Samaritan’s Purse International Relief

Humanitarian Response for Conflict-Affected Populations in Unity State

AID-OFDA-G-14-00086

SMART Nutrition Survey Report December 2015

Date of Submission: January, 2016

Project Length: September 3rd, 2015 – August 31, 2016

Headquarters Contact Drew Privette Regional Director, East Africa and Middle East

Samaritan’s Purse IHQ 801 Bamboo Rd. Boone, NC 29607 Phone: +1-828-278-1251 Email: dprivette@samaritan.org

Field Contact Mark Stevens Country Director Address: South Sudan Phone: +211 914 986 211 Email: mstevens@samaritan.org

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ACKNOWLEDGMENT

The Consultant would like to appreciate individuals and institutions who contributed

towards the successful completion of the anthropometry and mortality SMART survey

conducted in Mayendit South in Mayendit County, Unity State, South Sudan.

Special appreciation goes to:

OFDA for the funding of the assessment.

Samaritan’s Purse International Relief (SP) for their facilitation and relentless support

throughout the survey period. Special thanks goes to Ruth Sanders (National M & E

Manager), Simon Munyiri (M & E Officer- Mayendit), Justin, Peter, Courage (SP

Staff).

Mayendit County administration for their support with regards to security updates

and for ensuring smooth operations.

Survey enumerators, caretakers, local authorities and the general community for their

co-operation.

Nutrition Information Working Group – South Sudan for their technical inputs that

enriched the report.

Consultant. Martin Njenga Njoroge

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TABLE OF CONTENTS ACKNOWLEDGMENT .................................................................................................... 1

LIST OF TABLES............................................................................................................... 4

LIST OF FIGURES............................................................................................................. 5

ABBREVIATIONS ............................................................................................................. 6

EXECUTIVE SUMMARY.................................................................................................. 7

INTRODUCTION ........................................................................................................... 10

Background Information ................................................................................................ 10

Objectives ...................................................................................................................... 11

Specific Objectives ......................................................................................................... 11

METHODOLOGY........................................................................................................... 12

Survey Methodology ...................................................................................................... 12

a) Geographic Target area and Population Group ................................................... 12

b) Survey design ................................................................................................... 12

c) Sampling Methodology ........................................................................................ 12

d) Sample Size Determination .............................................................................. 12

e) Sampling procedure ............................................................................................. 13

SURVEY IMPLEMENTATION ...................................................................................... 14

i. Survey team recruitment.......................................................................................... 14

ii. Survey period .......................................................................................................... 14

iii. Survey training..................................................................................................... 14

iv. Survey management and organization.................................................................. 14

v. Data collection ........................................................................................................ 14

i. Data collection tools............................................................................................ 14

ii. Anthropometric survey........................................................................................ 15

iii. Vitamin A & Deworming supplementation and Measles immunization ........... 15

vi. Child Morbidity:............................................................................................... 15

iv. Mortality. ......................................................................................................... 16

vii. Data quality ......................................................................................................... 16

viii. Data management and Analysis ........................................................................... 16

ix. Survey Limitations ............................................................................................... 16

RESULTS .......................................................................................................................... 17

Demographic characteristics........................................................................................... 17

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RESULTS (0-5 MONTHS) ............................................................................................ 17

Nutrition .................................................................................................................... 17

Morbidity and health seeking behavior for children aged 0-5 months ......................... 20

RESULTS (6-59 MONTHS) .......................................................................................... 20

Anthropometry results (Based on 2006 WHO standards) ........................................... 20

Child Morbidity and Health Seeking Behaviour .......................................................... 24

Immunization and Supplementation........................................................................... 25

Mortality .................................................................................................................... 26

FOOD SECURITY AND LIVELIHOODS (Qualitative). ............................................ 27

i. Theme 1: Food Security....................................................................................... 28

ii. Theme 2: Livelihoods .......................................................................................... 29

DISCUSSION ................................................................................................................... 30

CHILDREN 0-5 MONTHS .......................................................................................... 30

a) Nutritional Status ................................................................................................ 30

b) Morbidity Status............................................................................................... 30

CHILDREN 6-59 MONTHS ........................................................................................ 30

a) Immediate factors................................................................................................ 31

b) Underlying factors............................................................................................ 32

c) Basic causes ......................................................................................................... 32

RECOMMENDATIONS.................................................................................................. 33

CONCLUSION................................................................................................................. 35

ANNEXES. ....................................................................................................................... 36

Annex 1: Selected clusters .............................................................................................. 36

Annex 2: Plausibility Results........................................................................................... 37

Annex 3: Map of Mayendit South in Mayendit County ................................................... 38

Annex 4: Mortality Questionnaire .................................................................................. 39

Annex 5: Food Security and Livelihoods Guide ............................................................. 40

Annex 6: Anthropometry questionnaire ........................................................................... 0

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LIST OF TABLES

Table 1: Summary of Survey findings ................................................................................... 8

Table 2: Estimated sample sizes for Anthropometry and retrospective mortality ................ 12

Table 3: Survey demographics results ................................................................................. 17

Table 4: Prevalence of wasting of children 0-5.9 months .................................................... 18

Table 5: Distribution by age and sex................................................................................... 21 Table 6: Prevalence of acute malnutrition based on weight-for-height z-scores (and/or

oedema) and by sex ............................................................................................................ 21 Table 7: Prevalence of acute malnutrition by age, based on weight-for-height z-scores and/or

oedema............................................................................................................................... 22

Table 8: Prevalence of underweight based on weight-for-age z-scores by sex ..................... 23

Table 9: Prevalence of underweight by age, based on weight-for-age z-scores .................... 23

Table 10: Prevalence of stunting based on height-for-age z-scores and by sex .................... 24

Table 11: Retrospective mortality results ............................................................................ 26

Table 12: Summary of KIIs and FGDs conducted. ............................................................ 28

Table 13: Recommendations .............................................................................................. 33

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LIST OF FIGURES

Figure 1: MUAC distribution of children 0-5 months ......................................................... 18

Figure 2: Underweight distribution of children 0-5 months ................................................ 19

Figure 3: Stunting distribution of children aged 0-5 months. .............................................. 19

Figure 4: Child morbidity (0-5 months) last 2 weeks ........................................................... 20

Figure 5: Distribution of W/H Z-scores for Sampled Children .......................................... 22

Figure 6: Prevalence of reported illness in children (6-59m) in the two weeks .................... 24

Figure 7: Immunization and supplementation coverage ...................................................... 25

Figure 8: Population pyramid ............................................................................................. 27

Figure 9: UNICEF conceptual framework on malnutrition. ............................................... 31

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ABBREVIATIONS

ACF………….…….. Action against Hunger- International BSFP………………... Blanket Supplementary Feeding Programme CI…………...………. Confidence Interval CMR………..…....….. Crude Mortality Rate ENA………….....…... Emergency Nutrition Assessment EPI……………...…... Expanded Programme on Immunization FGD………………....Focus Group Discussion FSL…………………. Food Security and Livelihoods GAM………...……... Global Acute Malnutrition GFD……………...….General Food Distribution HAZ………….…….. Height for Age Z score IDP…………...…….. Internally Displaced People IMCI…………..……. Integrated Management of Childhood Illnesses IO……………...….….In Opposition KAP…………………..Knowledge Attitude and Practices KII………….…...……Key Informant Interview LAZ…………………....Length for Age Z score MAM………….……... Moderate Acute Malnutrition MUAC……………….. Mid Upper Arm Circumference NIWG…………………Nutrition Information Working Group OFDA……………….. Office of US Foreign Disaster Assistance OTP………………….. Outpatient Therapeutic Programme PHCC/U………...…….Primary Health Care Center/ Unit PLW…………………. Pregnant and Lactating women PPS…………………….Probability Proportion to Size SAM…………….…..... Severe Acute Malnutrition SD……………………. Standard Deviation SFP……………………Supplementary Feeding Programme SMART………….…….Standardized Monitoring & Assessment in Relief and Transition SP……………………...Samaritan’s Purse SPLA…………………. Sudanese People Liberation Army SPLM…………………. Sudanese People Liberation Movement SSRA/C……………..... South Sudan Rehabilitation Agency/ Commission U5MR…………..….… Under 5 Mortality Rate UNICEF…………….... United Nations Children Fund UNIDO………………..Universal Interventions and Development Organization WFP……………………World Food Programme WASH………………….Water Sanitation and Hygiene WAZ…………………..Weight for Age Z score WHO………………… World Health Organization WHZ……………....…. Weight for Height Z score WLZ…………….……..Weight for Length Z score

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EXECUTIVE SUMMARY

Introduction Mayendit County is one of the nine counties of Unity State; it borders Leer, Koch, Tonj North, Tonj East, Rumbek North, and Panyijar counties. Mayendit South where the survey was conducted has five payams namely; Madol 1, Madol 2, Bhor, Pabuong and Malkuer. Agriculture is the county’s primary economic activity. The people are nomadic agro- pastoralists who engage in both agriculture and rearing of livestock, especially cattle. Fishing is also prevalent in the area. Samaritan’s Purse International Relief and UNIDO are implementing various interventions in the county namely food security, water, sanitation and hygiene (WASH) nutrition and health. Back in April 2014, the World Food Programme (WFP) and UNICEF conducted a rapid assessment which identified a population of 20,500 in southern Mayendit with a proxy Global Acute Malnutrition (GAM) rate of 29.2% and Severe Acute Malnutrition (SAM) rate of 1.9%. In August 2014, Samaritans Purse (SP) conducted mass Mid Upper Arm Circumference (MUAC) screening which registered a children under five (U5) proxy GAM rate of 9.9% and a Pregnant and Lactating Women (PLW) under nutrition rate of 26.2%. While Mayendit saw an improvement in malnutrition prevalence in 2014, recent mass MUAC screening conducted by SP in March 2015 registered a proxy GAM of 20.24% in children U5. Due to its more secure location, it is likely that southern Mayendit will receive an influx of Internally Displaced Persons (IDPs) as fighting resumes during the dry season. This will put additional pressure on already limited food resources and increase the likelihood of a deterioration of U5 and PLW’s nutritional status. In addition, the recent Knowledge Attitude and Practices (KAP) survey that was conducted in November 2015 by SP showed that the nutrition situation was poor as the levels were above the emergency threshold of 15%. To get a better understanding and assess the severity of the nutrition and mortality situation in Mayendit County, SP with OFDA funding conducted a Nutrition and Mortality SMART survey from the 10 th to 23th December, 2015. Enumerator training was conducted from 11 th to 14th December, 2015 with data collection conducted from the 15th to 23rd December, 2015. Objectives The overall survey objective was to determine the nutrition status among children aged 6 -59 months and to estimate crude and under-five retrospective mortality rates in Mayendit County. This also included collecting morbidity data (2-week recall), immunization and supplementation coverage, and a qualitative component on Food Security and Livelihoods (FSL). Methodology The survey was a cross sectional study with two-stage cluster sampling using SMART methodology. Anthropometric data, two-week retrospective morbidity, Measles and vitamin A coverage and retrospective mortality data was collected. The sampling frame was drawn from the population of five payams. The first stage involved random selection of 36 clusters based on probability to proportional to size using the ENA for SMART software Nov, 2013 version (9th July 2015 update).

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Results Findings of the nutrition survey indicate poor nutrition situation among the surveyed population as per WHO standards. The prevalence of Global Acute Malnutrition (GAM) in Mayendit County based on weight for height z scores /and or oedema was 16.1% [(12.1 - 21.0 95% C.I.) and the prevalence of Severe Acute Malnutrition (SAM) was 2.4% [1.3 – 4.5, 95% C.I.]. The poor nutrition situation is attributed to poor food security due to the insecurity and high incidence of disease among children aged 6-59 months. Results for Anthropometry, Mortality, and Immunization and Morbidity indicators are summarized below. Table 1: Summary of Survey findings

Children 6-59 months Anthropometric results(WHO 2006 Standards)

INDEX INDICATOR DECEMBER 2015

WHZ- scores

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

(74) 16.1 %

(12.1 - 21.0 95% C.I.)

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

(63) 13.7 %

(10.2 - 18.2 95% C.I.)

Prevalence of severe malnutrition (<-3 z-score and/ or no oedema)

(11) 2.4 %

(1.3 - 4.5 95% C.I.)

HAZ- scores

Prevalence of stunting (<-2 z-score)

(59) 12.8 %

(9.3 - 17.4 95% C.I.)

Prevalence of moderate stunting (<- z-scores and >=-3 z-score)

(56) 12.2 %

(8.8 - 16.6 95% C.I.)

Prevalence of severe stunting (<-3 z-score)

(3) 0.7 %

(0.2 - 1.9 95% C.I.)

WAZ- scores

Prevalence of underweight (<-2 z-score)

(66) 14.3 %

(11.2 - 18.2 95% C.I.)

Prevalence of moderate underweight (<- z-scores and >=-3 z-score)

(58) 12.6 %

(9.6 - 16.4 95% C.I.)

Prevalence of severe underweight (<-3 z-score)

(8) 1.7 %

(0.9 - 3.3 95% C.I.)

MUAC

Prevalence of global malnutrition (< 125 mm and/or oedema)

(34) 7.4 %

(5.0 - 10.9 95% C.I.)

Prevalence of global malnutrition (< 125 mm and >=115mm and/or oedema)

(27) 5.9 %

(3.6 - 9.3 95% C.I.)

Prevalence of global malnutrition (< 125 mm and/or oedema)

(7) 1.5 %

(0.8 - 3.0 95% C.I.)

Mortality (retrospective over 109 days prior to interview

Mortality results Crude mortality rate(CMR) (total deaths/10,000 people / day)

2.78 (2.22 – 3.47, 95% CI)

Under-five mortality rate(U5MR) (deaths in children under five/10,000 children under five / day)

0.71 (0.27-1.85, 95% CI)

Measles immunization & Vitamin A supplementation

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Conclusion and recommendations The findings of the assessment depict a poor nutrition situation, above the WHO emergency threshold in Mayendit South which is being caused by an interplay of factors ranging from household food insecurity, disease, poor maternal care practices and limited programme coverage. This calls for concerted efforts with an integrated approach on the interventions being implemented in the area with a special focus on the Supplementary Feeding Programme (SFP) due to the high cases of moderately malnourished children and Outpatient Therapeutic Programme (OTP) due to the high numbers of severely malnourished children. The IYCF programme currently being implemented requires to integrate a BCC and an IMCI component in order to improve the nutrition situation. In addition, the health programme implemented should be scaled up and increase its focus on integrated management of childhood illnesses (IMCI). In addition, the food security and livelihoods (FSL) programme implemented in the area require immediate scale-up as the population start the dry period and as drought makes most of the households vulnerable to food insecurity and eventually malnutrition. The FSL programme needs to focus on empowering the livelihoods of the population e.g. giving fishing nets, in order for them to be able to mitigate household food insecurity. Lastly, there is an urgent need to increase the coverage and scale up of the programmes currently implemented in Mayendit South in order to have a wider reach of the vulnerable populations.

Measles coverage ≥ 9 months

Overall Immunization Coverage Verified by card Verified by mothers recall

39.1% 22.4% 16.7%

Vitamin A coverage (6-59) last 6 months

Overall Vitamin A coverage

37.2%

Deworming (12-59) last 6 months Overall deworming coverage 25.3%

Morbidity for the last 2 weeks

Child Illness in the last 2 weeks

Yes No

57.0% 43.0%

Proportion of children by type of sickness

Fever Cough Diarrhea Skin Infection Eye infections Others

44.1% 26.5% 19.6 % 8.0% 1.3% 0.4%

Health seeking behavior

Treatment sought (64.6%)

Sought treatment WHERE?

PHCU

Shop

Traditional practitioner

64.6% 96.4% 3.6% 0.5%

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INTRODUCTION

Background Information Mayendit County is one of the nine counties of Unity State; it borders Leer, Koch, Tonj North, Tonj East, Rumbek North, and Panyijar counties. Mayendit South where the survey was conducted has five payams namely; Madol 1, Madol 2, Bhor, Pabuong and Malkuer. Since 2013, Unity State has been experiencing on and off conflict . In May 2015, fighting escalated as the SPLA moved in to regain SPLM/A-IO territory in counties: Mayendit, Leer, and Payiniar in Unity State, and Maiwut in the Upper Nile. As a result, humanitarian workers were instructed to evacuate the region which included the SP office in Mayendit (WFP, 2015). However, Mayendit South, due to its more remote and secure location, has recently had an influx of Internally Displaced Persons (IDPs) as fighting resumes during the dry season. Agriculture is the county’s primary economic activity. Southern Mayendit is characterized by black cotton soil, receives sufficient annual rainfall and is prone to flooding during the long rain seasons. According to the Food Security and Livelihoods assessment conducted by SP in November 2015, 24% of respondents relied on their own production and 47% relied on purchased food. The people are nomadic agro- pastoralists who engage in both agriculture and rearing of livestock, especially cattle. Fishing is also prevalent in the area. According to the Agriculture and Food Information System (AFIS) of South Sudan (2015), Unity State in particular Mayendit have shown early signs of drought causing pockets of starvation that could lead to a catastrophe without adequate humanitarian assistance. Back in April 2014, the World Food Programme (WFP) and UNICEF conducted a rapid assessment which identified a population of 20,500 in southern Mayendit with a proxy Global Acute Malnutrition (GAM) rate of 29.2% and Severe Acute Malnutrition (SAM) rate of 1.9%. In August 2014, Samaritans Purse (SP) conducted mass Mid Upper Arm Circumference (MUAC) screening which registered a children under five (U5) proxy GAM rate of 9.9% and a Pregnant and Lactating Women (PLW) under nutrition rate of 26.2%. While Mayendit saw an improvement in malnutrition prevalence in 2014, recent mass MUAC screening conducted by SP in March 2015 registered a proxy GAM of 20.24% in children U5. As already highlighted, due to its more secure location, southern Mayendit continues to receive an influx of Internally Displaced Persons (IDPs) as the conflict ensues. However, with the recent return of the opposition (SPLM/A-IO) in Juba on 25th December 2015, there is hope that the security situation will stabilize in the coming months. Due to the dry and hunger season in the coming months (January- April, 2016) it is anticipated that this period will put additional pressure on already limited food resources and increase the likelihood of a deterioration of U5 and PLW’s nutritional status. In addition, the recent KAP survey that was conducted in November 2015 by SP showed that the nutrition situation was poor as the levels were above the emergency threshold of 15%. To mitigate the deteriorating situation in Mayendit South, SP is implementing various interventions in the County namely food security, water, sanitation and hygiene (WASH) nutrition. Samaritan’s Purse in partnership with WFP resumed food distribution in September 2015 and expanded services within the host communities in Mayendit South to

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include monthly general food distributions (GFD) and blanket supplementary feeding programs (BSFP) thus improving availability and access to fortified and nutritious foods. UNIDO is also another partner in Mayendit South implementing an Outpatient Therapeutic Programme (OTP) targeting the severely malnourished children and a health programme. To get a better understanding and assess the severity of the nutrition and mortality situation in Mayendit County, SP with OFDA funding conducted a Nutrition and Mortality SMART survey.

Objectives The overall objective was to provide anthropometric data along with mortality rates, morbidity and FSL information using the SMART methodology for Mayendit South in Mayendit County.

Specific Objectives To estimate the prevalence of acute malnutrition of children aged 6-59 months To estimate the retrospective crude and U5 mortality rates.

To estimate the prevalence of some common child illnesses (suspected measles, diarrhea and acute respiratory illnesses).

To estimate the coverage of measles vaccination, Vitamin A supplementation and

deworming status among children aged 6-59 months. To describe the current household food security and livelihoods situation.

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METHODOLOGY

Survey Methodology The Standardized Monitoring and Assessment of Relief and Transition (SMART) methodology was used for this survey. The methodology provides a basic integrated method for assessing nutritional status and mortality rate.

a) Geographic Target area and population group The SMART nutrition survey was carried out in Mayendit South, in Mayendit County, Unity State in South Sudan. In Mayendit South, 5 payams were targeted for the survey i.e. Madol 1, Madol 2, Bhor, Pabuong and Malkuer. The study population for the anthropometric measurement and health (morbidity and immunization) was children from the age of 6 to 59 months; whereas all households formed the population for retrospective mortality .

b) Survey design

The survey was a cross sectional study with two-stage cluster sampling using SMART methodology. Anthropometric data, two-week retrospective morbidity data and retrospective mortality data was collected.

c) Sampling Methodology A two stage cluster sampling was employed to select the households participating in the surveys. Villages were considered the smallest geographical units.

d) Sample Size Determination Sample size for anthropometry and retrospective mortality was determined using Emergency Nutrition Assessment (ENA) for SMART software version 2011 (July 9th, 2015 update) . For anthropometry, a total of 522 children in 430 households were calculated and for mortality a total of 1966 persons and 277 households were calculated as a representative sample size using the parameters summarized in the table below. Table 2: Estimated sample sizes for Anthropometry and retrospective mortality

Parameter Anthro. Mortality Justification

Estimated Prevalence (%)

12.7 1.23 This was adopted from December, 2014 SMART Survey in Mayendit County by ACF.

Desired Precision (%) 3.5 0.6 Adopted from December, 2014 SMART Survey in Mayendit County by ACF (Anthropometry). Recommendation from Global SMART Guideline (Mortality)

Design Effect 1.38 1.5 Adopted from December, 2014 ACF SMART Survey, Mayendit County.

Recall Days 109 Recall Period from field event in Mayendit. Average Household Size 7.9 7.9 Adopted from September, 2014 ACF SMART &

Mortality Survey, Mayendit County.

% Children Under-Five 19 December, 2014 ACF SMART Survey, Mayendit County

% Non-response 10 10 To Cater for Expected Non-Response Rate Sample Size (HHs) 430 277

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Considering that the sample sizes for anthropometry and mortality yielded different households samples, the larger of the two calculations (430) was used. Based on issues that impact on the total number of households that could be done in a day i.e. travel hours, introduction and household listing, lunch breaks and time taken to administer a questionnaire in a household, 12 households were visited by a team per day. 36 clusters had been planned to be visited, however one cluster (Bengpulual village -30) was not covered because the cluster was deserted at the time of the survey due to cattle raiding that was going on in the area. This couldn’t allow the assessment to be carried out in this cluster

e) Sampling procedure The Nutrition survey employed two-stage cluster sampling methodology.

First stage sampling (selection of clusters)

The first stage was selection of clusters based on probability proportional to population size (PPS). Each village was considered as a smallest geographical unit. The population data used was compiled in Mayendit together with the local authorities. Village level population figures were updated with the support of the South Sudan Rehabilitation Agency (SSRA) focal persons, the chiefs of the payams who enabled accurate population estimates in consideration of population in and out migration. All villages from the 5 payams and their total population were entered in the ENA for SMART software (July 9 th, 2015 update version), and the software randomly assigned the clusters to the villages, based on their respective populations. (See annex 1)

Second stage sampling (selection of households)

The required numbers of households were selected using simple random sampling which first involved doing a listing of all the households and assigning each household a number. Secondly, they wrote all the numbers on a small piece of paper which were then folded and finally selection of 12 households was done. This ensured that all the households listed were given an equal chance of being selected. The team started the survey from any convenient household of the randomly selected households (12 households) to carry out anthropometric and mortality questionnaires which were conducted by the enumerators while ensuring confidentiality and privacy . All eligible children were included in the anthropometric survey. Revisits were done to households in which eligible children (under five) or entire family were found to be absent at first attempt.

Household definition

A household was defined as consisting of all persons with family or other social relationships among themselves eating from the same cooking pot and sharing a common roof.

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SURVEY IMPLEMENTATION

Survey details (methodology) were discussed with the Nutrition Information Working Group (NIWG) –South Sudan for validation of the methodology prior to the survey exercise and after the survey for the preliminary results. Validation of both happened on 3 rd December 2015 and 7 th January 2016 respectively. Relevant information on security and access were obtained from the SP Security focal person and SRRC authorities in Mayendit County. Meetings were held with the respective administrative authorities on arrival by the survey team.

i. Survey team recruitment This was conducted on 10 th December 2015 by the consultant and SP National M&E Manager. The recruitment of Survey team was done based on their prior experience in a similar survey and educational background.

ii. Survey period The survey was conducted from the 10 th to 28th December, 2015 (to include enumerators training and data collection of both the SMART data on nutrition, mortality & morbidity and qualitative data on food security and livelihoods.

iii. Survey training The teams were intensively trained for four days. The training focused on survey objectives, methodology, anthropometric measurements, field procedures, interviewing techniques, administration of the survey tools and conducting focus group discussions (FGDs) and key informant interviews (KIIs). Standardization test and field test were conducted as part of the training. Standardization test was to evaluate accuracy and precision of the survey enumerator’s measurements, each enumerator took measurements of 10 children (aged 6-59months) twice.

iv. Survey management and organization The survey had four teams each comprising of one team leader and two Survey Assistants. The teams were actively supervised by the Consultant and Samaritan’s Purse staff who were on the field with them. Each team was assisted by a village guide (recruited at the village level) to lead and guide the survey team within the village in locating the selected households.

v. Data collection

i. Data collection tools

Structured questionnaires were used to collect anthropometric & health data (anthropometric questionnaire) from all children within the eligible age range (6 -59 months) & for mortality data (individual mortality questionnaire) in households regardless of whether they had children or not. For the qualitative data, an interview guide was used and the information recorded verbatim on note books.

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ii. Anthropometric survey Structured questionnaires were used to collect anthropometric and morbidity data from all children within the eligible age range (6-59 months) using an anthropometric questionnaire. The collected data was:

Age: The age of the children was determined using a local calendar of events (no birth records available). The calendar of local events was jointly developed with the survey assistants and county leaders. A separate calendar of events was adapted for the northern and southern parts of the county to consider memorable events in each area.

Sex: Male or female

Weight: Children’s weights were taken without clothes using SECA digital scales (100 g precision).

Height/length: Children were measured using wooden UNICEF measuring boards (precision of 0.1 cm). Children less than 87 cm were measured lying down, while those greater than or equal to 87 cm were measured standing up.

Mid-upper arm circumference: MUAC measurements were taken at the mid-point of the left upper arm using child tapes (precision of 0.1 cm).

Bilateral pitting Oedema: Assessed by the application of normal thumb pressure

on both feet for three seconds. Occurrence of pitting oedema on both feet upon release of the fingers indicated nutritional oedema classified as severely malnourished.

Referral: All severely malnourished children found were referred using referral

forms to UNIDO while all moderately malnourished children were referred to SP

who are running a targeted supplementary feeding programme (TSFP).

iii. Vitamin A & Deworming supplementation and Measles immunization Data on measles and Vitamin A supplementation, deworming and measles vaccination were also collected to estimate their coverage.

Measles: Assessed by checking for measles vaccination on EPI cards or by recall

and was only done for eligible children aged 9-59 months.

Vitamin A: Mothers/caretakers were asked whether the child had received Vitamin

A in the last 6 months. Vitamin A capsule was shown to caregivers to aid in recall,

EPI cards were also be used. Eligible children were aged 6-59 months.

Deworming: Mothers/caretakers were asked whether the child had received

deworming tablets in the last 6 months. Deworming tablets was shown to caregivers

to aid in recall. Eligible children were aged above 12-59 months.

vi. Child Morbidity: Two-weeks retrospective morbidity data was collected from mothers/caregivers of all children included in the anthropometric measurement. The mother/caregiver was asked if the child had been ill in the past two weeks and if so, and then asked type of illness and treatment sought.

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iv. Mortality. Retrospective mortality data was collected in all the visited households, including those with no children aged 6-59 months. Information was collected on the age and sex of the household members, the number of household members present within the recall period, the number of persons who arrived on or left within the recall period, the number of births and deaths over the recall period and pregnancies during the recall period. The cause and location of death was also captured. Individual Mortality questionnaire was used to collect data.

vii. Data quality The recruitment of a highly qualified survey team, training survey assistants with emphasis on age estimation using calendar of local events, standardization test, piloting, close supervision of the teams by the Consultant and the SP staff, daily meetings during data collection to address challenges, data entry completed on a daily basis, and daily plausibility checks ensured the quality of the data collected in the field.

viii. Data management and Analysis Emergency Nutrition Assessment (ENA) for SMART software 2011 version (July 9th, 2015 update) was used to enter and analyze anthropometric and mortality data. Morbidity data was analyzed using Excel.

ix. Survey Limitations

Access challenges due to poor road network and the swampy nature of the area during this period of the year (many flooded areas).

Inability to access all selected villages (one selected cluster had recently moved due to cattle raids).

Long travel hours as teams had to walk long distances in flooded areas (2-4 hours, one

way) to access villages.

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RESULTS

Demographic characteristics A total of 406 households were visited for mortality survey. Total population sample was 2971.5 as summarized in the table below. Table 3: Survey demographics results

Parameters Results Total number of households 406

Total population sampled 2971.5

Males 1376.0 Females 1595.5

Sex Ratio 0.86

Average household size 7.3 Total population of under 5 520

% of under-five population 19.9%

RESULTS (0-5 MONTHS)

Nutrition

A total of 62 children (37 boys, 25 girls) under the age of 6 months were included in the survey. This represented 15.3% of all the households sampled (406) during the survey and was hence providing an adequate representation of the survey area. The children were selected from every household with a child less than 6 months. All the anthropometric measurements were taken for the children. A corrective factor, as recommended, was applied for the recumbent length measurements for the children who couldn’t straighten their legs due to their tender age/ or medical condition was adjusted in order to have the correct length measurements. Analysis was done by World Health Organization Anthro. Software version 3.2.2 (http://www.who.int/childgrowth/en) which is globally recommended for analysis of children below 6 months.

Anthropometry results (Based on 2006 WHO standards) A total of 62 children (37 boys, 25 girls) were assessed for their nutritional status through anthropometric measurements from 406 households.

a) Wasting

Data analysis for weight for length (WLZ) scores were based on WHO 2006 standards. The results showed that the children had an average mean WLZ score of -0.45 (_+2 SD) which showed that majority of the children were wasted. Of the malnourished children, 27.4% (16.7 – 51.5, 95% CI) were moderately wasted, <-2SD while 12.9% (6.3 – 24.6, 95% CI) were severely wasted, <-3SD. This is as shown by the table below:

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Table 4: Prevalence of wasting of children 0-5.9 months

Age N WLZ (%) 95% CI % < -3SD % < -2SD % > +1SD % > +2SD % > +3SD Mean SD

Total: 62 12.9 (6.3, 24.6)

27.4 (16.7, 41.5)

25.8 (15.1, 40.5)

14.5 (8.7%, 23.2)

3.2 (0.9%, 11.3)

-0.45 2.11

When the data was disaggregated by gender for wasting, it was realized that boys were more wasted with a mean value of -0.91 (-+1.92 SD) as compared to the girls who had a mean value of 0.23 (-+2.24SD). Assessment of wasting using MUAC shows a similar trend where a majority of the children are wasted, mean value of -0.5 (-+1.05SD). When the data is disaggregated by gender, slightly more boys are wasted as compared to the girls i.e. mean value –0.6 (-+1.13 SD) and -0.33 (-+0.92 SD) respectively. The wasting by MUAC is as shown in the figure below which depicts the MUAC distribution curve of the survey sample relative to the WHO- Gaussian curve. The findings indicate a slight shift to the left of the sample curve which indicates more children being wasted in the sampled population in comparison to the reference population.

Figure 1: MUAC distribution of children 0-5 months

b) Underweight The results showed that the children had an average mean WAZ score of -0.14 (_+1.38 SD) which showed that majority of the children were also underweight. Of the malnourished children, 9.7% (4.5 – 19.8, 95% CI) were moderately underweight, <-2SD while 1.6% (0.2 – 10.7, 95% CI) were severely underweight, <-3SD. This is as shown by the figure below which depicts the WAZ score distribution curve of the survey sample relative to the WHO- Gaussian curve. The findings indicate a slight shift to the left of the sample curve which indicates more children being underweight in the sampled population in comparison to the reference population.

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Figure 2: Underweight distribution of children 0-5 months

When the data is disaggregated by gender, the same trend observed for the wasting by WLZ scores and MUAC is also seen where more boys are underweight as compared to the girls i.e. mean value of -0.43 (-+1.18 SD) for boys as compared with a mean value for girls which was 0.31 (-+1.54 SD).

c) Stunting.

The results showed that the children had an average mean length for age (LAZ) score of 0.4 (-+1.78 SD) which showed that majority of the children were not stunted. This is as shown by the figure below which depicts the LAZ score distribution curve of the survey sample relative to the WHO- Gaussian curve. The findings indicate a slight shift to the right of the sample curve which indicates most of the children aged 0-5 months not being stunted in the sampled population in comparison to the reference population.

Figure 3: Stunting distribution of children aged 0-5 months.

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Morbidity and health seeking behavior for children aged 0-5 months Retrospective morbidity data was collected among children 0-5 months (two-week recall) to assess the occurrence of main diseases. Results showed that 43.5% (n=27) of children were reportedly sick in the two weeks prior to the survey (Figure 4). Among children reported sick, 44.2 % (n=19) had episodes of fever, 23.3% (n=10) reported cough, 14.0% (n=6) reported diarrhea and 18.6% (n=8) reported skin infection. Health seeking behaviour was assessed by asking the respondents what they did the last time the child was sick. Quality of health care services and duration taken before a sick child receives medical attention contributes to the severity of illness. Survey findings indicate a poor health seeking behaviours by the caregivers with only (39.3%) of the caregivers seeking assistance. All who sought assistance reported health facilities (PHCU) as where they took the child. This information is summarized in the figure below:

Figure 4: Child morbidity (0-5 months) last 2 weeks

RESULTS (6-59 MONTHS) Anthropometry results (Based on 2006 WHO standards) A total of 491 children (231 boys, 260 girls) were assessed for their nutritional status through anthropometric measurements from 406 households out of the 432 planned to be included in the survey. One cluster was not accessible. The survey achieved 94% of the sample size translating to a 6% non-response rate. The sample size was achieved as there was a high number of children included in the survey (above the expected 387 children for this number of households), which can be explained by large household size. The data analysis for Weight for Height Z scores (WHZ) was done with 460 children. The overall data quality was scored as excellent score of 8%, (see annex 2 plausibility check), and the standard deviation (SD) for WHZ was 1.13. Design effect for WHZ <-2 was 1.61 which indicated a normal distribution (as expected with no indication of pockets of malnutrition).

43.5

56.5

Child morbidity% (last 2 wks)

yes no

0

10

20

30

40

50

fever cough diarrhoea skininfection

44.2

23.3

14 18.6

Morbidity type % (last 2 weeks)

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a) Distribution by age and sex

The ages of the children were determined by recall using the calendar of local events developed by the survey teams during the training. Table 5: Distribution by age and sex Boys Girls Total Ratio AGE (mo) no. % no. % no. % Boy: girl

6-17 44 41.1 63 58.9 107 23.3 0.7

18-29 59 51.8 55 48.2 114 24.8 1.1 30-41 43 41.0 62 59.0 105 22.8 0.7

42-53 61 54.0 52 46.0 113 24.6 1.2

54-59 12 57.1 9 42.9 21 4.6 1.3 Total 219 47.6 241 52.4 460 100.0 0.9

As shown in table 3 above, the overall sex ratio of the survey sample was p =0.305 which indicates that boys and girls were equally represented as a whole demonstrating unbiased sample. The age ratio of 6-29 months to 30-59 months was 0.92, meaning there was good representation of the age groups (the value is expected to be around 0.85).

b) Wasting

Estimation of prevalence of malnutrition was done based on WHO 2006 standards. The prevalence of GAM was 16.1% (12.1 - 21.0 95% C.I.) and the prevalence of SAM was 2.4 % (1.3 - 4.5 95% C.I.) The nutrition situation is critical (above the emergency/critical level of 15% according to the WHO classification). Table 6: Prevalence of acute malnutrition based on weight-for-height z-scores (and/or oedema) and

by sex

All n = 460

Boys n = 219

Girls n = 241

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

(74) 16.1 % (12.1 - 21.0 95% C.I.)

(35) 16.0 % (11.2 - 22.4 95% C.I.)

(39) 16.2 % (11.3 - 22.6 95% C.I.)

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

(63) 13.7 % (10.2 - 18.2 95% C.I.)

(31) 14.2 % (9.3 - 21.1 95% C.I.)

(32) 13.3 % (9.2 - 18.7 95% C.I.)

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

(11) 2.4 % (1.3 - 4.5 95% C.I.)

(4) 1.8 % (0.7 - 4.6 95% C.I.)

(7) 2.9 % (1.3 - 6.4 95% C.I.)

The prevalence of oedema is 0.0 % Analysis of the data by sex shows that the difference in malnutrition between the boys and girls is not statistically significant and both genders are at equal risk of malnutrition.

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Figure 5: Distribution of W/H Z-scores for Sampled Children

Figure 5 depicts the WFH z-score distribution curve of the survey sample relative to the WHO- Gaussian curve. The findings indicate a slight shift to the left of the sample curve which indicates poor nutrition status of the sampled population in comparison to the reference population. The standard deviation SD for WHZ was s 1.13, (which lies within the acceptable range 0.8 – 1.2), indicating representativeness in the sample selection. However, the SD value was slightly high which was indicative of some difference in children between different payam clusters, especially clusters located in the swamps, and far off villages in Malkuer and Pabuong payams. Table 7: Prevalence of acute malnutrition by age, based on weight-for-height z-scores and/or oedema

Severe wasting (<-3 z-score)

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

Normal (> = -2 z score)

Age (mo) Total no. No. % No. % No. %

6-17 107 4 3.7 27 25.2 76 71.0

18-29 114 1 0.9 13 11.4 100 87.7 30-41 105 1 1.0 7 6.7 97 92.4

42-53 113 5 4.4 13 11.5 95 84.1

54-59 21 0 0.0 3 14.3 18 85.7 Total 460 11 2.4 63 13.7 386 83.9

As depicted by the table above, when the prevalence of wasting is disaggregated by age, the 6-17 months age group is more affected by wasting as compared to the other age-groups. For all the 6-59m children affected by moderate wasting, 25.2% are aged between 6-17 months. The prevalence of GAM based on MUAC was 7.4% [5.0 – 10.9 95% C.I.] and SAM based on MUAC was 1.5% [0.8 – 3.0 95% C.I.].

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c) Underweight

The prevalence of underweight was 14.3% [11.2-18.2, 95% C.I]. As was the case of acute malnutrition between boys and girls, there was no significant difference in the level of underweight between the boys and girls as they were both equally vulnerable to be affected by malnutrition. This is as shown by the table below: Table 8: Prevalence of underweight based on weight-for-age z-scores by sex

All n = 460

Boys n = 219

Girls n = 241

Prevalence of underweight (<-2 z-score)

(66) 14.3 % (11.2 - 18.2 95% C.I.)

(28) 12.8 % (9.0 - 17.9 95% C.I.)

(38) 15.8 % (11.2 - 21.7 95% C.I.)

Prevalence of moderate underweight (<-2 z-score and >=-3 z-score)

(58) 12.6 % (9.6 - 16.4 95% C.I.)

(26) 11.9 % (8.1 - 17.0 95% C.I.)

(32) 13.3 % (9.3 - 18.5 95% C.I.)

Prevalence of severe underweight (<-3 z-score)

(8) 1.7 % (0.9 - 3.3 95% C.I.)

(2) 0.9 % (0.2 - 3.7 95% C.I.)

(6) 2.5 % (1.2 - 5.2 95% C.I.)

When the data is disaggregated into the different age-groups, the same trend as seen with wasting is observed, i.e. more children aged 6-17m are more affected by being underweight as compared to the other age groups. This is true for both severe and moderate underweight where out of all the children affected by severe underweight and moderate underweight, 2.8% and 17.8% respectively are aged between 6-17 months. This is as shown in the table below. Table 9: Prevalence of underweight by age, based on weight-for-age z-scores

Severe underweight (<-3 z-score)

Moderate underweight (>= -3 and <-2 z-score )

Normal (> = -2 z score)

Age (mo) Total no. No. % No. % No. %

6-17 107 3 2.8 19 17.8 85 79.4

18-29 114 1 0.9 16 14.0 97 85.1 30-41 105 2 1.9 5 4.8 98 93.3

42-53 113 2 1.8 17 15.0 94 83.2

54-59 21 0 0.0 1 4.8 20 95.2 Total 460 8 1.7 58 12.6 394 85.7

d) Stunting

Stunting is an indicator of chronic (long-term) malnutrition which is mainly due to long term food deprivation, micronutrient deficiencies, recurrent illnesses and other factors which interrupt normal growth. Findings indicated an overall global chronic malnutrition prevalence of 12.8 % (9.3 - 17.4 95% C.I.) and severe chronic malnutrition prevalence of 0.7% (0.2 - 1.9, 95 CI). Stunting was slightly higher among boys 14.2 % (9.4 - 20.8 95% C.I.) than girls 11.6 % (7.6 - 17.4 95% C.I.) However, there was no significant difference in the level of stunting between the boys and girls indicating that boys and girls are at equal risk of being stunted .This is as shown in the table below:

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Table 10: Prevalence of stunting based on height-for-age z-scores and by sex

All n = 460

Boys n = 219

Girls n = 241

Prevalence of stunting (<-2 z-score)

(59) 12.8 % (9.3 - 17.4 95% C.I.)

(31) 14.2 % (9.4 - 20.8 95% C.I.)

(28) 11.6 % (7.6 - 17.4 95% C.I.)

Prevalence of moderate stunting (<-2 z-score and >=-3 z-score)

(56) 12.2 % (8.8 - 16.6 95% C.I.)

(31) 14.2 % (9.4 - 20.8 95% C.I.)

(25) 10.4 % (6.7 - 15.8 95% C.I.)

Prevalence of severe stunting (<-3 z-score)

(3) 0.7 % (0.2 - 1.9 95% C.I.)

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

(3) 1.2 % (0.4 - 3.7 95% C.I.)

Child Morbidity and Health Seeking Behaviour

Retrospective morbidity data was collected among children 6-59 months (two-week recall) to assess the occurrence of main diseases. Results showed that 57% (n=280) of children were reportedly sick in the two weeks prior to the survey (Figure 6). Among children reported sick, 44.1 % (n=198) had episodes of fever, 26.5% (n=119) reported cough, 19.6% (n=88) reported diarrhea, 8% (n=36) reported skin infection, 1.3% (n=6) reported eye infection and 0.4% (n=2) reported other illness. Health seeking behaviour was assessed by asking the respondents what they did the last time the child was sick. Quality of health care services and duration taken before a sick child receives medical attention contributes to the severity of illness. Survey findings indicate an average health seeking behaviours by the caregivers with more than half (64.6%) of the caregivers seeking assistance .Of those who sought assistance, (96.4%) sought assistance from health facilities (PHCU). Only a few of the caregivers (2.8%) sought assistance from the retail shop (3.6%) and traditional healers (0.5%).

Figure 6: Prevalence of reported illness in children (6-59m) in the two weeks

57%

43%

Morbidity (2 week recall)

Yes No

0.0%5.0%

10.0%15.0%20.0%25.0%30.0%35.0%40.0%45.0%

44.1%

26.5%

19.6%

8.0%

1.3% 0.4%

Type of illness

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Immunization and Supplementation

a) Vitamin A

World Health Organization (WHO) recommends that Vitamin A supplementation starts at 6months and subsequently at 6 months intervals until a child reaches age of 5 years. Caregivers were shown Vitamin A capsules and asked whether their children had taken a similar one in the preceding 6 months of the survey. The survey findings indicate that only 37.2% (n=183) of children 6-59months had received vitamin A supplementation within the last 6 months prior to the survey, which is below the recommended coverage of 80%.

b) Measles Vaccination The source of information on measles immunization was either the child’s health card or mother’s recall. The proportion of children 9-59months vaccinated against measles as verified by their card was found to be 22.4 %( n=109) and according to the mothers recall, 16.7 % (n=81). Only 39.1% of children in the surveyed population were found to have been vaccinated against measles. These coverage rates are below the recommended EPI coverage cut off points of 80%.

c) Deworming

Deworming of children under the age of 5 years is recommended by WHO in order to improve their health and nutrition status. From the survey results, only 23.3% (n= 114) of the children were found to have been dewormed in the last 6 months. This information is as summarized in the graph below:

Figure 7: Immunization and supplementation coverage

0.0%

10.0%

20.0%

30.0%

40.0%

Measles Vacci. Vitamin A Dewormed

39.1% 37.2%

25.3%

Immunization & Supplementation

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Mortality The retrospective mortality rate was calculated based on data collected on the 109 day recall. Out of 430 households planned to be sampled for mortality data, data was collected in 406 households. There were 2972 individuals recorded as present during the recall period, 520 of whom were children U5 (17.5%). Among all deaths recorded, 64 occurred in persons aged 18 – 49 years, 11 in 50-64 years age group, 5 in 12-17 & 65-120 years age group, 4 in U5 and 1 in 5-11 years age group. The Crude Mortality Rate (CMR) was 2.78 deaths per 10,000 per day [2.22 – 3.47, 95% C.I.] while the U5 Mortality Rate (U5MR) was 0.71 deaths per 10,000 per day [0.27 – 1.85 95% C.I.], as summarized in table 8 below. The CMR mortality rates were above and classified as emergency as per the WHO thresholds1. This is as summarized in the table below: Table 11: Retrospective mortality results Parameters Results Number of current household residents 2971.5

Number of people who joined household 729

Number of births during recall 45 Number of deaths during recall 90

Number of current household residents <5years old

520

Recall period (days) 109

CMR(deaths/10,000/day) 2.78 [2.22-3.47, 95% CI] DEFF 1.09

U5MR(deaths in children <5/10,000/day 0.71 [0.27-1.85, 95% CI] DEFF 1.00 Of the deaths recorded during the recall period 90% were caused by injury/traumatic, 7.8% were caused by illness and 2.2% were unknown. A total of 66.7% of the deaths reported occurred in the current place and 32.2% in the place of last residence and 1.1% during migration. Southern Mayendit is in the conflict ravaged zone/ cattle raiding as was revealed through focus group discussions. Further analysis is done of the population demographics to explain the high crude mortality rates of 2.78 which is classified as an emergency. On disaggregation of the data by gender, the results show that the males are highly affected with mortality cases as compared with the females with CMR of 5.13 (4.03 – 6.52) and 0.75 (0.39 – 0.41) respectively. On further disaggregation of the data by age groups, the results show that the persons aged above 18 years are mostly affected by the mortality i.e. 18-49 years (5.32), 50-64 years (6.17) and 65-120 years (6.28). This is as depicted by the following population demographic pyramid.

1 WHO emergency threshold of <2deaths/10,000/day (U5MR) mortality rate and <1 death/10,000/day

Crude Mortality Rate(CMR)

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Figure 8: Population pyramid

FOOD SECURITY AND LIVELIHOODS (Qualitative). The Sphere definition of food security considers a population to be food secure when all people, at all times, have physical and economic access to sufficient, safe and nutritious food for a healthy and active life. Within this definition, the two elements of food security are:

•Availability (the quality and quantity of the food supply); and •Access (entitlement to food through purchases, exchange and claims).

Food insecurity, is at the heart of food crises and food-related emergencies. It is an underlying cause of malnutrition and mortality, and a significant factor in longer term livelihood security. Food insecurity may cause irreparable damage to livelihoods, thereby reducing self-sufficiency. It is therefore part of the process leading to malnutrition, morbidity and mortality. In addition, the state of being food insecure directly contributes to destitution and damaged livelihoods in the long term. In other words, if there is acute food insecurity, there is a nutritional risk. The food security information during the survey was collected through key informant interviews (KII) and focus group discussions (FGDs). A total of 5 FGDs (in each of the five payams) and 12 KIIs (community, SP, UNIDO, WFP) were conducted. A total of 12 respondents participated in the KIIs while 40 respondents were from the FGDs conducted in the five payams in Mayendit South. Below is a summary of both FGDs and KIIs conducted in Mayendit South during the survey period.

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Table 12: Summary of KIIs and FGDs conducted.

Key Informant Interviews Respondent Affiliation

1. Samaritan’s Purse 3 KIIs conducted

2. UNIDO 3 KIIs conducted 3. WFP 1 KII conducted

4. Chiefs/ elders 5 KII conducted each representing each of the 5 payams in Mayendit.

Focus Group Discussions (8 persons per FGD) 1. FGD one

Madol 1, Madol 2, Malkuer, Bhor (women with children aged <5 years)

2. FGD two

3. FGD three 4. FGD four

5. FGD five Pabuong (men)

The qualitative data was first transcribed and then analyzed using the emerging themes. From the results for food security and livelihoods:

i. Theme 1: Food Security a) Sub-theme 1: Household dynamics

Majority of the respondents (>80%) reported increased intra-household

sharing of the food rations provided due to the large household sizes, hence

vulnerable.

Most of the respondents (40%) reported that there was more female-headed

households due to the conflict and hence vulnerable to food insecurity.

b) Sub-theme 2: Agriculture

Most of the respondents (>70%) reported that they had not planted food

crops in the previous season due to conflict and hence vulnerable, and

expected to worsen in the coming dry season.

c) Sub-theme 3: Food rations

Most of the respondents (64%) reported that food ration provision had been

erratic in the last three months.

A majority of the respondents (78%) agreed that the distribution of the food

rations was a challenge due to centralized distribution points, hence limiting

the coverage.

d) Sub-theme 4: Food prices

Almost all respondents (96%) reported increased food prices (>60%

increase) as compared with the same period last year and the markets

provided lesser variety of food products.

e) Sub-theme 5: Coping strategies

A majority of the respondents reported that their food security status was on

the decline with the respondent reporting themselves resorting to the

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following coping strategies; consumption of water lilies (70%), borrowing of

food from neighbors (55%) and fishing (40%).

ii. Theme 2: Livelihoods The majority of the respondents (67%) reported that selling of fish and firewood. Others (20%) reported selling okra. Due to the conflict and frequent cattle raids, almost all the respondents (92%) reported loss of cattle which they relied on for milk consumption and sale.

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DISCUSSION

CHILDREN 0-5 MONTHS

a) Nutritional Status The results indicate that children aged under 6 months are affected by malnutrition as evidenced by the higher wasting (-0.45) and underweight (-0.14) levels in this age group. This could be attributed by the poor infant feeding and nutrition practices in the survey area as evidenced by the recent KAP survey in November 2015 by SP that showed that only 35% of the under-fives are exclusively breastfed. On further disaggregation of the data by gender, it was also observed that the boys were more wasted and underweight as compared to the girls. This could also be explained by the lower exclusive breastfeeding rates of the boys (30%) compared to the girls (44%) as shown by the same KAP survey. This clearly shows the need to focus and scale up on infant feeding and nutrition interventions in Mayendit South. A component of behavior change communication for improved IYCN should be focused in the interventions in order to address the poor infant feeding practices (e.g. exclusive breastfeeding) of the boys and the overall nutrition situation of children under the age of 6 months.

b) Morbidity Status

The results indicate that more children (43.5%) under 6 months were reported to be sick in the last 2 weeks. The main type of illness being fever (44.2%) and cough (23.3%). This shows that more children under the age of 6 months are affected by illnesses which is an aggravating and contributing factor to the overall poor nutrition status of the children. Of particular interest from the findings is the poor health seeking behavior of the caregivers of these children aged 0-5 months where 60.7% did not seek treatment for the children who were sick during the same period. This increases vulnerability of these children since proper healthcare isn’t sought when they are sick yet they are most vulnerable to most diseases and eventually mortality. Their situation is complicated even the more by the poor exclusive breastfeeding rates, since breast milk provides natural immunity to disease. It is therefore important of the IYCF programme currently implemented in Mayendit South to focus on this health aspect and maternal care of the children under 6 months.

CHILDREN 6-59 MONTHS The results indicate that children aged 6-59 months are also affected by malnutrition as evidenced by the global acute malnutrition prevalence of 16.1% [12.1-21.0, 95% C.I] which is classified as an emergency nutrition situation as per WHO standards. The prevalence of underweight 14.3% [11.2-18.2, 95% C.I] is also classified as medium depicting a poor nutrition situation in Mayendit South. The poor nutrition situation in Mayendit South could be explained by an interplay of several basic, immediate and underlying factors that influence nutrition outcome as per the UNICEF conceptual framework on the causes of malnutrition as depicted in the figure below.

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Figure 9: UNICEF conceptual framework on malnutrition.

a) Immediate factors As shown by the survey results, the morbidity of the children aged 6-59 months was high with 57.0% of the children being sick within the last 2 weeks and mainly suffering from the main childhood illnesses known to aggravate the nutrition situation of children aged under 5 years i.e. fever (44.1%), cough (26.5%), diarrhea (19.6%) etc. In addition, the health seeking behavior was average with 64.6% of the caregivers seeking for medical assistance while 35.4% of the sick children didn’t receive any medical assistance when sick, further predisposing them to malnutrition. This calls for increased focus and scale up on integrated management of childhood illnesses (IMCI) which can be addressed by the existing health programme being implemented by UNIDO. In addition, the nutrition interventions implemented in the area by the partners require an integrated approach in order to offer integrated health and nutrition services. Secondly, the qualitative results pointed to inadequate food consumption for the children aged 6-59 months. A majority of the respondents (>80%) reported intra-household food sharing which included the 15 day ration provided by WFP and even the nutrit ion products given to malnourished children in the same households’ e.g. Plumpy nut. As highlighted from the household demographics results, the average household size was 7.3 and the proportion of children under the age of 5 years was 19.9%. This meant that there was a lot of household members that were in a household and this made these households to be vulnerable to malnutrition. This was also highlighted by the current coping mechanisms adopted by the households which included reducing the number of meals consumed per day. This was also worsened by the influx of the internally displaced people in Mayendit South.

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b) Underlying factors. From the survey results of the qualitative results, household food insecurity was highlighted as a point of concern in Mayendit South. Most of the respondents (>70%) reported that they had not planted food crops in the previous season due to insecurity. For those who had some sorghum crop in the fields located near the swamps most of them reported that both the food crop stored and the crop in the field would soon run out in the next coming weeks. They also reported that the coming season (January- May 2016) would be worse since it’s the dry season and most of the households would be food insecure. This is also as evidenced by a recent report in 2015 by Agriculture and Food Information System (AFIS), South Sudan that Mayendit had already shown early signs of drought which would impact cultivation and harvests. In addition, from the qualitative results, the respondents that most of the households had begun to adopt different coping mechanisms to mitigate the increasing household food insecurity. This included consumption of water lilies, borrowing from neighbors and reducing the number of meals. Secondly, the survey results also showed increased food prices and decreased variety from the local markets as compared to the same period last year. This has impacted the purchasing power of the household which on turn affects household access of the food. As reported by the recent Food Security Assessment done by SP in October 2015, in Mayendit, 47% relied on purchased food while 24% of respondents relied on their own production. This highlights financial barriers to access the limited food sold in the local markets. The situation was been excercebated by the conflict in Unity state in May 2015. In addition, most respondents (64%) reported that the food distribution had been erratic in the past few months. Also, some of the respondents reported that female headed households were more vulnerable to food insecurity due to increased work load for the caregivers and given the high numbers of persons per household. Most of the respondents (78%) interviewed in the qualitative tools reported that most of the food and nutrition interventions in Mayendit South were limited in their coverage due to the centralized service points with a majority of the programs located in Madol 1 and Bhor payams. This shows that household food insecurity is one of the contributing factors to the high malnutrition. With regard to poor maternal care practices, this is evidenced by the poor health seeking behavior of the caregivers where only 64.6% sought medical assistance for their children who had been sick in the last 2 weeks. Lastly, healthcare access was highlighted as a barrier for the villages that were remote and further from the centralized services. This was evidenced by only 1 primary healthcare unit (PHCU) being in operation in Mayendit South.

c) Basic causes The main basic causes that were highlighted from the qualitative assessment was instability of the area due to insecurity which affected accessibility of the area. All the respondents interviewed (N=52) agreed that insecurity (war and frequent cattle raid attacks) affected the nutrition situation by continuous disruption of relief and development operations in the area. This in turn had an impact with the accessibility of the area due to lack of proper infrastructure in the flood-prone area.

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RECOMMENDATIONS Table 13: Recommendations

Short Term Recommendations

Theme Recommendations By Who

Nutrition

Situation

Scale up the supplementary feeding program i.e. Targeted Supplementary Feeding

Program and the Blanket Supplementary Feeding Program and increase coverage by

having multiple distribution points in Mayendit South (esp. Malkuer, Pabuong payams).

Scale up of the IYCN programme to improve the infant and child feeding practices and

nutrition (e.g. EBF and dietary diversity) and include a behavior change &

communication (BCC) component through health education to address the malnutrition

disparities for children aged 0-5 months and integrated management of childhood

illnesses (IMCI) due to the high morbidity rates.

SP and

UNIDO

The out-patient therapeutic program (OTP) should be scaled up in the area and increase

its coverage by setting up the program in other payams/ PHCU/ PHCC due to the

spatial barriers in accessing the existing OTP which is currently centralized.

Health

status

Strengthening primary health care by increasing the coverage of the health program by

decentralizing the services to other PHCC/PHCU (e.g. Malkuer.)

Increased focus and scale up on integrated management of childhood illnesses (IMCI)

which can be addressed by the existing health programme being implemented in the

area.

Scale up of integrated health services which include outreach services and mobile clinics

emphasizing immunization campaigns, Vitamin A supplementation and deworming for

the U5 in Mayendit South in order to address the low coverage of the basic health and

nutrition interventions.

Food

Security

Retargeting of the households for food distribution by WFP in coming months in order

to ensure that all households are food secure. In addition, the food ration provision

should consider the number of persons in a household and female-headed households

which are more vulnerable to food insecurity especially during the upcoming hungry

season and the increased food prices.

Decentralize food distribution points, especially for payams located further from the

current distribution points e.g. Malkuer and Pabuong.

Strengthen the livelihoods of the communities by provision of fishing nets, seeds for

planting, livestock and consider cash for work programs (e.g. construction of dykes due

to the flood-prone area.)

Continuous screening of children U5 and PLW is required using MUAC measurements

in order to monitor the nutrition and food security situation, especially in the coming

months due to the anticipated dry period.

WFP,

FAO and

SP

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Long Term Recommendations

Theme Recommendations By Who

Nutrition Implement integrated nutrition programmes with a life-cycle approach by targeting all

the factors that influence nutrition at the community level. Social and Behaviour Change

and Communication (SBCC) strategies can be considered in the nutrition and health

programmes implemented in the area.

Integration of WASH activities in nutrition programmes can be considered due to the

poor water, hygiene and sanitation in the area and the strong linkage to child morbidity

and malnutrition

SP,

UNIDO

FSL A livelihoods approach which strengthens the local community’s resilience to recurrent

shocks should be considered. This could involve: 1) provision of quality seeds and

training of the communities of better farming techniques, better farm land utilization,

irrigation techniques, food preservation & post-harvest technologies etc. 2) provision of

fishing nets and support of the communities with better fishing equipment, tra ining on

small-scale fish ponds and processing for better markets. 3) Strengthening of the local

markets by providing better infrastructure. 4) Re-stocking and supporting the local

communities with livestock e.g. goats, chicken, cattle e.t.c.

WFP,

FAO, SP

Insecurity There is need to ensure peace and stability in the county due to the conflict and

increasing cases of cattle raiding which has led to increased mortality cases and limited

the program activities of the partners on the ground in Mayendit County.

The partners can also initiate peace initiatives and integrate conflict resolution

committees within their programmes.

Governm

ent of

South

Sudan

and

partners

Seasonal

flooding

There is need to improve the infrastructural developments in the county. These includes

constructing drainages and probably dykes to help overcome the challenge of

continuous flooding in the county. A Cash-for-work program could be considered by

both UN agencies and the partners working in the area.

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CONCLUSION

The findings of the assessment depict a poor nutrition situation, above the WHO emergency threshold in Mayendit South which is being caused by an interplay of factors ranging from household food insecurity, disease, poor maternal care practices and limited programme coverage. This calls for concerted efforts with an integrated approach on the interventions being implemented in the area with a special focus on the Supplementary Feeding Programme (SFP) due to the high cases of moderately malnourished children and Outpatient Therapeutic Programme (OTP) due to the high numbers of severely malnourished children. The IYCF programme currently being implemented requires to integrate a BCC and an IMCI component in order to improve the nutrition situation. In addition, the health programme implemented should be scaled up and increase its focus on integrated management of childhood illnesses (IMCI). In addition, the food security and livelihoods (FSL) programme implemented in the area require immediate scale-up as the population start the dry period and as drought makes most of the households vulnerable to food insecurity and eventually malnutrition. The FSL programme needs to focus on empowering the livelihoods of the population e.g. giving fishing nets, in order for them to be able to mitigate household food insecurity. Lastly, there is an urgent need to increase the coverage and scale up of the programmes currently implemented in Mayendit South in order to have a wider reach of the vulnerable populations.

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ANNEXES.

Annex 1: Selected clusters

Village Name Population Cluster Number Poolnor 400 1

Banejiek 400 2

Rotngech 210 3

Hele 500 4

Nyaljor 300 5

Mayiek/ Mayar 400 6

Dhorchak 500 7

Letwech 600 8

Kerthiang 310 9

Panthiang 300 10

Ken 400 11

Pakuor 180 12

Lungyier 500 13

Dhorkan 300 14

Maleakni 310 15

Wangkan 420 16

Nyakey 200 17

Kuerhok/ Jikuat 600 18

Nyaath 621 19

Nyoke 200 20

Papline 500 21

Kech Biet 200 22

Yat 580 23

Koh 320 24

Kech Kan 250 25

Nyamuon 180 26

Loang 40 27

Dhorbuoni 592 28

Dhorgapini 280 29

Bengpulual 310 30 (village moved due to insecurity)

Nyaying 280 31

Wangoany 104 32

Kuloy 230 33

Lingier 500 34

Mager 470 35

Guol 230 36

Manyal 310 RC

Gak Nyak 450 RC

Tholegaat 420 RC

Rier 500 RC

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Annex 2: Plausibility Results

Plausibility check for: SS_231215_SP_MAYENDIT_COUNTY.as

Standard/Reference used for z-score calculation: WHO standards 2006 (If it is not mentioned, flagged data is included in the evaluation. Some parts of this

plausibility report are more for advanced users and can be skipped for a standard evaluation)

Overall data quality

Criteria Flags* Unit Excel. Good Accept Problematic Score

Flagged data Incl % 0-2.5 >2.5-5.0 >5.0-7.5 >7.5

(% of out of range subjects) 0 5 10 20 0 (1.1 %)

Overall Sex ratio Incl p >0.1 >0.05 >0.001 <=0.001

(Significant chi square) 0 2 4 10 0 (p=0.305)

Age ratio(6-29 vs 30-59) Incl p >0.1 >0.05 >0.001 <=0.001

(Significant chi square) 0 2 4 10 0 (p=0.367)

Dig pref score - weight Incl # 0-7 8-12 13-20 > 20

0 2 4 10 0 (5)

Dig pref score - height Incl # 0-7 8-12 13-20 > 20

0 2 4 10 0 (7)

Dig pref score - MUAC Incl # 0-7 8-12 13-20 > 20

0 2 4 10 2 (10)

Standard Dev WHZ Excl SD <1.1 <1.15 <1.20 >=1.20

. and and and or

. Excl SD >0.9 >0.85 >0.80 <=0.80

0 5 10 20 5 (1.13)

Skewness WHZ Excl # <±0.2 <±0.4 <±0.6 >=±0.6

0 1 3 5 0 (0.14)

Kurtosis WHZ Excl # <±0.2 <±0.4 <±0.6 >=±0.6

0 1 3 5 1 (-0.35)

Poisson dist WHZ-2 Excl p >0.05 >0.01 >0.001 <=0.001

0 1 3 5 0 (p=0.080)

OVERALL SCORE WHZ = 0-9 10-14 15-24 >25 8 %

The overall score of this survey is 8 %, this is excellent.

There were no duplicate entries detected.

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Annex 3: Map of Mayendit South in Mayendit County

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Annex 4: Mortality Questionnaire DEMOGRAPHY & MORTALITY QUESTIONNAIRE

DATE OF INTERVIEW: [ D ][ D ]/[ M ][ M ]/ [ Y ][ Y ]

Was anyone in the household pregnant at the s tart of the recall period? No [ ] Yes [ ] If yes , how many? _______

2 HH definition: Group of people living under same roof & sharing food from the same pot for a period of at least 6 months. In home

with multiple wives, those living and eating in different houses are considered as separate HHs. Wives living in different ho uses and eating from same pot are considered as one HH.

COUNTY: PAYAM: NAME OF INTERVIEWER:

BOMA: VILLAGE:

CLUSTER NO. [ ][ ] TEAM NO. [ ][ ] HOUSEHOLD2 NO. [ ][ ]

01 02 03 04 05 06 07 08 09 10

No.

Name

Sex (M/F)

Age (years)

Joined on

or after:

Left on

or after:

Born on or

after:

Died on or

after:

Cause of

death 1= illness 2=injury

66=unknown

Location of

death 1=current location

2=during migration

3=in place of last residence

4=other

__________________________ (Start date of the recall period - ex. Jan. 1, 1900)

WRITE ‘Y’ for YES. Leave BLANK if NO.

a) Lis t a l l the people that s lept in this household last night. 1

2

3

4 5

6

7 8

9 10

11

12 13

14

15 b) List all the people that slept in this household on the first night of the recall period (FILL IN DATE/EVENT) but did NOT sleep in the household last night.

1 Y

2 Y 3 Y

4 Y 5 Y

6 Y 7 Y

c) List all the people that slept in this household on the first night of the recall period but have since died

1 Y

2 Y

3 Y 4 Y

5 Y

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Annex 5: Food Security and Livelihoods Guide FGD/ KII GUIDE

Food Availability

What are the main food crops on the ground this season?

What condition do you expect the next harvest to be (good, poor)? Explain and give reasons why. For example, (Poor because of pest infestation, lack of rain, late rain, not sufficient seeds planted, etc.). OR Good

because the rains were good this season, fertiliser was used, no pests experienced....etc.)

How much does it cost to buy 1kg of the staple from the market? How does this

compare to the same month last year (more, less, how much more?)

Food Access

Explain the main income sources/livelihoods of this community this season.

How many of you have more than one income source (e.g., work in the fields during harvest time, have daily labour work in the town in other seasons, other HH member contributes earnings too).

Tell me about stored food in your home: what staple do you store, how long does it last?

What do you do when you finish the stored food?

How many of you keep livestock? What do you keep? How do you use these animals (sell the milk, breed and sell after xx months, fatten and sell after x months).

Vulnerability and Coping Mechanisms during Food Insecurity

Have you faced food insecurity in the last 3 months?

What months are you most likely to face food insecurity in this area?

What do you do when you don’t have enough food for three meals a day (base this on experience if possible using the most recent examples).

In your opinion, which households face food shortage in this community?

WHY?

Additional Questions

[Partners] Are you currently implementing any FSL programs?

What are the main challenges with regard to food security in the area?

In your opinion, what is the current food security situation of the local population?

In your opinion, what do you recommend to be done in order to improve the food security situation in Mayendit South?

Annex 6: Anthropometry questionnaire ANTHROPOMETRIC & HEALTH QUESTIONNAIRE

(To be conducted in EVERY HH with children 6-59 months - from the random starting point onwards)

Date (D/M/Y): …..../…..../….... Cluster No: ……… Team No: …..… State: ……………….. County: ……..…….. Payam: ………………. Boma: ………..…….. Village:………....……

1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 1.1 1.11 1.12 1.13 1.14

Child no.

HH ref. no.*

Sex ---------

m = male f = female

Age in months (use

local calendar of events)

Weight in Kg

(ex 12.4)

Height in cm

(ex 78.1)

Oedema -----------

n = No y = Yes

MUAC in cm

(ex 11.3)

Vit. A in last 6 mths

-------------- 0 = No 1 = Yes

Dew orming in last 6

months ……………… 0 = No

1 = Yes

Measles Vaccine

--------------------- 0 = No

1 = Yes w ith EPI card 2 = Yes recall 88 = Child

<9m

Illness in past 2 w eeks?

-------------------- 0 = No 1 = Yes

If no, END SURVEY.

Type of Illness ---------------------

1 = Fever* 2 = Cough** 3 =

Diarrhoea*** 4 = Skin Infections 5 = Eye

infections 66 = Other (specify)

Treatment sought -----------------------

0 = None sought 1 = Hospital 2 = PHCC/PHCU

3 = Mobile /outreach clinic 4 = Village health care w orker

5 = Private physician 6 = Relative/ friend 7 = Shop 8 = Traditional

practitioner 9 = Pharmacy 66 = Other (specify)

1

2

3

4

5

6

7

8

9

10

11

12

Household (HH) definition: Group of people living under the same roof & sharing food from the same pot for a period of at least 6 months. In homes w ith multiple w ives, those living & eating in different houses are considered as separate HHs. Wives living in different houses and eating from the same pot are considered as one HH.