Anthropometric and Retrospective Mortality Survey In the ... · Table 21: Household Use for Soap...

Anthropometric and Retrospective Mortality Survey

In the County of Aweil East, Northern Bhar El Gazal State

South Sudan

Funded by

June 2009 Aweil East

South Sudan

ACF-USA nutrition surveys, Aweil East County, South Sudan, 2009

2

ACKNOWLEDGMENTS

Action Against Hunger would like to express its deep gratitude for the support given during the Anthropometric and retrospective Mortality Survey 2009 in Aweil East County. We would like to thank ACF-USA staff, particularly the support team without which the survey wouldn’t have been possible. Furthermore, we would like to thank the survey teams, for their endurance, dedication and team spirit which enabled to obtain good quality data. Thanks also to all drivers who ensured timely and safe movement of the survey teams. A special thanks to the SSRRC of Aweil East County for providing vital information on the geographical area and for participating in the survey and to the UN World Food Program for providing assistance in transport. We finally like to say many thanks to the individual families who pleasantly allowed the survey teams measure their children and provided the survey team with the information required to make it a success. For the funding of Anthropometric and Retrospective Mortality Survey Aweil East County, ACF-USA thanks the European Commission Humanitarian Office (ECHO)


3

TABLE OF CONTENTS

.I. EXECUTIVE SUMMARY ........................................................................................... 6

.II. INTRODUCTION ................................................................................................ 11

.III. OBJECTIVES .................................................................................................... 14

.IV. METHODOLOGY ............................................................................................... 14

.IV.1. Type of Survey ............................................................................................ 14

.IV.2. Sampling Methodology ................................................................................... 14

.IV.3. Data Collection and Field Work ........................................................................ 16

.IV.4. Guidelines and Formulas Used ......................................................................... 19

.IV.5. Survey Constraints ....................................................................................... 21

.V. RESULTS OF THE ANTHROPOMETRIC AND MORTALITY SURVEY ..................................... 22

.V.1. .Child Nutrition and Health ............................................................................. 22

V.1.1 Distribution by Age and Sex ............................................................................. 22

.V.2. Anthropometric Analysis ................................................................................. 23

.V.3. Vaccination Coverage .................................................................................... 25

.V.4. Children’s Morbidity ...................................................................................... 26

.V.5. Composition of the Households ......................................................................... 26

.VI. RESULTS OF THE QUALITATIVE QUESTIONNAIRE ...................................................... 27

.VI.1. Socio- demographic characteristics of the respondents ........................................... 27

.VI.2. Food Security and Livelihoods ......................................................................... 27

.VI.3. Health ...................................................................................................... 31

.VI.4. Water and Sanitation .................................................................................... 33

.VI.5. Maternal and Child Care Practices .................................................................... 35

.VII. DISCUSSION ................................................................................................... 36

.VIII. RECOMMENDATIONS ........................................................................................ 38

.IX. APPENDICES ................................................................................................... 40

.IX.1. Sample Size and Cluster Determination .............................................................. 40

.IX.2. Anthropometric Survey Questionnaire ................................................................ 49

.IX.3. Household enumeration data collection form for a death rate calculation survey (one

sheet/household) ....................................................................................... 50

.IX.4. Enumeration data collection form for a death rate calculation survey (one

sheet/cluster) ........................................................................................... 51

.IX.5. Calendar of Events ....................................................................................... 52

.IX.6. Qualitative Questionnaire ............................................................................... 54


4

INDEX OF TABLES

Table 1: Results Summary ........................................................................................................... 8Table 2: UN Agencies, International NGOs and Ministries in Aweil East County ......................................... 13Table 3: Population Figure, Prevalence, Precision, and Sample Sizes, Aweil East ...................................... 15Table 4: Distribution of Age and Sex of Sample ............................................................................... 22Table 5: Prevalence of Acute Malnutrition (based on weight-for height z-scores and/or oedema) .................. 23Table 6: Distribution of Acute Malnutrition and Oedema (based on weight-for-height z-scores) ..................... 23Table 7: Global and Severe Acute Malnutrition in z-scores .................................................................. 24Table 8: Prevalance of Malnutrition by Age (based on weight -for- height percentage of the median and oedema)

.......................................................................................................................................... 25Table 9: Measles vaccination coverage .......................................................................................... 25Table 10: Mortality Rate ........................................................................................................... 25Table 11: Prevalence of Reported Illness in Children Two Weeks Prior to Inverview )n=835) ......................... 26Table 12: Illness Breakdown in Children Two Weeks Prior to Inverview (n=835) ........................................ 26Table 13: Household Composition ................................................................................................ 26Table 14: Main Livelihood Activities (n=682) ................................................................................... 28Table 15: How Households are Obtaining Main Food Sources (n=682) ..................................................... 29Table 16: Top Coping Strategies When Food Stocks Decline (n=670) ...................................................... 29Table 17: Most Commonly Consumed Foods .................................................................................... 30Table 18: Current Water Sources (n=673) ....................................................................................... 33Table 19: Time to and from the Water Source ................................................................................. 33Table 20: Location of Defecation if there is no Toilet (n=654) ............................................................. 34Table 21: Household Use for Soap (n=265) ...................................................................................... 34 INDEX OF FIGURES

Figure 1: Distribution of sex by age group ............................................................................................................................ 22Figure 2: Weight for Height in z-scores compared to WHO population ........................................................................... 24Figure 3: Number of Feddans Planted or to be Planted in 2009 ....................................................................................... 28Figure 4: First Place of Treatment When Sick ...................................................................................................................... 31Figure 5: Distance to the Nearest Health Facility ............................................................................................................... 32Figure 6: Number of Times per day that Children are Fed ................................................................................................ 36


5

LIST OF ABBREVIATIONS ACF-USA Action Contre la Faim- USA, Action Against Hunger-USA

AMURT Ananda Marga Universal Relief Team

ENA Emergency Nutrition Assessment

FAO Food and Agricultural Organization

GAM Global Acute Malnutrition

IOM International Organization for Migration

IDP Internally Displaced People

INGO International Non Governmental Organization

IRC International Rescue Committee

MUAC Mid Upper Arm Circumference

MSF-F Médecins Sans Frontières-France

NBeG Northern Bahr el Ghazal

NCHS National Center for Health Statistic

OTP Outpatient Therapeutic Program

PHCU Primary Health Care Unit

SAM Severe Acute Malnutrition

SFP/C Supplementary Feeding Program/Center

SMART Standardized Monitoring and Assessment of Relief and Transitions

SPHERE Humanitarian Charter and Minimum Standards in Disaster Response

SPLM/A Sudan People Liberation Movement/Army

SPSS Statistical Package for the Social Sciences

SSRRC Southern Sudan Relief and Rehabilitation Commission

TFP/C Therapeutic Feeding Program/Center

UN United Nations

UNICEF United Nations Children’s Fund

VSF Veterinaires Sans Frontieres

WFH Weight for Height

WFP World Food Program

WHO World Health Organization

WVI World Vision International


6

.I. EXECUTIVE SUMMARY

Introduction

Aweil East County is one of the five counties that make up the state of Northern Bahr el Ghazal in Southern

Sudan. The county consists of the seven administrative payams of Malualbai, Baac, Madhol, Mangartong, Mangok,

Yargot and Wunlang running from north to south. Population figures for the total population of the county,

according to the World Health Organization and confirmed by the state level Ministry of Health, is estimated at

616,105.

Aweil East is traditionally an agro-pastoralist region. However, a majority of the population does not own

livestock and hence they are reliant on a more diversified livelihoods base. This livelihoods base includes: grass

and firewood collection; charcoal burning; casual labor; fishing; petty trade; and wild food collection. These

households tend to be heavily reliant on cash income, wild food collection and daily purchasing to meet their

needs as they lack the asset base to make longer term investments.

The community is currently facing a very serious hunger gap due to the fact that last year’s harvest was poor

yielding as a result of concurrent drought, floods and crop pest infestations. This early onset of the hunger

season and an increased reliance on market purchases adds particular pressures onto the most vulnerable

households who lack livestock and other assets. The delayed rains this year are also hampering planting which

will result in a shorter growing season in which to plant or re-plant seeds in hopes of obtaining good yields.

Aweil East County can be considered a location in which there is a chronic level of acute malnutrition above the

emergency threshold. The combination of food insecurity, lack of access to clean water and sanitation facilities,

disease outbreaks, and poor child care practices have a negative impact on the nutrition status of children under

five years of age.

Nutritional and retrospective mortality surveys are undertaken annually in Aweil East County by ACF in order to

estimate the malnutrition and the mortality rates in this county. This survey took place from June 10-23, 2009.

Survey Methodology The Standardized Monitoring and Assessment of Relief and Transitions (SMART) methodology was utilized in the

implementation of the Anthropometric and Mortality survey. Children aged 6-59 months formed the target

group. Complimenting these two survey tools, a qualitative questionnaire was also administered to households.

The objectives of the surveys included:


7

To assess the prevalence of acute malnutrition in children aged 6-59 months

To estimate the crude and under five mortality rate

To estimate the coverage of measles among targeted children

To identify the underlying causes and factors of malnutrition

The SMART survey methodology was used in the planning, training, field data collection and analysis of the

anthropometric and mortality surveys. Since village population was not available to help with cluster selection,

the total population of the county was used as a starting point and then accessible villages were entered

according to proportion-to-size information. Based on this information, the targeted sample sizes were 841

children for Anthropometric survey and 4344 for the Mortality survey. In order to reach these targets, the survey

needed to be administered in 42 randomly selected clusters.

A qualitative questionnaire was also administered to 683 households to collect information on food security and

livelihoods, water and sanitation, child care practices, and health. The households that were chosen for

participation were primarily those that participated in the Mortality survey.

At the conclusion of the surveys, the Anthropometric survey included 8441

The June 2009 ACF nutritional anthropometric survey in Aweil East County revealed GAM rates of 29.8% (25-

35.2%) and SAM rates of 7.8% (5.5-11.1%) (WHO 2005 standards). Both these rates exceed the WHO emergency

threshold for GAM and SAM, and are also a significant increase over June 2008 survey results of GAM rates of

19.9% (16.1-23.8) and SAM rates of 3.8% (1.9-5.6) (WHO 2005 standards). Immunization rates are low with 76.4%

of children between 9-59 months being vaccinated for measles; a proxy indicator for overall immunization and

health. Additionally, mortality rates were 0.2 (0.1-0.4%) for total crude mortality rates and 0.34 (0.1-1.0) for

under five mortality rates. Both of these rates are below the alert and emergency levels for total crude mortality

and under five mortality rates. The Results Summary Table can be found on the next page.

children, the Mortality survey

included 689 households encompassing 4431 residents, and the qualitative questionnaire included 683

households. Sample size target numbers were exceeded for both the Anthropometric and Mortality surveys. The

sample size target of 714 for the household questionnaire was only slightly missed.

Summary of Findings

Key nutrition and mortality findings:

1 While the survey incorporated 844 children, the final analysis incorporated 805 children after exclusion of 39 children due to incoherency.


8

Table 1: Results Summary

INDEX INDICATOR RESULTS

WHO (2005)

N=805

Z-scores

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

29.8% [25.0% - 35.2%]

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

7.8% [5.5% - 11.1%]

NCHS (1977) N=805

Z- scores

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

29.1% [24.5% -34.1%]

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

3.1% [1.9% - 5.1%]

% Median

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

18.0 % [14.0% - 22.8%]

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

0.7 % [0.3 – 1.9%]

MUAC Height >=65 cm N=805

Global Acute Malnutrition (<120mm) 10.9% [8.8% - 13.1%]

Severe Acute Malnutrition (<110mm) 2.9% [1.7% - 4.0%]

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

0.2 [0.10-0.40] 0.34 [0.12-1.0]

Measles immunization coverage (N= 806 children ≥ 9months old)

By card According to caretaker2

12.8% 10.7% 76.4%

Not immunized

Key food security and livelihoods findings:

• The surveyed population dependents on livelihood activities such as crop farming (59.2%), petty trade

(16%), and employment (9.2%) primarily.

• The main sources of income reported were petty trade (55.6%), sale of livestock and livestock products

(10.9%), sale of assets (7.6%), casual labor (9.2%), and permanent job salary (7.8%).

• The majority of the population has planted or will plant less than one feddan (35.1%) or between one

and two feddans (47.7%) this growing season.

• 95.9% of households do not have sufficient food sources and 63.4% of them have already depleted their

food stocks. Therefore, most households’ main food sources were purchase (75.4%), cultivation (24.7%),

and wild food collection (35.2%).

• As food stocks are declining, households are primarily resorting to wild food collection for consumption

or sale (51.2%), borrowing money (13.6%), selling personal assets (12.6%), and selling livestock assets

(10.8%).

2 When no EPI card was available for the child at the household, measles vaccination information was collected according to the caretaker/ mother of child


9

• The food consumption patterns showed that the most commonly consumed foods are cereals (84.2%),

sugar and honey (40.7%), meat (33.9%), oils and fats (23.7%), fish (19.9%) and pulses (18.7%).

Key water and sanitation findings:

• The main water source(s) cited for household use were boreholes (58.9%) and unprotected wells (28.7%).

• 14.6% of households remarked that they boil, filter/sieve or chemically treat their water prior to

consumption.

• 52.3% of households commented that it takes less than 30 minutes to walk to and from the water source;

the rest stated a longer time.

• Most households collect between two (39.5%) and three (39.7%) times per day.

• Based on an average Sudanese household size of 6.6 members, this amount of water collected per day

equates to 6-9 liters/capita/day which is far below the SPHERE emergency standard of 15

liters/capita/day.

• Only 7% of the households surveyed said they had access to a latrine. For those that did not, a majority

of households used the bush (85.8%) or open field (12.5%).

• 35.4% of households remarked that they had soap in the home at the time of the survey. Of this 35.4%

that had soap, only 15.5% washed before eating, 2.3% washed before feeding their children, and 1.5%

washed after defecation.

Recommendations Health and Nutrition

• To scale up emergency therapeutic feeding programs (expansion of OTP sites and expansion of intake

capacity at TFC)

• Partners to scale up/continue with General Food Distribution for households facing food shortage

• Continued surveillance of the food security and nutrition situation in Aweil East

• Education and provision of bed nets to reduce the incidence of malaria; especially for children under the

age of five years

Food Security and Livelihoods

• Contingency and preparedness measures need to be established to be able to respond to a deteriorating

food security and livelihoods situation due to the current dry spell and for the flood onset in August and

September 2009, preventing the nutrition situation from further deterioration


10

• A contingency is as well needed to enable appropriate responses to continuous food insecurity and

malnutrition in 2010 due to a prospected weak harvest in 2009.

• A safety net approach should be considered to respond to recurring annual food insecurity and

malnutrition, which could be facilitated through a regular cash transfer to the most vulnerable

households.

• Provision of seeds and tools, including agriculture training on improved techniques and plant protection

to all households in need for improving the agricultural production at household level

• Support increased household food production through diversification by introducing early maturing crop

varieties, vegetable gardens, and small animal livestock keeping

• Support the diversification of income sources through income generating activities

• The local riverside communities should be empowered on appropriate fishing techniques, processing and

preservation techniques

Water and Sanitation

• Prevention and mitigation measures for communities affected by recurring cholera/AWD

• Training in latrine construction at the community and household levels and provision of digging kits

• Increase the number of adequate and safe water schemes through construction, rehabilitation and

training on operation and maintenance


11

.II. INTRODUCTION

Aweil East County is one of the five counties that make up the state of Northern Bahr el Ghazal in Southern

Sudan. Its borders include Gogrial West County to the east, Southern Kordofan to the north-east, Southern Darfur

to the north, and Aweil South County to the south. Aweil East lies in the western flood plain livelihood zone

which is prone to seasonal flooding; especially in August and September. The flat terrain and sandy and clay soils

contribute to this flooding pattern. The county consists of the seven administrative payams of Malualbai, Baac,

Madhol, Mangartong, Mangok, Yargot and Wunlang running from north to south. Population figures for the total

population of the county, according to the World Health Organization and confirmed by the State level Ministry

of Health, is estimated at 616,105.


12

Northern Bahr el Ghazal is traditionally an agro-pastoralist region, and cattle ownership remains the primary

determinant of wealth and status. Livestock are sold for cash, traded for other products, form marriage dowries

and act as a source of milk and meat.

However, given that up to seventy percent of the population does not own any cattle, and over forty percent do

not own any livestock at all3

The population of Aweil East County has seen a high influx of returnees in the previous year, with an estimated

24% of all returnees in Northern Bahr El Ghazal State having settled in Aweil East.

, the majority of the population is reliant on a more diversified livelihoods base.

Agriculture is commonly undertaken during the annual cropping season, although generally at a subsistence level

that covers barely 3-6 months worth of the household’s staple food requirements. Very poor and poor households

(those with no or few livestock) undertake a range of seasonal and year-round livelihoods activities including:

grass and firewood collection; charcoal burning; casual labor; fishing; petty trade; and wild food collection.

These households tend to be heavily reliant on cash income, wild food collection and daily purchasing to meet

their needs as they lack the asset base to make longer term investments.

4 From March to May 2009

Northern Bahr el Ghazal State recorded 18,335 spontaneous returnees into the state.5

Aweil East County can be considered a location in which there is a chronic emergency state of acute

malnutrition, whereby the Global Acute Malnutrition rate is always above the WHO emergency level of 15%. A

nutrition survey conducted by ACF in June 2008 revealed a Global Acute Malnutrition (GAM) rate of 19.9% (16.1%-

Additionally, an

estimated 56% of Northern Bahr El Ghazal’s Internally Displaced People (IDP) population is currently settled in

Aweil East.

According to the 2008/2009 Annual Needs and Livelihood Assessment, only three counties in Southern Sudan

were expected to be severely food insecure in 2009. One of these counties was Aweil East County. A below

average crop harvest in 2008 as a result of wide spread flooding in the region, translated into an early onset of

the hunger gap by about a month and a half. In addition, regular market assessments by ACF have shown that

currently food prices are rising for staple food items and the cost of livestock is decreasing.

A rapid water and sanitation assessment in Aweil East County conducted in March 2009 by ACF showed that only

24% of the population has access to clean water. It also demonstrated that while some households show interest

in having latrines, the sanitation coverage rate in Aweil East is almost negligible.

3 Food Security Assessment and Cross Sectional Survey on Nutrition, Measles and Vaccination Coverage and Retrospective Mortality, Northern Bahr el Ghazal – Medecins Sans Frontieres (December 2008) 4 IOM – South Sudan North Bahr El Ghazal Sub-Office 5 Humanitarian Action in Southern Sudan Report Week 25, 15-21 June 2009


13

23.8%) and a Severe Acute Malnutrition (SAM) rate of 3.8% (1.9%-5.6%)6

Table 2: UN Agencies, International NGOs and Ministries in Aweil East County

. In May 2008, ACF therapeutic feeding

programs admitted 148 severely malnourished children for nutritional treatment, while in May 2009 a total of

285 children were admitted for treatment of severe acute malnutrition. Interviews with key community

informants during the survey indicated that communities believe that malnutrition is a cause for mortality in the

population, specifically for children.

There are several UN agencies, international NGOs (INGO), and Ministries operating in Aweil East to help with

basic infrastructural needs such as health clinics and schools, and to assist the general population with

livelihoods and food security, water and sanitation, and nutrition. Table 2 below shows some of the key partners

working in Aweil East.

IOM Returnee monitoring, food security, WASH

WFP General Food Distribution, Blanket SFP, Food For Training

UNICEF Nutrition, education, child survival, WASH

FAO Food Security and surveillance

World Vision International Nutrition, food aid, emergency response

Save the Children UK Education, protection, WASH, food security

Save the Children Sweden Education, child protection

IRC Medical treatment and child survival programs

AMURT Food security, education

Mercy Corps Food security, economic recovery and development, cash for work

VSF Livestock surveillance, vaccination, outbreak reporting, and restocking

Ministry of Health Medical treatment, immunizations

Ministry of Agriculture Food Security

Ministry of Infrastructure and

Rural Water Resources WASH

ACF Nutrition, surveillance, food security, WASH

Tearfund Health

Christian Solidarity

International Health

6 WHO 2005, Z-score


14

.III. OBJECTIVES

The objectives for the Anthropometric and Retrospective Mortality Survey were as following:

To assess the prevalence of acute malnutrition in children aged 6-59 months

To estimate the crude and under five mortality rate

To estimate the coverage of measles among targeted children

To identify the underlying causes and factors of malnutrition

.IV. METHODOLOGY

.IV.1. Type of Survey

The Anthropometric and Retrospective Mortality survey implemented in Aweil East County used the Standardized

Monitoring and Assessment of Relief and Transitions (SMART) methodology. During the survey, anthropometric

and mortality data were simultaneously collected. Qualitative data, in the forms of a qualitative questionnaire,

key informant interviews, focus group discussions, and general observation, were also collected in order to

complement the anthropometric survey findings.

.IV.2. Sampling Methodology

A two-stage cluster sampling method was used to collect data for both the Anthropometric and Retrospective

Mortality Surveys:

At the first stage, the sample size was determined by entering necessary information into the ENA for SMART

software for both Anthropometric and Retrospective Mortality surveys. The information included the estimated

population sizes, estimated prevalence rates of mortality and malnutrition and the desired precision and design

effect. As population figures for villages were not known, the total population figure of 616,105 was assumed

and then only the accessible villages were entered with populations proportion-to-size. This information was

confirmed by SSRRC, State level MoH and ACF staff. Table 3 shows how the sample size numbers were

calculated.


15

Table 3: Population Figure, Prevalence, Precision, and Sample Sizes, Aweil East

Anthropometric survey Retrospective Mortality survey

Population 123.221 616.105

Estimated prevalence 20 1

± desired precision % 4 0.4

Design effects 2 1.5

Sample sizes 765 3.949

Anthropometric survey: Using a malnutrition prevalence of 20% based on previous surveys with a precision of 4%

and a design effect of 1.5; a sample size of 765 was obtained. A buffer of 10% was included in the total sample in

order to compensate for missing data, thus, resulting in a sample size of 841 children from 6 months to 59

months.

Given the operational circumstances and the fact that one cluster needed to be finished in one working day, 20

children aged 6-59 months were estimated to be measured in one cluster which yielded a total of 42 clusters.

Mortality survey: Using an estimated mortality prevalence of 1.0%, a desired precision of 0.4, a design effect of

1.5 and a recall period of 90 days; a sample size of 3949 was obtained. A buffer of 10% was included in the total

sample in order to compensate for any missing data, thus, resulting in a sample size of 4344 persons. For the

mortality survey, 104 people present at the time of the survey were included for each cluster (4344/42 clusters)

At the second stage

In every selected household, all children aged 6-59 months were included in the Anthropometric survey. If there

was more than one wife/ caretaker in the household

, selection of households to be visited in each cluster was done using the EPI method. In

each selected cluster, the survey teams were led to the center of the village. The pen was spun in order to

ascertain which direction to walk. At the edge of the village, the pen was spun again, and the team then walked

along this second line counting and marking the households within a few arm’s length. The first house to be

visited was selected at random. The second house and each following were chosen by proximity, always choosing

the houses on the right hand when standing with the back to the main door of the sleeping quarters of the

mother. In areas where the houses were very sparsely located and where there was no house to the right, the

nearest house was selected to participate in the survey.

7

7 A household refers to a mother and her own or adopted children

, each wife was considered separately. If there were no

children in the household, the house remained a part of the sample that contributed zero children to the

Anthropometric survey. The survey team continued until a target of 20 was obtained. If the last household had


16

more children than needed to obtain the target of 20, then each child within the household was still measured

and the target number exceeded for that cluster. Households that were absent or where a parent was not

present were recorded as such and revisited at the end of the day; time and weather allowing. The age of the

children were recorded based on a combination of the parents’ knowledge of the birth date, the use of the ACF

calendar of events, birth cards, and child height.

The Mortality survey was administered to all households that had an adult member present.

Qualitative data was primarily collected through administration of a qualitative survey. This survey was

administered to 683 households total with a target of 17 households per team per day. These households

constituted primarily those that participated in the Mortality survey. However, if the number of household

members ‘present now’ for the Mortality survey was met before the quota for the household survey, then the

same methodology applied as before and houses to the right of the mother’s sleeping quarters were chosen to

complete the household questionnaire. Additionally, focus group discussions with both men and women from

Aweil East, and key informant interviews with community members, SSRRC, other NGOs, and Ministries were

conducted.

Anthropometric and Mortality Surveys, and qualitative questionnaires were administered in each household until

the daily quota for each one had been successfully obtained. The quotas were 20 children for anthropometric,

104 household members “present now” for mortality, and 17 households for qualitative. In total, the minimum

sample size for both the Anthropometric and Mortality surveys were met. The Anthropometric survey included

844 children, and the Mortality survey included 689 households encompassing 4431 residents. The sample size

target for the household questionnaire was 714 households with an actual 683 households that completed the

questionnaire in its entirety. Anthropometric, mortality and qualitative information were asked to the mother in

the household; in her absence the father of the household was asked.

.IV.3. Data Collection and Field Work

The survey teams, each consisting of 1 supervisor, 1 enumerator and 2 measurers were subjected to a

standardization test to ascertain their capability in taking accurate and precise measurements, so as to minimize

errors during data collection. The surveys were completed in 12 days.

.IV.3.1 Anthropometric Survey For each eligible child aged 6-59 months, information was collected during the anthropometric survey using an

anthropometric questionnaire (Appendix .IX.2). The information included:

Age: Recorded with the help of a local calendar of events (Appendix .X.5)


17

Gender: Male or female.

Weight: Targeted children were weighed without clothes using a SALTER balance of 25kg (precision of

100g).

Height: Children were measured on a measuring board (precision of 0.1cm). Children less than 85cm

were measured lying down, while those greater than or equal to 85cm were measured standing up.

Mid-Upper Arm Circumference: MUAC was measured at the mid-point of the left upper arm for

measured children (precision of 0.1cm). ACFIN MUAC tapes were used.

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

feet.

Measles vaccination: Assessed by checking for measles vaccination on EPI cards and probing caretakers.

Household status: Information was sought on the duration of stay in the area. This was used to

determine whether households were residents, displaced, returnees or temporarily in the area. 6 months

stay and reason for movement were used as criteria.

BCG scar: Assessed by checking the arm for the scar indicating that the child had received this series of

vaccinations

Vaccination card: Assessed whether the child had received vaccines in the past

Illness in the last 2 weeks: Assessed to see whether children were suffering from common childhood

diseases. This was used to see if they had had malaria, diarrhea, skin infections, worms or respiratory

infections.

All children who were found to be severely malnourished were referred to either the ACF-USA Outpatient

Therapeutic feeding Program or taken directly to the Therapeutic Feeding Centre; depending on presence of

medical complications and level of oedema. A total of 28 children were referred during the survey.

.IV.3.2 Mortality Survey

Each family selected at random (even if there was no child 6-59 months), was asked to state all family members

and indicate their age and sex. The family was then asked to indicate which of the listed family members were

present now and at the beginning of the recall period, which member joined or left during the recall period, and

which members were born or died during the recall period. (Appendix .IX.3).

.IV.3.3 Food Security and Livelihoods, and Water and Sanitation

Food security and livelihoods, and water and sanitation data were collected from the same households the

mortality data was collected in order to collect information to complement the Global Acute Malnutrition rates.


18

Information was collected during the anthropometric survey using a qualitative questionnaire (Appendix .IX.6).

Food security and livelihoods information included:

Main livelihood: Information was sought on what they consider to be their main livelihood(s)

Main source of income: Information was sought on what they consider to be their main source(s) of

income

Current month’s food source: Information was sought on what is the household’s main food source(s)

for the current month

Sufficiency of main food sources: Information was sought to determine if household thought their main

sources of food were sufficient

Coping strategies: Information was sought on what the household does when it’s food stocks decline in

order to determine coping mechanisms

Current food stock: Information was sought on how long their current food stock would last

Ensuring enough food: Information was sought open-endedly on what the household thought could be

done to ensure enough food for household consumption

Crops cultivated: Information was sought on what crops were cultivated or will be cultivated this

planting season

Feddans cultivated: Information was sought on how many feddans of land the household cultivated or

planned to cultivate this planting season

Livestock owned: Information was sought on which type of livestock the household owned

Fishing: Information was sought on whether the household was engaged in fishing, and why not if they

said no

Water and sanitation information included:

Current water source: Information was sought on what is the household’s current water source(s)

Time to water source: Information was sought on how many minutes it took to go to the water source

and back. This was to determine the time it took to obtain water.

Times per day collecting water: Information was sought on how many times a day water was collected

Water collection container: Information was sought on what type of container was used to actually

collect the water in.

Water storage container: Information was sought n what type of container was used to store the water

once it arrived at the household.

.IV.3.4 Data Quality Control Assurance


19

The use of an anthropometric standardization and cluster control sheet, thorough training of the 4 teams (each

consisting of 1 supervisor, 1 enumerator and 2 measurers), and close supervision by the Surveillance Program

Manager ensured that data collected was of good quality.

.IV.3.5 Field Exercise

The training was followed by a field exercise in a village not selected for the surveys. The methodology was

tested; the precision and the accuracy of the data collection were assessed, and the measurement techniques

were assessed. Additionally all the data collection forms were tested during the exercise. The exercise was

successful and the actual survey started the next day.

.IV.3.6 Data Entry and Analysis Anthropometric and mortality data processing and analysis was conducted using SMART/ENA software. Extreme

value flags and WHO verification guidelines were used to identify Z-score values where there was a strong

likelihood that some of the data items were incorrect; these data were not used in the analysis. The food

security, water and sanitation data entry was done in SPSS version 12. The data analysis was performed with

SPSS software version 12.

.IV.4. Guidelines and Formulas Used

.IV.4.1.1. Acute Malnutrition

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 are estimated from the weight for height (WFH) index values as well as presence of

bilateral oedema. The WFH indices are expressed in both Z-scores (standard deviation score) and percentage of

the median, according to both NCHS and WHO references.

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 is commonly 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.


20

Severe malnutrition is defined by WFH < -3 SD and/or existing bilateral oedema on the child’s lower limbs.

Guidelines for results expressed in Z-score:

Moderate malnutrition is defined by WFH < -2 SD and ≥ -3 SD and no oedema. Global acute malnutrition is defined by < -2 SD and/or existing bilateral oedema.

Severe malnutrition is defined by WFH < 70 % and/or existing bilateral oedema on the child’s lower limbs.

Guidelines for results expressed in percentage of median:

Moderate malnutrition is defined by WFH < 80 % and ≥ 70 % and no oedema. Global acute malnutrition is defined by WFH <80% and/or existing bilateral oedema

Mid-Upper Arm Circumference (MUAC) The weight for height index is the most appropriate index to quantify wasting in a population. However, MUAC is

a useful tool for rapid screening at a higher risk of mortality. MUAC measurements are used in children with a

height of 65 cm and above. The guidelines are as follows:

MUAC < 110 m and/or oedema Severe malnutrition and high risk of mortality MUAC ≥ 110 mm and <120 mm Moderate malnutrition and 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 Adequate nutritional status

.IV.4.1.2. Mortality

SMART methodology was utilized in mortality data collection over a 90 day recall period. The data gathered was

then used to calculate the Crude mortality rate (Appendices .X.3 and .X.4). It is calculated using the following

formula. The result is expressed per 10,000 people/day.

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

a = Number of recall days (90) 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

Thresholds are defined as follows8

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

:

Crude Mortality Rate (CMR):


21

Alert level: 1/10,000 persons/day Emergency level: 2/10,000 persons/day

Under five Mortality Rate (U5MR):

Alert level: 2/10,000 persons/day Emergency level: 4/10,000 persons/day

.IV.5. Survey Constraints

Access: Some villages were not included in the cluster selection as they were considered inaccessible either due

to physical access during the rainy season or for security reasons. This may have resulted in some villages from

not having a chance to be surveyed.

Recall bias: There was a 90 day recall for the mortality questionnaire that did not have a significant memorable

event attached to it and therefore recall bias could have been introduced into the data collection process.


22

.V. RESULTS OF THE ANTHROPOMETRIC AND MORTALITY SURVEY

.V.1. .Child Nutrition and Health

V.1.1 Distribution by Age and Sex

The distribution of the sex and age group shows that the total boy/ girl ratio is within the acceptable range of 0.8-1.2. Similarly, the sex ration within the age groups indicates a normal distribution. Table 4: Distribution of Age and Sex of Sample

Age groups in months

Boys Girls Total Ratio N % N % N % Boy:girl

6-17 89 51.1 85 48.9 174 21.6 1.0

18-29 96 53.0 85 47.0 181 22.5 1.1

30-41 106 52.0 98 48.0 204 25.3 1.1

42-53 90 50.0 90 50.0 180 22.4 1.0

54-59 35 53.0 31 47.0 66 8.2 1.1

Total 416 51.7 389 48.3 805 100.0 1.1

Figure 1: Distribution of sex by age group


23

.V.2. Anthropometric Analysis

.V.2.1. Distribution of Acute Malnutrition in Z-scores In the complete sample, the prevalence of Global Acute Malnutrition was found to be 29.8% (25.0% - 35.2%). The

prevalence of Severe Acute Malnutrition was 7.8% (5.5%-11.1%). In Table 5 the weight for height distribution by

age groups is demonstrated. There are no significant statistical differences of malnutrition levels between the

age groups.

Table 5: Prevalence of Acute Malnutrition (based on weight-for height z-scores and/or oedema)

Age groups

in months

Total N

Severe wasting

(<-3 z-score)

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

score )

Normal (> = -2 z score) Oedema

N % N % N % N % 6-17 174 18 10.3 29 16.7 127 73.0 0 0.0 18-29 181 22 12.2 38 21.0 121 66.9 0 0.0 30-41 204 5 2.5 44 21.6 154 75.5 1 0.5 42-53 180 11 6.1 48 26.7 121 67.2 0 0.0 54-59 66 6 9.1 18 27.3 42 63.6 0 0.0 Total 805 62 7.7 177 22.0 565 70.2 1 0.1

Out of the total of 805 children measured one child was found to have kwashiorkor (bilateral oedema), 62

children were found marasmic (severe wasting), and no children presented with marasmic- kwashiorkor.

The child with kwashiorkor was referred to the Therapeutic Feeding Centre in Malualkon for nutritional

treatment. (See Table 6)

Table 6: Distribution of Acute Malnutrition and Oedema (based on weight-for-height z-scores)

<-3 z-score >=-3 z-score Oedema present Marasmic kwashiorkor

N= 0 (0.0 %)

Kwashiorkor N= 1

(0.1 %) Oedema absent Marasmic

N= 62 (7.7 %)

Normal N=742

(92.2 %)

The figure below shows the weight for height distribution curves of the Anthropometric survey samples in Z-

scores for comparison with WHO populations. The curve is shifted to the left, with a mean Z- score of

-1.43 and a standard deviation of 1.04, which indicates that the population surveyed exhibits a poor nutrition

status compared with the WHO reference population.


24

Figure 2: Weight for Height in z-scores compared to WHO population

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

NCHS reference WHO reference

Global Acute Malnutrition 29.1 (24.5%-34.1%) 29.8% (25%-35.2%)

Severe Acute Malnutrition 3.1% (1.9%-5.1%) 7.8% (5.5%-11.1%)

According to both NCHS and WHO reference z-scores, Table 7 above shows that both the GAM and SAM rates

exceed the WHO emergency thresholds of 15% and 4% respectively. When comparing the severe acute

malnutrition rates between the WHO and NCHS reference populations, the severe acute malnutrition rate

according to the WHO reference population is significantly higher than the severe acute malnutrition rate

according to the NCHS reference population.

.V.2.2. Distribution of Acute Malnutrition in percentage of the median

In the overall sample the prevalence of global acute malnutrition was found to be 10.7% (6.9%-14.5%) and the

prevalence of severe acute malnutrition was found to be 0.1 % (-0.2%-0.5%). In Table 8 the prevalence of acute

malnutrition is presented in weight for height percentage of the median and oedema, and it can be seen that no

children were found to be suffering from severe wasting (N=0).


25

Table 8: Prevalance of Malnutrition by Age (based on weight -for- height percentage of the median and oedema)

Age groups

in months

Total N

Severe wasting (<70% median)

Moderate wasting (>=70% and <80%

median) Normal

(> =80% median) Oedema

N % N % N % N % 6-17 174 0 0.0 21 12.1 153 87.9 0 0.0 18-29 181 0 0.0 26 14.4 155 85.6 0 0.0 30-41 204 0 0.0 11 5.4 192 94.1 1 0.5 42-53 180 0 0.0 19 10.6 161 89.4 0 0.0 54-59 66 0 0.0 8 12.1 58 87.9 0 0.0 Total 805 0 0.0 85 10.6 719 89.3 1 0.1

.V.3. Vaccination Coverage

Table 9 shows the vaccination coverage among the surveyed population. The source of information used during the data collection was as following: Child health card or recall by the mother.

Table 9: Measles vaccination coverage

Population >= 9 months N= 804

Immunized by card 12.8%

(10.4% -15.1%)

Immunized by recall 10.7%

(8.5%-12.8%)

Not immunized 76.4%

(73.4%-79.3%)

.V.4. Mortality The retrospective death rate was calculated based on the data collected with a 90 days recall period. Data was

collected from families with or without children under 5 years. The results are summarized in the Table 10

below.

Table 10: Mortality Rate

Demographic data N

Current residents HH 4431

Current residents < 5 years in HH 1013

People who joined HH 132

< 5 years who joined HH 26

People who left HH 200


26

<5 years who left HH 22

Birth 74

Death 8

Death < 5 years old 3

Recall period (days) 90

CMR (death/10.000 people/ day 0.20 (0.10-0.40)

U5MR (deaths in children < 5 years/ 10.000/day 0.34 (0.12-1.00)

.V.4. Children’s Morbidity

Table 11: Prevalence of Reported Illness in Children Two Weeks Prior to Interview (n=835)

6-59 months

Prevalence of Reported Illness

56.3%

Table 12: Illness Breakdown in Children Two Weeks Prior to Interview (n=835)

Illness 6-59 months Malaria 19.1% Diarrhoea 12.4% Acute Respiratory Infection 6.3% Skin Infection 4% Worms 2.3% Other 5.2% As Tables 11 and 12 above depict, in the two weeks prior to the survey, over half the children surveyed had a

reported illness (56.3%). The top two illnesses included malaria (19.1%) and diarrhoea (12.4%). Both of these

preventable illnesses increase the child’s susceptibility to malnutrition as food quantity consumed and nutrient

absorption are decreased when the child is sick.

.V.5. Composition of the Households

Mortality survey was administered in 689 households during the survey. As seen in Table 13 below, the findings

revealed an under- five year average of 1.5 children per household and an overall average of 6.6 persons per

household.

Table 13: Household Composition

Age group N % Average per household


27

Under 5 years 1013 22.9 1.5 Adults 3418 77.1 5.1 Total 4431 100 6.6

.VI. RESULTS OF THE QUALITATIVE QUESTIONNAIRE

A qualitative questionnaire was administered to 683 households to collect information on food security and

livelihoods, water and sanitation, child care practices, and health9

.VI.1. Socio- demographic characteristics of the respondents

. Information collected was supplemented by

information collected by key informant interviews, focus group discussions, and observation.

This survey revealed that households are primarily residents (94.3%) but the population also consists of returnees

(3.2%), temporary residents (1.6%), and IDPs (0.7%).The status of each household was characterized by the

household themselves. Therefore, it is possible that they may consider themselves as residents rather than

returnees, temporary residents or IDPs. This could account for any discrepancies found in returnee percentages

found in other reports.

Survey respondents were 95.5% female; male respondents were surveyed if the female adult household member

was not present or unable to respond.

.VI.2. Food Security and Livelihoods

The main habitants of the Aweil County are Dinka who are predominantly agro-pastoralists. While cattle

ownership remains the primary determinant of wealth and status, this survey shows that a majority of the

population does not own cattle (79.2%). As Table 14 shows, they are dependent on other livelihood activities such

as crop farming (59.2%), petty trade (16%), and employment (9.2%). The main sources of income reported were

petty trade (55.6%), sale of livestock and livestock products (10.9%), sale of assets (7.6%), casual labor (9.2%),

and permanent employment salary (7.8%). It is important to note that 21.1% of households reported that they

had no source of income.

9 Many of the questions asked could have multiple responses thereby leading to percentages for individual questions not equaling 100%.


28

Table 14: Main Livelihood Activities (n=682)

Livelihood Activity Percentage

Crop Farming 59.2%

Agro-pastoralism 24.5%

Petty Trade 16%

Employment 9.2%

The population in Aweil East practices small scale farming mainly of cereals and pulses such as sorghum, millet,

maize, cowpeas, groundnut, and simsim. Sometimes, vegetables such as okra, pumpkin, tomatoes and cabbages

are planted. Qualitative survey results reflect this pattern of cropping with 93.6% of households saying they have

or will plant sorghum, 8.1% maize, 14.8% simsim, and 13.9% groundnuts. Only 4.2% of respondents said they will

plant vegetables but those mentioned were primarily okra and pumpkin. The majority of the population has

planted or will plant less than one feddan (35.1%) or between one and two feddans (47.7%) this growing season;

see Figure 3. When asked during assessments by ACF and other humanitarian organizations why they are not

cultivating more land especially given that it is plentiful, the majority of people cited reasons including

insufficient seed supply, drought and too much flooding.

Figure 3: Number of Feddans Planted or to be Planted in 2009

.00 less than 1 1-2 2-3 3-4 more than 4Number of feddans

0102030

Pe

rce

n

This ACF June 2009 survey shows that 95.9% of households do not have sufficient food sources and 63.4% of them

have already depleted their food stocks. Most households’ main food source(s) for July 2009 were purchase

(75.4%), cultivation (24.7%), and wild food collection (35.2%) (See Table 15).The ability to purchase food is a


29

source of distress as the main livelihoods reported are crop farming (59.2%) and agro-pastoralism (24.5%) which

are severely affected by the delayed rains and hence cultivation activities do not provide a positive outlook.

Table 15: How Households are Obtaining Main Food Sources (n=682)

Activity Percentage

Purchasing 75.4%

Cultivation 24.7%

Wild Food Collection 35.2%

Livestock 5%

Kinship 2.3%

Fishing 1.2%

Food Aid 0.6%

Additionally, Table 16 shows that as food stocks are declining, households are primarily resorting to wild food

collection for consumption or sale (51.2%), borrowing money (13.6%), selling personal assets (12.6%), and selling

livestock assets (10.8%). These types of coping strategies are to be expected but also have a negative impact on

household assets and hence their ability to recover following this food insecurity period.

Table 16: Top Coping Strategies When Food Stocks Decline (n=670)

Strategy Percentage

Wild Food Collection 51.2%

Borrow Money 13.6%

Sell Personal Assets 12.6%

Sell Livestock Assets 10.8%

Ask for Food Gifts 9.1%

Decrease Number of Meals

7.8%

During this survey, households were asked what could be done to ensure that they had enough food. The

majority of respondents said cultivation (56.1%), procurement of seeds and tools (20.9%), and food aid (14.9%).


30

As this was an open ended question, participants commented on their own without influence. It is possible that

those that mentioned cultivation could have been referring to the beginning of rains so that they could plant or

to provision of seeds and tools for planting.

Only half of the households surveyed owned livestock (53.3%). Of those that did, the major type owned was goat

(31.2%), chickens (23.6%) and cows (20.8%).

Fishing activities in Aweil East typically take place in March and April and then again from October to December

of every year; though some people are able to carry on with fishing throughout the rest of the months of the

year. The tools used for fishing include modern net, hooks, or locally made fishing equipment like Thoi and

Roke. There are not many household in Aweil East that fish and therefore fishing contributes minimally to

livelihoods in this county. Survey results show that only 8.3% participate in fishing activities with the main constraints being no access to fishing points (45.7%), lack of labor to fish (19%), or lack of fishing equipment

(16.1%).

Households were asked what types of food they consumed within the previous 7 days before the survey. The food

consumption patterns showed that the most commonly consumed foods were cereals (84.2%), sugar and honey

(40.7%), meat (33.9%), oils and fats (23.7%), fish (19.9%) and pulses (18.7%)10

Table 17: Most Commonly Consumed Foods

. The absence of vegetables and

fruits in the diet highlights the risk of deficiencies in micronutrients, which is a major cause leading to

malnutrition.

Food Percentage

Cereals 84.2%

Sugar and Honey 40.7%

Meat 33.9%

Oils and Fats 23.7%

Fish 19.9%

Pulses (Beans and Lentils) 18.7%

10 Of the households that ate meat, 75.% of them only ate it once or twice per week.


31

.VI.3. Health

Health services in Aweil East are supported by MoH and NGOs. The 33 health facilities in Aweil East consist of

one Hospital in Akuem, six PHCCs and 26 PHCUs. Two PHCCs (Malualkon and Malualbaai) and six PHCUs

(Warawar, Bakou, Amethgolduang, Mangartong, Nyanlath and Adoor) are jointly run by IRC and government. Tear

Fund is running two PHCUs in Omdurman and Waragany, Diocese of Rumbek and the government one PHCC in

Gordhim, and Christian Solidarity International one PHCC in Mabel. The government is running one PHCC in

Wanyjok, and 15 other PHCUs within the county.

According to qualitative research, the majority of the population seeks medical treatment when ill and only goes

to see traditional healers when the problem persists. There are some people, including those cut off by long

distances, who use the traditional/witchdoctors as they are the only people available in their vicinity. These

statements can be complimented by this survey’s results (see Figure 4) showing that when household members

are first sick they go to PHCC/Us (62.1%), the hospital (17.2%), or the pharmacy (9.3%) primarily; only 4.6% said

they go to traditional healers first. There are people however who do refuse to go to health centers even if they

are nearby. Key informants say that often pregnant women are the first to refuse health care in health centers

and only like to do so if they are either seriously sick or when they hear that others had successful prenatal care

services and treatment.

Figure 4: First Place of Treatment When Sick

Traditional healerCHW

PHCC/UHospital

Relatives/friendPharmacy

No assistanceOther

No response

Treatment Provider

0102030405060

Perc

ent

Most health units are located in the mid-land with no real facility in the far-low and high-lands. Therefore, key

informants say that it is on average a 6-15 kilometer walk to reach a health centers. This is supported by Figure

5 below that 49.7% say it takes more than 2 hours to reach a health facility, 18.2% say 1-2 hours; only 14.8% say

they are less than a 30 minute walk.


32

Figure 5: Distance to the Nearest Health Facility

Nearest Health Facilityless than 30 minutes30 minutes to 1 hour1-2 hours2 hours or more

With 33 existing health units, there are several operational problems that hinder the functioning of the units and

the ability to treat patients. As reported by the County Health Preventive and Curative Officers, the health

centers lack proper drugs, staff motivational strategies, and interventions/supports. Drugs were previously

supplied directly by NGOs however the government took over drugs procurement responsibility, and while

supplies are supposed to reach health units every 3 months, there has been no shipment received since February

2009.

This survey revealed 0.2 [0.05 – 0.35] /10,000/day crude mortality rates and 0.35 [-0.07 – 0.75] /10,000/day

under-five mortality rates. Both findings are below the respective 1% alert and 2% emergency levels.

However, mortality data have to be considered with great caution as people are reluctant to talk about death

and the reported rates could be highly underestimated.

Immunization rates continue to be low in Aweil East County. Survey results show that only 21.4% of children have

received the BCG vaccination and 23.5% received the measles vaccine. Extended Programs on Immunization (EPI)

have frequently been arranged and implemented by WHO but by March 2009 children have not been immunized

against the six killer diseases. Reasons cited include WHO not receiving the vaccines from government/MoH.

In the two weeks prior to the survey, over half the children surveyed had a reported illness (56.3%). The top two

illnesses included malaria (19.1%) and diarrhoea (12.4%). Recurrent acute watery diarrhoea (AWD)/cholera

outbreaks have plagued Aweil East County since October 2008, with the most recent cases being reported during

the last week of June 2009. Outbreaks were registered in many payams/ bomas with most hard hit areas being

Makuac, Kiir, Peth, Ameth and Akuem.

The June 2009 ACF nutritional anthropometric survey in Aweil East County revealed GAM rates of 29.8% (25-

35.2%) and SAM rates of 7.8% (5.5-11.1%) (WHO 2005 standards). Both rates exceed the SPHERE standards for


33

GAM (>15%) and SAM (>4%), and are also a significant increase over June 2008 survey results which showed GAM

rates of 19.9% (16.1-23.8) and SAM rates of 3.8% (1.9-5.6) (WHO 2005 standards).

.VI.4. Water and Sanitation

Qualitative survey results show that households in Aweil East County are using a variety and combination of

water sources to meet their daily needs. The main water source(s) cited were boreholes (58.9%) and unprotected

wells (28.7%) with rivers, ponds, seasonal springs, and surface run-off also as small contributors (see Table 18).

The source(s) of water used is dependant on many factors including seasonal availability, borehole breakdowns,

lack of alternative water sources, and distance to the source. Borehole water is considered the only safe water

supply and while 58.9% of the population is accessing this at some point, a large portion of the population is

using unsafe water supplies. Also, the survey results show that only 14.6% of households remarked that they boil,

filter/sieve or chemically treat their water prior to consumption.

Table 18: Current Water Sources (n=673)

Source Percentage

Borehole 58.9%

Unprotected Well 28.7%

River 5.6%

Ponds/Apiir 4.8%

Seasonal Spring 1.9%

Surface Runoff 1.9%

The time it takes for households to walk to and from the water source varies; half the households (52.3%)

commented that it takes less than 30 minutes, the other half stating longer time. (See Table 19).

Table 19: Time to and from the Water Source

Time N=671 Less Than 30 Minutes 52.3%

30-60 Minutes 28.8%

More Than 60 Minutes 17.1% The number of times/day that water is collected varies upon the distance to the source, household duties, and

number of household members able to collect and carry the water. Most households collect between two (39.5%)


34

and three (39.7%) times per day. Water is usually collected in 20 liter jerry cans (77.6%) with storage mainly

being in locally crafted pots (65%).

Based on an average household size of 6.6 members, this amount of water equates to 6-9 liters/capita/day

which is far below the SPHERE emergency standard of 15 liters/capita/day. There are several reasons that could

contribute to this low daily per capita consumption rate including distance to the water source, number of

households sharing the daily water source, water scheme breakdowns, unreliable water supply, long queue time,

and lack of containers for carrying and storing water.

Sanitation needs for Aweil East County are also not adequate. Only 7% of the households surveyed said they had

access to a latrine. For those that did not, a majority of households used the bush (85.8%) or open field (12.5%).

A small percentage (1.4%) did remark that they go to the river which could be an important factor for the spread

of water-borne illnesses. (See Table 20). Stools of children under the age of 3 were primarily thrown outside the

house compound (88%) with only 2.5% being buried or thrown in a latrine.

Table 20: Location of Defecation if there is no Toilet (n=654)

Location Percentage

Bush 85.8%

Open Field 12.5%

River 1.4%

Other 0.2%

Health and hygiene practices for treating water prior to consumption, and proper handwashing practices also

were not observed or reported. Only 35.4% of households remarked that they had soap in the home at the time

of the survey. As depicted in Table 21, of this 35.4% that had soap, only 15.5% washed before eating, 2.3%

washed before feeding their children, and 1.5% washed after defecation. The majority of households that had

soap used it to wash clothes (93.6%), wash utensils (29.4%) or bathe (23.8%). A small minority of households that

did not have soap did tell us that they used alternates; 3.5% used tree bark, 2.2% used ash, and 0.9% used thou

kou.

Table 21: Household Use for Soap (n=265)

Use Percentage

Wash Clothes 93.6%

Wash Utensils 29.4%

Bathe 23.8%


35

Wash Before Eating 15.5%

Wash Before Feeding Children

2.3%

Wash After Defecation 1.5%

Lack of adequate quality and quantity of water, of proper sanitation, and of good hygiene practices lead to the

spread of diarrhea and other illnesses; and could be a factor in the reoccurring acute watery diarrhea

(AWD)/cholera outbreaks which have plagued Aweil East County since October 2008.

.VI.5. Maternal and Child Care Practices

Adequate child care practices are acknowledged as a significant determinant of good wellbeing and nutrition

among children. The UNICEF causal framework for malnutrition places care practices as one of the top three

underlying causes of malnutrition; the other two being food security and health. Breastfeeding and

complementary feeding practices are two major components of proper care practices.

This survey revealed that 83.6% of women initiated breastfeeding within one hour after delivery, with 75.5% of

women breastfeeding the child on demand (i.e. when the child cried, reached for the breast, etc). Of the 504

women that had children under the age of 5 years old, 70.4% were still breastfeeding. Of those that had ceased

breastfeeding, this primarily occurred when the child was over 24 months (59.1%) or between the ages of 18-24

months (22.8%). While it is not known if Sudanese women in Aweil East County are exclusively breastfeeding

their children for the first 4-6 months11

Until the child reaches the age of 6 months, all nutrients are provided through breast milk and other food

sources are not needed or advisable. After this age, it is necessary to introduce complimentary foods to the child

so that they can receive all the essential nutrients needed to maintain a good health and nutritional status.

Survey results showed that only 15.4% of children between the ages of 4-6 months received complimentary foods

at this essential growth stage. The majority of children received complimentary foods from the age of 6-10

, it is being shown that the majority are breastfeeding through at least 18

months of age. The length of breastfeeding is also promoted traditionally in the community in Aweil East County,

where it is accepted that a child be allowed to breastfeed for two to three years. However, there is a portion of

the community that is more affluent and ceasing to breastfeed at 12 months of age, but the older generation is

against this. Survey results also show that for children that were no longer breastfeeding, the main reasons were

because the child was too old or the mother was pregnant. While the cultural implications of breastfeeding while

pregnant were not explored in this survey, it is important to sensitize mothers to the fact that breastfeeding

while pregnant should continue and will not harm the unborn child.

11 Exclusive breastfeeding was not researched in this survey


36

months (33.7%) or after the age of 10 months (38.3%). There is a need to sensitize mothers on timely

complimentary feeding practices.

In addition to the proper timing for food introduction, the types of food and numbers of meals provided to the

children each day is very significant to meeting their overall nutritional needs. Respondent’s said that the foods

they feed to their 6-59 month old children include porridge (65.4%), breast milk (27.5%), other foods such as

sorghum and normal ‘adult’ foods in combination with wild foods (23.7%), and cow/goat milk (22.2%). Figure 6

below shows that children were fed between 0 and more than 3 times per day with the highest percentage

receiving 2 meals a day.

Figure 6: Number of Times per day that Children are Fed

nil once twice thrice > 3 timesNumber of Times Per Day

0

10

20

30

Pe

rce

n

.VII. DISCUSSION

The June 2009 ACF Anthropometric survey in Aweil East County revealed GAM rates of 29.8% (25-35.2%) and SAM

rates of 7.8% (5.5-11.1%) (according to WHO 2005 standards). Both these rates exceed the WHO emergency

threshold for GAM and SAM, and are also a significant increase over June 2008 survey results of GAM rates of

19.9% (16.1-23.8) and SAM rates of 3.8% (1.9-5.6) (WHO 2005 standards). Key indicators are pointing to the

development of an acute nutritional emergency that is considerably higher than the normal chronic emergency

levels. The results could be linked to the following:

Food intake and food insecurity The community is facing a very serious hunger gap due to the fact that last year’s harvest was poor yielding as a

result of concurrent drought, floods and crop pest infestations. Based on an ACF post harvest crop assessment in

October 2008, some households only harvested enough food to last until December 2008; thereby instigating an

earlier hunger gap than in a normal year. Discussions with key informants have also concluded that the 2008

harvest was far below than that of 2007. Additionally, rains are late this year and planting is being delayed. This


37

is initiating fear that not only will yields be reduced for the October harvest but also that the annual floods

could come on time in August/September, and hence further reducing crop yields.

Increases in staple food prices, and decreased selling prices (and terms of trade) for cattle, are also affecting

the food security situation and the ability of households to obtain sufficient food quantity. This is especially

problematic given that during the survey, 63.4% of households reported that their food stocks were already

depleted; with an additional 28.6% stating that all stocks will be used by mid-July. The combination of these

factors not only contributes to the current food insecurity and malnutrition situation, but could also have

negative push-on effects for households’ livelihoods and next year’s food security and nutrition situation.

Disease prevalence: Over half the children surveyed had a reported illness (56.3%) within 14 days prior to the survey. The top two

illnesses included malaria (19.1%) and diarrhoea (12.4%). Survey results show that a small percentage of children

have been vaccinated in this county; 21.4% had BCG vaccination, 23.5% had measles vaccine. Extended Programs

on Immunization (EPI) had not occurred by March 2009 to immunize children against the six killer diseases.

Additionally, acute watery diarrhea (AWD)/cholera outbreaks have been reoccurring since October 2008, with

the most recent cases being reported during the last week of June 2009. Preventing disease and immunizing

children are important to keep a healthy population that is less susceptible to high malnutrition rates.

Inadequate water and sanitation situation: In Aweil East County, only 58.9% of the population is accessing clean water through boreholes as a main water

source, and 7% have access to proper latrines and sanitation. Handwashing procedures are also low with only

15.5% washing hands before eating, 2.3% washing before feeding their children, and 1.5% washing after

defecation. These low percentages can be contributed to distance and sources of water, functionality of water

schemes and pumps, ability and knowledge to build latrines, and knowledge and implementation of proper

hygienic practices.

Lack of adequate quality and quantity of water, proper sanitation, and good hygiene practices leads to the

spread of diarrhea and other illnesses; and is a key instigating factor in the reoccurring acute watery diarrhea

(AWD)/cholera outbreaks which have plagued Aweil East County since October 2008, with the most recent cases

being reported during the last week of June 2009. Diarrhea and other illnesses lead to reduced food quantity

intake and decreased nutrient absorption thereby contributing to a decline in nutritional status.

Inappropriate maternal and child care practices:


38

Poor child care practices in Aweil East County may be a contributing factor to high malnutrition rates. While

there is good breastfeeding initiation after delivery, and prolonged breastfeeding duration primarily through the

age of 18-24 months, complimentary feeding practices need to be improved. This survey reveals that only 15.4%

of children are receiving foods at the proper age. This has a serious affect on the health and nutritional status of

a child if he/she is not receiving the proper quantity and quality of foods at vital growth stages.

.VIII. RECOMMENDATIONS

Health and Nutrition

• To scale up emergency therapeutic feeding programs (expansion of OTP sites and expansion of intake

capacity at TFC)

• Partners to scale up/continue with General Food Distribution for households facing food shortage

• Continued surveillance of the food security and nutrition situation in Aweil East

• Education and provision of bed nets to reduce the incidence of malaria; especially for children under the

age of five years

Food Security and Livelihoods

• Contingency and preparedness measures need to be established to be able to respond to a deteriorating

food security and livelihoods situation due to the current dry spell and for the flood onset in August and

September 2009, preventing the nutrition situation from further deterioration

• A contingency is as well needed to enable appropriate responses to continuous food insecurity and

malnutrition in 2010 due to a prospected weak harvest in 2009.

• A safety net approach should be considered to respond to recurring annual food insecurity and

malnutrition, which could be facilitated through a regular cash transfer to the most vulnerable

households.

• Provision of seeds and tools, including agriculture training on improved techniques and plant protection

to all households in need for improving the agricultural production at household level

• Support increased household food production through diversification by introducing early maturing crop

varieties, vegetable gardens, and small animal livestock keeping

• Support the diversification of income sources through income generating activities

• The local riverside communities should be empowered on appropriate fishing techniques, processing and

preservation techniques


39

Water and Sanitation

• Contingency planning for prevention and mitigation measures in communities affected by recurring

cholera/AWD

• Training in latrine construction at the community and household levels and provision of digging kits

• Increase the number of adequate and safe water schemes through construction, rehabilitation and

training on operation and maintenance

• Hygiene promotion to encourage good hygienic practice with a specific focus on hand washing


40

.IX.

APPENDICES

.IX.1. Sample Size and Cluster Determination

Payam Boma Geographical unit Population size Assigned cluster BAAC ANGOOT MACHAR CHUEL 1039 BAAC ANGOOT RUMAKOC 1039 BAAC ANGOOT RUM GIER 1039 BAAC ANGOOT RIANG AWAI 1039 BAAC ANGOOT ANGOT 1039 1 BAAC MALOU MAYOM ROK 1039 BAAC MALOU RUMDIER 1039 BAAC MALOU MABOK 1039 BAAC MALOU JOOC 1039 BAAC MALOU WUN TIT 1039 BAAC MALOU RUMDHAAL 1039 BAAC MALOU LUETH MALUAL 1039 BAAC MALOU HONG AKOL 1039 BAAC MALUALKON MATHIANG 1039 BAAC MALUALKON RIANG AGUER MABIOR 1039 BAAC MALUALKON WARATANY 1039 BAAC MALUALKON MAJAK PAGONG 1039 BAAC MALUALKON MALUALKON 6962 2 BAAC MALUALKON AUCHUEI 1039 BAAC MALUALKON KON CI BEK 1039 BAAC MALUALKON WUN TIT 1039 BAAC MALUALKON HONG KOU 1039 BAAC MALUALKON RIANG LOCH 1039 BAAC MANYIEL CIYOK 1039 BAAC MANYIEL BAAC 1039 BAAC MANYIEL WAR UGAP 1039 BAAC MANYIEL MAYEN BAAC 1039 3 BAAC MANYIEL ANGOT NHOM 1039 BAAC MANYIEL AUCHER 1039 BAAC MANYIEL ANUEI 1039 BAAC MANYIEL LOL MADIING 1039 BAAC MANYIEL CHUOM 1039 BAAC MANYIEL MARIAL PIOL 1039 BAAC MANYIEL AKUOL LUAL 1039 BAAC MANYIEL MABIOR 1039 BAAC MANYIEL WUN TIT 1039 BAAC PARIAK RUM AGUER ABIEM 1039 BAAC PARIAK LUETH LUAL 1039 BAAC PARIAK PARIAK/PARAK LANG 6754 4


41

BAAC PARIAK PAN ABYEI 1039 BAAC PARIAK MAJOK 1039 BAAC PARIAK NYUM DIT 1039 BAAC PARIAK NYUM THII 1039 MALUAL BAAI ADOOR ATUET 1039 BAAC RULNYIN MALEK 1039 BAAC RULNYIN AJOK ARIATH 1039 BAAC RULNYIN HONG ANGUI 1039 BAAC RULNYIN OMDURUMAN/MADHURMAN 7793 5 BAAC RULNYIN RUOL NYIN 1039 BAAC RULNYIN RUMYUOL 1039 BAAC RULNYIN WARLANG 1039 BAAC WARAWAR ALUETH 1039 BAAC WARAWAR WAR REL 1039 BAAC WARAWAR YAR ACHOT 1039 BAAC WARAWAR AUCHIR 1039 BAAC WARAWAR MATHIANG DIT 6754 6 BAAC WARAWAR WARAWARTHII 1039 BAAC WARAWAR AKUAC 1039 BAAC WARAWAR MAROL 1039 BAAC WARAWAR WAR CHUM 1039 BAAC WARAWAR YITH AKEN 1039 BAAC WARAWAR WARAWAR 8312 7 BAAC WARAWAR KUORUEI 1039 BAAC WARAWAR HONGAU 1039 BAAC WARAWAR KUETH DIT 1039 BAAC WARAWAR MABIL CHAN 1039 BAAC WARAWAR ADUT ADHOT 5715 8 BAAC WARAGANY WARGUET 1039 BAAC WARAGANY AGOK 1039 BAAC WARAGANY WARLIET 1039 BAAC WARAGANY RIANG AWAI 1039 BAAC WARAGANY BACHMANGAN 1039 BAAC WARAGANY LUETH NYANG 1039 BAAC WARAGANY MAJOK AKEN 1039 BAAC WARAGANY MAJAK 1039 BAAC WARAGANY WARPIEN 1039 BAAC WARAGANY BERIC 1039 BAAC WARAGANY BACH ANEI 1039 BAAC WARAGANY MATHIANG 1039 BAAC WARAGANY MARENG TENG 1039 BAAC WARAGANY RUM RAAN DIT 1039 9 MADHOL AJIEP LONGJAL 1039 MADHOL AJIEP AJIEP 1039 MADHOL AJIEP AKOL DIT 1039 MADHOL AJIEP MANGAR AKOL 1039 MADHOL AJIEP RUM DENG AYUP 1039 MADHOL AJIEP MAKER AJIETH 1039 MADHOL AMAR JAL MATHIANG 1039 MADHOL AMAR JAL MACHER ABYEI 1039


42

MADHOL AMAR JAL AMER JAL 1039 MADHOL AMAR JAL WAR AJAP 1039 MADHOL DOK KUL WARTHOU 1039 MADHOL DOK KUL ANGUOTH 1039 MADHOL DOK KUL MAN AWAN 1039 MADHOL DOK KUL WUNKUEL 1039 10 MADHOL DOK KUL RUMBUOL 1039 MADHOL DOK KUL DOKUL 6754 MADHOL DOK KUL PANHIAL 1039 MADHOL MABOK TONG MADHOL 5715 11 MADHOL MABOK TONG RUM MALONG 1039 MADHOL MABOK TONG MANYIEL 5715 MADHOL MABOK TONG PANMUOI 1039 MADHOL MABOK TONG PAN RIANG 1039 MADHOL MABOK TONG MABOK TONG 6234 12 MADHOL MABOK TONG ATUET 8001 MADHOL MAJOK DUT NYETHKOU 1039 MADHOL MAJOK DUT AKUAC DIT 1039 MADHOL MAJOK DUT WARLANG 1039 MADHOL MAJOK YITHIOU MAJOK YINYHIOU 1039 MADHOL MAJOK YITHIOU TOM KIEU 1039 13 MADHOL MAJOK YITHIOU WARAYEN 1039 MADHOL MAJOK YITHIOU MAROL 1039 MADHOL MAJOK YITHIOU MADHIAU AGUR DINY 1039 MADHOL MAJOK YITHIOU KAARIC 1039 MADHOL MAJOK YITHIOU WARNYIEL 1039 MADHOL MAJOK YITHIOU WARCHUM 1039 MADHOL MAJOK YITHIOU TUUL 1039 MADHOL MAJOK YITHIOU WURAWAR 1039 MADHOL MALUALDIT MALUALDIT 1039 MADHOL MAROL AKOT MATHIANG 1039 MADHOL MAROL AKOT RUMNYAL 1039 MADHOL RUM ROL MAJAK DHIEU 1039 MADHOL MAROL AKOT MAKUEI DENG 1039 MADHOL MAROL AKOT MAROL AKOT 1039 14 MADHOL MAROL AKOT GUAR DHUEC 1039 MADHOL PAGAI MABIOR DENG DIT 1039 MADHOL PAGAI ADIMMALEK 1039 MADHOL PAGAI PAGAI 6858 MADHOL PAGAI ADUANY 1039 MADHOL PAGAI MABIL THONY 1039 MADHOL PAGAI MABIL LANG 1039 MADHOL PAGAI PANTHONY 1039 15 MADHOL RUM ROL MAYOM GAI 1039 MADHOL RUM ROL WARAWAR BAI 1039 MADHOL RUM ROL ATUONG RIAL 1039 MADHOL RUM ROL WARAWAR 1039 MADHOL RUM ROL TIT ADUONG 1039 MADHOL RUM ROL MANYIEL 1039 MADHOL RUM ROL RUM THOI 1039


43

MADHOL RUM ROL RUM ROL 1039 MADHOL RUM ROL AMIN 1039 MADHOL RUM ROL RUMJOCH 1039 MADHOL RUM ROL KUEL 1039 MADHOL WAR BAAI MALITH ALEK YAI 1039 MADHOL WAR BAAI RUTH THIEP 1039 MADHOL WAR BAAI RUMALUIL 1039 16 MADHOL WAR BAAI MACHAR DUT WOL 1039 MADHOL WAR BAAI KONGDAI 1039 MADHOL WAR BAAI RUMAPUOTH 1039 MADHOL WAR BAAI MADHOL KON 1039 MADHOL WAR BAAI WARBAI 1039 MADHOL WAR BAAI KUANYTHUOR 1039 MALUAL BAAI ADOOR ATUET 1039 MALUAL BAAI ADOOR WARCUEI 1039 MALUAL BAAI ADOOR THOI 1039 MALUAL BAAI ADOOR TOYOR 1039 MALUAL BAAI AJIERIAK ATHIANG 1039 MALUAL BAAI AJIERIAK MANGAR TONG ADHEN 1039 MALUAL BAAI AJIERIAK RUMDENG ANGOL 1039 MALUAL BAAI AJIERIAK MAKUEI DONG 1039 17 MALUAL BAAI AJIERIAK MADHOL 1039 MALUAL BAAI AJIERIAK HECHEC 1039 MALUAL BAAI AJIERIAK AWANG THOU 1039 MALUAL BAAI AJIERIAK MATHIANG DUT AKOT 1039 MALUAL BAAI AJIERIAK RUM GENG ATEM 1039 MALUAL BAAI AJIERIAK LUETH DENG 6234 MALUAL BAAI AJIERIAK TIT 1039 MALUAL BAAI AJIERIAK AJIERIAK 1039 MALUAL BAAI AJIERIAK PAN GUK 1039 18 MALUAL BAAI AJIERIAK MADING AMEL 1039 MALUAL BAAI AJIERIAK MAYEN 1039 MALUAL BAAI LIETH MAJAK ARIEU 1039 MALUAL BAAI LIETH ATADOU 1039 MALUAL BAAI LIETH MULO 1039 MALUAL BAAI LIETH WATHJONG 1039 MALUAL BAAI LIETH LOL KOU 1039 MALUAL BAAI LIETH ARIEU 6754 19 MALUAL BAAI LIETH GUATBOT 1039 MALUAL BAAI LIETH MABOK 1039 MALUAL BAAI LIETH MABIOR 1039 MALUAL BAAI LIETH MATHIANG WETTHOU 1039 MALUAL BAAI LIETH MAKUEI ARIANG 1039 MALUAL BAAI LIETH RUMGOT 1039 MALUAL BAAI LIETH MARIIK 1039 MALUAL BAAI LIETH WARLANG 1039 MALUAL BAAI LIETH LIETH 7273 20 MALUAL BAAI LIETH RUMMANYIEL 1039 MALUAL BAAI LIETH WARRUAL 1039 MALUAL BAAI LIETH MAYEN 1039


44

MALUAL BAAI MARIALNGAP WUNANGOR 1039 MALUAL BAAI MARIALNGAP AKUAACDIT 1039 MALUAL BAAI MARIALNGAP AKONG 5195 MALUAL BAAI MARIALNGAP JERAKOL 1039 MALUAL BAAI MARIALNGAP WUNMUONYDIT 1039 MALUAL BAAI MARIALNGAP AMETHWEDUANG 1039 21 MALUAL BAAI MARIALNGAP TITUBIT 1039 MALUAL BAAI MARIALNGAP MAJAK PALUIL 1039 MALUAL BAAI MARIALNGAP MAROL AKEN 1039 MALUAL BAAI MARIALNGAP RUMWEL 1039 MALUAL BAAI MARIALNGAP ARENG 1039 MALUAL BAAI MARIALNGAP MAYOMDOHOK 1039 MALUAL BAAI MARIALNGAP DIERADHEL 1039 MALUAL BAAI MARIALNGAP MARIALNGAP 1039 MALUAL BAAI MARIALNGAP KUELABUOK 1039 MALUAL BAAI MARIALNGAP AGUATH 1039 MALUAL BAAI MAROL LACH MINIK 1039 MALUAL BAAI MAROL LACH MALUAL BAI 5715 22 MALUAL BAAI MAROL LACH AWALA 1039 MALUAL BAAI MAROL LACH MAKUAC ALAJAM 1039 MALUAL BAAI MAROL LACH DENYIC 1039 MALUAL BAAI MAROL LACH ROLCOL 1039 MALUAL BAAI MAROL LACH MANYIEL 1039 MALUAL BAAI MAROL LACH PANDHAK 1039 MALUAL BAAI MAROL LACH PANAPUOTH 1039 MALUAL BAAI MAROL LACH ALOL 1039 MALUAL BAAI MAROL LACH AMETH/MAJAK/MALEK DENG

AGUER 6234 23

MALUAL BAAI PETH PANTER 1039 MALUAL BAAI MAROL LACH MATHIANG ADIM 5923 MALUAL BAAI PETH WARCUEI/TOCH ADHOT MAJAK 5195 24 MALUAL BAAI PETH PETH CENTER 5195 MALUAL BAAI WUNK KUEL WARLANG 1039 MALUAL BAAI WUNK KUEL ARAMKUETH 1039 MALUAL BAAI WUNK KUEL WUNKUETH 1039 MALUAL BAAI WUNK KUEL MADING 1039 MALUAL BAAI WUNK KUEL CHUOM 1039 MALUAL BAAI WUNK KUEL MAJOK 1039 MALUAL BAAI WUNK KUEL RIANG ANGUI 1039 MALUAL BAAI WUNK KUEL MAROL DUER 1039 25 MANGARTONG KANAJAK MAJAK AJUONG 1039 MANGARTONG KANAJAK WANYJOK 7273 MANGARTONG KANAJAK PAROT 1039 MANGARTONG KANAJAK WARAPATH 1039 MANGARTONG KANAJAK KANAJAK 1039 MANGARTONG KANAJAK PANAPUOTH 1039 MANGARTONG KANAJAK PANLIET 1039 MANGARTONG MABIL MABIL 6234 26 MANGARTONG MANGARTONG MACHIER 1039 MANGARTONG MANGARTONG PAN TIT 1039


45

MANGARTONG MANGARTONG MATHIANG 1039 MANGARTONG MANGARTONG RUMAGOK 1039 MANGARTONG MANGARTONG AMATNHIEN 1039 MANGARTONG MANGARTONG NYIANG MIR 1039 MANGARTONG MANGARTONG WUT RIONG 1039 MANGARTONG MANGARTONG ROL NGOR 1039 MANGARTONG MANGARTONG BUR AKOL 1039 27 MANGARTONG MANGARTONG RUPTHIOU 1039 MANGARTONG MANGARTONG MANYIER 1039 MANGARTONG MANGARTONG WAK KON 1039 MANGARTONG MANGARTONG RUP AGIEU 1039 MANGARTONG MANGARTONG ABYEI 1039 MANGARTONG MANGARTONG MANGOK LUAL 1039 MANGARTONG MAROL AJUONG MABOK NGOR 1039 MANGARTONG MAROL AJUONG CIBILIK 1039 MANGARTONG MAROL AJUONG THANY THANY 1039 MANGARTONG MAROL AJUONG MAKER MAWEIN 1039 MANGARTONG MAROL AJUONG RUP MALEK 1039 MANGARTONG MAROL AJUONG WARANYAK 1039 MANGARTONG RIALDIT MABOK APUOK 1039 MANGARTONG RIALDIT RUP ROL 1039 28 MANGARTONG RIALDIT RIAL DIT 1039 MANGARTONG RIALDIT RIAL DIT BAK 1039 MANGARTONG RIALDIT MANGOK 1039 MANGARTONG RIALDIT GUM ROU 1039 MANGARTONG RIALDIT THOC AJUONG 1039 MANGARTONG RIALDIT MAPER PING DONG 1039 MANGARTONG RIALDIT RUP WET AROU 1039 MANGARTONG RIALDIT MALOU WET WOL 1039 MANGARTONG RIALDIT WAR KECH 1039 MANGARTONG RIALDIT MARIAL ADAL 1039 MANGARTONG RIALDIT CHITING 1039 MANGARTONG RIALDIT RUM WET KOR 1039 MANGARTONG RIALDIT RUM ANGOR 1039 MANGARTONG RIALDIT MAJAK DHIAMA 1039 29 MANGARTONG RIALDIT WAR AKECH 1039 MANGARTONG RIALDIT WAR PACH 1039 MANGOK MABIOR WUNDING MAKOL 1039 MANGOK MABIOR WUNDING MABOK AGANY 1039 MANGOK MABIOR WUNDING MANYANG 1039 MANGOK MABIOR WUNDING MAKUEIKOU 1039 MANGOK MABIOR WUNDING AKEKROF 1039 MANGOK MABIOR WUNDING WUTLOL 1039 MANGOK MABIOR WUNDING MANGAR DHEL 1039 MANGOK MAKUACH MALEK PALUAL 1039 MANGOK MAKUACH MAJAK AKUENY 1039 MANGOK MAKUACH RUMWEL 1039 MANGOK MAKUACH AJIEP 1039 MANGOK MAKUACH AGOR 1039 30 MANGOK MAKUACH NGAMHAR 1039


46

MANGOK MAKUACH MAKUACH 1039 MANGOK MAKUACH MARIAL NGOP 1039 MANGOK MAKUACH MAYEN GOP 1039 MANGOK MAKUACH MAWUT MANGA 1039 MANGOK MAKUACH NYAANG DIT 1039 MANGOK MAMEER DEEK WOLAPUK 1039 MANGOK MAMEER GUK AMOL 1039 MANGOK MAMEER MAYOM AKOT 1039 MANGOK MANGOK RIANG AKOT 1039 MANGOK MANGOK MALITHBUOL 1039 MANGOK MANGOK MALOU 1039 MANGOK MANGOK MANGOK 1039 MANGOK MANGOK AYIIDHIOP 1039 31 MANGOK MANGOK PANGI 1039 MANGOK MANGOK MAJOK MOU AKUENY 1039 MANGOK MANGOK MABOK 1039 MANGOK MANGOK MARIAL ADOT 1039 MANGOK MANGOK AKONDOK 1039 MANGOK MANGOK WUNRAK 1039 MANGOK MANGOK AGOL 1039 MANGOK MANGOK WARCHUEI 1039 WUNLANG GAL WAKMACHAR 1039 WUNLANG GAL GAL 1039 WUNLANG GAL WARNYIEL 1039 WUNLANG GAL MATHIANG 1039 WUNLANG GAL ABYEI/THURLANG 1039 WUNLANG MAJAK GIER HONGAGOK/MAJAKGIER 1039 32 WUNLANG MAKUEI AGEP RIANGMEI 1039 WUNLANG MAKUEI AGEP LUETHWEK 1039 WUNLANG MAKUEI AGEP PANTHOU 1039 WUNLANG MAKUEI AGEP NGAWEL 1039 WUNLANG MAKUEI AGEP WUT-RUAL 1039 WUNLANG MAKUEI AGEP MAKUEI AGEP 1039 WUNLANG MAKUEI AGEP AJOK LUAL 1039 WUNLANG MANYIEL MALOU 1039 WUNLANG MANYIEL MAYOM 1039 WUNLANG MANYIEL WUNHONG 1039 WUNLANG MANYIEL DOOR ABUUN 1039 WUNLANG MANYIEL MANYIEL 1039 WUNLANG MANYIEL WUN YIK 1039 33 WUNLANG MANYIEL MAYOM 1039 WUNLANG MANYIEL MARIAL KUEL 1039 WUNLANG RUM MANYIEL LUONY LUAL 1039 WUNLANG RUM MANYIEL RUMMAJOK 1039 WUNLANG RUM MANYIEL MAYOM WOL 1039 WUNLANG RUM MANYIEL MAYEN NUOK 1039 WUNLANG RUM MANYIEL RUMLOC 1039 WUNLANG RUM MANYIEL MABOK 1039 WUNLANG RUM MANYIEL MALEK BOL AKON 1039 WUNLANG RUM MANYIEL RUMMANYIEL 1039


47

WUNLANG RUM MANYIEL LULIC 1039 WUNLANG RUM MANYIEL RUMMAPER 1039 WUNLANG RUM MANYIEL WARPAC 1039 WUNLANG RUM MANYIEL PAOLUIL 1039 34 WUNLANG RUM MANYIEL MALOU 1039 WUNLANG RUM MANYIEL MANY-KOOR 1039 WUNLANG RUMATHOI AKUAC 1039 WUNLANG RUMATHOI RIANGBAR 1039 WUNLANG RUMATHOI MANYIEL/ABYEI 1039 WUNLANG RUMATHOI MACHAR 1039 WUNLANG RUMATHOI RUMATHOI 1039 WUNLANG RUMATHOI MANGAR 1039 WUNLANG TONG-GOI JOKTHOK 1039 WUNLANG TONG-GOI ALAKOU 1039 WUNLANG TONG-GOI KOUIC 1039 WUNLANG TONG-GOI LOL NHOM 1039 WUNLANG TONG-GOI TONG-GOI 1039 WUNLANG TONG-GOI ARENGPINY 1039 35 WUNLANG TONG-GOI KAR ARIATH 1039 WUNLANG WAR-DONG YOMDIT 1039 WUNLANG WAR-DONG MACHAR TIT 1039 WUNLANG WAR-DONG AJUAJA 1039 WUNLANG WAR-DONG WAR KUEL THII 1039 WUNLANG WAR-DONG LONGANGUEK 1039 WUNLANG WAR-DONG WAR LANG 1039 WUNLANG WAR-DONG WARDONG 1039 WUNLANG WAR-DONG WAR KUELDIT 1039 WUNLANG WAR-DONG AJIEP 1039 WUNLANG WAR-DONG RIALDIT 1039 YARGOT HALBUL KUNYUK 1039 YARGOT HALBUL ANGUEK 1039 YARGOT HALBUL HALBUL 5715 36 YARGOT HALBUL GEER 1039 YARGOT HALBUL MATIAT 1039 YARGOT MAJOK BUOL RUM DHUK AYUOPACHEL WEI 1039 YARGOT MAJOK BUOL MALUALDIT 1039 YARGOT MAJOK BUOL MAKUAL MEL 1039 YARGOT MAJOK BUOL RUM ACHOL 1039 YARGOT MAJOK BUOL LOLKOU 1039 YARGOT MAJOK BUOL MALEK LOL 1039 YARGOT MAJOK BUOL AMIIR DENG ABUK 1039 37 YARGOT MAJOK BUOL MAJOK BUOL 1039 YARGOT MAJOK BUOL MAJOK AKECH 1039 YARGOT MAJOK BUOL GEEU 1039 YARGOT MAJOK BUOL KARICH 1039 YARGOT MAKUAC AKUEL TITCHUOR 1039 YARGOT MAKUAC AKUEL RUM ALEU 1039 YARGOT MAKUAC AKUEL DAI ABAL 1039 YARGOT MAKUAC AKUEL HONG THOK 1039 YARGOT MAKUAC AKUEL MAGAK 1039


48

YARGOT MAKUAC AKUEL ACHOK KUEI 1039 YARGOT MAKUAC AKUEL PANYIKUEL 1039 YARGOT MAKUAC AKUEL ATUEK CHOK 1039 YARGOT MAKUAC AKUEL RUMBUOL 6754 38 YARGOT MAKUAC AKUEL LANGIC 1039 YARGOT MAKUAC AKUEL GOKTHOK 1039 YARGOT MAKUAC AKUEL AKUEMKOU 7273 YARGOT MAKUAC AKUEL MACHAR TUOP 1039 39 YARGOT MAKUEI WET TONG MAKOL PANYIER 1039 YARGOT MAKUEI WET TONG MAKOL PANLUIL 1039 YARGOT MAKUEI WET TONG DHAL AKOT 1039 YARGOT MAKUEI WET TONG WUNYIIK/WAR AYAK 7793 YARGOT MAKUEI WET TONG MAKUEI WET TONG 1039 YARGOT MAKUEI WET TONG HONG AKONG 1039 YARGOT MAKUEI WET TONG MARIAL AKECJOK 1039 40 YARGOT MAKUEI WET TONG PANKOU 1039 YARGOT MAKUEI WET TONG YARGOT 6234 YARGOT MAKUEI WET TONG LUALABAK 1039 YARGOT MAKUEI WET TONG UDOM 1039 YARGOT MAKUEI WET TONG MALEK ANGUEI 1039 YARGOT NYAKRAL GUENGKOU 7273 41 YARGOT NYAKRAL CHUEI MALWAL/ AGUOK MADING 1039 YARGOT NYAKRAL KARMAKUOCH 1039 YARGOT NYAKRAL ANGOT 1039 YARGOT NYAKRAL NYAKRAL 1039 YARGOT NYAKRAL WAKABIL 1039 YARGOT YARGOT WUNTHOU 5715 42 YARGOT YARGOT MAROL NGOR 1039 YARGOT YARGOT RUMKOU 1039 YARGOT YARGOT MATTIIANG 1039 MANGOK MAKUACH MANGARANGUEI 6754


49

.IX.2. Anthropometric Survey Questionnaire

No.

HH. No.

HH Status

Age mth

Sex (F/M)

Weight Kg

Height Cm

Malnutrition Status

Oedema Y/N

MUAC Cm

Measles C/M/N

BCG Scar

Present Y/N

Vaccination card

Present? Y/N

In the last

illness, if any did

the child have?

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 26 27 28 29 30

(1) Status: 1= Resident, 2= Displaced (Because of fighting, flood, etc length < 6months), 3= Family temporary resident in the village (Cattle camp, water point, visiting family…..), 4= Returnees

(2) Measles: C= according to EPI card, M=according to mother, N=not immunized against measles (3) Illness in the last two weeks: 1=No illness, 2=Malaria, 3=Diarrhoea, 4=Respiratory infections, 5=Measles,

6=Skin Infection, 7=Worm infestation, 8=Others (Specify)


50

.IX.3. Household enumeration data collection form for a death rate calculation survey (one sheet/household)

Survey Payam: 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

Current HH members – total

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

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


51

.IX.4. Enumeration data collection form for a death rate calculation survey (one sheet/cluster)

Survey Payam: Village: Cluster number: HH number: Date: Team number:

N Current HH

member

Current HH members who

arrived during recall (exclude births)

Past HH members who left during

recall (exclude deaths)

Births during recall

Deaths during 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 26 27 28 29 30 31 32

.IX.5. Calendar of Events

MONTH Seasons 2004 2005 2006 2007 2008 2009 JANUARY (NYIETH)

53 41 29 17 5

Transplantation of tobacco Well digging Cattle taken to Toch(lowland)

Signing of CPA in Naivasha

War btn Dinka malual/Misiriya.

CPA celebration in Malakal

FEBRUARY (KOL)

52 40 28 16 4

Cutting grass for roofing the houses. Threshing of Dura Wild food collection

War btn Dinka malual/Misiriya.

Malakal fighting btn SAF

and SPLA.

MARCH 51 39 27 15 3 Clearing of field in preparation for planting. Roofing of the houses. Cutting tree for fencing fields Harvesting of tobacco

Mengitis outbreak. War btn Dinka malual/Misiriya.Malong Paul appointed as governor of NBGS.

Issuance of arrest warrant.

APRIL

50 38 26 14 2

Fishing. Bush Burning for cultivation/hunting . Rain begins. Maloda making(blacksmithing)

Garden fencing

Pope John Paul’s death. Guinea worm filters

distributed. Creation of

bomas/payams(SPLM) councils

Census done in all of South Sudan. Peace conference btn Dinka malual and Misiriya.

MAY 49 37 25 13 1

Planting Sim sim, groundnuts, sorghum, millet, Maize. Cattle brought to midland.Fishing.fencing continues

Integration of katiba Ajer led by Abdalbagi Ayii with SPLA

SPLA 16 anniversary. 20 govt officials died in plane crash in Rumbek. SAF and SPLA fought in Abyei

Traditional chiefs’ conference in Bentiu. Evangelist Mark Dan’s crusade in Wanyjok/ Aweil town

JUNE 48 36 24 12

planting of maize groundnut begins. Weeding of first plants. Cattle in mid/high land

Measles immunization campaign. Malaria campaign.

ACF –French nutrition

survey. Nhomlaau radio opened in

malualkon

JULY 59 47 35 23 11

Hunger begins. Collection of wild fruits. Weeding completed. Chasing birds from crop fields. Planting groundnut/maize.

Cattle in concentration camps in midland.

Death of Dr. Garang in a plane crash.

North-south road construction begun. Local chiefs received sorghum to sell at cheap prices.

Flooding.

AUGUST 58 46 34 22 10


53

Harvest of sorghum weeding of gnuts. Cattle in highland. Flooding

Salva Kiir swon in as president in Khartoum. Kuol Manyang appointed as caretaker for NBGS.

SEPTEMBER 57 45 33 21 9

Harvesting. Initiation ceremonies. wedding ceremonies Appointment of Mareng as first governor.

OCTOBER 56 44 32 20 8

Frequent traditional dancing. A lot of liquor brewing. fruit trees producing/ripening

Governor visited all the counties in the state.

-

NOVEMBER 55 43 31 19 7

Harvesting of gnuts. . Rain stops. Circumcision. Marriage ceremonies. Mudding of houses. Flood water receding.

Cattle in midland. Cold dry wind

Malakal conflict btn SAF and SPLA. Madut Biar appointed as NBGS governor.

Dinka malual/misiriya war

DECEMBER (KONPIU)

54 42 30 18 6 Christmas celebration

Traditional dancing by women. Holiday for school children. Fishing. Cattle to toch. Marriages ceremonies. Male

circumcision

CANS started


54

.IX.6. Qualitative Questionnaire

No Questions HH1 HH2 HH3 HH4 HH5

1 Status of the Household 1=Resident 2=IDP 3= Temporarily resident 4=Returnee

2 Sex of respondent 1=Male 2=Female

3 What is your main livelihood activity(s)? A= Pastoralism B= Fishing C= Crop farming D= Employment E= Agro-pastoralist F= Petty trade G= Other (specify)

4 What is/are your main source(s) of income? A=No income B= Sale of livestock C= Sale of livestock products D= Sale of crops E= Petty trading e.g. sale of firewood F=Casual labour G=Permanent job H= Sale of personal assets I= Remittance J=Other(Specify)

5 What is/are the household’s main food source(s) in the current

month? A=Cultivation B= Livestock

C= River(fishing) D=Buying E= Food Aid F= Wild food collection G=Kinship H= Other (specify)

6 Are your main sources of food sufficient for your household? 1=Yes (skip to qn 9) 2= No

7 If your answer is NO in question 6 above give reasons for insufficient food sources? (Note the answers in the field and code later for analysis- refer to the attached).


55


8 What do you do when your household food stock declines? A=Borrow money B=Receive money from relatives C=Ask for food from relatives, friend, neighbours (no repayment) D=Rely on food distribution (WFP, NGOs) E=Sell livestock assets F=Sell personal assets (other than livestock) G=Send children away (to relatives, friends e.t.c) H=Wild food collection I=Eat immature crops J=Reduce number of meals K=Other (specify)

9 How long will your current food stock last you? l= Less than a month 2= 1-3 months 3= 4-6 months 4= More than 6 months 5= Already completed.

10 What do you think could be done to ensure enough food?

11 Which crops did you cultivate/are you cultivating this year? 1=Sorghum 2= Maize 3=Cowpeas 4=Groundnuts 5=Simsim 6=Other

12 How many feddans of land did you cultivate/are you cultivating this year? 1=Less than 1 2= One to two 3= Two to three 4=Three to four 5= More than four

13 Which livestock do you own? 1=None 2=Cows 3=Goats 4=Chicken


56

5=Donkey 6=Sheep 7=Others

14 Does this household do fishing? 1=Yes (skip to qn 16) 2=No


15 If no, why? A= Lack of fishing equipments B= Lack of enough fish in the fishing points C= Lack of labour D= No access to fishing point E=Other (Specify)

16 What is the frequency of the following foods the HH consumed in the last 7 days? (no. days/wk) A=Meat and offal B=Cereals (sorghum, maize etc) C= Milk and milk products D= Beans, lentils and nuts E= Vegetables F= Fruits G= Fish and seafood H= Eggs I=Spices, condiments and beverages J= Sugar/honey K= Roots and tubers L= Oil/fats

A= B= C= D= E= F= G= H= I= J= K= L=

A= B= C= D= E= F= G= H= I= J= K= L=

A= B= C= D= E= F= G= H= I= J= K= L=

A= B= C= D= E= F= G= H= I= J= K= L=

A= B= C= D= E= F= G= H= I= J= K= L=

17 Do you have children under 5 years old? 1=Yes 2=No (skip to qn 25)

18 When did you start breastfeeding your youngest child after birth? (for those who do not answer immediate, probe why) 1=Immediate (within 1 hr) 2= More than 1 hr 3= 1 day 4=More than 1 day 5=Others (specify)

19 How do you breastfeed your youngest child (less than or equal to 24 months)? 1= On demand 2= Own choice 3= Others (specify)

20 How old was your youngest child when he/she stopped breastfeeding?


57

1= Child still breastfeeding (skip to qn 22 ) 2= Less than 3 months 3= 4-6 months 4= 6-12 months 5= 12-18 months 6= 18-24 months 7= Older than 24 months

21 Why did the child stop breastfeeding at this age? 1= Mother was pregnant 2= Mother couldn’t produce enough milk 3= Mother died 4= Child refused the breast 5=Heath worker/traditional healer said to stop 6= Child too old to be breastfeeding 7= Other (specify)



58

22 At what age did your youngest child (less than or equal to 24 months) start to receive food other than breast milk, vitamins, minerals and medicines? 1= Less than 4 months 2= More than or equal to 4- 6 months 3= More than or equal to 6-10months 4=More than 10months

23 Which foods are fed to your children; 6-59 months? A=Breast milk B= Cow/goat milk C= Porridge (specify) D= Vegetables E= Other (specify)

24 How many times did you feed your younger children (6-59 months) in a day in the last 7 days? 1= None/nil 2= Once 3=Twice 4= 3 times 5= More than 3 times

25 What is/ are your main current water source(s) for household consumption/use? A= River B= Lake C= Borehole D= Unprotected well E= Surface run-off F= Rain water G=Swamp water H= Seasonal spring I=Laga J= Other (specify)

26 How long does it take to go to the main source of water and back? 1= Less than 30 minutes 2= 30 minutes to 1 hour 3=More than 1 hour

27 How many times a day do you collect/fetch water? 1= 1time 2= 2 times 3=3 times 4=More than 3 times

28 What type of container do you use to collect water? 1= Jerry can (10 liter) 2= Jerry can (20 liter) 3=Pot 4= Bladder 5= Other (specify)

29 What type of container do you use to store water? 1= Jerry can (10 liter) 2= Jerry can (20 liter) 3=Pot 4= Bladder 5=Other (specify)


59


30 What do you do to water before drinking? A= Nothing B= Boiling C= Use of traditional methods D= Use chemicals E= Filter/sieves F=Decant

31 Does your household have access to a toilet facility? 1=Yes 2= No (skip to qn 33)

32 If yes, who owns the toilet? 1= Own toilet 2= Neighbours 3=Community 4=Others (specify)

33 If no, where do you go/use (probe)? A= Bush B=Open field C=Near the river D= Behind the house E= Other(specify)

34 What happens with the stools of young children (0-36 months) when they do not use the latrine or toilet facility? A=Children always use toilet or latrine B=Thrown into toilet or latrine C=Thrown outside the yard D=Buried in the yard E=Not disposed of or left on the ground F= Wash in river or water point G=No young children in the household H=Other(specify)

35 Do you have soap in the household? 1=Yes (go to qn 36) 2=No (probe if other alternatives to soap are used and specify which ones and skip to qn 37)

36 If yes what do you use it for? A= Wash hands before eating (self) B=Before feeding children C= After defecation/soiling D=Wash clothes E=Other (specify)’


60

1. Exclusive breastfeeding: 4-6 months 2. Timely complimentary feeding: ≥6 and ≤10 months

Question 7; if your answer is NO in question 6 give reasons for insufficient food sources?

A=Not enough rain (drought) B=Too much rain (flood) C=Diseases killed livestock/destroyed crops D=Pests killed livestock/destroyed crops E=Insecurity F=Livestock/crops stolen G=Not enough livestock H=Not enough land I=Not enough fish in the rivers J=Not enough people in household for production K=Not enough materials (seeds, tools, equipment) for production L=Do not have enough skill/training/education to increase production M=Sickness (illness) or handicapped N=Too young or too old

No Questions HH1 HH2 HH3 HH4 HH5 37 When a member of your household is sick where does

he/she first

seek treatment? 1=Traditional healer 2=Community health worker 3=PHCC/U 4=Hospital 5=Relative/friend 6= Pharmacy 7= No assistance 8= Other(specify)

38 How long does it take to walk to the nearest health facility? 1= Less than 30 minutes 2= More or equal to 30 minutes and less than 1hr 3= More or equal to 1 hr and less than 2 hrs 4= More or equal to 2 hrs


61

O=Do not have enough money to buy food P=Prices of food are too high Q=Lack of/inadequate income R=Other (specify)

Additional information to be gathered through key informant interviews and observation WFP food aid (FFR, FFW, FFE etc) - obtain information from WFP and SSRRC. Markets: Include how many markets are in the Payam; whether they sell food stuffs; food price changes Livestock: Where does the community buy or sell livestock; whether livestock are at home or in the cattle camps; milk availability Fishing: Probe whether there are any fishing grounds in the surveyed location and which months of the year the community does fishing. Water: Consider availability of portable water such as seeking to know how many boreholes/taps are in the area, how many are functional e.t.c Health care: Find out how many health facilities (PHCCs and PHCUs) are available in the surveyed area as well as additional information on health care seeking patterns.

Anthropometric and Retrospective Mortality Survey In the ... · Table 21: Household Use for Soap...

Documents

Transcript of Anthropometric and Retrospective Mortality Survey In the ... · Table 21: Household Use for Soap...