emergency nutrition assessment final report · annex 1: kutupalong results of 2x2 tests of...

Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 1

EMERGENCY NUTRITION ASSESSMENT FINAL REPORT

COX’S BAZAR, BANGLADESH

OCTOBER 22 - NOVEMBER 27 2017


ACKNOWLEDGEMENTS

The Emergency Nutrition Assessment in Cox’s Bazar, Bangladesh was conducted on behalf of the Nutrition

Sector by Action Against Hunger In collaboration with the Government of Bangladesh, the United Nations

High Commissioner for Refugees, the World Food Programme, the United Nations Childrens’ Fund, Save

the Children, and the Centers for Disease Control and Prevention. The assessment was funded by the

United Nations High Commissioner for Refugees, the United Nations Childrens’ Fund, and the European

Commission Humanitarian Aid and Civil Protection, however the opinions expressed in this report may not

reflect the official opinion of these organizations.

Action Against Hunger wishes to thank the Government of Bangladesh and the local governments of Cox’s

Bazar, Ukhia, and Teknaf for their support in making this assessment a reality.

Action Against Hunger also thanks the persons surveyed for their availability and flexibility, without which

the results of this assessment could not have been possible. Family members and their measured children

are warmly thanked for their cooperation and for welcoming survey teams into their homes for data

collection.

Action Against Hunger also thanks the community volunteers and community leaders for their collaboration

in identifying survey areas and households during data collection.

Special thanks and gratitude to the survey teams who made the assessment possible through their

professionalism and dedication in the field.

Coordination team:

Leonie Toroitich-Van Mil, Nutrition Head of Department, Action Against Hunger, Bangladesh

Mohammad Lalon Miah, Survey Manager, Action Against Hunger, Bangladesh

Alexandra Humphreys, Flying Survey Manager, Action Against Hunger

Technical support:

The Emergency Nutrition Assessment Technical Working Group

Eva Leidman, Epidemiologist, CDC Emergency Response and Recovery Branch

Oleg Bilukha, Associate Director of Science, CDC Emergency Response and Recovery Branch

Blanche Greene Cramer, EIS Officer, CDC Emergency Response and Recovery Branch

Aimee Summers, Epidemiologist, CDC Emergency Response and Recovery Branch

Emilie Robert, Health and Nutrition Technical Advisor, Action Against Hunger, France

Claudia Grigore, Mobile Data Collection Officer at CartONG


TABLE OF CONTENTS

ACKNOWLEDGEMENTS ................................................................................................................................. 2

TABLE OF CONTENTS ..................................................................................................................................... 3

LIST OF TABLES .............................................................................................................................................. 7

LIST OF FIGURES .......................................................................................................................................... 10

ACRONYMS ................................................................................................................................................. 11

EXECUTIVE SUMMARY ................................................................................................................................ 13

OBJECTIVES ............................................................................................................................................. 13

METHODOLOGY ...................................................................................................................................... 13

RESULTS .................................................................................................................................................. 14

1. INTRODUCTION ................................................................................................................................... 15

1.1 CONTEXT ........................................................................................................................................... 15

1.1.1 Geography and Demography ..................................................................................................... 15

1.1.2 Displacement and the Camps .................................................................................................... 16

1.1.3 Food Security and Livelihoods ................................................................................................... 18

1.1.5 Water, Sanitation, and Hygiene ................................................................................................. 19

1.1.6 Health ......................................................................................................................................... 20

1.1.7 Nutrition ..................................................................................................................................... 22

1.1.8 Infant and Young Child Feeding Practices .................................................................................. 22

1.1.9 Protection................................................................................................................................... 23

1.1.10 Humanitarian Actors ................................................................................................................ 23

1.2 Survey Justification ........................................................................................................................... 26

1.3 Survey Objectives .............................................................................................................................. 27

1. METHODOLOGY .................................................................................................................................. 29

2.1 Type of Survey and Target Population .............................................................................................. 29

2.2 Sample Size Calculation .................................................................................................................... 29

2.3 Sampling ............................................................................................................................................ 32

2.3.1 Cluster Selection ........................................................................................................................ 32

2.3.2 Household Selection .................................................................................................................. 33

2.3.3 Selection of Individuals to Survey .............................................................................................. 34

2.4 Collected Variables............................................................................................................................ 35

2.4.1 Demography & Mortality .................................................................................................... 35


2.4.2 Anthropometry .......................................................................................................................... 35

2.4.3 Morbidity ................................................................................................................................... 35

2.4.4 Infant and Young Child Feeding ................................................................................................. 36

2.4.5 Receipt of Services ..................................................................................................................... 36

2.5 Indicators and Cut-offs ...................................................................................................................... 37

2.5.1 Mortality Indices ........................................................................................................................ 37

2.5.2 Anthropometric Indices ............................................................................................................. 38

2.5.3 Anaemia ..................................................................................................................................... 40

2.6 Questionnaire, Training, and Supervision ......................................................................................... 41

2.6.1 Questionnaire ............................................................................................................................ 41

2.6.2 Training ...................................................................................................................................... 41

2.6.3 Supervision ................................................................................................................................. 42

2.7 Data Management ............................................................................................................................ 42

2.8 Ethical Considerations ....................................................................................................................... 43

2.9 A Note on Interpretation .................................................................................................................. 43

3. RESULTS ................................................................................................................................................... 46

3.1 Kutupalong Refugee Camp................................................................................................................ 46

3.1.1 Data Quality ............................................................................................................................... 46

3.1.2 Demography and Mortality ........................................................................................................ 48

3.1.3 Prevalence of Acute Malnutrition by WHZ ................................................................................ 50

3.1.4 Prevalence of Acute Malnutrition by MUAC .............................................................................. 52

3.1.5 Prevalence of Acute Malnutrition WHZ vs. MUAC .................................................................... 54

3.1.6 Low MUAC in Women ................................................................................................................ 55

3.1.7 Low MUAC in Infants .................................................................................................................. 55

3.1.8 Prevalence of Chronic Malnutrition ........................................................................................... 56

3.1.9 Prevalence of Underweight ....................................................................................................... 56

3.1.10 Prevalence of Anaemia ............................................................................................................ 57

3.1.11 Prevalence of Morbidity........................................................................................................... 58

3.1.12 IYCF Indicators .......................................................................................................................... 59

3.1.13 Receipt of Services ................................................................................................................... 62

3.1.14 Care-seeking Behaviour ........................................................................................................... 64

3.2 Makeshift Settlements ...................................................................................................................... 68

3.2.1 Data Quality ............................................................................................................................... 68






3.2.6 Low MUAC in Women ................................................................................................................ 77



3.2.9 Prevalence of Underweight ....................................................................................................... 78

3.2.10 Prevalence of Anaemia ............................................................................................................ 79

3.2.11 Prevalence of Morbidity........................................................................................................... 80

3.2.12 IYCF Indicators .......................................................................................................................... 81

3.2.13 Receipt of Services ................................................................................................................... 84

3.2.14 Care-seeking Behaviour ........................................................................................................... 86

3.3 Nayapara Refugee Camp ................................................................................................................... 89

3.3.1 Data Quality ............................................................................................................................... 89





3.3.6 Low MUAC in Women ................................................................................................................ 98



3.3.9 Prevalence of Underweight ..................................................................................................... 100

3.3.10 Prevalence of Anaemia .......................................................................................................... 100

3.3.11 Prevalence of Morbidity......................................................................................................... 101

3.3.12 IYCF Indicators ........................................................................................................................ 103

3.3.13 Receipt of Services ................................................................................................................. 106

3.3.14 Care-seeking Behaviour ......................................................................................................... 108

4. DISCUSSION ........................................................................................................................................... 110

4.1. The Malnutrition Landscape .......................................................................................................... 110

4.2. Underlying Causes of Malnutrition ................................................................................................ 113

4.3 Receipt of Services .......................................................................................................................... 115

4.4 Limitations of the Assessment ........................................................................................................ 116


5. Conclusion and Recommendations....................................................................................................... 117

Annex 1: Kutupalong Results of 2x2 Tests of Statistical Significance per Epi Info Software .................... 119

Annex 2: Makeshift Settlements Results of 2x2 Tests of Statistical Significance per Epi Info Software .. 120

Annex 3: Nayapara Results of 2x2 Tests of Statistical Significance per Epi Info Software ....................... 121

Annex 4: Survey Team Training Schedule ................................................................................................. 122

Annex 5: Makeshift Settlements Cluster Determination .......................................................................... 125

Annex 6: Survey Questionnaire ................................................................................................................ 126

Annex 7: Cluster Control Form .................................................................................................................. 136

Annex 8: Anthropometric Measurement Form Children .......................................................................... 137

Annex 9: Anthropometric Measurement Form Women .......................................................................... 138

Annex 10: Event Calendar ......................................................................................................................... 140

Annex 11: Referral Form ........................................................................................................................... 143

Annex 12: Kutupalong Refugee Camp Plausibility Check ......................................................................... 144

Annex 13: Makeshift Settlements Plausibility Check ................................................................................ 154

Annex 14: Nayapara Refugee Camp Plausibility Check ............................................................................ 167


LIST OF TABLES

Table 1: Summary of Key Indicators, Cox’s Bazar, November 2017 ........................................................... 14

Table 2: Health Facilities Existing Prior to August 25th, 2017 in Ukhia and Teknaf, Cox’s Bazar, Bangladesh

Ministry of Health and Family Welfare 2017* ............................................................................................ 21

Table 3: Stabilization Centres and Outpatient Therapeutic Programmes Operating in Kutupalong Refugee

Camp During Survey Data Collection .......................................................................................................... 24

Table 4: Stabilization Centres and Outpatient Therapeutic Programmes Operating in the Makeshift

Settlements During Survey Data Collection ................................................................................................ 24

Table 5: Stabilization Centres and Outpatient Therapeutic Programmes Operating in Nayapara Refugee

Camp During Survey Data Collection .......................................................................................................... 25

Table 6: Overview of Reported Representative Estimates of Global Acute Malnutrition for Rakhine State

and Cox’s Bazar since 2015 ......................................................................................................................... 27

Table 7: Sample Size Calculation Parameters Anthropometry ................................................................... 30

Table 8: Cut-offs for the Indices for Weight-for-Height z-score (WHZ), Height-for-Age z-score (HAZ), and

Weight-for-Age z-score (WAZ) according to WHO reference 2006 ............................................................ 38

Table 9: WHO Classification for Severity of Malnutrition by Prevalence among Children Under Five ...... 39

Table 10: WHO Cut-off Values for Anthropometric Measurements Using MUAC to Assess Moderate and

Severe Acute Malnutrition .......................................................................................................................... 39

Table 11: IPC classification Acute Malnutrition by MUAC .......................................................................... 40

Table 12: WHO Cut-off Values for Prevalence of Anaemia based on Haemoglobin Measurement .......... 40

Table 13: WHO Classification of Public Health Significance of Anaemia and Iron Deficiency in Populations

based on Haemoglobin Measurement ....................................................................................................... 40

Table 14: KTP Households and Children 6-59 months Planned vs. Surveyed ............................................. 46

Table 15: KTP Median z-score ± Standard Deviation for WHZ, HAZ, and WAZ .......................................... 47

Table 16: KTP Overall Data Quality per ENA Plausibility Check .................................................................. 47

Table 17: Demographics of Kutupalong Refugee Camp ............................................................................. 48

Table 18: KTP Distribution of Age and Sex Children 6-59 months .............................................................. 49

Table 19: KTP Prevalence of Acute Malnutrition per WHZ and/or Oedema, WHO Reference 2006 ......... 51

Table 20: KTP Prevalence of Acute Malnutrition by Sex per WHZ and/or Oedema, WHO Reference 2006

.................................................................................................................................................................... 51

Table 21: KTP Prevalence of Acute Malnutrition by Age per WHZ and/or Oedema, WHO Reference 2006

.................................................................................................................................................................... 52

Table 22: KTP Prevalence of Acute Malnutrition by MUAC ........................................................................ 53

Table 23: KTP Low MUAC in Women 15-49 Years ...................................................................................... 55

Table 24: KTP Low MUAC in Infants 0-5 Months ........................................................................................ 56


Table 25: KTP Prevalence of Chronic Malnutrition by HAZ, WHO Reference 2006 .................................... 56

Table 26: KTP Prevalence of Underweight by WAZ, WHO Reference 2006 ............................................... 57

Table 27: KTP Prevalence of Anaemia in Children 6-59 months per WHO ................................................. 57

Table 28: KTP Two-week Prevalence of Diarrhoea, Cough, and Fever in Children 6-9 Months ................. 59

Table 29: KTP Infant and Young Child Feeding Indicators .......................................................................... 60

Table 30: KTP Receipt of Immunizations and Food/Nutrition Assistance .................................................. 63

Table 31: KTP Two-week Recall of Care-seeking Behaviour for Children 6-59 Months with Diarrhoea .... 65

Table 32: KTP Two-week Recall of Care-seeking Behaviour for Children 6-59 Months with Cough .......... 65

Table 33: KTP Two-week Recall of Care-seeking Behaviour for Children 6-59 Months with Fever ........... 66

Table 34: MS Households and Children 6-59 months Planned vs. Surveyed ............................................. 68

Table 35: MS Median z-score ± Standard Deviation for WHZ, HAZ, and WAZ ........................................... 69

Table 36: MS Overall Data Quality per ENA Plausibility Check ................................................................... 69

Table 37: Demographics of the Makeshift Settlements ............................................................................. 70

Table 38: MS Distribution of Age and Sex, Children 6-59 months .............................................................. 71

Table 39: MS Prevalence of Acute Malnutrition per WHZ and/or Oedema, WHO Reference 2006 .......... 73

Table 40: MS Prevalence of Acute Malnutrition by Sex per WHZ and/ or Edema, WHO Reference 2006. 73

Table 41: MS Prevalence of Acute Malnutrition by Age per WHZ and/ or Edema, WHO Reference 2006 74

Table 42: MS Prevalence of Acute Malnutrition by MUAC ......................................................................... 75

Table 43: MS Low MUAC in Women 15-49 Years ....................................................................................... 77

Table 44: MS Low MUAC in Infants 0-5 Months ......................................................................................... 78

Table 45: MS Prevalence of Chronic Malnutrition by HAZ, WHO Reference 2006..................................... 78

Table 46: MS Prevalence of Underweight by WAZ, WHO Reference 2006 ................................................ 79

Table 47: MS Prevalence of Anaemia in Children 6-59 months per WHO.................................................. 79

Table 48: MS Two-week Prevalence of Diarrhoea, Cough, and Fever in Children 6-59 Months ................ 81

Table 49: MS Infant and Young Child Feeding Indicators ........................................................................... 82

Table 50: MS Receipt of Immunizations and Food/Nutrition Assistance ................................................... 85

Table 51: MS Two-week Recall of Care-seeking Behaviour for Children 6-59 Months with Diarrhoea ..... 86

Table 52: MS Two-week Recall of Care-seeking Behaviour for Children 6-59 Months with Cough ........... 87

Table 53: MS Two-week Recall of Care-seeking Behaviour for Children 6-59 Months with Fever ............ 87

Table 54: NYP Households and Children 6-59 months Planned vs. Surveyed ............................................ 89

Table 55: NYP Median z-score ± Standard Deviation for WHZ, HAZ, and WAZ .......................................... 90

Table 56: NYP Overall Data Quality per ENA Plausibility Check .................................................................. 90

Table 57: Demographics of Nayapara Refugee Camp ................................................................................ 91


Table 58: NYP Distribution of Age and Sex, Children 6-59 months ............................................................ 92

Table 59: NYP Prevalence of Acute Malnutrition in Nayapara Refugee Camp per WHZ and/or Oedema,

WHO Reference 2006 ................................................................................................................................. 94

Table 60: NYP Prevalence of Acute Malnutrition by Sex per WHZ and/or Oedema, WHO Reference 2006

.................................................................................................................................................................... 95

Table 61: NYP Prevalence of Acute Malnutrition by Age per WHZ and/or Oedema, WHO Reference 2006

.................................................................................................................................................................... 95

Table 62: NYP Prevalence of Acute Malnutrition by MUAC ....................................................................... 96

Table 63: NYP Low MUAC in Women 15-49 Years ...................................................................................... 99

Table 64: NYP Low MUAC in Infants 0-5 Months ........................................................................................ 99

Table 65: NYP Prevalence of Chronic Malnutrition by HAZ, WHO Reference 2006 ................................. 100

Table 66: NYP Prevalence of Underweight by WAZ, WHO Reference 2006 ............................................. 100

Table 67: NYP Prevalence of Anaemia in Children 6-59 months per WHO .............................................. 101

Table 68: NYP Two-week Prevalence of Diarrhoea, Cough, and Fever in Children 6-59 Months ............ 102

Table 69: NYP Infant and Young Child Feeding Indicators ........................................................................ 104

Table 70: NYP Receipt of Immunizations and Food/Nutrition Assistance ................................................ 107

Table 71: NYP Two-week Recall of Care-seeking Behaviour for Children 6-59 Months with Diarrhoea .. 108

Table 72: NYP Two-week Recall of Care-seeking Behaviour for Children 6-59 Months with Cough ........ 109

Table 73: NYP Two-week Recall of Care-seeking Behaviour for Children 6-59 Months with Fever ......... 109

Table 74: Comparison of Malnutrition Indicators and Cut-offs Across all Three Surveys ........................ 110

Table 75: Comparison of Key Indicators and Across all Three Surveys .................................................... 115

Table 76: Comparison of Key Indicators and Across all Three Surveys .................................................... 116


LIST OF FIGURES

Figure 1: Map of Sixty-four Districts in Bangladesh with Cox’s Bazar in Red, Wikipedia Commons, 2009 15

Figure 2: Refugee Sites by Population and Location Type, ISCG, October 22nd, 2017 ................................ 17

Figure 3: KTP Age Distribution of Children 6-59 months ............................................................................ 49

Figure 4: KTP Distribution of the WHZ of the Sample Compared to the WHO 2006 Reference ................ 50

Figure 5: KTP Prevalence of Acute Malnutrition by Age per MUAC ........................................................... 53

Figure 6: KTP Prevalence of Acute Malnutrition WHZ vs. MUAC ............................................................... 54

Figure 7: KTP 24-Hour Recall of Consumption of Liquids in Children 6-23 Months ................................... 61

Figure 8: KTP 24-Hour Recall of Food Group Consumption in Children 6-23 Months ................................ 62

Figure 9: MS Age Distribution of Children 6-59 months ............................................................................. 71

Figure 10: MS Distribution of the WHZ of the Sample Compared to the WHO 2006 Reference ............... 72

Figure 11: MS Prevalence of Acute Malnutrition by Age per MUAC .......................................................... 75

Figure 12: MS Prevalence of Acute Malnutrition WHZ vs. MUAC .............................................................. 76

Figure 13: MS 24-Hour Recall of Consumption of Liquids in Children 6-23 months .................................. 83

Figure 14: MS 24-Hour Recall of Food Group Consumption in Children 6-23 Months .............................. 84

Figure 15: NYP Age Distribution of Children 6-59 months.......................................................................... 92

Figure 16: NYP Distribution of the WHZ of the Sample Compared to the WHO 2006 Reference .............. 93

Figure 17: NYP Prevalence of Acute Malnutrition by Age per MUAC ......................................................... 97

Figure 18: NYP Prevalence of Acute Malnutrition WHZ vs. MUAC ............................................................. 98

Figure 19: NYP 24-Hour Recall of Consumption of Liquids in Children 6-23 Months ............................... 105

Figure 20: NYP 24-Hour Recall of Food Group Consumption in Children 6-23 Months ........................... 106

Figure 21: The Population Influx of Rohingya Refugees during the Emergency Assessment ................... 112


ACRONYMS

ACF Action Against Hunger - Action Contre la Faim

ARI Acute Respiratory Infection

BF Breastfeeding

BSFP Blanket Supplementary Feeding Programme

CDC Centers for Disease Control and Prevention

CDR Crude Death Rate

CI Confidence Interval

CMAM Community Management of Acute Malnutrition

CMAM-I Community Managemnt of Acute Malnutrition- Infants

DEFF Design Effect

DHS Demographic and Health Survey

FAO Food and Agriculture Organization

FSL Food Security and Livelihoods

GAM Global Acute Malnutrition

GBV Gender Based Violence

GFD General Food Distribution

HAZ Height-for-Age z-score

HH Household

IFRC International Federation of Red Cross and Red Crescent

IGA Income Generating Activity

IOM The International Organization for Migration

IYCF Infant Young Child Feeding

IPC Integrated Food Security Phase Classification

IRC International Rescue Committee

ISCG Inter Sector Coordination Group

IYCF Infant and Young Child Feeding

KTP Kutupalong Refugee Camp

MAD Minimum Acceptable Diet

MAM Moderate Acute Malnutrition

MHCP Mental Health and Care Practices

MICS Multiple Indicator Cluster Survey

MMD Minimum Dietary Diversity

MMF Minimum Meal Frequency

MMR Maternal Mortality Ratio

MNP Micronutrient Powder

MoHFW Ministry of Health and Family Welfare

MR Measles-Rubella

MS Makeshift Settlements

MSF Medecins sans Frontieres

MUAC Mid-Upper Arm Circumference

NGO Non-Governmental Organization

NRR Non-Response Rate

NYP Nayapara Refugee Camp

OCHA United Nations Office for the Coordination of Humanitarian Affairs

OCV Oral Cholera Vaccine

OPV Oral Polio Vaccine


OR Odds Ratio

OTP Outpatient Therapeutic Programme

PLW Pregnant and Lactating Women

PPS Population Proportional to Size

PSU Primary Sampling Unit

RUTF Ready to Use Therapeutic Food

SAM Severe Acute Malnutrition

SARPV Social Assistance and Rehabilitation for the Physically Vulnerable

SC Stabilization Centre

SD Standard Deviation

SENS Standard Expanded Nutrition Survey

SFP Supplementary Feeding Programme

SHED Society for Health Extension and Development

SMART Standardized Monitoring and Assessment of Relief and Transition

SRS Simple Random Sampling

SSU Secondary Sampling Unit

TSFP Targeted Supplementary Feeding Programme

UNFPA The United Nations Population Fund

UNHCR UN High Commissioner for Refugees

UNICEF United Nations Childrens’ Fund

WASH Water, Sanitation, and Hygiene

WAZ Weight-for-Age Z-score

WFP World Food Programme

WHO World Health Organization

WHZ Weight-for-Height Z-score

WSB Wheat Soy Blend


EXECUTIVE SUMMARY

This emergency nutrition assessment was composed of three population representative SMART

surveys within Cox’s Bazar, Bangladesh. The aim of the assessment was to understand the

nutrition status of the Rohingya living within Kutupalong Refugee Camp, Nayapara Refugee

Camp, and the Makeshift Settlements of Ukhia and Teknaf upazilas. Data collection took place

from October 22nd to November 27th, 2017.

OBJECTIVES The principal objective was the evaluation of the nutritional status among Rohingya children 6-59

months within the three survey areas, as well as to provide salient nutrition and nutrition-sensitive

data to inform an effective humanitarian response to the Rohingya Crisis in Cox’s Bazar.

Additionally, the assessment aimed to:

Estimate demographic characteristics of the households

Estimate crude death rate and under five death rate in the past three months

Measure anthropometric indicators among children 0-59 months and women 15-49 years

Determine the prevalence of anaemia per haemoglobin and morbidity per two-week recall

Estimate infant and young child feeding indicators

Assess immunisation coverage and the receipt of services

METHODOLOGY The survey of Kutupalong Refugee Camp (October 22nd to 28th) selected households using simple

random sampling among those residing within the camp. Household lists were provided by

UNHCR (n=2,621) as well as household enumeration lists (n=2,174) created the week prior to

data collection. The total estimated population of Kutupalong Refugee Camp was 24,499. The

survey of the Makeshift Settlements (October 29th to November 20th) selected households using

two-stage cluster sampling among refugees residing outside of Kutupalong and Nayapara

Refugee Camp. 96 clusters were drawn with a planned 14 households per cluster. The total

estimated population of the Makeshift Settlements was 720,902. The survey of Nayapara Refugee

Camp (November 20th to 27th) selected households using simple random sampling among those

residing within the camp. Household lists provided by UNHCR (n=3,709) as well as household

enumerations lists (n=5,206) created the week prior to data collection. The total estimated

population of Nayapara Refugee Camp was 38,997.

Analysis of the data was conducted using ENA for SMART software (version 9th July 2015), Stata

Version 13 and EPI info 7.2.10. The anthropometric data was cleaned by ENA for SMART

software following SMART flag recommendations (+/- 3 of the survey’s observed median).


RESULTS The prevalence of GAM in children 6-59 months per WHZ were above the 15% WHO emergency

threshold in Kutupalong and the Makeshift Settlements, with Nayapara falling just below the same

cut-off (see table 1 below). In all three sites, stunting in children 6-59 months was above the 40%

critical threshold, and anaemia in children 6-59 months was above the 40% threshold for high

public health significance. Indicators of low MUAC for women 15-49 years and infants 0-5 months

although inferential, are of concern. Two-week recall of diarrhoea, acute respiratory infection, and

fever indicate a high disease burden in children under five. Breastfeeding is common but exclusive

breastfeeding is very low. The malnutrition status of the Rohingya at the time of assessment

constituted a serious public health emergency in need of additional humanitarian support.

Although there exist contextual differences between the three surveys and population subsets,

the overall findings suggest a context of persistently high acute and chronic malnutrition

in the Rakhine State of Myanmar, where, following the violence on August 25th, 2017 acute

malnutrition rapidly deteriorated among the Rohingya in the Rakhine State as well as

across the border in Cox’s Bazar.

Table 1: Summary of Key Indicators, Cox’s Bazar, November 2017

Indicator Sample Kutupalong RC

Makeshift Settlements

Nayapara RC

% 95% CI % 95% CI % 95% CI

% Children


1. INTRODUCTION

1.1 CONTEXT

1.1.1 Geography and Demography

Located in the southeast of Bangladesh in the Chittagong Division, Cox’s Bazar is one of

Bangladesh’s sixty-four districts (zilas). Named after the town of Cox’s Bazar, it is bordered by

Chittagong District to the North, Bandarban District and the Myanmar border to the East, and the

Bay of Bengal to the West. Cox’s Bazar is known for having one of the world’s longest natural sea

beaches and for being prone to severe weather events such as cyclones. Cox’s bazar is located

in the tropical monsoon region, which is characterized by high temperature, heavy rainfall, and

high humidity. Despite being characterized by the tropical climate “wet” and “dry” seasons, the

Bangla calendar is divided into six seasons: summer (Grisma), rainy (Barsa), autumn (Sarat), late

autumn (Hemanta), winter (Shhit), and spring (Basanta), with an average annual temperature of

32.8 °C (91.0 °F). Earthquakes and related tsunamis are additional natural threats to the region.

Cox’s Bazar is itself comprised of the eight sub-districts (upazilas) including Ukhia and Teknaf,

which host virtually the entire Rohingya population displaced within Bangladesh.

Figure 1: Map of Sixty-four Districts in Bangladesh with Cox’s Bazar in Red, Wikipedia

Commons, 2009

Officially known as The Republic of the Union of Myanmar, Myanmar is a sovereign State and the

second largest country by area in the Southeast Asian region. In the 2016 United Nations


Development Index Report, Myanmar ranked 146 out of 188 countries and territories1. Within

Myanmar, the majority of the Rohingya live in the western coastal State of Rakhine (one of the

poorest States in Myanmar) which sits across the Naf River from Cox’s Bazar. According to the

World Bank, the poverty rate of Myanmar as a whole is 37.5% while in the Rakhine State the

poverty rate is 78.0%2. Access to education, health services, and adequate nutrition are low in

Rakhine State. Rakhine State has an insufficient number of trained physicians per capita and

some of the lowest immunisation rates in the country. A 2015 SMART Survey conducted in

Maungdaw and Buthidaung Townships of Rakhine State reported emergency levels of acute

malnutrition. The previously concerning situation is believed to have deteriorated significantly due

to recent violence and displacement. In Bangladesh, basic services available prior to the

population movements from Myanmar have been severely strained.

1.1.2 Displacement and the Camps

Ongoing waves of violence have sent Rohingya over the border into Bangladesh since the early

1970s. Most recently, attacks on police posts and the subsequent backlash in northern Rakhine

in October 2016 saw an influx of 87,000 Rohingya persons displaced into Bangladesh by July of

20173. Attacks on police posts and the subsequent backlash in northern Rakhine on August 25th,

2017 caused an estimated 603,000 Rohingya persons to flee to Bangladesh from Myanmar, by

the commencement of this assessment4. These influxes joined an estimated 125,000 Rohingya

who had arrived in Bangladesh during earlier waves of violence. These estimates are based on

official data provided by the Inter Sector Coordination Group (ISCG) the main coordination body

for humanitarian agencies in Cox’s Bazar.

1 UNDP (2016) Human Development Report 2 World Bank (2014) Ending Poverty and Boosting Shared Prosperity in a Time of Transition 3 Ibid. 4 ISCG 22 Oct 2017 Situation Report: Rohingya Refugee Crisis


Figure 2: Refugee Sites by Population and Location Type, ISCG, October 22nd, 2017

Kutupalong Refugee Camp (KTP) is located in the Ukhia upazila of Cox’s Bazar. The first of two

government-run UNHCR-supported camps established in 1992, Kutupalong Refugee Camp was

created in response to a large influx of Rohingya at the time. The camp adopted the name of the

pre-existing small town and market of Kutupalong. Kutupalong Refugee Camp is bordered by the

Kutupalong Makeshift Settlements to the west and south, and by the Raja Palong rural area to

the north and east. The estimated population within Kutupalong Refugee Camp was 24,499 at

the beginning of the Kutupalong Refugee Camp Survey (October 22nd, 2017).

Nayapara Refugee Camp (NYP) is located in the Teknaf sub-district (upazila) of Cox’s Bazar. The

second of two government-run UNHCR-supported camps established in 1992 due to a large influx

of Rohingya at the time. Nayapara Refugee Camp is bordered by the Nayapara Makeshift

Settlements to the north. The estimated population within Nayapara Refugee Camp was 38,997

at the beginning of the Nayapara Refugee Camp Survey (November 20th, 2017).

The makeshift and spontaneous settlements (MS) include all refugee settlements in Ukhia and

Teknaf sub-districts outside of the two official refugee camps (Kutupalong and Nayapara) and

excluding Rohingya who have been absorbed into host communities. The two largest makeshift

sites were originally Kutupalong Makeshift (which borders Kutupalong Refugee Camp) and


Balukhali Makeshift, but the rapid expansion of these sites has blurred borders and created new

colloquial distinctions. Built on previously forested land with stretches of rice paddy, these informal

settlements lacked basic infrastructure including water points, health facilities, and roads. The

newest development is the designation of a 3,000-acre piece of land known as Kutupalong

Extension, which stretches from Kutupalong Makeshift to Balukhali Makeshift Settlements, to host

new arrivals. This expansive area has been further divided into “zones” known as “AA”, “BB”,

“CC”, etc. The estimated population of all makeshift and spontaneous settlements was 720,902

at the beginning of the Makeshift Settlements Survey (October 29th, 2017).

1.1.3 Food Security and Livelihoods

The Rakhine State of Myanmar is characterized as one of the least developed States in the

country, with 78.0% of the Rakhine State population falling below the poverty line5. A 2011 food

security assessment conducted in northern Rakhine State by the World Food Programme (WFP)

noted a deteriorating food security situation with the share of severely food insecure households

increasing from 38% in 2009 to 45% in 20116. The general population of Rakhine State is largely

dependent on agriculture and fishing as sources of food and income. Rice is the main crop in the

region, although coconut and nipa palm are also cultivated. Fishing is a major source of income,

with most production transported to and sold in Yangon. Women generally tend small livestock

such as chickens, and goats, while men herd larger animals such as buffalo and cattle. The

vending of timber, bamboo, and fuel collected from the mountains also contribute to income

generation. In the Final Report of the Advisory Commission on Rakhine State released this year,

the environment in Rakhine State was described as one of “protracted conflict, insecure land

tenure, and lack of livelihood opportunities”7. This has negatively affected local economies and

reduced opportunities for livelihoods and income generating activities (IGAs). Barriers to trade,

livelihood opportunities, and health services for Rohingya in Rakhine have led to the use of

negative coping mechanisms; including reduced meal frequency and relying on food purchased

on credit.

In Cox’s Bazar, Rohingya refugees are living in overcrowded conditions with few legal means for

IGAs. The Rohingya are largely not allowed to work or move out of the camps, and are

increasingly putting themselves at risk in order to access food, fuel, and other basic needs. These

risks include moving outside of designated areas to collect firewood, reduction of food intake, and

survival sex8. In addition, recent reports suggest that many Rohingya refugees are relying on

some sort of informal assistance or borrowing to meet basic needs. These practices ultimately

affect household safety and food security, while increasing tensions within the affected population

and in relation to host communities9. Small-scale vending by the Rohingya is informal and illegal.

Traders are largely from the host community, with a small margin being Rohingya refugees who

5 World Bank (2014) Ending Poverty and Boosting Shared Prosperity in a Time of Transition 6 WFP (2011) Food Security Assessment Northern Rakhine State Myanmar 7 Advisory Commission on Rakhine State (2017) Towards a Peaceful, Faire, and Prosperous Future for the People of Rakhine 8 OXFAM (2017) Rapid Protection, Food Security, and Market Assessment 9 Ibid.


arrived prior to 2007. Small-scale agriculture and animal husbandry is difficult to achieve given

overcrowding and lack of available land.

In a November 2017 OXFAM report released just prior to the conclusion of this assessment, more

than 80% of focus group respondents relied on dry food assistance from NGOs as their primary

food source. Despite this indication of high reliance on food assistance, 50% of interviewed

traders witnessed humanitarian food assistance being re-sold, with reports that funds from re-

sold assistance is being directed to buying fresh foods, medicine, and other basic needs10. In the

same assessment, focus group participants reported being able to access on average 11-12 food

groups before arriving in Bangladesh, but consuming 3-4 food groups now. Several assessments

have concluded that markets within the camps are well functioning with good capacity to meet

increases in demand11. In the same OXFAM assessment, 92% of those interviewed said ‘lack of

money’ was the main constraint of populations to access markets and 73% of those interviewed

during the IRC assessment said money was their most pressing need12.

1.1.4 Water, Sanitation, and Hygiene

The water, Sanitation, and Hygiene (WASH) context of Rakhine State is underdeveloped, with

poor access to clean water and sanitation facilities. In a 2009 Multiple Indicator Cluster Survey

(MICS), Rakhine State was found to have some of the poorest WASH indicators in Myanmar, with

only 57.7% of the population using an improved source of drinking water13, while an estimated

58% of households in rural Myanmar do not have improved toilet facilities, often relying on open

pit latrines14. The survey also reported that an estimated 20% of households in rural Myanmar

were without available soap and water to support adequate handwashing practices. The lack of

adequate WASH infrastructure and practices in Rakhine State are further exacerbated by frequent

natural hazards such as storms and floods.

In Cox’s Bazar, insufficient WASH facilities across camps and makeshift sites were aggravated

by the Barsa rains in September and October 2017. Poor sanitation facilities, insufficient latrines,

and poor drainage have increased risks of diarrhoeal and other waterborne disease outbreaks in

the crowded camps. In settlements that emerged spontaneously, virtually no access to potable

water or sanitation facilities existed prior to the influx. In other areas water points were hastily

erected. The Cox’s Bazar WASH sector reported (ISCG WASH Sector Situation Report- 5

November) that 4,637 tubewells with hand-pumps had been installed. However infrastructure

surveys found over 30% of waterpoints needing immediate rehabilitation/replacement15. A multi-

sector needs assessment conducted by IRC on October 7th, 2017 in Teknaf and Ukhia as well as

two neighbouring upazilas found that 25% of families reported drinking water was inconsistently

available, and 31% had practiced open defecation16. Furthermore, some WASH facilities are

constructed precariously on steep inclines, which can be dangerous at night and in the event of

rain. There are serious concerns about latrines that were constructed too close to water points,

10 Ibid. 11 Ibid. 12 IRC (2017) Undocumented Myanmar Nationals Influx to Cox’s Bazar, Bangladesh 13 UNICEF (2009) Myanmar Multiple Indicator Cluster Survey 14 USAID (2015-16) Myanmar Demographic and Health Survey 15 ISCG WASH sector Situation report, 5th November 2017 16 IRC (2017) Undocumented Myanmar Nationals Influx to Cox’s Bazar, Bangladesh


latrines that are difficult to desludge due to location, and the extensive practice of open defecation

in the newest sites17.

1.1.5 Health

Access to health services in Rakhine State is low compared to Myanmar at large. The World

Health Organization (WHO) recommends 22 health workers per 10,000 people. In Rakhine State,

the United Nations Office for the Coordination of Humanitarian Affairs (OCHA) Humanitarian

Needs Overview 2018 reported that there are currently 5 health workers per 10,000 people,

compared to the national average of 16 health workers per 10,000 people18. The Rakhine State

also has some of the lowest immunisation rates in the country with just 41% of children having all

basic vaccination coverage19,20. As of 2016, less than 19% of women were giving birth in a

professional health facility and skilled providers attended less than 1 in 3 births21. Myanmar’s

maternal mortality ratio (MMR) was 282 / 100,000 live births in 2014, making it one of the worst

in the region; Rakhine State’s MMR was even higher at 314 / 100,000 live births22. The 2015-16

Myanmar DHS reported that in Rakhine State 62% of children 6-59 months and 55% of women

15-49 suffered from anaemia (Hb


below facilities have virtually no ambulances or other vehicles to use for outreach or mobility of

services.

Table 2: Health Facilities Existing Prior to August 25th, 2017 in Ukhia and Teknaf, Cox’s

Bazar, Bangladesh Ministry of Health and Family Welfare26 2017* *This list is not exhaustive, as it does not include all charitable and faith-based hospitals and clinics

Within the camps and settlements, a high burden of acute respiratory infections (ARI) have

persisted, particularly among children less than five years of age27. Inadequate vaccination

coverage, vector control measures, and water and sanitation conditions contribute to an

environment where communicable diseases can easily spread. A WHO report released October

11th, 2017 concluded that the affected population is at high risk of outbreaks of a host of diseases

including cholera, hepatitis E, dysentery, dengue, chikungunya, Japanese encephalitis, malaria,

scrub typhus, as well as scabies28. Dengue hemorrhagic fever is one of the leading causes of

death among children under ten years in Myanmar29. Measles is endemic to both Myanmar and

Bangladesh, with measles being the fifth leading cause of death among children under five years

in Bangladesh30. Measles outbreaks among the Rohingya population have been reported in Cox’s

Bazar in both 2016 and 2017.

26 Bangladesh Ministry of Health and Family Welfare http://facilityregistry.dghs.gov.bd/search.php 27 WHO (2017) Public Health Situation Analysis and Interventions Bangladesh/Myanmar 28 WHO (2017) Public Health Situation Analysis and Interventions Bangladesh/Myanmar 29 WHO (2008) Joint Plan of Action on Dengue 30 WHO (2005) World Health Report

Health Facility types Number of Health Facilities

Location Capacity

District Hospital 1 Cox’s Bazar City 250 beds

Upazila Health Complex 1 Ukhia 50 beds

Union Health Centres 2 Ukhia Outpatient

Union Sub-centres 4 Ukhia Outpatient

Community Clinics 15 Ukhia Outpatient

NGO Clinics 3 Ukhia Outpatient

Upazila Health Complex 1 Teknaf 50 beds

Hospital 1 Teknaf 10 beds

Union Health Centres 4 Teknaf Outpatient

Union Health & Family Welfare Centres

2 Teknaf Outpatient

Union Sub-centres 2 Teknaf Outpatient

Community Clinics 13 Teknaf Outpatient

NGO Hospitals/Clinics 3 Teknaf Outpatient


1.1.6 Nutrition

Rakhine State has the worst nutritional status among children under five in all of Myanmar,

according to the 2015-16 Myanmar DHS, reporting that 38% of children less than age five years

were chronically malnourished, 14% were acutely malnourished, and 34% were underweight. The

results of two 2015 SMART Surveys conducted by Action Against Hunger in Maungdaw and

Buthidaung Townships of Rakhine State reported GAM prevalence of 19.0% [14.7-24.2]31 and

15.1% [11.8-19.2], and SAM prevalence of 3.9% [2.4-6.4] and 2.0% [1.1-3.6], respectively. These

prevalencesare likely influenced by the widespread poverty and periodic conflict, which have

created a protracted malnutrition context in Rakhine State.

SMART Surveys conducted by Action Against Hunger in Kutupalong and Nayapara Refugee

Camps in November 2016 indicated moderately high GAM prevalences of 12.7% [10.0-16.1] and

12.5% [9.7-16.1] and SAM prevalences of 0.7% [0.2-1.9] and 0.5% [0.1-1.7] respectively.

Screenings and rapid assessments prior and post August 25th, 2017 reported GAM prevalences

exceeding emergency levels among new arrivals3233, and Outpatient Therapeutic Programmes

(OTPs) were reporting an 8-fold increase in admissions34.

1.1.7 Infant and Young Child Feeding Practices

The 2009 Myanmar MICS Survey reported 44% of women initiating breastfeeding during the first

hour of birth, and an extremely low exclusive breastfeeding rate of 1.3% for infants 0-5 months in

Rakhine State35. The 2015-16 Myanmar DHS found that infants in Rakhine State have the lowest

rates of timely initiation of breastfeeding at 37%, and were the most likely to receive prelacteal

feeding (introduction of something other than breastmilk prior to initiating breastfeeding). The

2015 SMART Survey conducted by Action Against Hunger in Maungdaw and Buthidaung

Townships of Rakhine State reported very low rates of children 6-23 months achieving a minimum

acceptable diet (MAD) (achieving both minimum dietary diversity and minimum meal frequency)

of 8.3% and 3.3%, respectively.

There is concern that the multi-day journey to Cox’s Bazar and introduction into overcrowded

camps with poor WASH infrastructure will have very negative consequences for Rohingya infants

and young children. Although a SENS Survey conducted by Action Against Hunger in Kutupalong

Refugee Camp and Nayapara Refugee Camp in November-December 2016 showed relatively

high rates of timely initiation of breastfeeding (93.4% and 92.9%) and stable rates of exclusive

breastfeeding (89.7% and 77.3%) the low rates of minimum acceptable diet (11.3% and 10.6%),

respectively, remains concerning. In contrast, according to the 2014 Bangladesh DHS, the

national rate of exclusive breastfeeding among Bangladeshi nationals was just 55%36. The rapid

influx of new arrivals has brought new concerns for the IYCF status for Rohingya infants and

young children as a whole.

31 95% Confidence Interval 32 Nutrition Rapid SMART survey Balukhali Makeshift Settlement, May 2017 33 Nutrition Rapid SMART survey Shamlapur Demarcated Areas, May 2017 34 Action Against Hunger Programme data 35 UNICEF (2009) Multi Indicator Cluster Survey 36 USAID (2014) Bangladesh Demographic and Health Survey


1.1.8 Protection

The November 2017 rapid assessment by OXFAM identified key threats to protection for

Rohingya living in Cox’s Bazar; including lack of lighting, restricted movement for women,

firewood collection, and increased gender-based violence (GBV)37. The lack of lighting at night

leaves women vulnerable to assault and sexual violence and children vulnerable to kidnapping

and human trafficking. Women fleeing Myanmar often did not bring their burqas, putting pressure

on them to stay within the shelters until nightfall for reasons of modesty. This has directly affected

women’s access to WASH facilities--as indicated by reports of women consuming less food and

water in order to reduce their need to leave their shelter during the day--and restricted the ability

of female-headed households to access markets. Firewood collection for cooking fuel requires

family members to venture into the forests, with numerous accounts of sexual assault and

kidnappings. GBV is a growing concern as overcrowding and vulnerable portions of the population

are at increased risk. There have been reports of women being approached by “foreigners” and

recruited for “jobs” outside of the camps only to disappear, in addition to accounts of daughters

being married off younger than normal or men taking a second wife for economic or protection

purposes. High levels of stress and ongoing protection concerns highlight the need to strengthen

services for mental health and care practices (MHCP)38.

1.1.9 Humanitarian Actors

A well-rounded interpretation of the malnutrition context is strengthened by an understanding of

the humanitarian assistance landscape during the assessment data collection period. The

services and programmes most directed at the treatment and prevention of acute malnutrition

among children 6-59 months include stabilization centres (SCs), outpatient therapeutic

programmes (OTPs), targeted supplementary feeding programmes (TSFPs), and blanket

supplementary feeding programmes (BSFPs). SCs function for the treatment of acute malnutrition

with medical complications. OTPs function for the treatment of severe acute malnutrition without

medical complications. TSFPs function for the treatment of moderate acute malnutrition. BSFPs

function to prevent acute malnutrition in general. These key programmes are further strengthened

by IYCF-E support, deworming services, immunisation campaigns, and micronutrient

supplementation interventions.

Table 3 below shows the SCs and OTPs that were in operation during the entire course of the

survey in Kutupalong Refugee Camp (October 22nd to 28th). This list is not exhaustive, as it does

not capture SCs and OTPs that may have begun operations after the beginning of data collection.

As shown, there was one confirmed SC and one confirmed OTP implemented by ACF-UNHCR

operating during that period. With an estimated population of 24,499 at the commencement at the

survey, and estimating 14.5% of the population were children 6-59 months per the Kutupalong

Refugee Camp survey results, there were two programmes or 1 programme for every 1,776

37 OXFAM (2017) Rapid Protection, Food Security, and Market Assessment 38 WHO Report


children 6-59 months capable of treating severe acute malnutrition. In addition, there was

one TSFP and one BSFP implemented by ACF-WFP.

Table 3: Stabilization Centres and Outpatient Therapeutic Programmes Operating in

Kutupalong Refugee Camp During Survey Data Collection

Activity Target Location N Implementing

Organization (s)

SC Children 6-59

months Kutupalong Refugee

Camp 1 ACF-UNHCR

Total Number of Stabilization Centres 1 -

OTP Children 6-59

months Kutupalong Refugee

Camp 1 ACF-UNHCR

TOTAL Number of Outpatient Therapeutic Programmes 1 -


survey in Makeshift Settlements (October 29nd to November 20th). This list is not exhaustive, as it

does not capture SCs and OTPs that may have begun operations after the beginning of data

collection. As shown, there were four confirmed SCs and thirty-one confirmed OTPs implemented

by various humanitarian actors operating during that period. With an estimated population of

720,902 at the commencement at the survey, and estimating 18.3% of the population were

children 6-59 months per the Makeshift Settlements survey results, there were 35 programmes

or 1 programme for every 3,769 children 6-59 months capable of treating severe acute

malnutrition. In addition, there were eleven TSFPs and thirteen BSFPs implemented by various

humanitarian actors.

Table 4: Stabilization Centres and Outpatient Therapeutic Programmes Operating in the

Makeshift Settlements During Survey Data Collection


Organization (s)

SC Children 6-59

months

Ukhia Upazila Health Complex, Teknaf Upazila

Health Complex 2 MoHFW

Kutupalong MS 1 MSF

Leda MS 1 IOM


OTP Children 6-59

months

Balukhali MS 3 ACF, SHED

Chakmarkul 1 ACF

Hakimpara 3 ACF, Concern Worldwide


Jamtoli 2 Concern Worldwide, Save

the Children

Kutupalong MS* 4** ACF, SARPV

Leda 2 ACF

Moynarghona 1 ACF

Shamlapur 2 ACF

Thangkhali 2 ACF, Concern Worldwide

Unchiprang 2 SARPV, SHED

Zone AA 1 ACF

Zone BB 2 ACF

Zone CC 1 ACF

Zone DD 1 ACF

Zone NN 2 ACF, Concern Worldwide

Zone PP 1 Save the Children

Zone SS 1 ACF


*One OTP in Kutupalong MS began operating on October 31st, 2017, two days after the Makeshift

Settlements survey data collection had begun

**Includes one mobile OTP


survey in Naypara Refugee Camp (November 20th to 27th). This list is not exhaustive, as it does

not capture SCs and OTPs that may have begun operations after the beginning of data collection.

As shown, there was no SC and one confirmed OTP implemented by ACF-UNHCR operating

during that period. With an estimated population of 38,997 at the commencement at the survey,

and estimating 13.5% of the population were children 6-59 months per the Nayapara Refugee

Camp survey results, there were two programmes or 1 programme for every 2,632 children 6-

59 months capable of treating severe acute malnutrition. In addition, there was one TSFP

and one BSFP implemented by ACF-WFP.

Table 5: Stabilization Centres and Outpatient Therapeutic Programmes Operating in

Nayapara Refugee Camp During Survey Data Collection


Organization (s)

SC Children 6-59

months Nayapara Refugee Camp 0 -



OTP Children 6-59

months Nayapara Refugee Camp 1 ACF-UNHCR


In addition to the above services, several campaigns occurred across all camps and settlements

in Ukhia and Teknaf prior to or during the assessment:

Measles vaccination campaign conducted Nov 18th - 30th (MoHFW, WHO, UNICEF,

IOM, MSF IFRC, Save the Children).

Oral Cholera Vaccine (OCV) vaccination campaign with first round conducted on Oct 10th

targeting all persons over one year of age. and the second round Nov 4th targeting children

12 months-59 months (MoHFW, WHO, IOM, UNHCR)

Nutrition Action Week was conducted Nov 10th - 26th (MoHFW, UNICEF, Nutrition Sector)

with the aim of administering vitamin A capsules to children 6-59 months, deworming

children 24-59 months, and screening and referring SAM, MAM, and at-risk cases.

1.2 Survey Justification

The most recent surveys from the Rakhine State of Myanmar as well as camps and settlements

within Cox’s Bazar show high prevalences of acute malnutrition (see table 6 below). Screenings

and rapid assessments in Cox’s Bazar indicated GAM prevalences exceeding emergency levels

among new arrivals. OTPs reported an 8-fold increase in admissions after August 25th, 2017.

Furthermore, the overcrowding in the camps and strained water and sanitation infrastructure was

likely increasing the vulnerability of children under five. Due to the rapid influx of refugees and

mass displacement, overcrowding, overstretched resources, and lack of available data on the

malnutrition status of the population, the Nutrition Sector agreed to conduct an emergency

nutrition assessment. The Nutrition Sector organised the emergency nutrition assessment

technical working group; members of which included ACF, CDC, UNHCR, UNICEF, WFP, and

Save the Children.


Table 6: Overview of Reported Representative Estimates of Global Acute Malnutrition for

Rakhine State and Cox’s Bazar since 2015

N Survey Date Country Location GAM by

WHZ 95% CI

Survey Type

Source

1 May 2017 Bangladesh Balukhali Makeshift 21.2% [15.7-28.1] SMART ACF, Nutrition Sector

2 May 2017 Bangladesh Leda Makeshift 14.6% [9.8-21.2] SMART ACF

3 May 2017 Bangladesh Shamlapur 19.6% [14.2-26.5] SMART ACF, Nutrition Sector

4 Feb 2017 Bangladesh Ukhia & Teknaf (host communities)

11.3% [9.1-14.0] SMART ACF

5 Nov 2016 Bangladesh Kutupalong RC 12.7% [10.0-16.1] SENS ACF, UNHCR

6 Nov 2016 Bangladesh Nayapara RC 12.5% [9.7-16.1] SENS ACF, UNHCR

7 2015-2016 Myanmar Rakhine State 13.9% - DHS MoH, USAID

8 Dec 2015 Bangladesh Kutupalong RC 12.5% [9.5-16.2] SENS ACF, UNHCR

9 Dec 2015 Bangladesh Nayapara RC 13.1% [9.9-17.0] SENS ACF, UNHCR

10 Dec 2015 Bangaldesh Kutupalong Makeshift 20.1% [16.3-24.4] SMART ACF, MSF

11 Oct 2015 Myanmar Maungdaw, Rakhine 19.0% [24.1-14.7] SMART ACF

12 Oct 2015 Myanmar Buthidaung, Rakhine 15.1% [19.2-11.8] SMART ACF

1.3 Survey Objectives

This emergency nutrition assessment aimed to determine the nutrition status of Rohingya children

under five in the Ukhia and Teknaf Upazilas of Cox’s Bazar, as well as select indicators of

demography and mortality, anthropometry, morbidity, IYCF, and receipt of health services.

Demographic data collected during the assessment was expected to assist humanitarian actors

in the planning and targeting of humanitarian interventions. The assessment was designed to

provide estimates separately for registered refugees, unregistered refugees who arrived prior to

August 25th, 2017, and unregistered refugees who arrived post August 25th, 2017.

The specific objectives of the assessment were as follows:

Demography

To estimate the household demographic composition in terms of age and sex

distribution, proportion of pregnant and lactating women

To estimate household demographic composition by arrival subset

To estimate crude death rate and under five death rate in the past three months


Anthropometry

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

To measure the prevalence of stunting in children 6-59 months

To measure the prevalence of underweight in children 6-59 months

To measure the prevalence of low mid-upper arm circumference (MUAC) (


To determine the enrollment of children 6-59 months in OTPs

To determine the enrollment of children 6-59 months in BSFPs

To determine the proportion of children 6-59 months that have received micronutrient

powder since August 25th, 2017

1. METHODOLOGY

2.1 Type of Survey and Target Population

All three surveys were cross sectional household surveys conducted using the SMART

(Standardized Monitoring and Assessment in Relief and Transitions) Survey design for

anthropometric data. While survey teams surveyed every selected household regardless of

household demographics, the target population for anthropometric indicators were children 0-59

months and women 15-49 years.

For Kutupalong Refugee Camp, households were selected by Simple Random Sampling (SRS)

among those residing within the camp regardless of registration status. The Primary Sampling

Unit (PSU) was the household. Household lists included a UNHCR registered refugee list

(n=2,621 households) as well as household enumeration lists created to capture unregistered

persons and new arrivals (n=2,174 households). Newly arrived households were enumerated the

week preceding data collection. Total sampling frame population size 24,449. There were no

exclusions due to inaccessibility.

For the Makeshift Settlements, households were selected using two-stage cluster sampling

among refugees residing in Ukhia and Teknaf Upazilas, yet outside of Kutupalong Refugee Camp,

Nayapara Refugee Camp, and host communities. The PSU was the cluster, and the Secondary

Sampling Unit (SSU) was the household. Rohingya refugees that were absorbed by the host

communities were excluded from the assessment due to difficulties in locating them, as well as

ethical concerns. Total sampling frame population size 720,902 based on ISCG population

estimates updated October 26th, 2017. There were no exclusions due to inaccessibility, however,

as some areas not included in the sampling frame became populated after survey planning was

complete, and therefore were excluded by default.

For Nayapara Refugee Camp, households were selected by SRS among those residing within

the camp regardless of registration status. The PSU was the household. Household lists included

a UNHCR registered refugee list (n=3,709 households) as well as household enumeration lists

created to capture unregistered persons and new arrivals (n=5,206 households). Newly arrived

households were enumerated the four days preceding data collection. Total sampling frame

population size was 38,997. There were no exclusions due to inaccessibility.

2.2 Sample Size Calculation

Parameters used to calculate sample size for anthropometry and the evidence or working

assumptions which informed the decision, are summarized in table 7 below. All calculations were

made using ENA for SMART software (version 9th July 2015). The sample sizes were designed


to achieve adequate precision for estimates of acute malnutrition disaggregated for three

population subsets: registered refugees, unregistered refugees arriving prior to August 25th, 2017,

and unregistered refugees arriving post August 25th, 2017.

Table 7: Sample Size Calculation Parameters Anthropometry

Parameter Kutupalong Makeshift Nayapara Assumptions / Source of Information

Estimated GAM

Prevalence

18%

(13% GAM for 50% Pop) + (23% GAM for 50% Pop)

22%

(19% GAM for 25% Pop) + (23% GAM for 75% Pop)

24%

GAM for registered refugees estimated at 13% based on 2016 SENS data (see Table 6). GAM for unregistered refugees arriving prior to August 25 estimated at 19% based on 2017 SMART data. GAM for unregistered refugees arriving post August 25 estimated at 23% based on 2017 SMART data from Balukhali MS. GAM for Nayapara Refugee Camp updated to reflect the findings from Kutpualong refugee camp (the first survey completed). Registered camps estimated to host approximately 50% registered refugees and 50% new arrivals. Makeshift Settlements estimated to be 25% older arrivals and 75% newer arrivals based on estimates from ISCG.

± Desired Precision

5.3 3.25 4.25

Precision based on SMART guidelines, updated to allow for sufficient precision for three population groups: registered refugees, unregistered refugees arriving prior to August 25th, 2017 and unregistered refugees arriving post August 25th, 2017 (sub-populations of each sample).

Design Effect 1.0 1.3 1.0

Kutupalong and Nayapara surveys applied simple random sampling (DEFF of 1.0). Given the large number of clusters planned and no indication of large heterogeneity in the Makeshift Settlements a DEFF of 1.3 was assumed.

Sample Size Children 6-59

months 202 883 388 -


Average Household

Size

4.75

(5.2 for 50% Pop) + (4.3

for 50% Pop)

4.3 5.4

Average HH size for unregistered (4.3) based on full enumeration of households by UNHCR Oct 7-11, 2017. Average HH size for Kutupalong based on UNHCR registration data (4.75) and UNHCR enumeration Oct 7-11 (4.3). Average HH size for Nayapara based on results from Kutupalong survey (5.4).

% of Children under 5

16.5%

(14% of 50% Pop) + (19% of 50% Pop)

19% 16.1%

% of children under five for unregistered based on full enumeration of households by UNHCR Oct 7-11, 2017. % of children under five for Kutupalong based on UNHCR registration data and UNHCR enumeration Oct 7-11. % of children under five for Nayapara based on results from Kutupalong survey.

% Non-response

Rate 18% 10% 40%

Previous surveys (2015/2016) in the registered camps observed non-response rates between 4-7%. A higher non-response rate was used in anticipation of rapid population movement. In camps, enumeration of households would be conducted the week prior to data collection, while household lists would be updated the day prior in the Makeshift Settlements. Non-response rate for Nayapara based on results from the Kutupalong survey.

Sample Size (Households)

349 1,335 723 -

Parameter Kutupalong Makeshift Nayapara Assumptions / Source of Information

Estimated death rate per 10,000

/day

1.0 1.0 1.0 Absent data on mortality among this population, emergency levels of mortality were assumed.

± Desired precision

per 10,000/day

0.50 0.3 0.45

Precision is based on SMART guidance, updated to ensure reasonably precise estimates for three population groups: registered refugees, unregistered refugees arriving before August 25 and the new influx (arriving since August 25), sub-populations of each sample.

Design Effect

1.0 1.3 1.0 Surveys in the refugee camps applied simple random sampling. Given the large number of clusters planned and no indication of large


heterogeneity in mortality a DEFF of 1.3 was assumed.

Recall period in day

120 132 141

The end of Ramadan (June 25, 2017) was used as the beginning of the recall period. The midpoint of data collection was anticipated to be October 22, November 3, and November 12 for Kutupalong, Makeshift/spontaneous, and Nayapara respectively. The end of Ramadan is memorable and allows for an assessment before and after the influx.

Sample size (population)

1,281 4,576 1,345

Average HH Size

4.75

(5.2 for 50% Pop) + (4.3

for 50% Pop)

4.3 5.4

Average HH size for unregistered (4.3) based on full enumeration of households by UNHCR Oct 7-11, 2017. Average HH size for Kutupalong based on UNHCR registration data (4.75) and UNHCR enumeration Oct 7-11 (4.3). Average HH size for Nayapara based on results from Kutupalong survey (5.4).

% Non-response

Rate 18% 10% 40%

Previous surveys (2015/2016) in the registered camps observed non-response rates between 4-7%. A higher non-response rate was used in anticipation of rapid population movement. In camps, enumeration of households would be conducted the week prior to data collection, while household lists would be updated the day prior in the Makeshift Settlements. Non-response rate for Nayapara based on results from the Kutupalong survey.

Sample Size (Households)

329 1,183 415 -

2.3 Sampling

2.3.1 Cluster Selection

Only the Makeshift Settlements Survey applied a cluster sampling strategy. A sample size of

1,335 households was calculated based on the chosen parameters (see table 7 above).

According to the survey planning, it was estimated that if the teams departed their lodging at 7am

and returned at 6pm there would be 11 hours (660 minutes) available each day for data collection.

Travel to and from the survey sites would take approximately 3 hours (180 minutes). About 1 hour

(60 minutes) would be used for lunch and hydration breaks. In total, this left 7 hours (420 minutes)

to survey households. Little time would be necessary for orientation or introductions to local

leaders as one team member had arrived the day prior to make introductions, map the area, and

select the households. With an estimated 5 minutes walking between households and 25 minutes


of actual time spent surveying, it was estimated that 14 households could be surveyed in each

day of data collection.

Therefore, 1,335 households / 14 households per day = 95.4 clusters

The number of clusters was rounded up to 96 to achieve sufficient sample

Population estimates from each of the makeshift and spontaneous settlements was obtained from

the ISCG. The sampling frame included all Rohingya persons within these settlements regardless

of date of arrival. Clusters were assigned using population proportional to size (PPS) per ENA

software. Reserve clusters were not implemented as more than 80% of the sample size for

children was reached. A complete list of selected clusters is availabe in Annex 5.

For larger sites and sites with multiple clusters, segmentation was often used. The segmentation

method was also applied when the cluster contained more than 200 households. Often the most

efficient way to segment sites was to use blocks or sub-blocks. Block boundaries and estimated

populations per block used as segments were obtained in select sites from WFP as well as the

Bangladeshi military. Further division could be based on natural landmarks (canal, road, hill, etc.)

or public places (markets, schools, mosques, etc.).

In well-organised (generally older and more established) settlements population estimates could

be gathered from the UNHCR, ACF field staff, and the Bangladeshi Military. When possible, these

figures were triangulated between all three. Once segmented, clusters were selected using PPS.

In unorganised settlements (newer, less military or humanitarian presence) block designation

could be incomplete or nonexistent. In these cases, additional time was invested into

understanding the hierarchy of local community leaders (majis) who maintained lists of the

families they coordinated, and could therefore provide further population estimates. By

understanding the hierarchical structure of majis in a given area (head majis, sub-majis,

geographic delineations) it was possible to use majis as proxies for segments to carry out the

segmentation process. Reducing the likelihood of overlap was reinforced by mapping all maji

areas within natural boundaries such as canals, roads, and borders with established settlements.

Reducing the likelihood of gaps was reinforced by interviewing majis and asking if there were new

majis who had recently moved into the area or

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