oedema) (29) 3.3 %

(1.8 - 4.9 95% C.I.)

Prevalence of moderate acute malnutrition (<80% and >= 70%, no oedema) (29) 3.3 %

(1.8 - 4.9 95% C.I.)

Prevalence of severe acute malnutrition (<70% and/or oedema)

(0) 0.0 % (0.0 - 0.0 95% C.I.)

Table 10: Global and Severe Acute Malnutrition in % of the median

NCHS Reference WHO Reference

Global acute malnutrition 3.30% [1.8% - 4.8%]

1.2 % (0.4% - 1.9%)

Severe acute malnutrition 0.0% [0.0% - 0.0%]

0.0% (0.0% - 0.0%)

Table 11: Global and Severe Acute Malnutrition in percentage of median

V.2.3 Risk of Mortality: Mid-Upper Arm Circumference (MUAC)

The data of all children whose height >65cms are analyzed in the table below. The MUAC analysis reveals that 5.6% of the children measured are malnourished according to the MUAC criteria.

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MUAC (mm) > 65 - < 75 cm >=75 – < 90 cm >=90 cm Total

N % N % N % N %

< 110 2 1.0 3 0.8 0 0.0 5 0.6

110<= MUAC <120 29 14.6 13 3.6 0 0.0 42 5.0

120<= MUAC <125 35 17.7 12 3.3 2 0.7 49 5.8

125<=MUAC <135 58 29.3 71 19.8 20 7.1 149 17.8

>= 135 74 37.4 260 72.4 259 92.2 593 70.8

TOTAL 198 100.0 359 100.0 281 100.0 838 100.0

Table 12: MUAC Distribution, Apac and Oyam districts, April-May 2008

V.2.4 Measles Vaccination Coverage

The source of information on immunization was either the child’s health card or the mother’s recall. A child was considered fully vaccinated if he had received the last dose of the EPI (from 9 months of age, according to the national protocol). It is important to mention however, that these results should be interpreted with caution since they are based on the caretaker’s recall, when no health card is available.

Population >=9 months N=799 Immunized with card 37.8% Immunized without card 45.8% Not immunized 16.3%

Table 13: Measles Vaccination Coverage in all the divisions surveyed

V.3 Retrospective Mortality Survey

The crude mortality rate was calculated from the figures collected from families with or without children under 5 years, over the past 112 days. The recall period was chosen in order to fit with January 1st, 2008.

Demographic data Current resident HH 4691 Current resident < 5 years old 1038 People who joined HH 204 < 5 years old who joined HH 24 People who left HH 378 < 5 years old who left HH 33 Birth 65 Death 38 Death < 5 years old 20 CMR (deaths /10,000 people/day) 0.71 (0.43-0.99) U5MR (deaths in children<5/ 10000 / day ) 1.75 (0.89-2.61)

Table 14: Demographic information

The overall Crude Mortality Rate and the under-5 mortality rates were below the alert levels of 1/10,000 and 2/10,000 per day respectively.

15

V.4 Additional Household Information

V.4.1 Household characteristics

The majority of the households were headed by males (80.8%). Women (18.3%) and grandparents (0.9%) were also reported as being the head of households. Most heads of households had primary school education (68.2%) followed by secondary education (20.6%) and no education (7.7%). The majority reported being residents of villages (92.2%) and returnees (7.5%).

V.4.2 Food security

Sources of income

Although a household may have several sources of income, the top 3 main sources of income reported by households were crop sales (41%), casual labor (24%) and petty trade (12%).

Figure 4: Sources of Income

Livestock

Nearly three-fourth (73.6%) of the respondents reported owning animals. The majority owned chicken (81.4%) followed by goats (54.7%) and cattle (38.0%). More than half of the households (58.8%) who have animals reported owning more than 1 type of animals. Food stocks Around 84.1% reported having no stock (54.8%) or less than 1 month stock (29.3%). This was based on self-report and the surveyors did not verify the declared stocks. The low food stock levels corroborate the assumed importance of market purchase of food.

Coping strategies

When food is inadequate, the top three responses for coping mechanisms included reducing the number of meals (53.8%), increasing the casual labor (34.5%) and buying less expensive food (32.6%). Reducing number of meals per day and purchasing less expensive food (likely to be less nutritious) affects the diet quantity and

16

quality. Also, people tend to harvest immature crops (15.4%), affecting as well the sources of income and the diets quality. Furthermore, many reported buying food on credit (37.7%). People also reported borrowing or receiving food (11.4%). Although the sources of borrowing are not known, it indicates the presence of a social network. However, it could be that the respondents were also borrowing on credit. This also corroborates the importance of market purchase (and credit) at a time when there are limited food stores. The majority of the respondents (99.4%) reported not receiving any food aid.

Dietary diversity

Cereals (13.3%), vegetables (29.7%) and legumes (43.3%) were among the most commonly consumed food sources reported. There was a low level of food diversity with the majority (84.6%) reporting consuming 1 to 3 food group sources. Those who own animals reported consuming poultry and cattle, but only a small percentage reported consuming meat/chicken/eggs and milk. It is possible that the products are being sold. Alternatively, due to the recall method, there could be errors in recall on the part of the respondent and in probing by the interviewers. It is also possible that the respondents did not have these foods the previous day. Lack of adequate nutrition practices for children was apparent. Children were fed at the same time as the caretakers. Children were given 1-2 (88.5%) meals per day. Adults (92.5%) reported having 1-2 meals per day.

V.5 Water and Sanitation

Water source

Less than half of the households surveyed (43%) indicated that they collect water from a protected water point (protected spring, hand pump, or tap). The statement of the household respondent was taken into consideration and could not be verified.

Latrine type

Nearly three-quarters of the surveyed households (74%) reported having a household latrine. Nearly 14% used the bush while others used group latrine (6%) or neighbor’s (7%) latrines. Among those who do not have household latrines, the main reason for not having it included lack of money (41%), lack of materials (26%) and lack of knowledge (22%).

Hand washing Practices

People reported washing hands before eating (85%), after eating (75%), before food preparation (31%), after use of latrine (27%), after working in the garden (10%), after handling animals (20%), and after changing the child (6%). Hand washing practices, although present, need to be reinforced, particularly hand washing after latrine use and changing the child.

17

VI DISCUSSION

The results (expressed in Z-score) of previous nutritional surveys allows for an analysis of the evolution of the nutritional situation in Apac and Oyam districts. The results of the 2008 survey show a slight though not significant increase in the prevalence of acute malnutrition as compared to the rates found in the previous years:

Feb-05 (n=956)

Apr-06 (n=900)

Apr-07 (n=669)

Apr-08 (n=866)

Global Acute Malnutrition (W/H <-2Z-scores and/or oedema)

4.4% (2.8%-6.8%)

4.7% (2.9%-7.2%)

4.6% (3.0-6.3%)

5.9% (4.1-7.7%)

Severe Acute Malnutrition (W/H <-3Z-scores and/or oedema

1.4% (0.5%-3.0%)

0.8% (0.2%-2.3%)

0.9% (0.0%-1.9%)

0.3% (0.0-0.7%)

Measles vaccination coverage

Confirmed by card 27% 54% 30% 37.8%

Not confirmed 73% 33% 56% 45.8%

Table 15: Evolution of acute malnutrition rates, Apac and Oyam districts, 2005-2008.6

Similarly, the WHO reference indicator shows that the prevalence of acute malnutrition is 2008 is 7.2% compared to 5.4% in 2007 which is not significantly high. The malnutrition rates as indicated by the anthropometric survey shows the prevalence of acute malnutrition to be lower than the WHO emergency thresholds of 15%. Although the survey gives an indication of the prevalence rate, additional sources of information as shown by the attendance in nutritional centres need to be taken into consideration. Incidence rates as indicated by attendance in nutritional centres implies the need for continued support for the time being until the population is better able to sustain itself further through several food security and water and sanitation activities.

Admissions in ACF nutritional centers, Apac & Oyam districts, 2007 / 2008

020406080

100120140160180

Janu

ary

Febr

uary

Mar

ch

Apr

il

May

June

July

Aug

ust

Sep

tem

ber

Oct

ober

Nov

embe

r

Dec

embe

r

Janu

ary

Febr

uary

Mar

ch

Apr

il

May

June

months

nb o

f adm

issi

ons

in T

FP

0

500

1000

1500

2000

2500

nb o

f adm

issi

ons

in S

FP

TFPSFP

Fig.5. Number of beneficiaries in charge in ACF Nutritional Centres, 2007-2008, Apac and Oyam districts 6 Although the geographical areas surveyed in 2005 and 2006 surveys are not the same in 2007 and in 2008, the targeted people are the same, whether in camps or returned to their village of origin.

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Since January 2007, 12,858 moderately malnourished children and 1,542 severely malnourished children were treated in the nutrition centres in Apac and Oyam.

Majority of the respondents had reported having food stocks that would be available for less than 1 month period. Many are likely to face food shortage until the next harvest period. One of the main sources of income appears to be through crop sales. Usually crops from the first harvest period (June-July) are sold while crops from the second harvest (December) are kept for the household. In 2007, considerable amounts of the second harvest crops were lost due to floods and rains. This could partly explain the low food stocks reported. Alternatively, many may be dependent on income from petty trade and casual labor to purchase food. However, it is likely that the ability to purchase food in adequate quantity and quality will be limited. This is reflected in poor food practices. There is less food diversity. Although actual food intake was not assessed, it is apparent that with just 1-2 meals per day, quality and quantity of children’s diet is far from satisfactory. It seems to be a need for better child and infant feeding practices. Furthermore, child care practices are inadequate.

Considerable proportion of the respondents does not have access to safe sources of water. Furthermore, hygiene practices need to be further strengthened.

Regarding the immunization coverage, 37.8% of children have received measles vaccine according to their mother and 45.8% of children were vaccinated based on the vaccination card. However one should be cautious when interpreting the vaccination reported by caretakers without cards to prove. Immunization coverage needs to be further improved to prevent childhood susceptibility to measles and other diseases.

Based on the high number of admissions in the supplementary feeding centers, there is still a need in terms of treatment of malnourished children. We can therefore say that the nutritional need has low intensity, but a large magnitude, since it affects a large number of children despite the relatively low rates. Although the rates of malnutrition are low, there are a number of factors that need to be taken into consideration:

Health Access: Anemia is widely prevalent. Malaria, diarrhea and respiratory tract infections are

among the main types of diseases reported among children in both districts. HIV/AIDS is also another major factor. The district often has a shortage of drugs, further intensifying infections and also discouraging the population from seeking health services.

Water and Sanitation: Nearly half of the survey respondents reported collecting water from

unprotected water points. Access to clean and safe water can contribute to the reduction of morbidity due to water-borne diseases, which can reduce susceptibility to malnutrition in a vulnerable population. Hand washing practices need to be strengthened, particularly after latrine use.

Food Security: People reported low food stocks. Some reported getting food on credit, which indicates

that some households could be more vulnerable than others. Moreover, when food is inadequate, people tend to buy less expensive food, reduce the number of meals per day or tend to reduce portion size, which is likely to affect dietary quantity and quality.

Nutrition and Health Education: Children were also not fed frequently. They were most likely to be

left under the care of slightly older siblings. They were also more likely to be fed only at the same time as the adults (1-2 times a day). These suggest that the children feeding practices combined with poor child care and hygiene practices increase the risk of infection among children which can lead to or aggravate malnutrition.

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VII RECOMMENDATIONS

The global acute malnutrition rate is below the critical level. A more global approach to managing malnutrition is necessary: Health and Nutrition:

- To continue the treatment of severely and moderately malnourished children under 5 years old in therapeutic and outpatient centers.

- To reinforce the capacity of MOH staff (hospital and health center staff) in the management of acute malnutrition. The health staff at all levels including district hospitals and health centers (including HCII, HCIII and HC IV) need to be trained on detection and management of acute malnutrition.

- To strengthen the capacity of communities by training VHTs/community volunteers on how to detect and refer acutely malnourished children less than 5 years to enable early detection and referral

- To monitor the nutritional status of the population on an annual basis. - To conduct nutrition surveillance and to train MoH staff in nutrition surveillance to better monitor the

nutritional status and the factors contributing to malnutrition - To continue conducting EPI campaigns whenever necessary with systematic routine immunization

activities to ensure all children are vaccinated against childhood diseases - To promote nutrition and healthy behaviors in the communities and health centers, with an emphasis on

breastfeeding, weaning, complementary foods, and balanced diets Food Security:

- To continue with programs devoted to the generation of incomes at household level Water and Sanitation:

- To emphasize on the promotion of adequate hygiene practices - To improve the access to safe drinking water at communities level

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VIII ANNEXES

VIII.1 Annex I. Assignment of Clusters, Apac and Oyam districts

Geographical unit Population size Assigned cluster ABOKE Akwiridid 11593 1 Apach 9066 Apuru 7535 2 Ogwangacuma 9254 3 Opeta 7545 ALITO Alito 10933 4 Ayara 7446 5 Ayala 11949 6 Okweodot 9317 7 Otkwac 7426 Adelogo 10752 8 Apala 9862 9 AYER Abur 7477 10 Alemi 8811 Ayer 4803 11 Ilera 6695 Okwor 6016 12 Te-lela 8347 OYAM ABER Ocini 10495 13 Kamdini 15460 14,15 MINAKULU Amwa 9878 Oyoro 12213 16 Adel 8339 17 Atek 10730 18 Kuluabura 5318 Aceno 10761 19 LORO Agulurude 13992 20 Adyeda 18998 21,22 Alutkot 12982 23 Adigo 11200 24 ACABA Anyeke 8557 25 Abanya 6408 Atekober 9207 26 Dogapio 10343 27 Obangangeo 9184 28 ICEME Omolo 5223 Aungu 11874 29 Aloni 7748 30

21

Awio 8562 Orupu 11846 31 NGAI Akuca 8939 32 Bar 7891 33 Acut 7813 Ajerijeri 7397 34 Aramita 7922 35 Omac 9469 OTWAL Okii 12358 36 Acokara 6645 37 Abella 6524 Ajul 12494 38 Alibi 8139 39 Amukugungu 6778 40

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VIII.2 Annex II:. Selected villages, Apac and Oyam districts

ABOKE Akwiridid parish; village OkelcuCony (Cluster 1) Apuru parish; village Pukica (Cluster 2) Ogwangacuma parish; village Aculbanya (Cluster 3) ALITO Alito parish; village Ocere (Cluster 4) Ayaka parish; village Ajuki "A" (Cluster 5) Ayala parish; village Te Opok (Cluster 6) Okweodot parish; village Alake (Cluster 7) Adelogo parish; village Olengobir (Cluster 8) Apala parish; village Jinga (Cluster 9) AYER Abur parish; village Aweki (Cluster 10) Ayer parish ; village Ouka (Cluster 11) Okwor parish; village Aditawuru (Cluster 12) ABER Ocini parish; village Adak B (Cluster 13) Kamdini parish; village Bedmot (Cluster 14) Kamdini parish; village Buya (Cluster 15) MINAKULU Oyoro parish; village Acwara Tera (Cluster 16) Adel parish; village Ocok Ocan (Cluster 17) Atek parish; village Arak East (Cluster 18) Aceno parish; village Acandano (Cluster 19) LORO Agulurude parish; village Acanmakweri (Cluster 20) Adyeda parish; village Odongoyere (Cluster 21) Adyeda parish; village Alica (Cluster 22) Alutkot parish; village Agomi (Cluster 23) Adigo parish; village Aloc (Cluster 24) ACABA Anyeke parish; village Akaidebe (Cluster 25) Atekober parish; village Aruda (Cluster 26) Dogapio parish; village Apala (Cluster 27) Obangangeo parish; village Adak A (Cluster 28) ICEME Aungu parish; village Amukugungu (Cluster 29) Alóno parish ; village Otwonalop (Cluster 30) Orupu parish; village Ongica (Cluster 31) NGAI Akuca parish; village Ngai T.C (Cluster 32) Bar parish; village Kok kecikweri (Cluster 33) Ajerijeri parish; village Angom B (Cluster 34) Aramita parish; village Aweipeko (Cluster 35) OTWAL Okii parish; village Anyomolyec (Cluster 36) Acokara parish; village Adagayela (Cluster 37) Ajul parish; village Railway Station (Cluster 38) Alibi parish; village Adaganii (Cluster 39) Amukugungu parish; village Amor Omwodo Cuka (Cluster 40)

STEPS • Spin the Pen in the Center. • Walk to the border. • Spin the pen again and walk in that direction to the border,

numbering the houses. • At the second border, choose a random number and start the

survey at that house. Choose the next closest house to your right.

• If you run out of houses, return to

the nearest border point, spin the pen, and start the numbering again

• If turning right, you come to a house that has already been surveyed or is vacated, choose the next closet one to the right

• In villages, draw a map and write the number of each house on the map. It is not necessary to walk to the house and number it. (As it may be a long distance). Once the random number is selected, you can find the house based off your map.

VIII.3 Annex III: Household Selection

Center

Border

VIII.4 Annex IV: Anthropometric survey questionnaire

District/Village: _________________________ Date: _________________ Cluster number: _______ Team number: _______ Child no.

HH. no.

Name (optional) Sex (F/M)

Birthday Age in months

Weight (kg) ±100g

Height (cm) ±0.1cm

Oedema (Y/N)

% W/H Muac (mm)

Measles (0,1,2)

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

VIII.5 Annex IV: Calendar of Events in Apac/Oyam Districts

MONTH ANNUAL EVENTS EVENTS PER MONTH AND PER YEAR

2003 2004 2005 2006 2007 2008

JANUARY 1ST new year, 26th victory day

63

51

39

27

15

3

FEBUARY Cleaning the field, opening school

62

50

38

26

23rd presidential election 14

2

MARCH

Women’s day, Sea-nut season

Beginning of rainy season 61

Beginning of rainy season, Barlonyo attack7 march 2004,

49

Beginning of rainy season, 37

Beginning of rainy season 25

Beginning of rainy season 13

Beginning of rainy season 1

APRIL Easter, White-aunt season, Fools day 1stDay

60

48

36

24

12

0

MAY 1st labor day, Mango season

59

47

35

23

11

JUNE

3RD martyrs day, 9th heroes day

58

Attack on Aboke girls 28 people killed and 7 abducted

46

34

22

10

JULY Harvest of millet Harvest 1st

session 57 Harvest 1st session 45

Harvest 1st session 33

Harvest 1st sessions 21

9

AUGUST Ascension day

56

44

32

20

8

SEPTEMBER Weeding of 2nd session

55

43

31

19

7

OCTOBER 9th independence day

54

42

Death of former president Milton Obote 10/10/05

30

18 Flood

6

NOVEMBER Harvest of maize and millet

Harvest 2nd session 53

Harvest 2nd session 41

Harvest 2nd session 29

Harvest 2nd session 17

Harvest 2nd session 5

DECEMBER

25th Christmas, 26th boxing day

cessation of fire and peace talk between LRA and government

52

peace talks failed and Museveni declare war

40

28

16

4

VIII.6 Annex VI: 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

ID HH member

Present now

Present at beginning of recall (include those not present now and indicate

which members were not present at the start of the recall period )

Sex Date of

birth/or age in years

Born during recall

period?

Died during the recall

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 Nutrisurvey 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 recall Total deaths Deaths < 5

VIII.7 Annex VII: Household Questionnaire

Section A - Socio-Demographic

HH #

1. Who is the head of the household? 1 = Father 2 = Mother 3 = grandparents 4 = other (specify)

2. Is your family 1= resident in the village7 2 = returnee from camp 3 = IDP camp resident 4 = migrant from countryside 5=Other (specify)

3. Highest level of education of the head of household 1= Primary school 2=Secondary school 3=Higher education 4=University 5=None 6=Other (specify)

1 2 3 4 1 2 3 4 5 1 2 3 4 5 6 1

2

3

4

5

6

7

8

9

7 Regular resident and not displaced at any time in the past

Section B. Food Security

HH #

4. What are the top three sources of income (Enter zero < three) 1=Crop sales 2=Animals/products 3=Petty trade 4=Handicraft 5=Casual labour 6=Boda boda 7=Salary 8=Brewing 9=Charcoal/ wood sales

5. Does the HH own animals 1=Yes 2=No If no, go to Q.7

6. If yes, what types of animals are owned by the HH (Enter number; enter 0 if do not have type) 1=Poultry (chicken, ducks) 2=Pigs 3=Goats 4=Cattle 5=Other

7. What is the estimated duration of current HH food stocks in months

8. When food is not adequate in your HH what do you do? (List 3 only) 1= Less expensive less preferred food 2= Increase casual labor for food 3= Reduce number of meals per day 4= Limit meal portion size 5= Borrow or receive food assistance from relatives/next of kin 6= Begging food from non-relatives 7= Harvest immature crop 8= Buy food on credit 9= Ask children to work for cash 10= Sell household assets

9. Does the HH get food aid? 1= Yes 2= No

10. What foods have you eaten in the past 24 hours? List all 1= Cereals (Millet, sorg, ) 2= Legumes (bean, peas) 3=Tubers/ roots (Cassava, potato) 4= Milk & milk products 5= Meat/ chicken 6= Fish 7= Vegetables 8= Fruits 9= Oil 10= Eggs 11= Sugar / honey (Do not read) (Enter only the numbers)

11. Number of meals per day currently for children (C) & adults (A)

1 2 3 1 2 1 2 3 4 5 Months 1 2 3 1 2 A C

1 2 3 4 5 6 7 8 9 10 11

Section C. Water And Sanitation

HH #

12. Where do you collect water for drinking and household purposes? 1=River, stream 2=Handpump 3=Tap 4=Protected Spring 5=Unprotected Spring/unprotected hand dug well 6=Other (specify

13. Do you pay fees for your water? 1=Yes 2=No

14. What does the HH use for latrine? 1=Household latrine 2=Group latrine 3=Neighbour’s latrine 4=Bush 5=Other (specify) If 1 go to Q.16 If 2,3,4,5 go to Q.15

15. What prevents you from having a latrine in your house? 1=Lack of money 2=Lack of materials 3=Do not know how to construct latrine 4=no space 5=others (specify)

16. When do you wash your hands?1=Before eating 2=After eating 3=After defactation/use of latrine 4=After working in gardens 5=After touching animals 6=Before breastfeeding 7=Before food preparation 8=After changing the child 9=Other (specify) (Do not read)

1 2 3 4 5 6 1 2 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 6 7 8 91 2 3 4 5 6 7 8 9 10 11 12 13