EMERGENCY NUTRITION ASSESSMENT FINAL REPORT COX’S BAZAR, BANGLADESH OCTOBER 22 - NOVEMBER 27 2017
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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
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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
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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
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3.2.2 Demography and Mortality ...... 70 3.2.3 Prevalence of Acute Malnutrition by WHZ ...... 72 3.2.4 Prevalence of Acute Malnutrition by MUAC ...... 74 3.2.5 Prevalence of Acute Malnutrition WHZ vs. MUAC ...... 76 3.2.6 Low MUAC in Women ...... 77 3.2.7 Low MUAC in Infants ...... 77 3.2.8 Prevalence of Chronic Malnutrition ...... 78 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 3.3.2 Demography and Mortality ...... 91 3.3.3 Prevalence of Acute Malnutrition by WHZ ...... 93 3.3.4 Prevalence of Acute Malnutrition by MUAC ...... 95 3.3.5 Prevalence of Acute Malnutrition WHZ vs. MUAC ...... 97 3.3.6 Low MUAC in Women ...... 98 3.3.7 Low MUAC in Infants ...... 99 3.3.8 Prevalence of Chronic Malnutrition ...... 99 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
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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
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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 Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 7
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
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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
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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
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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 Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 11
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
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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).
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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 Makeshift Kutupalong RC Nayapara RC Indicator Sample Settlements % 95% CI % 95% CI % 95% CI % Children <5 16.1% [14.6-17.7] 20.3% [19.3-21.4] 15.0% [13.8-16.3] Households Average HH Size (SD) 5.4 (2.7) 5.6 (2.3) 6.4 (2.6) CDR Households - - 1.36 [1.07-1.73] 0.75 [0.56-1.01] 0-5DR Households - - 1.22 [0.70-2.13] 0.80 [0.37-1.73] GAM (WHZ) 24.3% [19.5-29.7] 19.3% [16.7-22.2] 14.3% [11.2-18.1] SAM (WHZ) Children 6-59 mos. 7.5% [4.9-11.2] 3.0% [2.2-4.2] 1.3% [0.5-2.9] GAM (MUAC) 5.9% [3.7-9.4] 8.6% [6.8-10.7] 7.0% [4.9-9.9] MUAC <210mm Women 15-49 yrs. 7.3% [5.2-10.1] 8.7% [6.7-11.1] 3.2% [2.1-4.7] MUAC <110mm Infants 0-5 mos. 31.6% [18.4-48.6] 25.8% [19.2-33.7] 23.1% [13.3-36.9] Stunting (HAZ) 43.4% [37.6-49.4] 44.1% [40.7-47.5] 44.4% [39.5-49.3] Anaemia (Hb<11.0 Children 6-59 mos. 47.9% [41.9-54.0] 47.9% [44.1-41.7] 46.6% [41.8-51.6] g/dL) Measles Immun. 55.0% [49.4-60.5] 45.3% [38.5-52.3] 88.0% [84.5-90.8] Cholera Immun. All Persons ≥ 1 yr. 78.1% [69.7-79.1] 88.5% [84.0-91.9] 87.3% [86.0-88.4] Exclusive BF Infants 0-5 mos. 82.1% [66.0-91.5] 56.1% [45.1-66.4] 72.2% [58.4-82.8] Cont. BF at 1 yr. Children 12-15 mos. 100% - 97.3% [89.2-99.2] 96.4% [76.3-99.6] Min. Acceptable Diet Children 6-23 mos. 8.8% [4.6-16.2] 6.4% [3.8-10.4] 15.7% [10.2-23.4] Diarrhoea 40.5% [35.1-46.1] 41.3% [36.5-47.2] 34.3% [30.0-39.1] ARI Children 6-59 mos. 55.7% [50.1-61.1] 57.7% [52.7-62.4] 50.3% [45.4-55.1] Fever 37.5% [32.3-43.1] 25.2% [20.5-30.6] 16.9% [13.6-20.9]
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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
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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 Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 16
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 Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 17
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.
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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
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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<11.0 g/dL). Both Myanmar and Bangladesh are endemic to dengue, chikungunya, and malaria. Malaria is a major public health problem in Myanmar, and Rakhine State is classified as a high-risk malaria-endemic area. Both countries experience a high tuberculosis disease burden. In a 2016 Rakhine State needs assessment, 52% of respondents reported that they did not have access to adequate healthcare23. The OCHA Humanitarian Needs Overview 2018 noted that although basic medical services are widespread access to these services is particularly low within the Muslim community due to obstacles including movement restrictions, language differences, and inability to pay for services24. In Cox’s Bazar the large influx of new arrivals has severely strained all health services, and overcrowding in the camps has increased the risk of disease outbreaks. The existing facilities in Cox’s Bazar and surrounding areas reported a 150-200% increase in patients in October 201725. Table 2 below summarizes the operational health facilities in Ukhia and Teknaf upazilas in Cox’s Bazar existing prior to August 25th, 2017. Despite being located in the town of Cox’s Bazar, the District Hospital is listed as it is the main hospital for referral. Cox’s Bazar has a basic health infrastructure but no designated trauma care facilities. Furthermore, not all of the listed facilities are accessible by the Rohingya population, given distance and cost of services. In addition, the
17 REACH (2018) Rohingya Crisis: Mapping Infrastructure and Services in Refugee Camps and Sites 18 OCHA (2017) 2018 Myanmar Humanitarian Needs Overview 19 Children 12-13 months vaccinated against tuberculosis, diphtheria, pertussis, tetanus, hepatitis B, Haemophilus influenza, polio, and measles/measles rubella 20 Myanmar Demographic and Health Survey 2015-16 21 USAID (2015-16) Myanmar Demographic and Health Survey 22 UNFPA (2014) Myanmar Census 23 Center for Diversity and National Harmony (2017) Rakhine State Needs Assessment II 24 OCHA (2017) 2018 Myanmar Humanitarian Needs Overview 25 WHO (2017) Public Health Situation Analysis and Interventions Bangladesh/Myanmar
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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 Number Health Facility types of Health Location Capacity Facilities 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 2 Teknaf Outpatient Welfare Centres Union Sub-centres 2 Teknaf Outpatient Community Clinics 13 Teknaf Outpatient NGO Hospitals/Clinics 3 Teknaf Outpatient
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
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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 Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 22
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 Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 23
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
Implementing Activity Target Location N Organization (s) Children 6-59 Kutupalong Refugee SC 1 ACF-UNHCR months Camp Total Number of Stabilization Centres 1 - Children 6-59 Kutupalong Refugee OTP 1 ACF-UNHCR months Camp TOTAL Number of Outpatient Therapeutic Programmes 1 -
Table 4 below shows the SCs and OTPs that were in operation during the entire course of the 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
Implementing Activity Target Location N Organization (s) Ukhia Upazila Health Complex, Teknaf Upazila 2 MoHFW Children 6-59 SC Health Complex months Kutupalong MS 1 MSF Leda MS 1 IOM Total Number of Stabilization Centres 4 - Balukhali MS 3 ACF, SHED Children 6-59 OTP Chakmarkul 1 ACF months Hakimpara 3 ACF, Concern Worldwide
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Concern Worldwide, Save Jamtoli 2 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 TOTAL Number of Outpatient Therapeutic Programmes 31 - *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
Table 5 below shows the SCs and OTPs that were in operation during the entire course of the 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
Implementing Activity Target Location N Organization (s) Children 6-59 SC Nayapara Refugee Camp 0 - months Total Number of Stabilization Centres 0 -
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Children 6-59 OTP Nayapara Refugee Camp 1 ACF-UNHCR months TOTAL Number of Outpatient Therapeutic Programmes 1 -
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.
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Table 6: Overview of Reported Representative Estimates of Global Acute Malnutrition for Rakhine State and Cox’s Bazar since 2015
GAM by Survey N Survey Date Country Location 95% CI Source WHZ Type 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 11.3% [9.1-14.0] SMART ACF communities) 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
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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) (<115mm, <110mm, & <105mm) in infants 0-6 months To measure the prevalence of low MUAC (<210mm) in women 15-49 years
Morbidity
To determine the prevalence of anaemia among children 6-59 months To determine the two-week period prevalence of diarrhoea among children 6-59 months To determine the two-week period prevalence of acute respiratory illness with fever among children 6-59 months To determine the two-week period prevalence of fever (without cough) among children 6-59 months To determine health care seeking behaviour among children who had been ill in the 2 weeks prior to the survey To measure the prevalence of total, mild, moderate, and severe anaemia among children 6-59 months
IYCF
To estimate timely initiation of breastfeeding among children 0-23 months To estimate prevalence of exclusive breastfeeding among infants 0-5 months To estimate the introduction of complementary foods among children 6-8 months To estimate continued breastfeeding at 1 year (among children 12-15 months) and at 2 years (in children 20-23 months) To estimate minimum dietary diversity among children 6-23 months (>=4 of 7 groups) To estimate minimum meal frequency among children 6-23 months (>=3 times) To estimate minimum acceptable diet among children 6-23 months (MDD & MMF) To assess the consumption of liquids among children 0-23 months To assess the consumption of iron-rich or iron-fortified foods among children 6-23 months
Receipt of Services
To determine the coverage of measles vaccination among children 6-59 months since August 25th, 2017 To determine the coverage of oral cholera vaccine (OCV) among all persons over 1 year of age since August 25th, 2017 To determine the proportion of households that have received at least one food distribution since August 25th, 2017 Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 28
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 Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 29
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 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 18% 22% August 25 estimated at 23% based on 2017 SMART data from Balukhali MS. Estimated (13% GAM (19% GAM GAM 24% for 50% Pop) for 25% Pop) GAM for Nayapara Refugee Camp updated to Prevalence + (23% GAM + (23% GAM reflect the findings from Kutpualong refugee for 50% Pop) for 75% Pop) 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. Precision based on SMART guidelines, updated to allow for sufficient precision for three population ± Desired groups: registered refugees, unregistered 5.3 3.25 4.25 Precision refugees arriving prior to August 25th, 2017 and unregistered refugees arriving post August 25th, 2017 (sub-populations of each sample). Kutupalong and Nayapara surveys applied simple random sampling (DEFF of 1.0). Given the large Design Effect 1.0 1.3 1.0 number of clusters planned and no indication of large heterogeneity in the Makeshift Settlements a DEFF of 1.3 was assumed. Sample Size Children 6-59 202 883 388 - months
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Average HH size for unregistered (4.3) based on full enumeration of households by UNHCR Oct 7- 11, 2017. 4.75
Average Average HH size for Kutupalong based on UNHCR Household (5.2 for 50% 4.3 5.4 registration data (4.75) and UNHCR enumeration Size Pop) + (4.3 Oct 7-11 (4.3). for 50% Pop)
Average HH size for Nayapara based on results from Kutupalong survey (5.4). % of children under five for unregistered based on full enumeration of households by UNHCR Oct 7-11, 2017. 16.5%
% of Children % of children under five for Kutupalong based on (14% of 50% 19% 16.1% under 5 UNHCR registration data and UNHCR Pop) + (19% enumeration Oct 7-11. of 50% Pop)
% of children under five for Nayapara based on results from Kutupalong survey. 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 % Non- camps, enumeration of households would be response 18% 10% 40% conducted the week prior to data collection, Rate 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 349 1,335 723 - (Households)
Parameter Kutupalong Makeshift Nayapara Assumptions / Source of Information Estimated death rate Absent data on mortality among this population, 1.0 1.0 1.0 per 10,000 emergency levels of mortality were assumed. /day Precision is based on SMART guidance, updated ± Desired to ensure reasonably precise estimates for three precision population groups: registered refugees, 0.50 0.3 0.45 per unregistered refugees arriving before August 25 10,000/day and the new influx (arriving since August 25), sub- populations of each sample. Surveys in the refugee camps applied simple Design 1.0 1.3 1.0 random sampling. Given the large number of Effect clusters planned and no indication of large
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heterogeneity in mortality a DEFF of 1.3 was assumed. 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 Recall period 22, November 3, and November 12 for 120 132 141 in day Kutupalong, Makeshift/spontaneous, and Nayapara respectively. The end of Ramadan is memorable and allows for an assessment before and after the influx. Sample size 1,281 4,576 1,345 (population) Average HH size for unregistered (4.3) based on full enumeration of households by UNHCR Oct 7- 11, 2017. 4.75
Average HH Average HH size for Kutupalong based on UNHCR (5.2 for 50% 4.3 5.4 Size registration data (4.75) and UNHCR enumeration Pop) + (4.3 Oct 7-11 (4.3). for 50% Pop)
Average HH size for Nayapara based on results from Kutupalong survey (5.4). 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 % Non- camps, enumeration of households would be response 18% 10% 40% conducted the week prior to data collection, Rate 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 329 1,183 415 - (Households)
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 Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 32
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 households without a designated maji. Once segmented, clusters were selected using PPS.
Mapping teams visited all clusters during the day preceding data collection to map boundaries of the selected cluster, draw segments (where applicable), and fully enumerate all households within selected cluster or segment. Majis often maintained lists of households within their block. These lists were reviewed and updated. Given the complexity of mapping and listing newly settled areas with ongoing population displacement, a full day was allocated for mapping and listing each cluster.
2.3.2 Household Selection
Per the SMART methodology, a household (HH) was defined as a group of people who live together and share food and resources. A person was considered a member of the household if they had spent at minimum the night prior with the household.
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Households were randomly selected from updated housholds lists.
In Kutupalong and Nayapara Refugee Camps, UNHCR provided a list of all registered refugee households. Households with new arrivals were mapped and listed by community volunteers during the week preceding data collection for each camp respectively. All new arrivals were mapped and listed regardless of whether they were living in pre-existing camp blocks, newly settled areas of the refugee camps, or in non-house shelters (e.g., mosques, schools). These lists were then combined to form a sampling frame and houses were selected randomly using SRS.
In the Makeshift Settlements, one member of the survey team arrived in each cluster one day prior to data collection. This team member would identify the local maji for the selected block and determine if there was an existing list of households. If a list was available, the team member worked to update the list, adding any households that had joined and dropping any households that had left. If a list was not available, a new list of all households was created while walking the perimeter of the block with the help of the maji. Once the team member was in possession of a complete and updated list, 14 households were selected using a random number generator. Selected households were informed that data collection teams would visit the following day.
All households were eligible regardless of registration status, date of arrival, or whether they had children. Survey teams attempted to survey 14 randomly selected households. Efforts were made to revisit absent households twice. Absent households were not replaced.
2.3.3 Selection of Individuals to Survey
All consenting children 0-59 months of age present within selected households were measured and the appropriate data was collected. . All consenting women 15-49 years of age present within selected households were measured for MUAC.Efforts were made to return to the household to measure women and children that were absent at the time of the interview. In certain cases, anthropometric data of age-eligiblechildren was not collected:
If a child was absent from a household during the visit, could not be located by a family member, and was not found after revisiting the household. If a child presented with a handicap or physical malformation which would affect the accuracy of an anthropometric measurement. If a child was too ill to be safely and respectfully measured. In this context, there were generally no problems with weighing the children 6-59 months without clothing. Where there was hesitation, children were weighed in another room with just the caregiver and a female team member for privacy. The only item that was left on children was a single string tied around the waist called “tabiz” which holds religious significance and would require cutting to remove. Despite sometimes including small bells, the tabiz were left on all children, and due to their light weight (<15 grammes) they were not corrected for. During the survey, children suffering from acute malnutrition (MUAC <125 mm, and/or presence of oedema) and women with low MUAC (MUAC <210 mm) were referred to the nearest appropriate nutrition programme centre when possible. The referral form is available in Annex 11.
In Kutupalong Refugee Camp, 3 women 15-49 years and 10 children 6-59 months were referred for treatment.
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In the Makeshift Settlements, 9 women 15-49 years and 6 children 6-59 months were referred for treatment. In Nayapara Refugee Camp, 3 women 15-49 years and 0 children 6-59 months were referred for treatment.
2.4 Collected Variables
2.4.1 Demography & Mortality Age and sex of all current household members were collected. In addition, information was collected on the number of persons that were in the household. For current household members, teams noted whether the individual was born or joined the households since the start of the recall period. In addition, age was collected for people that left the household or died since the beginning of the recall period. The recall period started from 25th June 2016, the end of Ramadan.
2.4.2 Anthropometry
Age was recorded among children 0-59 months as a date of birth (day/month/year) only if the information was confirmed by supportive documentation such as vaccination or birth registration cards. Where documentation was unavailable, age was estimated using a local calendar of events and recorded in months. The complete local events calendar is availabe in Annex 10. Weight was recorded among children 6-59 months in kg to the nearest 0.1kg using an electronic SECA scale. Children who could easily stand still were weighed on their own. When children could not stand independently, the double weighing method was applied with the help of a caregiver. All children were measured without clothes and weight was taken 2-3 times to ensure accuracy. Height was recorded among children 6-59 months in cm to the nearest 0.1cm. A height board was used to measure bare headed and barefoot children. Children less than 87cm were measured lying down and those equal to or above 87cm were measured standing up. Two team members worked in unison to take the measurements of each child. MUAC was recorded in children 0-59 months and women 15-49 years to the nearest mm. All subjects were measured on the left arm using standard MUAC tapes. The presence of oedema among children 6-59 months was recorded as “yes” or “no”. All children were checked for the presence of oedema by applying pressure with thumbs for three continuous seconds on the tops of both feet. If any cases were identified they required confirmation by a supervisor or the survey manager.
2.4.3 Morbidity
Diarrhoea was assessed among children 6-59 months by a two-week recall. Diarrhoea was defined as passage of three or more loose or liquid stools in a day.
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Cough (with fever) was assessed among children 6-59 months by a two-week recall, defined as cough (with rapid or difficulty breathing) and fever. This indicator was used as a proxy for suspected pneumonia. Fever (without cough) was assessed among children 6-59 months by a two-week recall, defined as fever in the absence of respiratory symptoms (cough). This indicator was used as a proxy for suspected malaria. Anaemia was determined among children 6-59 months according to blood haemoglobin content which was measured utilizing HemoCue (Hb 301) tests. Severe anaemia was defined as children 6-59 months with haemoglobin levels <7.0 g/dL Moderate anaemia was defined as children 6-59 months with haemoglobin levels between 7.0 and 9.9 g/dL Mild anaemia was defined as children 6-59 months with haemoglobin levels between 10.0 and 10.9 g/dL Any anaemia was defined as children 6-59 months with haemoglobin levels <11.0 g/dL
2.4.4 Infant and Young Child Feeding
Early Initiation of Breastfeeding, defined as the proportion of children 0-539 months who were put to the breast within one hour of birth. Exclusive breastfeeding, defined as the proportion of children 0-5 months who were breastfed and did not receive any liquids other than breast milk on the day preceding the survey. Continued breastfeeding at 1 year, defined as the proportion of children 12-15 months who were fed breast milk on the day preceding the survey. Continued breastfeeding at 2 years, defined as the proportion of children 20-23 months of age who were fed breast milk during the day preceding the survey. Introduction of complementary foods, defined as the proportion of children 6-8 months who were fed both breast milk and a complementary food during the day preceding the survey. Minimum dietary diversity (MDD), defined as the proportion of children 6-23 months of age who received foods from 4 or more of the following food groups: (1) grains, roots, tubers, (2) legumes, nuts (3) dairy products, (4) flesh foods, (5) eggs, (6) Vitamin A rich fruits and vegetables, (7) other fruits and vegetables. Minimum meal frequency (MMF), defined as the proportion of children 6-23 months who received greater than or equal to three meals per day. Minimum acceptable diet (MAD), defined as the proportion of children 6-23 months who were achieving both MDD and MMF.
2.4.5 Receipt of Services
39 0-5 months: inclusive of the 5th month or up to 6 months Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 36
Measles immunisation coverage was assessed by any dose of measles vaccination administered since August 25th, 2017, as confirmed by card or recall. There was a combined measles/rubella vaccination campaign from 16 September- 4th October, and from 18th November – 30th November. The campaign was a combined measles/rubella vaccine (MR) for persons 1 to 15 years, oral polio vaccine (OPV) for children 0 to 59 months and Vitamin A for children 6 to 59 months. Given combined administration, measles vaccination coverage can be assumed to be a proxy for coverage of OPV and Vitamin A. Cholera immunisation coverage was assessed by any dose of Oral Cholera Vaccination (OCV) administered since August 25th, 2017, as confirmed by finger mark or recall. The OCV campaign 1st round was conducted on 10th October and a 2nd round was conducted from 4th November. The general food distribution (GFD) indicator was defined as any current member of the household receiving at least one bag of rice from a general food distribution since August 25th, 2017. OTP enrollment was defined as any child 6-59 months with SAM currently enrolled in an OTP at the time of the survey. Caregivers were shown RUTF sachets to confirm. SAM was defined as low MUAC and/or low WHZ and/or Oedema were considered. BSFP enrollment was defined as any child currently enrolled in a BSFP at the time of the survey. Caregivers were shown WSB++ package to confirm. Target age group was determined by enrollment criteria in the respective sites: only children 6-23 months were considered for Kutupalong and Nayapara Refugee camps; children 6-59 months were included for the Makeshift Settlements. Receipt of micronutrient powder (MNP) was assessed by any child 6-59 months having received at least one sachet of MNP since August 25th, 2017. Caregivers were shown a MNP sachet to confirm. Target age group was determined by enrollment criteria in the respective sites: only children 6-23 months were considered for Kutupalong and Nayapara Refugee camps; children 6-59 months were included for the Makeshift Settlements.
2.5 Indicators and Cut-offs 2.5.1 Mortality Indices
The CDR is the most useful health indicator to monitor and evaluate the severity of an emergency situation. The crude death rate (CDR) is defined as the number of people in the total population who die over a specified period of time. It is calculated from the following formula: CDR= Number of deaths / (mid-interval population/10,000) x time interval = deaths/10,000/day
0–5DR is the number of children aged from birth to under 5 years who die over a specified period of time in relation to the total number of children below 5 years of age in the population. It is calculated from the following formula: 0-5DR= Number of deaths of children 0-5 years/ (mid-interval population/ 10,000) x time interval = deaths/10,000/day
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The emergency threshold for CDR is 0.4 deaths/10.000/days and for 0-5DR it’s 0.9 deaths/10.000/day for South Asia region according to the SPHERE standards 2.5.2 Anthropometric Indices
Acute malnutrition is the physical manifestation of a sudden disruption of an individual’s ability to consume or absorb nutrients. In children 6-59 months of age, acute malnutrition is estimated using Weight-for-Height z-score (WHZ) and/or MUAC combined with the presence of oedema. WHZ is calculated using ENA Software by comparing the observed weight of a selected child to the mean weight of children from the reference population for a given height. When using WHZ, the distribution of the sample is compared against the 2006 WHO reference population. The WHZ cut-offs are displayed in table 8 below. Global acute malnutrition (GAM) is the sum of moderate and severe acute malnutrition. Chronic malnutrition is the physical manifestation of long-term malnutrition which retards growth. In children 6-59 months of age, chronic malnutrition is estimated using Height-for-Age z-score (HAZ). HAZ is calculated using ENA Software by comparing the observed height of a selected child to the mean height of children from the reference population for a given age. When using HAZ, the distribution of the sample is compared against the 2006 WHO reference population. The HAZ cut-offs are displayed in table 8 below. Global chronic malnutrition is the sum of moderate and severe chronic malnutrition. Underweight is the physical manifestation of both acute malnutrition and chronic malnutrition. In children 6-59 months of age, underweight is estimated using Weight-for-Age z-score (WAZ). WAZ is calculated using ENA Software by comparing the observed weight of a selected child to the mean weight of children from the reference population for a given age. When using WAZ, the distribution of the sample is compared against the 2006 WHO reference population. The HAZ cut- offs are displayed in table 8 below. Global underweight is the sum of moderate and severe underweight.
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
CHRONIC ACUTE MALNUTRITION UNDERWEIGHT MALNUTRITION (WHZ) (WAZ) (HAZ) <-2 z-score and/or GLOBAL <-2 z-score <-2 z-score oedema <-2 z-score and ≥ -3 <-2 z-score and ≥ -3 <-2 z-score and ≥ -3 MODERATE z-score z-score z-score
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<-3 z-score and/or SEVERE <-3 z-score <-3 z-score oedema
Malnutrition as identified by WHZ, HAZ and WAZ have been classified by the WHO in terms of public health significance. These are presented in table 9 below. Table 9: WHO Classification for Severity of Malnutrition by Prevalence among Children Under Five40
GLOBAL GLOBAL ACUTE GLOBAL CHRONIC Severity MALNUTRITION UNDERWEIGHT Interpretation MALNUTRITION (WHZ) (WAZ) (HAZ) Critical / Very High ≥ 15% ≥ 40% ≥ 30% Emergency High ≥ 10% - <15% ≥ 30% - < 40% ≥ 20% - < 30% Serious
Medium ≥ 5% - < 10% ≥ 20% - < 30% ≥ 10% - < 20% Poor
Low < 5% < 20% < 10% Acceptable
The second anthropometric measure used to assess acute malnutrition is MUAC. In children 6- 59 months of age, MUAC is measured using a MUAC tape and children are categorized as moderate or severe based on the WHO established cut-offs displayed in table 10 below.
Table 10: WHO Cut-off Values for Anthropometric Measurements Using MUAC to Assess Moderate and Severe Acute Malnutrition
Severity MUAC (mm)
Severe Acute Malnutrition (SAM) <115 Moderate Acute Malnutrition (MAM) ≥ 115 and < 125 No Acute Malnutrition ≥ 125
40 WHO Cut-off Points and Summary Statistics http://www.who.int/nutgrowthdb/about/introduction/en/index5.html
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Table 11: IPC classification41 Acute Malnutrition by MUAC
Severity MUAC (mm)
Extreme critical >17% Critical 11.0-16.9% Alert-Serious 6-11% Acceptable <6%
2.5.3 Anaemia
Anaemia is a condition where the number of red blood cells and their oxygen carrying capacity are insufficient to meet the body’s physiological needs. Although anaemia can be influenced by many factors, including but not limited to age, gender, and elevation above sea level, as well as nutritional deficiencies (including folate, vitamin B, and vitamin A) it remains an important indicator of iron status. For this assessment, the haemoglobin content of finger prick whole blood samples from children 6-59 months were measured and evaluated per WHO recommendations (see tables 11 and 12 below). Table 12: WHO Cut-off Values for Prevalence of Anaemia based on Haemoglobin Measurement
Hb (g/dL) Severity
< 7.0 g/dL Severe ≥ 7.0 - <10.0 g/dL Moderate ≥ 10.0 - <11.0 g/dL Mild ≥ 11.0 g/dL No Anaemia
Table 13: WHO Classification of Public Health Significance of Anaemia and Iron Deficiency in Populations based on Haemoglobin Measurement42
Prevalence of Anaemia Category of Public Health Significance
41 IPC Acute Malnutrition Addendum 2016 42 WHO 2000 The Management of Nutrition in Major Emergencies Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 40
≥ 40% High 20.0 - 39.9% Medium 5.0 - 19.9% Low
2.6 Questionnaire, Training, and Supervision 2.6.1 Questionnaire
The survey questionnaire was developed by Action Against Hunger Bangladesh in close collaboration with the Nutrition Sector. The paper questionnaire was then translated into xls script by staff from CartONG. Data was collected on tablets (Lenovo) utilizing the KoboToolbox application. All teams carried a back-up tablet and hard copies of the questionnaire in the event a tablet failed at any point. The questionnaire had been translated from English into Bangla and back translated to test translation accuracy and cultural appropriateness. A field test was conducted in order to pilot the questionnaire and confirm team comprehension of the methodology. The questionnaires were administered in the local Chittagonian language, however, as the languages are very similar and the Rohingya language is rarely written. The full survey questionnaire is available in Annex 6, the cluster control form in Annex 7, anthropometric form for children 0-59 months in Annex 8, anthropometric form for women 15-49 years in Annex 9.
2.6.2 Training
All team members, supervisors, and support staff (35 persons) participated in a 5-day training from October 15th-19th, 2017. The training was conducted by Action Against Hunger with technical support from UNHCR, CartONG, and the CDC and it included a pre-test, classroom instruction, role-playing, small group work, a standardisation test, a field test, and a final post-test. The pre- test and post-tests were administered to gauge the level of comprehension prior to and upon completion of the training. During the training, survey team members were trained on the survey objectives, the SMART methodology, household selection, anthropometric measurements, haemoglobin measurement, questionnaire content, and mobile data collection. The training schedule is included in Annex 4. The quality of anthropometric measurement was assessed through a standardisation test. The standardisation test was conducted with ten healthy 6-59 month children and their accompanying caregivers not included in the assessment. All children were measured twice by each team member in order to ensure the accuracy and precision of measurement taking. Team measurer roles were designated based on the standardisation test results. The field test was conducted the day following the standardisation test in the Kutupalong Extension Zone.
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2.6.3 Supervision
Data collection was conducted from October 22nd-28th in Kutupalong Refugee Camp, Oct 29th- Nov 20th in the Makeshift Settlements, and Nov 20th-27th in Nayapara Refugee Camp. During data collection in the Makeshift Settlements, 96 clusters were surveyed. Each of the six teams surveyed 16 clusters and each cluster was finished in one day. Each team was composed of five team members, with the following designated roles:
Mapper – arrive the day prior to the survey team to identify cluster, segment if >200 households, create a complete list of <200 households, randomly select 14 households, and visit all 14 households to confirm accurate information Team leader and measurer - identified households, took anthropometric measurements of children 0-59 months, and gave additional support to the team Interviewer - conducted verbal interview, determined correct age of children 0-69 months Data entry - captured GPS coordinates, worked with interviewer to enter all collected data into the tablet during and after the interview Measure assistant - assisted in anthropometric measurements, measured woman’s MUAC, administered haemoglobin test The supervision of the survey teams during the assessment consisted of one Action Against Hunger survey manager, three UNICEF supervisors, and two CDC technical supervisors (one CDC technical supervisor during the Kutupalong Refugee Camp survey, and one CDC technical supervisor during the Nayapara Refugee Camp survey). The same three UNICEF supervisors were in the field for the entirety of the assessment. Survey teams were supervised on a daily basis, with two teams per UNICEF supervisor on a rotating basis in order to assure diversity of perspectives and information sharing. All data were uploaded daily in order to monitor the quantity and quality of data collected. During supervision:
Household selection was observed to assure compliance with the SMART methodology Precise measurement taking, proper completion of forms, accurate entry of data into tablets, and quality of interview were regularly monitored by supervisors Supervisors were prepared to confirm cases of oedema in case any were identified Teams were debriefed by supervisors on a daily basis, and team meetings were conducted by the survey manager every second evening in order to maintain an open feedback loop from survey teams to supervisors.
2.7 Data Management
Data were collected in two forms: a paper copy with anthropometric data for children 0-59 months and women 15-49 years, and an electronic copy of all collected data entered into tablets. The data were uploaded daily to a secure server, and paper copies were submitted to the survey manager each evening. Daily random checks of entered data were conducted by the survey manager in addition to a daily plausibility check of anthropometric data to assess and assure
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continued data quality. Supervisors and team leaders played an important role in assuring quality data collection at the field level. All Anthropometric and mortality data was analysed using ENA for SMART software (version 9th July 2015); SMART flags were used for exclusion of z-scores out of range values (-/+3 and +/- 3 from the observed survey mean). IYCF, Care Practices, WASH and Food Security data were analysed using Stata Version 13 and EPI info 7.2.10.
2.8 Ethical Considerations Prior to data collection the assessment team received written approval from Director of Institute of Public Health and Nutrition for the implementation of the assessment. This approval has been shared with MoH&FW representatives in Cox’s Bazar. All participants were asked to consent verbally after the objectives of the survey were clearly explained and before any data was collected. The households maintained their right to refuse the survey and women had the right to refuse partaking in the interview without a male family member present. All participation was voluntary. Children were always measured in the presence of a parent or older member of the family, and children that were ill (particularly if the illness appeared to be contagious) were not required to be measured. All data was securely stored during and after the assessment. Personal identifying information was not retained in the dataset. 2.9 A Note on Interpretation
The analyses contained in this report rely on data disaggregation to better understand the population subsets residing in the refugee settlements of Ukhia and Teknaf in Cox’s Bazar. The primary population subsets of interest are the following:
Registered refugees: defined as any Rohingya person who self-reported they were registered with UNHCR and acknowledged by the Government of Bangladesh, regardless of date of arrival or location of residence within the sampling frame (although most reside within Kutupalong and Nayapara Refugee Camps). Referred to as “Registered” or “Registered Households” in this report.
Unregistered refugees who self-reported arriving prior to the violence on August 25th, 2017: defined as any Rohingya person who is not formally registered with UNHCR, regardless of location of residence within the sampling frame, who arrived prior to August 25th, 2017. This subset is referred to as “Old Arrivals” in this report.
Unregistered refugees who self-reported arriving after the violence on August 25th, 2017: defined as any Rohingya person who is not formally registered with UNHCR, regardless of location of residence within the sampling frame, who arrived post August 25th, 2017. This subset is referred to as “New Arrivals” in this report. Most data presented in this report are disaggregated by the above population subsets. Where a subset sample is very small and does not contribute to a robust interpretation it is included in the analyses of “All” but excluded from disaggregated analyses. For example, an analysis of Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 43
“Registered Refugees” compared to “New Arrivals” in Kutupalong Refugee Camp which does not examine “Old Arrivals”. Where a sample isn’t large enough to render a reliable disaggregation (<30 observations, in adherence with the Central Limit Theorem) it is excluded with the note “Inadequate sample size for disaggregation”. The three surveys are abbreviated in subheadings and titles for efficiency and to help orient the reader within the report. Kutupalong Refugee Camp is shortened to “KTP”, the Makeshift Settlements to “MS”, and Nayapara Refugee Camp to “NYP”.
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RESULTS Kutupalong Refugee Camp October 22nd - 28th 2017
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3. RESULTS 3.1 Kutupalong Refugee Camp 3.1.1 Data Quality
In total, among the 405 households surveyed in Kutupalong Refugee Camp, the teams attempted to survey 313 children aged 6-59 months. 41 children were not present at the time of interview and were not located after revisiting, 2 children were ill at the time of the interview and were therefore not measured (non-measurement data, however, were collected). The height data from 1 child was excluded from the analyses per WHO flags, which contributed to the overall percentage of flagged data of 0.4%, well below the SMART methodology recommendation of less than 5%. The overall anthropometric analysis utilizes the data from 269 children. In terms of data quantity, a sufficient number of households and children were surveyed. According to the SMART methodology, a minimum of 80% of the sample size must be achieved to ensure data quality. For this survey, 116% of households and 133% of children 6-59 months were surveyed (see table 13 below), well above the SMART methodology cut-off. However, in general the number of households surveyed should not exceed the planned household sample size. In this case, after two days of data collection it was apparent that new arrivals were being rapidly shifted out of Kutupalong Refugee Camp into the Makeshift Settlements. The sample size was increased mid data collection using SRS, which is consistent with the methodology and enabled the survey to achieve an adequate sample size. In total, the survey teams surveyed 405 households of 561 attempted, equaling a non-response rate (NRR) of 28%.
Table 14: KTP Households and Children 6-59 months Planned vs. Surveyed
Percentage Planned Children 6-59 Percentage Planned Households Surveyed / Children 6-59 Months Surveyed / Households Surveyed Planned Months Surveyed Planned 349 405 116%* 202 269 133% *Increased sample size mid data collection using SRS in response to high rates of household absence due to population movements The standard deviation (SD) of WHZ (See table 14 below) was 1.11, the SD of HAZ was 1.11, and the SD of WAZ was 1.02, all three of which fall within the normal range of 0.8 and 1.2. This indicates an adequate distribution of data around the mean and data of good quality. The WHZ SD was considered “good” by the ENA Plausibility score (see table 15 below). Other statistical tests administered to test the distribution of the sample included:
Shapiro-Wilk test for normal (Guassian) distribution of the data, which concluded WHZ (p=0.190), HAZ (p=0.140), and WAZ (p=0.104) were all normally distributed. The Skewness coefficient, which concluded there may be a slight overrepresentation of malnutrition in the population (-0.23). Considered “good” by the ENA Plausibility score. The Kurtosis coefficient, which concluded there were slightly smaller “tails” of data in the distribution than expected (-0.21). Considered “good” by the ENA Plausibility score.
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Table 15: KTP Median z-score ± Standard Deviation for WHZ, HAZ, and WAZ
Unavailable Excluded z-scores Index N Median z-score ± SD z-scores (SMART flags) WHZ (6-59 months) 268 -1.28 ± 1.11 0 1 HAZ (6-59 months) 267 -1.79 ± 1.11 0 2 WAZ (6-59 months) 269 -1.89 ± 1.02 0 0
The sex-ratio between boys and girls 6-59 months of age was satisfactory at 1.22 boys/girls (p=0.100) indicating that statistically boys and girls are equally represented. Still, when examining the data in table 17 there appears to be a slight overrepresentation of boys from 30-41 months (sex-ratio=1.43 boys/girls), however this did not affect the data quality. Overall, the distribution of sex was considered “excellent” by the ENA Plausibility score. Concerning age, among children 6-59 months included in the sample, 65% had exact birthdays as confirmed by supportive documentation. The age-ratio between the categories of 6-29 months and 30-59 months is satisfactory at 0.81 (p=0.660) as this falls near the desired value of 0.85 as recommended by the SMART methodology. Overall, the distribution of age was considered “excellent” by the ENA Plausibility score. Digit preference scores for weight, height, and MUAC were all considered “excellent” by the ENA Plausibility score with the scores of 6, 7, and 7, respectively. The overall data quality score was 7%, which is considered a survey of “excellent” quality by the ENA Plausibility score. The Kutupalong Plausibility report is presented in Annex 12.
Table 16: KTP Overall Data Quality per ENA Plausibility Check
Criteria SD Flagged Sex-ratio Age-ratio Digit Pref. Weight
Observed 1.11 0.4% (p=0.100) (p=0.660) 6 Desired 0.8-1.2 < 5% (p>0.05) (p>0.05) < 13 Score Good Excellent Excellent Excellent Excellent
Criteria Digit Pref. Height Digit Pref. MUAC Skewness Kurtosis Overall Score
Observed 7 7 -0.23 -0.21 7 Desired < 13 < 13 < ± 0.6 < ± 0.6 < 15 Score Excellent Excellent Good Good Excellent
Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 47
3.1.2 Demography and Mortality
During the planning stages of the assessment, the average household size was estimated to be 4.8 and the proportion of children less than five years in the population was estimated to be 16.5%. Following the analysis of the data, the average household size was determined to be 5.4 and the proportion of children less than five years was found to be 16.1% for the sample surveyed (see table 16 below). Further disaggregation demonstrates that although the registered refugee households have a larger average household size than the new arrivals (5.9 vs 4.7), they have on average fewer pregnant and lactating women (6.9% vs. 10.9%) and fewer children under five years (13.3% vs. 21.6%). Some of these demographic differences may be influenced by the availability of family planning services within Kutupalong Refugee Camp.
Table 17: Demographics of Kutupalong Refugee Camp
All Households Registered New Arrivals Population Subset N % 95% CI N % 95% CI N % 95% CI All Household Members* 2,202 100.0 - 1,414 64.2 - 741 33.7 - Average HH size, mean (SD) 5.4 (2.7) 5.9 (2.8) 4.7 (2.3) All, <5 years 355 16.1 [14.6-17.7] 188 13.3 [11.6-15.2] 160 21.6 [18.8-24.7] All, 5-10 years 400 18.2 [16.6-19.8] 267 18.9 [16.9-21.0] 123 16.6 [14.1-19.5] All, 11-17 years 434 19.7 [18.1-21.4] 304 21.5 [19.4-23.7] 119 16.1 [13.6-19.0] All, 18-59 years 945 42.9 [40.9-45.0] 619 43.8 [41.2-46.4] 309 41.7 [38.2-45.3] All, ≥60 years 68 3.1 [2.4-3.9] 36 2.5 [1.8-3.5] 30 4.1 [2.8-5.7] Female 1,106 50.2 [48.1-52.3] 707 50.4 [47.8-53.0] 367 49.5 [45.9-53.1] Women, 15-49 Years 536 24.3 [22.6-26.2] 351 24.8 [22.6-26.2] 173 23.4 [20.4-26.5] Pregnant and lactating women 180 8.2 [7.1-9.4] 98 6.9 [5.7-8.3] 74 10.9 [8.9-13.4] Pregnant women 44 2.0 [1.5-2.7] 24 1.7 [1.1-2.5] 81 2.6 [1.6-4.0] Lactating women 136 6.2 [5.2-7.3] 74 5.2 [4.1-6.5] 62 8.4 [6.6-10.6] Number of days to arrive from Question not asked of registered households 8.3 days (5.9) Myanmar, mean (SD) *Demographics include all current household members, regardless of presence at time of interview
The distribution of age of children 6-59 months demonstrates equal representation of children 6- 23 months and children 24-59 months (see Figure 3). The distribution shows one distinct peak at 30 months and a slight peak at 38 months. This peak at 30 months is likely influencing the higher ratio of boys to girls (1.4) reported in table 17.
Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 48
Figure 3: KTP Age Distribution of Children 6-59 months
16
14
12
10
8
6
NumberChildren of 4
2
0 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 Age in Months
Table 18: KTP Distribution of Age and Sex Children 6-59 months
Age Category Boys Girls Total Ratio (months) boy : girl N % N % N % 6-17 39 57.4 29 42.6 68 25.3 1.3 18-29 27 51.9 25 48.1 52 19.3 1.1 30-41 39 58.2 28 41.8 67 24.9 1.4 42-53 30 52.6 27 47.4 57 21.2 1.1 54-59 13 52.0 12 48.0 25 9.3 1.1 Total 148 55.0 121 45.0 269 100.0 1.2
Mortality data was collected in Kutupalong Refugee Camp, however due to errors identified and corrected before beginning data collection in makeshift and Nayapara surveys, was not analysed or reported.
Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 49
3.1.3 Prevalence of Acute Malnutrition by WHZ
The prevalence of acute malnutrition by WHZ was based on the analysis of 268 children, after the exclusion of one child per SMART flags. The distribution curve of figure 4 below illustrates the distribution of the WHZ for the surveyed sample (the red curve) in comparison to the WHO 2006 reference population (the green curve). There were no identified cases of ooedema in Kutupalong Refugee Camp. The WHZ mean is -1.28 with a standard deviation of ± 1.11 (the standard deviation falls between 0.8 and 1.2 indicating data of good quality). The red curve representing the surveyed population is shifted to the left of the reference population, demonstrating that the acute malnutrition status of the surveyed population is inferior. The slight spread of the surveyed population curve may be attributable to small measurement errors and or a slight heterogeneity of the population. The prevalence of global and severe acute malnutrition per WHZ are presented in table 18 below:
Figure 4: KTP Distribution of the WHZ of the Sample Compared to the WHO 2006 Reference
The prevalence of GAM among children 6-59 months in Kutupalong Refugee Camp per WHZ was 24.3% [19.5-29.7] well above the WHO emergency cut-off of 15%, as was the lower confidence interval of 19.5% (see table 18 below). This prevalence was higher among new arrivals than registered refugees (27.3% vs. 21.8%). This suggests that new arrivals may be more susceptible to suffering from acute malnutrition, yet analysis did not show a statistically significant association between arrival subset and prevalence of GAM. The prevalence of MAM in Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 50
Kutupalong Refugee Camp was 16.8% [12.8-21.7] and was also higher among new arrivals than registered refugees (20.7% vs. 13.6%) but this was not found to be statistically significant. The prevalence of SAM in Kutupalong Refugee Camp was 7.5% [4.9-11.2] which, as opposed to the GAM and MAM prevalences, was actually higher in the registered refugees than the new arrivals (8.2% vs. 6.6%) but this was not found to be statistically significant. Upon disaggregating the prevalence of GAM into age categories, children 6-23 months had a higher prevalence than children 24-59 months (30.7% vs. 21.1%) but this was not found to be statistically significant. The overall ratio of GAM to SAM cases was also higher than normally expected in emergencies (24.3/7.5 = 3.24), while given the reported mean and SD, one would expect a ratio closer to 4.0 per the SMART Methodology43. Results from all 2x2 statistical analyses for Kutupalong Refugee Camp are available in Annex 1.
Table 19: KTP Prevalence of Acute Malnutrition per WHZ and/or Oedema, WHO Reference 2006
Moderate Acute Severe Acute Global Acute Malnutrition Children 6-59 months N Malnutrition Malnutrition N % 95% CI N % 95% CI N % 95% CI All 268 65 24.3 [19.5-29.7] 45 16.8 [12.8-21.7] 20 7.5 [4.9-11.2] Registered Refugees 147 32 21.8 [15.9-29.1] 20 13.6 [9.0-20.1] 12 8.2 [4.7-13.7] New Arrivals 121 33 27.3 [20.1-35.8] 25 20.7 [14.4-28.7] 8 6.6 [3.4-12.5] Children 6-23 months 88 27 30.7 [22.0-41.0] 17 19.3 [12.4-28.8] 10 11.4 [6.3-19.7] Children 24-59 months 180 38 21.1 [15.8-27.6] 28 15.6 [11.0-21.6] 10 5.6 [3.0-9.9]
Regarding acute malnutrition by WHZ among children 6-59 months as disaggregated by sex, the prevalence of acute malnutrition was higher for boys than girls in Kutupalong Refugee Camp; with GAM (27.9% vs. 19.8%), MAM (19.0% vs. 14.0%), and SAM (8.8% vs. 5.8%) (see table 19 below). This may suggest that the boys 6-59 months in Kutupalong Refugee Camp were more vulnerable to acute malnutrition than the girls, although analysis did not show a statistically significant association between sex and acute malnutrition. Table 20: KTP Prevalence of Acute Malnutrition by Sex per WHZ and/or Oedema, WHO Reference 2006
Moderate Acute Severe Acute Global Acute Malnutrition Children 6-59 months Malnutrition Malnutrition N % 95% CI N % 95% CI N % 95% CI All 65 24.3 [19.5-29.7] 45 16.8 [12.8-21.7] 20 7.5 [4.9-11.2] (n=268) Boys 41 27.9 [21.3-35.6] 28 19.0 [13.5-26.2] 13 8.8 [5.2-14.5] (n=147)
43 ACF Canada (2015) The SMART Plausibility Check for Anthropometry Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 51
Girls 24 19.8 [13.7-27.8] 17 14.0 [9.0-21.4] 7 5.8 [2.8-11.5] (n=121)
Regarding acute malnutrition by WHZ among children 6-59 months as disaggregated by age category, the prevalence of SAM was highest among the 6-17 month category (13.4%) and lowest among the 54-59 months category (7.0%) (see table 20 below). The prevalence of MAM was also highest among the 6-17 month category (20.9%), however, the age category with the lowest MAM prevalence was the 30-41 month category (11.9%). Overall the age category with the highest percentage of children who were not acutely malnourished was the 18-29 month category (80.8%).
Table 21: KTP Prevalence of Acute Malnutrition by Age per WHZ and/or Oedema, WHO Reference 2006
Severe Acute Moderate Acute Not Acutely Edema Malnourished Malnutrition Malnourished Age (months) Total N % N % N % N % 6-17 67 9 13.4 14 20.9 44 65.7 0 0.0 18-29 52 1 1.9 9 17.3 42 80.8 0 0.0 30-41 67 5 7.5 8 11.9 54 80.6 0 0.0 42-53 57 4 7.0 9 15.8 44 77.2 0 0.0 54-59 25 1 4.0 5 20.0 19 76.0 0 0.0 Total 268 20 7.5 45 16.8 203 75.7 0 0.0
3.1.4 Prevalence of Acute Malnutrition by MUAC
The prevalence of acute malnutrition in children 6-59 per MUAC was much lower than the prevalence per WHZ, and this is discussed in greater detail in section 3.1.5. The prevalence of GAM in Kutupalong Refugee Camp per MUAC was 5.9% [3.7-9.4] which according to the IPC Classification falls under “acceptable”. (see table 21 below). The prevalence of GAM per MUAC was very similar for registered refugees and new arrivals (6.1% vs. 5.8%), a difference which was not statistically significant. The prevalence of MAM in Kutupalong Refugee Camp per MUAC was 5.2% [3.1-8.5], but was slightly higher for registered refugees than new arrivals (6.1% vs. 4.1%). The prevalence of SAM in Kutupalong Refugee Camp per MUAC was 0.7% [0.2-2.7], with a prevalence of 1.7% for new arrivals and no identified SAM cases among registered refugees. When disaggregated by age category, children 6-23 months had a much higher prevalence of GAM per MUAC than children 24-59 months (14.8% vs. 1.7%) and additional statistical analysis showed a significant association between age 6-23 months and acute malnutrition per MUAC (OR 10.3 [95% CI 2.85-37.14] and p=0.001). This suggests that children 6-23 months were more than ten times as likely to suffer from acute malnutrition than children 24-59 months as determined by MUAC.
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Table 22: KTP Prevalence of Acute Malnutrition by MUAC
Global Acute Malnutrition Moderate Acute Severe Acute Children 6-59 months N by MUAC Malnutrition by MUAC Malnutrition by MUAC N % 95% CI N % 95% CI N % 95% CI All 269 16 5.9 [3.7-9.4] 14 5.2 [3.1-8.5] 2 0.7 [0.2-2.7] Registered Refugees 148 9 6.1 [3.2-11.2] 9 6.1 [3.2-11.2] 0 0.0 - New Arrivals 121 7 5.8 [2.8-11.5] 5 4.1 [1.8-9.3] 2 1.7 [0.5-5.8] Children 6-23 months 88 13 14.8 [8.8-23.7] 11 12.5 [7.1-21.0] 2 2.3 [0.6-7.9] Children 24-59 months 181 3 1.7 [0.6-4.8] 3 1.7 [0.6-4.8] 0 0.0 -
The prevalences of acute malnutrition per MUAC as disaggregated by age category (see figure 5 below) demonstrate that the highest prevalence of GAM, MAM, and SAM fall within the youngest age category of 6-17 months. The only two SAM cases per MUAC fell in this category, giving it a SAM prevalence of 2.9%, and a MAM prevalence of 16.2% (overall GAM prevalence of 19.1%). In contrast, no cases of acute malnutrition were identified in the age categories of 18-29 months and 54-59 months by MUAC.
Figure 5: KTP Prevalence of Acute Malnutrition by Age per MUAC
Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 53
3.1.5 Prevalence of Acute Malnutrition WHZ vs. MUAC
The prevalence of acute malnutrition among children 6-59 months was notably different as identified by WHZ and MUAC in Kutupalong Refugee Camp. The prevalence of GAM was four times higher per WHZ (24.3% vs. 5.9%), the prevalence of MAM was more than three times higher per WHZ (16.8% vs. 5.2%), and the prevalence of SAM was ten times higher per WHZ (7.5% vs. 0.7%). As is demonstrated in figure 6 below, overall, 65 cases of GAM were identified per WHZ and 16 cases of GAM were identified per MUAC. Of the 65 cases, 76.9% (50) of them were not identified as GAM according to MUAC. When disaggregated by age category, the difference in GAM per WHZ of children 6-23 months vs. 24-59 months (30.7% vs. 21.1%) was not statistically significant. While the difference in GAM per MUAC of children 6-23 months vs. 24-59 months (14.8% vs. 1.7%) was statistically significant. This disparity between numbers of identified cases is likely influenced by MUAC’s known bias towards identifying acute malnutrition in younger and small children44.
Figure 6: KTP Prevalence of Acute Malnutrition WHZ vs. MUAC
44 Briend A, Golden MH, Grellety Y, Prudhon C, Hailey P. (1995) Use of mid-upper-arm circumference for nutritional screening of refugees Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 54
3.1.6 Low MUAC in Women
Low MUAC in women was defined as a mid-upper arm circumference below 210mm for the purposes of this assessment. The results from Kutupalong Refugee Camp indicated a prevalence of low MUAC of women 15-49 years of 7.3% [5.22-10.1]. This prevalence was higher among new arrival women than registered women (13.4% vs. 4.8%) (see table 22 below). Analysis showed a statistically significant association between arrival subset and low MUAC in women (OR 3.06 [95% CI 1.49-6.28]) (p=0.003). This suggests that new arrival women were three times as likely to have low MUAC than registered refugee women, and were more susceptible to suffering from acute malnutrition. Low MUAC for all pregnant and lactating women in the sample regardless of population subset was 9.9%, but this was not statistically significant from the rest of the women in the sample. The average MUAC for the women in Kutupalong Refugee Camp at the time of the survey was 257mm. These findings suggest that women 15-49 years who arrived after August 25th, 2017 and those who are pregnant or lactating are more vulnerable to acute malnutrition. Table 23: KTP Low MUAC in Women 15-49 Years
MUAC <210mm Women 15-49 years N N % [95% CI] All 453 33 7.3% [5.2-10.1] Registered Refugees 311 15 4.8% [2.9-7.9] New Arrivals 134 18 13.4% [8.6-20.4] PLW 161 16 9.9% [6.2-15.6]
Women 15-49 years N Mean MUAC mm (SD)
All 453 257 (36.40)
3.1.7 Low MUAC in Infants
The cut off for low MUAC for infants 0-5 months was assessed at <115mm, <110mm, and <105mm for this assessment (see table 23 below). Within Kutupalong Refugee Camp it was found that among the 38 children measured, 42.1% of infants 0-5 months were <115mm, 31.6% were <110mm, and 21.1% were <105mm. The mean MUAC measurement of infants 0-5 months was 117mm.
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Table 24: KTP Low MUAC in Infants 0-5 Months
Infants 0-5 months Low MUAC (n=38) N % [95% CI] MUAC <115mm 16 42.1 [27.0-58.8] MUAC <110mm 12 31.6 [18.4-48.6] MUAC <105mm 8 21.1 [10.5-37.6] Infants 0-5 months N Mean MUAC (SD) All 38 118 mm (15.51)
3.1.8 Prevalence of Chronic Malnutrition
The prevalence of chronic malnutrition among children 6-59 months in Kutupalong Refugee Camp was 43.4% [37.6-49.4], above the WHO cut-off of 40% indicating it is of critical public health significance (see table 24 below). This global prevalence was higher among new arrivals than registered refugees (47.5% vs. 40.4%) but this was not found to be statistically significant. The prevalence of moderate chronic malnutrition was also somewhat higher among new arrivals than registered refugees (33.3% vs. 26.0%), while severe chronic malnutrition was very similar (14.2% vs. 14.4%). These persistently high prevalence of chronic malnutrition speak to the long-term malnutrition context in both Rakhine State as well as Kutupalong Refugee Camp.
Table 25: KTP Prevalence of Chronic Malnutrition by HAZ, WHO Reference 2006
Global Chronic Moderate Chronic Severe Chronic Children 6-59 months N Malnutrition Malnutrition Malnutrition N % 95% CI N % 95% CI N % 95% CI All 267 116 43.4 [37.6-49.4] 77 28.8 [23.7-34.5] 39 14.6 [10.9-19.3] Registered Refugees 146 59 40.4 [32.8-48.5] 38 26.0 [19.6-33.7] 21 14.4 [9.6-21.0] New Arrivals 120 57 47.5 [38.8-56.4] 40 33.3 [25.5-42.2] 17 14.2 [9.0-21.5]
3.1.9 Prevalence of Underweight
The prevalence of underweight among children 6-59 months in Kutupalong Refugee Camp was 45.0% [39.1-51.0], well above the WHO cut-off of 30%, indicating it is of critical public health significance (see table 25 below). This prevalence was slightly higher among new arrivals than registered refugees (47.1% vs. 43.2%) as was moderate underweight (32.2% vs. 28.4%) a difference which was not statistically significant,. The prevalence of severe underweight was 14.9% for both new arrivals and registered refugees. As this malnutrition indicator acts as a Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 56
composite score between acute and chronic malnutrition, it speaks to both the long-term and short-term effects of malnutrition on the population in Rakhine State and within Kutupalong Refugee Camp.
Table 26: KTP Prevalence of Underweight by WAZ, WHO Reference 2006
Global Underweight Moderate Underweight Severe Underweight Children 6-59 months N N % 95% CI N % 95% CI N % 95% CI All 269 121 45.0 [39.1-51.0] 81 30.1 [24.9-35.8] 40 14.9 [11.1-19.6] Registered Refugees 148 64 43.2 [35.5-51.3] 42 28.4 [21.7-36.1] 22 14.9 [10.0-21.5] New Arrivals 121 47 47.1 [38.4-56.0] 39 32.2 [24.6-41.0] 18 14.9 [9.6-22.3]
3.1.10 Prevalence of Anaemia
Anaemia was measured among all children 6-59 months once consent was granted. The overall prevalence of anaemia was 47.9% [41.9-54.0] within Kutupalong Refugee Camp, well above the WHO cut-off of 40% for a significant public health concern (see table 26 below). This prevalence was somewhat higher among new arrivals than registered refugees (51.3% vs. 44.2%) a difference which was not statistically significant. When the sample was disaggregated by age, the prevalence of anaemia was found to be higher among children 6-23 months than children 24- 59 months (57.0% vs. 43.6%). Analysis showed a statistically significant association between age category and anaemia (OR 1.71 [95% CI 1.02-2.88]) (p=0.049). No cases of severe anaemia were identified. Overall, these findings indicate that nearly half of the children 6-59 months were suffering from anaemia in Kutupalong Refugee Camp, and children under two years were 1.71 times more likely to suffer from anaemia than children 12-59 months and new arrivals potentially more susceptible to anaemia than registered refugees.
Table 27: KTP Prevalence of Anaemia in Children 6-59 months per WHO
Registered New Arrivals All Children 6-59 months (n=147) (n=113) (n=265) N % 95% CI N % 95% CI N % 95% CI Any Anaemia 127 47.9 [41.9-54.0] 65 44.2 [36.4-52.4] 58 51.3 [42.1-60.5] (Hb<11.0 g/dL) Mild Anaemia 81 30.6 [25.3-36.4] 43 29.3 [22.4-37.2] 35 31.0 [23.1-40.1] (Hb 10.0 to <11.0 g/dL) Moderate Anaemia 46 17.4 [13.2-22.4] 22 15.0 [10.0-21.7] 23 20.4 [13.9-28.8] (Hb 7.0 to <10.0 g/dL) Severe Anaemia 0 0.0 - 0 0.0 - 0 0.0 - (Hb <7.0 g/dL) Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 57
Any Anaemia
49 57.0 [46.3-67.1] (Hb<11.0 g/dL)
23 23
- Mild Anaemia 26 30.2 [21.4-40.8] (n=86) (Hb 10.0 to <11.0 g/dL) Moderate Anaemia 23 26.7 [18.4-37.1] (Hb 7.0 to <10.0 g/dL)
Children 6 Children
months Severe Anaemia 0 0.0 - (Hb(n= <7.0 g/dL) Inadequate sample size for disaggregation Any Anaemia
) 78 43.6 [36.5-51.0] (Hb<11.0 g/dL)
59 - Mild Anaemia 55 30.7 [24.4-37.9]
(n=179 (Hb 10.0 to <11.0 g/dL) Moderate Anaemia 23 12.9 [8.7-18.6] (Hb 7.0 to <10.0 g/dL)
Children 24 Children
months Severe Anaemia 0 0.0 - (Hb(n= <7.0 g/dL)
3.1.11 Prevalence of Morbidity
The prevalence of diarrhoea among children 6-59 months per two-week recall was 40.5% [35.1-46.1] within Kutupalong Refugee Camp (see table 27 below). This was statistically higher (p=0.0002) among new arrivals than registered refugees (51.4% vs. 30.4%). Analysis showed a statistically significant association between arrival subset and prevalence of diarrhoea (OR 2.41 [95% CI 1.51-3.84]) (p=0.001). This suggests that new arrival children 6-59 months were more susceptible to suffering from diarrhoeal episodes when compared with registered population 6-59 months. The prevalence was also somewhat higher for children 6-23 months than children 24-59 months (46.5% vs. 37.5%) but this was not found to be statistically significant. The prevalence of acute respiratory infection with a fever among children 6-59 months per two-week recall was 55.7% [50.1-61.1] within Kutupalong Refugee Camp. The rates were higher among new arrivals than registered refugees (64.2% vs. 47.8%). Analysis showed a statistically significant association between arrival subset and ARI (OR 1.96 [95% CI 1.24-3.09]) (p=0.004). This suggests that new arrival children 6-59 months were nearly twice as likely to be suffering from ARI when compared with registered population 6-59 months. The prevalence of ARI was somewhat higher for children 6-23 months than children 24-59 months (59.4% vs. 53.9%), however this was not statistically significant. The prevalence of fever without cough among children 6-59 months per two-week recall was 37.5% [32.3-43.1] within Kutupalong Refugee Camp. The rates were somewhat higher among new arrivals than registered refugees (39.9% vs. 35.4%) %), a difference which was not statistically significant, and somewhat higher in children 6-23 months than children 24-59 months (42.6% vs. 35.1%), a difference which was also not statistically significant. The morbidity indicators suggest that new arrival children 6-59 months are more susceptible to diarrhoeal disease and acute respiratory infection, and that children under two years may have been more vulnerable to communicable diseases in Kutupalong Refugee Camp.
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Table 28: KTP Two-week Prevalence of Diarrhoea, Cough, and Fever in Children 6-9 Months
All Registered Refugees New Arrivals Children 6-59 months (n=309) (n=161) (n=148) N % 95% CI N % 95% CI N % 95% CI
Diarrhoea 125 40.5 [35.1-46.1] 49 30.4 [23.8-38.0] 76 51.4 [43.3-59.3]
Children 6-23 months (n=101) 47 46.5 [37.0-56.3] Inadequate sample size for disaggregation Children 24-59 months (n=208) 78 37.5 [31.2-44.3] Acute Respiratory Infection with 172 55.7 [50.1-61.1] 77 47.8 [40.2-55.6] 95 64.2 [56.1-71.5] Fever Children 6-23 months (n=101) 60 59.4 [49.5-67.6] Inadequate sample size for disaggregation Children 24-59 months (n=208) 112 53.9 [47.0-60.6]
Fever without Cough 116 37.5 [32.3-43.1] 57 35.4 [28.4-43.1] 59 39.9 [32.3-48.0]
Children 6-23 months (n=101) 43 42.6 [33.3-52.4] Inadequate sample size for disaggregation Children 24-59 months (n=208) 73 35.1 [29.0-41.9]
3.1.12 IYCF Indicators
It is important to note when interpreting the IYCF indicators from this assessment, that the survey sample sizes were calculated based on anticipated prevalences of GAM for children 6-59 months. The sample size and precision were not calculated for IYCF indicators, leading to lower precision and larger confidence intervals for some of the results. The IYCF results of this survey should therefore be interpreted with caution and in consideration of the width of their associated confidence intervals. Within Kutupalong Refugee Camp, 97.9% [93.5-99.3] of children 0-23 months had been breastfed at some point prior to the survey date, and this rate was very similar among new arrivals and registered refugees (100.0% vs. 96.4%) (see table 28 below). The timely initiation of breastfeeding is defined as “the provision of mother’s breast milk to infants within one hour of birth” per the WHO. Of the caregivers interviewed in Kutupalong Refugee Camp with a child 0-23 months, 69.6% [61.3-76.7] reported that breastfeeding had been initiated within one hour of birth, 22.5% between one and 24 hours after birth, and 5.8% more than 24 hours after birth. The prevalence of timely initiation of breastfeeding was higher among registered refugees than new arrivals (86.7% vs. 48.4%) a difference which was likely influenced by the accessibility of supportive IYCF services within the camp.
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Of the caregivers interviewed with an infant 0-5 months, 82.1% [66.0-91.5] reported exclusively breastfeeding the infant on the day preceding the survey. Of the caregivers interviewed with a child 12-15 months, 100.0% reported continued breastfeeding of the child until one year of age. Of the caregivers interviewed with a child 20-23 months, 75.0% [39.3-93.3] reported continued breastfeeding of the child until two years of age. Of the caregivers interviewed with an infant 6-8 months, 47.6% [26.3-69.8] reported the infant was being fed complementary foods. This indictor should be interpreted with caution, however, as it does not speak to whether or not introduction of complementary foods began before 6 months. Minimum dietary diversity was reported as 9.8% [5.3-11.7] among children 6-23 months. This was higher among registered refugees than new arrivals (14.8% vs. 4.3%). Minimum meal frequency was reported as 53.9% [44.1-63.5] among children 6-23 months. This was higher among registered refugees than new arrivals (64.8% vs. 42.6%). Minimum acceptable diet was reported as 8.8% [4.6-16.2] among children 6-23 months. This was higher among registered refugees than new arrivals (13.0% vs. 4.3%).
Table 29: KTP Infant and Young Child Feeding Indicators
Infants and Young Children All Registered New Arrivals 0-23 months (n=141) N % 95% CI N % 95% CI N % 95% CI Ever breastfed 138 97.9 [93.5-99.3] 75 96.2 [88.6-98.8] 62 100.0 - Infants 0-23 months (n=141) Timely initiation of breastfeeding 96 69.6 [61.3-76.7] 65 86.7 [76.8-92.7] 30 48.4 [36.2-60.8] Infants 0-23 months (n=138) Exclusive breastfeeding 32 82.1 [66.0-91.5] Infants 0-5 months (n=39) Cont. breastfeeding at one year 31 100.0 - Children 12-15 months (n=31) Cont. breastfeeding at two Inadequate sample size for disaggregation years* 9 75.0 [39.3-93.3] Children 20-23 months (n=12) Intro. of complementary Foods* 10 47.6 [26.3-69.8] Infants 6-8 months (n=21) Minimum dietary diversity 10 9.8 [5.3-11.7] 8 14.8 [7.5-27.2] 2 4.3 [1.0-15.8] Children 6-23 months (n=102) Minimum meal frequency 55 53.9 [44.1-63.5] 35 64.8 [51.1-76.5] 20 42.6 [29.2-57.2] Children 6-23 months (n=102) Minimum acceptable diet 9 8.8 [4.6-16.2] 7 13.0 [6.2-25.0] 2 4.3 [1.0-15.8] Children 6-23 months (n=102) Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 60
*Results should be interpreted with caution, as the sample size is less than 30
Overall, children 0-23 months scored poorly on all IYCF indicators. Figure 7 below shows the frequency of liquids or beverages consumed during the 24 hours preceeding the survey for two age groups: infants 0-5 months and children 6-23 months. This indicator aimed to look at what could be displacing breastmilk. Among infants 0-5 months, an age where exclusive breastfeeding is crucial for optimal health, the beverages most frequently consumed were water (7.7%) and milk (7.7%). Among children 6-23 months, an age where complementary foods in addition to continued breastfeeding are advised, the frequency of beverages consumed was identical except for water, which 92.2% of children 6-23 months had reportedly consumed during the 24-hour recall. A complete list of the beverages in each category is available in Annex 6. Additionally, there is a common practice in parts of Myanmar and Bangladesh where a newborn is fed a sweet beverage (sweetened with sugar or honey) just after birth. It is thought that giving the child such a drink will cause the child to speak sweetly later in life. Caregivers were specifically asked about this practice for children 0-23 months. In Kutupalong Refugee Camp, 2.3% of caregivers reported having given their newborn a sweet drink shortly after birth.
Figure 7: KTP 24-Hour Recall of Consumption of Liquids in Children 6-23 Months
24-Hour Recall Consumption of Liquids
Infants 0-5 months (n=136) Children 6-23 months (n=361)
Other Tea or Coffee 9.6% Thin Porridge 31.9% Yogurt Broth Juice 8.1% Milk 13.6% 3.7% Infant Formula 1.9% 37.8% Water 96.1% 0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0% 90.0% 100.0%
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Figure 8 below shows what categories of food were being consumed at the highest frequency. The most category most frequently consumed was “grain” at 63.0% and the category least frequently consumed was “legume” at 2.0%. The high rate of grain consumption was consistent with the general food distributions WFP had been providing to the population consisting mainly of rice. The “meat/fish” category was the second most frequently consumed food group at 27.5%, which was likely influenced by the fishing livelihoods in the region. In almost every food category, fewer of the new arrival children than the registered refugee children 6-23 months were consuming these foods. The only exception was for vitamin A rich fruits and vegetables (19.2% vs. 18.5%). A complete list of the food items in each category is available in Annex 6.
Figure 8: KTP 24-Hour Recall of Food Group Consumption in Children 6-23 Months
24-hour Recall Consumption of Food Groups Percentage of Children 6-23 months 70% 63.0% 60% 57.8% 51.1% 50%
40% 33.3% 33.3% 27.5% 30% 25.9% 23.5% 21.3% 18.5% 18.6% 19.2% 17.7% 20% 13.0% 8.8% 10.6% 10% 6.4% 3.7% 4.3% 2.0% 0.0% 0% Grain Legume Dairy Meat/Fish Egg VitA Fruit Veg Other Fruit Veg All Registered New Arrivals
3.1.13 Receipt of Services
Measles vaccination coverage was assessed by documentation or household recall. Among children 6-59 months, the measles vaccination coverage rate was 55.0% [49.4-60.5] within Kutupalong Refugee Camp (see table 29 below). This rate was much higher among registered refugees than new arrivals (73.3% vs. 34.8%). This difference was likely due to a lack of health services in Rakhine State. In addition, the most recent measles vaccination campaign prior to the survey was conducted in mid-September 2017, and many new arrivals migrated to Kutupalong Refugee Camp after that period. Meanwhile, the rate of measles immunisations evidenced by a vaccination card was only 18.5% [14.5-23.2] and was much higher among registered refugees than new arrivals (34.8% vs. 0.7%). The near zero-rate of measles vaccinations as evidenced by
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vaccination card is not surprising when considering the haste with which many households fled Rakhine State. OCV coverage was assessed by household recall. Among all persons over one year of age, the OCV rate was determined to be 78.1% [69.7-79.1], notably higher among registered refugees than new arrivals (92.7% vs. 49.4%). This disparity by population subset was consistent for children 12-59 months (94.9% vs. 49.3%) as well as all persons >5 years (92.6% vs. 49.6%). The receipt of GFD indicator is defined as any household from which a household member has received at least one bag of rice since August 25th, 2017. Per this operational definition, 52.5% [45.7-53.1] of new arrival households were included. This question was not asked of registered refugee households as they were not eligible for this distribution. At the time of the assessment, 9 children were identified as SAM. Only 1 child was found to be enrolled in the OTP. Among registered population 33.3% of the children were enrolled in the OTP. Looking at the children eligible for enrollment in BSFP, a total of 75 children were found eligible. However only 43 children were enrolled in the BSFP at time of the assessment with 87.5% of the registered population and only 23.5% of the new arrival population were enrolled. Lastly, 85 children 6-23 months were identified eligible for MNP. However only 38 children hadreceived at time of the assessment with 74% of the registered population and only 2.9% of the new arrival population were enrolled.
Table 30: KTP Receipt of Immunizations and Food/Nutrition Assistance
Measles Vaccination All Registered New Arrivals (recall since August 25, 2017) N % 95% CI N % 95% CI N % 95% CI Confirmed by vaccination card or caregiver 170 55.0 [49.4-60.5] 118 73.3 [65.9-79.7] 49 34.8 [27.3-43.1] Children 6-59 months (n=309) Children 6-23 months 55 54.5 [44.5-64.0] 39 72.2 [58.6-82.7] 15 32.6 [20.5-47.5] (n=101) Children 24-59 months 115 55.3 48.4-62.0 79 73.8 [64.5-81.3] 34 35.8 [26.8-46.0] (n=208) Confirmed by vaccination card 57 18.5 [14.5-23.2] 56 34.8 [27.8-42.5] 1 0.7 [0.0-4.9] Children 6-59 months (n=309) Confirmed by caregiver 113 36.6 [31.4-42.1] 62 38.5 [31.3-46.3] 48 34.0 [26.7-42.3] Children 6-59 months (n=309) Not vaccinated 133 43.0 [37.6-48.7] 40 24.8 [18.8-32.1] 91 64.5 [56.3-72.0] Children 6-59 months (n=309) Unknown 6 1.9 [0.9-4.3] 3 1.9 [0.6-5.7] 1 0.7 [0.0-4.9] Children 6-59 months (n=309) Oral Cholera Vaccine N % 95% CI N % 95% CI N % 95% CI (recall since August 25, 2017) All persons ≥ 1 year of age 1,659 78.1 [69.7-79.1] 1,270 92.7 [91.2-94.0] 349 49.4 [45.7-53.1] (n=2,124) Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 63
Children 12-59 months 245 74.7 [69.7-79.1] 169 94.9 [90.5-97.4] 70 49.3 [41.1-57.5] (n=277) Persons ≥ 5 years of age 1,458 78.9 [77.0-80.7] 1,135 92.6 [91.0-93.9] 288 49.6 [45.5-53.6] (n=1,847) Food Assistance N % 95% CI N % 95% CI N % 95% CI Receipt of GFD since August 25, 2017 Registered refugees not included in GFDs 83 52.5 [44.7-50.2] Households (405) OTP enrollment45 33.3 1 11.1 [9.3-62.6] 1 [2.4-90.9] 0 0 - Children 6-59 months (n=9) 46 BSFP enrollment47 35 87.5 [72.8-94.8] 43 57.3 [45.7-68.2] 8 23.5 [12.0-40.9] Children 6-23 months (n=75) Receipt of MNP48 since 25th August 2017 38 44.7 [34.3-55.6] 37 74.0 [60.0-84.6] 1 2.9 [0.4-19.8] Children 6-23 months (n=85)
3.1.14 Care-seeking Behaviour
Assessing care-seeking behaviour is another method for understanding a population’s preferences and access to services. Care-seeking behaviour was reported by the caregivers whose child had shown symptoms of diarrhoea, ARI, or fever within the two-week recall period. Among children 6-59 months with reported diarrhoea, the most commonly sought care was with a clinic or hospital 50.4% [41.6-59.2] followed by the local pharmacy 20.0% [13.8-28.1] (see table 30 below). In 15.2% [9.9-22.7] of cases no care was sought. Among children 6-59 months with a reported cough with fever, the most commonly sought care was with a clinic or hospital 55.8% [48.2-63.1] followed by the local pharmacy 17.4% [12.4- 23.9] (see table 31 below). In 14.5% [10.0-20.7] of cases no care was sought. Among children 6-59 months with a reported fever without a cough, the most commonly sought care was with a clinic or hospital 50.0% [40.9-59.1] followed by the local pharmacy 17.2% [11.3-25.4] and no care sought 17.2% [11.3-25.4] (see table 32 below). In all cases new arrivals were less likely to seek care in a clinic or hospital, and more likely to forego healthcare altogether.
45 OTP eligibility: children 6-59 months with SAM according to WHZ <-3 and/ or MUAC < 115 an/or oedema 46 Calculated as follows: number of SAM cases with SAM from registered population in programme / total number of SAM cases from registered population 47 BSFP KTP eligibility: children 6-23 months- not acutely malnourished 48 MNP KTP eligibility: children 6-23 months Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 64
Table 31: KTP Two-week Recall of Care-seeking Behaviour for Children 6-59 Months with Diarrhoea
All Registered New Arrivals Care-seeking for Children (n=125) (n=49) (n=73) 6-59 months with Diarrhoea N % 95% CI N % 95% CI N % 95% CI
Clinic or hospital 63 50.4 [41.6-59.2] 27 55.1 [41.0-68.5] 33 45.2 [34.1-56.8] Community or traditional 4 3.2 [1.2-8.3] 3 6.1 [2.0-17.6] 1 1.4 [0.2-9.3] healer Pharmacy 25 20.0 [13.8-28.1] 14 28.6 [17.6-42.9] 11 15.1 [8.5-25.4]
Other care 14 11.2 [6.7-18.1] 2 4.1 [1.0-15.2] 12 16.4 [9.5-26.9]
No care sought 19 15.2 [9.9-22.7] 3 6.1 [2.0-17.6] 16 21.9 [13.8-33.0]
Table 32: KTP Two-week Recall of Care-seeking Behaviour for Children 6-59 Months with Cough
All Registered Refugees New Arrivals Care-seeking for Children (n=172) (n=77) (n=92) 6-59 months with Cough N % 95% CI N % 95% CI N % 95% CI
Clinic or hospital 96 55.8 [48.2-63.1] 45 58.4 [47.1-69.0] 48 52.2 [41.9-62.3] Community or traditional 6 3.5 [1.6-7.6] 4 5.2 [1.9-13.2] 2 2.2 [0.5-8.4] healer Pharmacy 30 17.4 [12.4-23.9] 21 27.3 [18.4-38.4] 9 9.8 [5.1-17.9]
Other care 15 8.7 [5.3-14.0] 0 0.0 - 15 16.3 [10.0-25.4]
No care sought 25 14.5 [10.0-20.7] 7 9.1 [4.4-18.0] 18 19.6 [12.6-29.0]
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Table 33: KTP Two-week Recall of Care-seeking Behaviour for Children 6-59 Months with Fever
All Registered New Arrivals Care-seeking for Children (n=116) (n=57) (n=57) 6-59 months with Fever N % 95% CI N % 95% CI N % 95% CI
Clinic or hospital 58 50.0 [40.9-59.1] 32 27.6 [20.1-36.5] 25 21.6 [14.9-30.1] Community or traditional 7 6.0 [2.9-12.2] 4 3.5 [1.3-9.0] 3 2.6 [0.8-7.8] healer Pharmacy 20 17.2 [11.3-25.4] 15 12.9 [7.9-20.5] 5 4.3 [1.8-10.1]
Other care 11 9.5 [5.3-16.4] 1 0.8 [0.1-6.0] 10 8.6 [4.7-15.4]
No care sought 20 17.2 [11.3-25.4] 5 4.3 [1.8-10.1] 14 12.1 [7.2-19.5]
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RESULTS Makeshift Settlements October 29th - November 20th 2017
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3.2 Makeshift Settlements 3.2.1 Data Quality
In total, among the 1,305 households surveyed in the Makeshift Settlements the teams attempted to survey 1,113 children 6-59 months. 25 children were not present at the time of interview and were not located upon revisiting, 1 child was not measured for height and 1 was not measured for MUAC due to physical malformities (all additional data were collected). Furthermore, the weight data from 1 child was excluded from analyses per WHO flags, which contributed to the overall percentage of flagged data of 0.1%, well below the SMART methodology recommendation of less than 5.0%. The overall anthropometric analysis utilizes the data from 1,088 children. In terms of data quantity, a sufficient number of households and children were surveyed. According to the SMART methodology, a minimum of 80% of the sample size must be achieved to ensure data quality. For this survey, 98% of planned households and 123% of planned children 6-59 months were surveyed (see table 33 below), well above the SMART methodology cut-off. In total, the survey teams surveyed 1,305 households of 1,335 attempted, equaling a NRR of 2%. Table 34: MS Households and Children 6-59 months Planned vs. Surveyed
Percentage Percentage Planned Surveyed Percentage Planned Surveyed Planned Surveyed Surveyed / Surveyed / Children 6- Children 6- Surveyed / Clusters Clusters Households Households Planned Planned 59 Months 59 Months Planned 96 96 100% 1,335 1,305 98% 883 1,088 123%
The standard deviation (SD) of WHZ (See table 34) was 0.93, the SD of HAZ was 1.08, and the SD of WAZ was 0.91, all three of which fall within the normal range of 0.8 and 1.2. This indicates an adequate distribution of data around the mean and data of good quality. The WHZ SD was considered “excellent” by the ENA Plausibility score (see table 35). Other statistical tests administered to test the distribution of the sample included:
Shapiro-Wilk test for normal (Gaussian) distribution of the data were marginally significant for WHZ (p=0.037) and HAZ (p=0.024); and non-significant for WAZ (p=0.083). The Skewness coefficient, which concluded the distribution of malnutrition in the population was symmetrical (>-0.2 and <0.2) and was considered “excellent” by the ENA Plausibility score. The Kurtosis coefficient (0.13) which concluded the “tails” of data in the distribution were as expected. Considered “excellent” by the ENA Plausibility score. The Poisson Distribution (p=0.020) which indicated that there was a slight aggregation of malnutrition cases in certain clusters. Considered “good” by the ENA Plausibility score.
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Table 35: MS Median z-score ± Standard Deviation for WHZ, HAZ, and WAZ
Unavailable Excluded z-scores Excluded z-scores Index N Median z-score ± SD Design Effect z-scores (SMART flags) % (SMART flags) WHZ (6-59 months) 1,086 -1.20 ± 0.93 1.33 26 1 0.1% HAZ (6-59 months) 1,071 -1.78 ± 1.08 1.28 26 16 1.5% WAZ (6-59 months) 1,083 -1.83 ± 0.91 1.64 25 5 0.5%
The sex-ratio between boys and girls 6-59 months was satisfactory at 1.12 boys/girls (p=0.051) indicating that statistically boys and girls are equally represented. Still, the p-value approaches significance (just >0.05) and when examining the data there appears to be a slight overrepresentation of boys from 54-59 months (sex-ratio=1.37 boys/girls) (see table 37 below), however this did not affect the data quality. Overall, the distribution of sex was considered “good” by the ENA Plausibility score. Concerning age, among children 6-59 months included in the sample, only 20% had exact birthdays as confirmed by supportive documentation. The age-ratio between the categories of 6- 29 months and 30-59 months is satisfactory at 0.86 (p=0.781) as this falls near the desired value of 0.85 as recommended by the SMART methodology. Overall, the distribution of age was considered “excellent” by the ENA Plausibility score. Digit preference scores for weight and MUAC were considered “excellent” while height was considered “good” by the ENA Plausibility score with the scores of 3, 8, and 4, respectively. The overall data quality score was 5%, which is considered a survey of “excellent” quality by the ENA Plausibility score. The Plausibility report is presented in Annex 13.
Table 36: MS Overall Data Quality per ENA Plausibility Check
Criteria SD Flagged Sex-ratio Age-ratio Digit Pref. Weight Observed 0.93 0.1% (p=0.051) (p=0.781) 3 Desired 0.8-1.2 < 5% (p>0.05) (p>0.05) < 13 Score Excellent Excellent Good Excellent Excellent
Criteria Digit Pref. Height Digit Pref. MUAC Skewness Kurtosis Poisson Distrib. Overall Score Observed 8 4 -0.15 0.13 (p=0.020) 5 Desired < 13 < 13 < ± 0.6 < ± 0.6 > 0.001 < 15 Score Good Excellent Excellent Excellent Good Excellent
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3.2.2 Demography and Mortality
During the planning stages of the assessment, the average household size was estimated to be 4.3 persons per household and the proportion of children less than five years of age in the population was estimated to be 19.0%. Following the analysis of the data the average household size was determined to be 5.6 persons per household and the proportion of children less than five years of age was found to be 20.3% for the sample surveyed (see table 36 below). New arrivals and old arrivals had a similar household size (5.7 vs 5.5 persons per houshold), similar percentage of pregnant and lactating women (9.7% vs. 10.2%) and a similar percentage of children under five years (20.4% vs. 19.7%). However, there was an overall higher proportion of new arrival households to old arrival households than expected given updated population estimates. This may be due to households misidentifying as “new arrivals”. This is discussed further in the limitations section of this report.
Table 37: Demographics of the Makeshift Settlements
All Households New Arrivals Old Arrivals Population Subset N % 95% CI N % 95% CI N % 95% CI All Household Members* 6,146 100.0 - 5,249 85.4 - 859 14.0 - Average HH size, mean (SD) 5.6 (2.3) 5.7 (2.4) 5.5 (2.1) All, <5 years 1,249 20.3 [19.3-21.4] 1,069 20.4 [19.2-21.5] 169 19.7 [17.1-22.6] All, 5-10 years 1,148 18.7 [17.8-19.6] 963 18.4 [17.4-19.3] 176 20.5 [18.4-22.8] All, 11-17 years 974 15.9 [14.9-16.9] 850 16.2 [15.1-17.3] 121 14.1 [12.1-16.3] All, 18-59 years 2,508 40.8 [40.0-41.8] 2,132 40.6 [39.5-41.7] 362 42.1 [40.4-43.9] All, ≥60 years 267 4.3 [3.8-4.9] 235 43.5 [38.4-49.4] 31 36.1 [24.1-53.8] Female 3,156 51.4 [50.2-52.5] 2,706 51.6 [50.2-52.9] 433 50.4 [48.2-52.6] Women, 15-49 Years 1,458 23.7 [23.0-24.5] 1,251 23.8 [23.0-24.7] 199 23.2 [21.7-24.7] Pregnant and lactating women 604 9.8 [9.1-10.6] 510 9.7 [9.0-10.5] 88 10.2 [8.5-12.3] Pregnant women 194 3.2 [2.7-3.6] 167 3.2 [2.7-3.7] 26 3.0 [2.1-4.3] Lactating women 405 6.6 [6.2-7.2] 343 6.5 [6.0-7.1] 62 7.2 [5.8-9.0] Lactating w/child < 6 months 133 2.2 [1.8-2.6] 111 2.1 [1.7-2.6] 22 2.6 [1.9-3.5] Lactating w/child > 6 months 272 4.5 [4.0-5.0] 232 4.4 [3.9-5.0] 40 4.7 [3.5-6.2] Number of days to arrive from Question not asked of old Question not asked of old 6.3 days (5.1) Myanmar, mean (SD) arrival households arrival households *Demographics include all current household members, regardless of presence at time of interview Of the 1,088 children included in the analysis, 937 were from new arrival households, 140 were from old arrival households, and 11 were from registered households.
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The distribution of age of children 6-59 months demonstrates relatively equal representation of children 6-23 months and children 24-59 months (see Figure 9 below). The distribution shows distinct peaks at 18, 25, and 37 months and a slight peak at 26 months.
Figure 9: MS Age Distribution of Children 6-59 months
50 45 40 35 30 25 20
15 NumberChildren of 10 5 0 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 Age in Months
Table 38: MS Distribution of Age and Sex, Children 6-59 months
Age Category Boys Girls Total Ratio (months) boy : girl N % N % N % 6-17 135 53.6 117 46.4 252 22.6 1.2 18-29 127 48.1 137 51.9 264 23.7 0.9 30-41 142 55.0 116 45.0 258 23.2 1.2 42-53 115 52.8 103 47.2 218 19.6 1.1 54-59 70 57.9 51 42.1 121 10.9 1.4 Total 589 52.9 524 47.1 1,113 100.0 1.1
The Crude Death Rate (CDR) for the Makeshift Settlements was 1.36 [1.07-1.73], well above the CDR Emergency Threshold of 0.4 for the South Asian Region per Sphere Standards. The under five Death Rate (U5DR) for the Makeshift Settlements was 1.22 [0.70-2.13], well above the Emergency Threshold of 0.9 for the South Asian Region per Sphere Standards.
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3.2.3 Prevalence of Acute Malnutrition by WHZ
The prevalence of acute malnutrition by WHZ was based on the analysis of 1,086 children, after the exclusion of one child per SMART flags or 0.1% of the data. The distribution curve of figure 10 below illustrates the distribution of the WHZ for the surveyed sample (the red curve) in comparison to the WHO 2006 reference population (the green curve). There were no identified cases of oedema in the Makeshift Settlements. The WHZ mean is -1.20 with a standard deviation of ± 0.93 (the standard deviation falls between 0.8 and 1.2 indicating data of good quality). The red curve representing the surveyed population is shifted to the left of the reference population, demonstrating that the acute malnutrition status of the surveyed population is inferior. The slight excess of observations between +1 and +2 z- scores of the surveyed population curve may be attributable to small measurement errors or natural outliers in the population. The prevalence of acute malnutrition global and severe per WHZ are presented in table 38 below:
Figure 10: MS Distribution of the WHZ of the Sample Compared to the WHO 2006 Reference
The prevalence of GAM among children 6-59 months in the Makeshift Settlements was 19.3% [16.7-22.2] well above the WHO emergency cut-off of 15%, as was the lower confidence interval of 16.7%. This prevalence was slightly higher among old arrivals than new arrivals (20.0% vs. 19.5%). The prevalence of MAM in the Makeshift Settlements was 16.3% [13.9-19.0] and was also slightly higher among old arrivals than new arrivals (17.1 vs. 16.4%). The prevalence of SAM
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in the Makeshift Settlements was 3.0% [2.2-4.2] and was very similar between old arrivals and new arrivals (2.9% vs. 3.1%). None of the differences between old and new arrivals were statistically significant. When disaggregated by age category, the prevalence of GAM was higher in children 6-23 months than children 24-59 months (29.8% vs. 14.2%). There was a statistically significant association between age and GAM (OR 2.57 [95% CI 1.89-3.50]) (p=0.001). This suggests that children 6-23 months are 2.5 times as likely to be acutely malnourished than children 24-59 months in the Makeshift Settlements. Results from all 2x2 statistical analyses for the Makeshift Settlements are available in Annex 2.
Table 39: MS Prevalence of Acute Malnutrition per WHZ and/or Oedema, WHO Reference 2006
Global Acute Moderate Acute Severe Acute Children 6-59 months N Malnutrition Malnutrition Malnutrition N % 95% CI N % 95% CI N % 95% CI All 1,086 210 19.3 [16.7-22.2] 177 16.3 [13.9-19.0] 33 3.0 [2.2-4.2] New Arrivals 935 182 19.5 [16.6-22.7] 153 16.4 [13.7-19.4] 29 3.1 [2.2-4.4] Old Arrivals 140 28 20.0 [14.5-26.9] 24 17.1 [11.3-25.1] 4 2.9 [1.2-6.7] Children 6-23 months 349 104 29.8 [24.6-35.6] 83 23.8 [19.1-29.2] 21 6.0 [3.9-9.2] Children 24-59 months 734 104 14.2 [11.5-17.3] 94 12.8 [10.4-15.7] 10 1.4 [0.8-2.4]
Regarding acute malnutrition by WHZ among children 6-59 months as disaggregated by sex, the prevalence of acute malnutrition was slightly higher for boys than for girls in the Makeshift Settlements; with GAM (20.2% vs. 18.3%), MAM (17.1% vs. 15.4%), and SAM (3.1% vs. 3.0%) (see table 39 below). However, none of these differences were found to be statistically significant.
Table 40: MS Prevalence of Acute Malnutrition by Sex per WHZ and/ or Edema, WHO Reference 2006
Global Acute Moderate Acute Severe Acute Children 6-59 months Malnutrition Malnutrition Malnutrition N % 95% CI N % 95% CI N % 95% CI All 210 19.3 [16.7-22.2] 177 16.3 [13.9-19.0] 33 3.0 [2.2-4.2] (n=1,086) Boys 117 20.2 [16.8-24.1] 99 17.1 [13.8-21.0] 18 3.1 [2.1-4.7] (n=579) Girls 93 18.3 [14.9-22.3] 78 15.4 [12.5-18.8] 15 3.0 [1.8-4.9] (n=507)
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Regarding acute malnutrition by WHZ among children 6-59 months as disaggregated by age category, the prevalence of SAM was highest among the 6-17 month category (6.9%) and lowest among the 42-53 month category (1.4%) (see table 40 below). The prevalence of MAM was also highest among the 6-17 month category (26.7%) and the lowest among the 54-59 month category (7.5%). The overall age category with the highest percentage of children who were not acutely malnourished was the 54-59 month category (90.8%). This suggests that younger children are more vulnerable to acute malnutrition in the Makeshift Settlements.
Table 41: MS Prevalence of Acute Malnutrition by Age per WHZ and/ or Edema, WHO Reference 2006
Severe Acute Moderate Acute Not Acutely Edema Malnourished Malnutrition Malnourished Age (months) Total N % N % N % N % 6-17 247 17 6.9 66 26.7 164 66.4 0 0.0 18-29 256 5 2.0 39 15.2 212 82.8 0 0.0 30-41 248 6 2.4 36 14.5 206 83.1 0 0.0 42-53 215 3 1.4 27 12.6 185 86.0 0 0.0 54-59 120 2 1.7 9 7.5 109 90.8 0 0.0 Total 1,086 33 3.0 177 16.3 876 80.7 0 0.0
3.2.4 Prevalence of Acute Malnutrition by MUAC
The prevalence of GAM in the Makeshift Settlements per MUAC was 8.6% [6.8-10.7] which according to the IPC Classification falls under “Alert-Serious”. The prevalence of GAM per MUAC was higher among new arrivals than old arrivals (9.3% vs. 3.6%) (see table 41 below). There was a statistically significant association between arrival subset and acute malnutrition (OR 2.67 [95% CI 1.22-5.82]) (p=0.015). This suggests that new arrival children 6-59 months are 2.67 times more likely to suffer from acute malnutrition identified by MUAC than old arrival children 6-59 months. The prevalence of MAM per MUAC was 7.3% [5.6-9.4] and was again higher for new arrivals than old arrivals (7.9% vs. 3.6%). The prevalence of SAM per MUAC was 1.3% [0.8-2.1], with a prevalence of 1.4% for new arrivals. There were no identified SAM per MUAC cases among the old arrivals. When disaggregated by age category, the prevalence of GAM by MUAC was higher in children 6-23 months than children 24-59 months (22.3% vs. 2.0%). There was a statistically significant association between age and GAM per MUAC (OR 13.8 [95% CI 7.81-24.41]) (p=0.001). This suggests that children 6-23 months were more than 13 times as likely to suffer from acute malnutrition as determined by MUAC than children 24-59 months in the Makeshift Settlements.
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Table 42: MS Prevalence of Acute Malnutrition by MUAC
Global Acute Malnutrition Moderate Acute Severe Acute Children 6-59 months N by MUAC Malnutrition by MUAC Malnutrition by MUAC N % 95% CI N % 95% CI N % 95% CI All 1,087 93 8.6 [6.8-10.7] 79 7.3 [5z.6-9.4] 14 1.3 [0.8-2.1] New Arrivals 936 87 9.3 [7.3-11.8] 74 7.9 [6.0-10.3] 13 1.4 [0.8-2.3] Old Arrivals 140 5 3.6 [1.7-7.5] 5 3.6 [1.7-7.5] 0 0.0 - Children 6-23 months 350 78 22.3 [17.4-28.0] 65 18.6 [14.1-24.1] 13 3.7 [2.2-6.2] Children 24-59 months 737 15 2.0 [1.2-3.3] 14 1.9 [1.2-3.1] 1 0.1 [0.0-1.0]
The prevalences of acute malnutrition per MUAC as disaggregated by age category (see figure 11 below) demonstrate that the highest prevalences of GAM, MAM, and SAM fall within the youngest age category of 6-17 months. 11 of the 14 SAM cases fell in this age category, giving it a SAM prevalence of 4.5%, and MAM prevalence of 19.4% (overall GAM prevalence of 23.9%). In contrast, no cases of acute malnutrition were identified in the 54-59 month age category.
Figure 11: MS Prevalence of Acute Malnutrition by Age per MUAC
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3.2.5 Prevalence of Acute Malnutrition WHZ vs. MUAC
The prevalence of acute malnutrition among children 6-59 months was notably different as identified by WHZ and MUAC in the Makeshift Settlements. The prevalence of all indicators was more than twice as high per WHZ than MUAC: the prevalence of GAM was (19.3% vs. 8.6%), the prevalence of MAM was (16.3% vs. 7.3%), and the prevalence of SAM was (3.0% vs. 1.3%). As is demonstrated in figure 12 below. Overall, 210 cases were identified per WHZ and 93 cases were identified per MUAC. Of these 210 cases, 68.6% (144) of them were not identified as GAM according to MUAC. When disaggregated by age category, the difference in GAM per WHZ for children 6-23 months vs. 24-59 months (29.8% vs. 14.2%) was statistically significant (OR 2.57 [95% CI 1.89-3.50]) (p=0.001). When the difference in GAM per MUAC of children 6-23 months vs. 24-59 months (22.3% vs. 2.0%) was analysed, it was also found to be statistically significant (OR 13.8 [95% CI 7.81-24.41]) (p=0.001). However, the odds ratios were distinct, with children 6-23 months nearly 3 times as likely to be GAM per WHZ, yet more than 13 times as likely to be GAM per MUAC when compared to children 24-59 months. This disparity was likely influenced by MUAC’s known bias towards identifying acute malnutrition in younger and small children49.
Figure 12: MS Prevalence of Acute Malnutrition WHZ vs. MUAC
49 Briend A, Golden MH, Grellety Y, Prudhon C, Hailey P. (1995) Use of mid-upper-arm circumference for nutritional screening of refugees Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 76
3.2.6 Low MUAC in Women
Low MUAC in women was defined as a mid-upper arm circumference below 210mm for the purposes of this assessment. The results from the Makeshift Settlements indicated a prevalence of low MUAC among women 15-49 years of 8.7% [6.7-11.1] (see table 42 below). This prevalence was higher among new arrival women than old arrival women (9.4% v. 3.7%). There was a statistically significant association between arrival subset and low MUAC (OR 2.67 [95% CI 1.22-5.82]) (p=0.008). This suggests that new arrival women were more susceptible to suffer from acute malnutrition. Low MUAC for all pregnant and lactating women in the sample regardless of population subset was 11.2%, surpassing that of new arrival women overall. There was a statistically significant association between arrival subset and low MUAC (OR 1.56 [95% CI 1.07-2.27]) (p=0.026). This suggests that PLW are more susceptible than non-PLW to suffer from acute malnutrition. The average MUAC for women in Makeshift Settlements at the time of the survey was 247mm.
Table 43: MS Low MUAC in Women 15-49 Years
MUAC <210mm Women 15-49 years N N % [95% CI] All 1,385 120 8.7% [6.7-11.1] New Arrivals 1,191 112 9.4% [7.3-12.1] Old Arrivals 187 7 3.7% [1.2-11.0] PLW 583 65 11.2% [8.4-14.7]
Women 15-49 years N Mean MUAC (SD)
All 1,385 247mm (31.80)
3.2.7 Low MUAC in Infants
The cut off for low MUAC for infants 0-5 months was assessed at <115mm, <110mm, and <105mm for this assessment (see table 43 below). Within the Makeshift Settlements it was found that, 33.6% of infants 0-5 months were <115mm, 25.8% were <110mm, and 21.1% were <105mm. The mean MUAC measurement of infants 0-5 months was 119mm.
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Table 44: MS Low MUAC in Infants 0-5 Months
Infants 0-5 months Low MUAC (n=128) N % [95% CI] MUAC <115mm 43 33.6 [26.5-41.5] MUAC <110mm 33 25.8 [19.2-33.7] MUAC <105mm 27 21.1 [15.2-28.5] Infants 0-5 months N Mean MUAC (SD) All 128 119mm (17.4)
3.2.8 Prevalence of Chronic Malnutrition
The prevalence of chronic malnutrition among children 6-59 months in the Makeshift Settlements was 44.1% [40.7-47.5], above the WHO cut-off of 40% indicating it is of critical public health significance (see table 44 below). This global prevalence was higher among new arrivals than old arrivals (44.1% vs. 43.1%), a difference which was not statistically significant. The prevalence of moderate chronic malnutrition was slightly higher among old arrivals than new arrivals (35.0% vs. 31.8%). The prevalence of severe chronic malnutrition was also higher among new arrivals than old arrivals (12.4% vs. 8.0%). These persistently high prevalences of chronic malnutrition speak to the long-term malnutrition context existing in Rakhine State.
Table 45: MS Prevalence of Chronic Malnutrition by HAZ, WHO Reference 2006
Global Chronic Moderate Chronic Severe Chronic Children 6-59 N Malnutrition Malnutrition Malnutrition months N % 95% CI N % 95% CI N % 95% CI All 1,086 472 44.1 [40.7-47.5] 343 32.0 [29.2-35.0] 129 12.0 [10.1-14.3] New Arrivals 922 407 44.1 [40.4-48.0] 293 31.8 [28.6-35.1] 114 12.4 [10.3-14.8] Old Arrivals 137 59 43.1 [35.5-51.0] 48 35.0 [27.6-43.3] 11 8.0 [4.2-14.7]
3.2.9 Prevalence of Underweight
The prevalence of underweight among children 6-59 months in the Makeshift Settlements was 41.3% [37.5-45.1], above the WHO cut-off of 30% indicating it is of critical public health significance (see table 45 below). This global prevalence was similar between old arrivals and new arrivals (41.7% vs. 41.1%). The prevalence of moderate and severe underweight was higher among old arrivals than new arrivals (33.8% vs. 29.6% and (11.6% vs. 7.9%) respectively. These high prevalences of underweight speak to the long-term malnutrition context along with an acute malnutrition crisis in both Rakhine State and the Makeshift Settlements. Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 78
Table 46: MS Prevalence of Underweight by WAZ, WHO Reference 2006
Children 6-59 Global Underweight Moderate Underweight Severe Underweight N months N % 95% CI N % 95% CI N % 95% CI All 1,083 447 41.3 [37.5-45.1] 326 30.1 [26.9-33.5] 121 11.2 [9.0-13.8] New Arrivals 934 384 41.1 [37.0-45.3] 276 29.6 [26.2-33.1] 108 11.6 [9.1-14.6] Old Arrivals 139 58 41.7 [31.5-52.8] 47 33.8 [23.6-45.8] 11 7.9 [4.7-13.0]
3.2.10 Prevalence of Anaemia
The overall prevalence of anaemia among children 6-59 months was 47.9% [44.1-51.7] within the Makeshift Settlements, well above the WHO cut-off of 40% for significant public health concern (see table 46 below). This prevalence was similar between old arrivals and new arrivals (50.0% vs. 47.7%). When the sample was disaggregated by age, the prevalence of anaemia was found to be higher among children 6-23 months than children 24-59 months (61.6% vs. 41.3%). There was a statistically significant association between age and anaemia (OR 2.22 [95% CI 1.72-2.89]) (p=0.001). Suggesting that children 6-23 months are more than twice as likely to suffer from anaemia than children 24-59 months in the Makeshift Makeshift Settlements. Very few cases of severe anaemia were identified (n=3). Overall, these findings indicate that nearly half of the children 6-59 months in the Makeshift Settlements were suffering from anaemia, with children under 2 years being the most vulnerable.
Table 47: MS Prevalence of Anaemia in Children 6-59 months per WHO
All New Arrivals Old Arrivals Children 6-59 months (n=1,082) (n=931) (n=140) N % 95% CI N % 95% CI N % 95% CI Any Anaemia 518 47.9 [44.1-51.7] 444 47.7 [43.4-52.0] 70 50.0 [42.7-57.4] (Hb<11.0 g/dL) Mild Anaemia 333 30.8 [27.7-34.0] 291 31.3 [27.9-34.9] 40 28.6 [22.4-35.6] (Hb 10.0 to <11.0 g/dL) Moderate Anaemia 183 16.9 [14.5-19.7] 152 16.3 [13.7-19.3] 30 21.4 [15.3-29.2] (Hb 7.0 to <10.0 g/dL) Severe Anaemia 2 0.2 [0.1-0.7] 1 0.1 [0.0-0.1] 0 0.0 - (Hb <7.0 g/dL) Any Anaemia
23 23 215 61.6 [55.8-67.1] 188 61.2 [54.9-67.2]
- (Hb<11.0 g/dL) Mild Anaemia Inadequate sample size for 112 32.1 [27.5-37.1] 99 32.3 [27.3-37.6] (Hb 10.0 to <11.0 g/dL) disaggregation
(n=349)
months Moderate Anaemia
Children 6 Children 102 29.2 [24.4-34.5] 88 28.7 [23.5-34.5] (Hb 7.0(n= to <10.0 g/dL)
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Severe Anaemia 1 0.3 [0.1-2.0] 1 0.3 [0.1-2.3] (Hb <7.0 g/dL) Any Anaemia 303 41.3 [37.5-45.3] 256 41.0 [36.6-45.6] (Hb<11.0 g/dL)
59 - Mild Anaemia 221 30.2 [26.5-34.1] 192 30.8 [26.7-35.2]
(n=733) (Hb 10.0 to <11.0 g/dL) Moderate Anaemia 81 11.1 [8.8-13.8] 64 10.3 [7.9-13.3] (Hb 7.0 to <10.0 g/dL)
Children 24 Children
months Severe Anaemia 1 0.1 [0.1-0.9] 0 0.0 - (Hb(n= <7.0 g/dL)
3.2.11 Prevalence of Morbidity
The prevalence of diarrhoea among children 6-59 months per two-week recall was 41.3% [36.5-46.2] within the Makeshift Settlements (see table 47 below). This was higher among new arrivals than old arrivals (41.8% vs. 34.5%), although this difference was not statistically significant. The prevalence was also higher among children 6-23 months compared with children 24-59 months (48.1% vs. 38.0%). There was a statistically significant association between age and the prevalence of diarrhoea (OR 1.51 [95% CI 1.17-1.95]) (p=0.002). This suggests that children 6-23 months were more susceptible to suffering from diarrhoeal episodes than children 24-59 months. The prevalence of acute respiratory infection with fever among children 6-59 months per two-week recall was 57.7% [52.7-62.4] within the Makeshift Settlements. The prevalence was very similar between new arrivals and old arrivals (57.3% vs. 57.2%). When results between children 6-23 months and children 24-59 months (58.6% vs. 57.2%) were also similar. The prevalence of fever without cough among children 6-59 months per two-week recall was 25.2% [20.5-30.6] within the Makeshift Settlements. This was higher among new arrivals compared to old arrivals (26.5% vs. 13.8%). There was a statistically significant association between arrival subset and prevalence of fever without cough (OR 2.26 [95% CI 1.38-3.69]) (p=0.001). This suggests that new arrival children are more susceptible to suffering from fever without cough than old arrivals. The prevalence as also somewhat higher for children 6-23 moths than children 24-59 months (27.2% vs. 24.3%), but this was not statistically significant. The morbidity indicators suggest that children under two were more susceptible to diarrhoeal disease compared to children 24-59 months, and that new arrival children were more likely to suffer from a fever without a cough in the Makeshift Settlements compared to old arrival population.
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Table 48: MS Two-week Prevalence of Diarrhoea, Cough, and Fever in Children 6-59 Months
All New Arrivals Old Arrivals Children 6-59 months (n=1,110) (n=954) (n=145) N % 95% CI N % 95% CI N % 95% CI
Diarrhoea 458 41.3 [36.5-46.2] 399 41.8 [36.8-47.0] 50 34.5 [22.4-50.0]
Children 6-23 months (n=360) 173 48.1 [41.4-54.7] 153 48.4 [41.6-55.3] Inadequate sample size for disaggregation Children 24-59 months (n=750) 285 38.0 [33.0-43.3] 246 38.6 [33.2-44.2] Acute Respiratory Infection with 640 57.7 [52.7-62.4] 547 57.3 [52.1-62.4] 83 57.2 [45.6-68.1] Fever Children 6-23 months (n=360) 211 58.6 [52.4-64.5] 184 58.2 [51.5-64.7] Inadequate sample size for disaggregation Children 24-59 months (n=750) 429 57.2 [51.9-62.3] 363 56.9 [51.3-62.3]
Fever without Cough 280 25.2 [20.5-30.6] 253 26.5 [21.4-32.4] 20 13.8 [8.1-22.4]
Children 6-23 months (n=360) 98 27.2 [21.2-34.3] 90 28.5 [22.1-35.9] Inadequate sample size for Children 24-59 months disaggregation 182 24.3 [19.6-29.6] 163 25.6 [20.3-31.6] (n=750)
3.2.12 IYCF Indicators
It is important to note when interpreting the IYCF indicators from this assessment, that the survey sample sizes were calculated based on anticipated prevalences of GAM for children 6-59 months. The sample size and precision were not calculated for IYCF indicators, leading to lower precision and larger confidence intervals for some of the results. The IYCF results of this survey should therefore be interpreted with caution and in consideration of the width of their associated confidence intervals. Within the Makeshift Settlements, 98.6% [97.1-99.3] of children 0-23 months had been breastfed at some point prior to the survey date, and this rate was very similar among new arrivals and old arrivals (98.4% vs. 100.0%) (see table 48 below). Of the caregivers interviewed in the Makeshift Settlements with a child 0-23 months, 42.9% [35.6-50.4] reported initiating breastfeeding within one hour of birth, 39.8% between one and 24 hours after birth, and 16.5% more than 24 hours after birth. The prevalence of timely initiation of breastfeeding was higher among old arrivals than new arrivals (67.7% vs. 39.7%). Of the caregivers interviewed with an infant 0-5 months, 56.1% [45.1-66.4] reported exclusively breastfeeding the infant on the day preceding the survey.
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Of the caregivers interviewed with a child 12-15 months, 97.3% [89.2-99.2] reported continued breastfeeding of the child until one year of age. Of the caregivers interviewed with a child 20-23 months, 71.1% [54.3-83.6] reported continued breastfeeding of the child at two years of age. Of the caregivers interviewed with an infant 6-8 months, 71.6% [57.1-82.8] reported the infant was being fed complementary foods. Minimum dietary diversity was reported as 8.3% [5.2-13.0] among children 6-23 months. This was somewhat higher among new arrivals than old arrivals (8.5% vs. 5.1%) Minimum meal frequency was reported as 61.2% [54.7-67.5] among children 6-23 months. This was similar among old arrivals and new arrivals (61.5% vs. 60.6%). Minimum Acceptable diet was reported as 6.4% [3.8-10.4] among children 6-23 months. This was higher among new arrivals than old arrivals (6.6% vs. 2.6%).
Table 49: MS Infant and Young Child Feeding Indicators
Infants and Young Children 0-23 All New Arrivals Old Arrivals months (n=497) N % 95% CI N % 95% CI N % 95% CI Ever breastfed 490 98.6 [97.1-99.3] 423 98.4 [96.1-99.2] 62 100.0 - Infants 0-23 months (n=497) Timely initiation of breastfeeding 210 42.9 [35.6-50.4] 168 39.7 [32.3-47.6] 42 67.7 [50.7-81.1] Infants 0-23 months (n=490) Exclusive breastfeeding 74 56.1 [45.1-66.4] 60 55.1 [42.7-66.8] Infants 0-5 months (n=132) Cont. breastfeeding at one year 71 97.3 [89.2-99.2] 56 96.9 [86.6-99.2] Children 12-15 months (n=73) Inadequate sample size for Cont. breastfeeding at two years disaggregation 32 71.1 [54.3-83.6] 29 69.1 [51.6-82.4] Children 20-23 months (n=45) Introd. of complementary Foods 48 71.6 [57.1-82.8] 39 67.2 [51.7-79.8] Infants 6-8 months (n=67) Minimum dietary diversity 30 8.3 [5.2-13.0] 27 8.5 [5.1-13.9] 2 5.1 [1.5-16.0] Children 6-23 months (n=361) Minimum meal frequency 221 61.2 [54.6-67.5] 192 60.6 [53.4-67.3] 24 61.5 [45.4-75.5] Children 6-23 months (n=361) Minimum acceptable diet 23 6.4 [3.8-10.4] 21 6.6 [3.8-11.2] 1 2.6 [0.4-13.8] Children 6-23 months (n=361)
Overall, children 0-23 months scored poorly on all IYCF indicators. Figure 13 below shows the frequency of liquids or beverages consumed during the 24 hours preceeding the survey for two age groups: infants 0-5 months and children 6-23 months. This indicator aimed to look at what could be displacing breastmilk. Among infants 0-5 months, an age where exclusive Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 82
breastfeeding is crucial for optimal health, the most frequently consumed beverages were water at 37.8%, thin porridge at 9.6%, and milk at 8.1%. Few infants 0-5 months had been fed infant formula (3.7%), juice (2.2%) or yogurt (1.5%). Among children 6-23 months, an age where complementary foods in additional to continued breastfeeding are advised, the most frequently consumed beverages were water (96.1%), thin porridge (31.9%), and juice (26.6%). Fewer children 6-23 months had consumed other beverages at 15.0%, milk at 13.6%, tea or coffee at 3.9%, yogurt at 2.5%, and infant formula at 1.9%. A complete list of the beverages considered in each category is available in Annex 6. Additionally, there is a common practice in parts of Myanmar and Bangladesh where a newborn is fed a sweet beverage (sweetened with sugar or honey) just after birth. It is thought that giving the child such a drink will cause the child to speak sweetly later in life. Caregivers were specifically asked about this practice for children 0-23 months. In the Makeshift Settlements, 67.6% of caregivers reported having given their newborn a sweet drink shortly after birth.
Figure 13: MS 24-Hour Recall of Consumption of Liquids in Children 6-23 months
24-Hour Recall Consumption of Liquids
Infants 0-5 months (n=136) Children 6-23 months (n=361)
0.7% Other 15.0%
Tea or Coffee 3.9% 9.6% Thin Porridge 31.9% 1.5% Yogurt 2.5% Broth 2.2% Juice 26.6% 8.1% Milk 13.6% 3.7% Infant Formula 1.9% 37.8% Water 96.1% 0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0% 90.0% 100.0%
Figure 14 below shows what categories of food were being consumed most frequently. The food group most frequently consumed was “grain” at 75.8% and the least frequently consumed was “dairy” at 1.1%. The high rate of grain consumption was consistent with the general food distributions WFP had been providing to the population which consisted mainly of rice. The lack of many dairy products in the diet may have a cultural influence. The “meat/fish” category was the
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second most commonly consumed food group at 37.4%, which was likely influenced by the fishing livelihoods in the region. Of most food categories, fewer of the new arrival children than the old arrival children 6-23 months were consuming these foods. The exceptions were vitamin A rich fruits and vegetables (30.0% vs. 25.6%) and meat/fish (39.1% vs. 23.1%) which new arrival children 6-23 months were consuming more frequently than old arrival children. A complete list of the food items considered in each category is available in Annex 6.
Figure 14: MS 24-Hour Recall of Food Group Consumption in Children 6-23 Months
24-hour Recall Consumption of Food Groups
100%
90% 87.2%
80% 75.8% 74.5%
70%
60%
50% 39.1% 40% 37.4% 29.5% 30.0% 30% 25.6% 25.6% 23.1%
20% 15.4% 15.2% 13.9% 15.4% 10.1% 9.5% 10% 6.2% 5.0% 1.1% 1.3% 0.0% 0% Grain Legume Dairy Meat/Fish Egg VitA Fruit Veg Other Fruit Veg All Old Arrivals New Arrivals
3.2.13 Receipt of Services
Measles vaccination coverage was assessed by documentation or household recall. Among children 6-59 months, the measles vaccination coverage was 45.3 [38.5-52.3] within the Makeshift Settlements (see table 49 below). This rate was much higher among old arrivals than new arrivals (83.5% vs. 39.1%). This difference was likely due to a lack of health services in Rakhine State. In addition, the most recent measles vaccination campaigns prior to the survey were conducted mid-September 2017 and early November 2017 and a portion of new arrivals migrated to the Makeshift Settlements after that period. Meanwhile, the rate of measles immunisations evidenced by a vaccination card was only 5.6% [3.7-8.4] and was higher among old arrivals than new arrivals (16.6% vs. 3.9%). The low rate of measles vaccinations as evidenced by vaccination card is not surprising when considering the lack of health services within Rakhine State and the haste with which many households fled Rakhine State. Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 84
OCV coverage was assessed by household recall. Among all persons over one year of age, cholera immunisation coverage was determined to be 88.5% [84.0-91.9], higher among old arrivals than new arrivals (97.2% vs. 87.0%). This disparity by population subset was consistent for children 12-59 months (97.8% vs. vs 89.8%) as well as all persons >5 years (97.1% vs. 86.4%). The receipt of general food distribution indicator is defined as any household from which a household member has received at least one bag of rice since August 25th, 2017. Per this operational definition, 82.7% [75.0-87.6] of old and new arrival households were included. This rate was higher for new arrivals than old arrivals (88.4% vs. 44.3%) which was consistent with distributions targeting new arrival households. At the time of the assessment, 42 children were identified as SAM. Only 7 children were found to be enrolled in the OTP. Among old arrival population 33.3% of the children were enrolled in the OTP, while among the new arrivals only 15.8% were enrolled in the OTP. Looking at the children eligible for enrollment in BSFP (6-59 months), a total of 860 children were found eligible. However only 100 children were enrolled in the BSFP at time of the assessment with 47.5% of the old arrival population and only 5.6% of the new arrival population enrolled. Lastly, 1,073 children 6-23 months were identified eligible for MNP. However only 107 children had received MNP at time of the assessment with 30.0% of the old arrival population and only 6.9% of the new arrival population were enrolled.
Table 50: MS Receipt of Immunizations and Food/Nutrition Assistance
Measles Vaccination All New Arrivals Old Arrivals (recall since August 25, 2017) N % 95% CI N % 95% CI N % 95% CI Confirmed by vaccination card or caregiver 504 45.3 [38.5-52.3] 374 39.1 [32.6-46.0] 121 83.5 [69.8-91.7] Children 6-59 months (n=1,112) Children 6-23 months 156 43.2 [35.3-51.4] 122 38.5 [30.6-47.0] 31 79.5 [57.5-91.8] (n=361) Children 24-59 months 348 46.3 [39.2-53.7] 252 39.4 [32.7-46.6] 90 84.9 [67.8-91.8] (n=751) Confirmed by vaccination card 62 5.6 [3.7-8.4] 37 3.9 [2.3-6.5] 24 16.6 [9.0-28.5] Children 6-59 months (n=1,112) Confirmed by caregiver 442 39.8 [33.2-46.7] 337 35.3 [28.8-42.3] 97 66.9 [51.6-79.3] Children 6-59 months (n=1,112) Not vaccinated 605 54.4 [47.4-61.2] 579 60.6 [53.6-67.1] 24 16.6 [8.4-30.2] Children 6-59 months (n=1,112) Unknown 3 0.2 [0.2-1.2] 3 0.3 [0.0-1.4] 0 0.0 - Children 6-59 months (n=1,112) Oral Cholera Vaccine N % 95% CI N % 95% CI N % 95% CI (recall since August 25, 2017) All persons ≥ 1 year of age 5,195 88.5 [84.0-91.9] 4,359 87.0 [81.8-90.8] 801 97.2 [92.2-99.0] (n=5,871) Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 85
Children 12-59 months 886 91.0 [86.2-94.2] 747 89.8 [84.3-93.5] 131 97.8 [91.0-99.5] (n=974) Persons ≥ 5 years of age 4,309 88.0 [83.4-91.4] 3,612 86.4 [81.2-90.3] 670 97.1 [92.1-99.0] (n=4,897) Food/Nutrition Assistance N % 95% CI N % 95% CI N % 95% CI Receipt of GFD since August 25, 2017 1,072 82.7 [75.0-87.6] 984 88.4 [82.3-92.7] 82 44.3 [26.0-64.4] Households (n=1,305) Current OTP enrollment 7 16.7 [8.2-31.0] 6 15.8 [7.3-30.8] 1 33.3 [3.8-86.3] Children 6-59 months (n=42) Current BSFP enrollment 100 11.6 [7.5-17.7] 41 5.6 [7.5-17.7] 57 47.5 [29.4-66.3] Children 6-59 months (n=860) Receipt of MNP since August 25, 2017 107 10.0 [6.9-14.3] 64 6.9 [4.6-10.3] 42 30.0 [17.3-46.7] Children 6-59 months (n=1,073)
3.2.14 Care-seeking Behaviour
Care-seeking behaviour was reported by the caregivers whose child had shown symptoms of diarrhoea, ARI, or fever within the two-week recall period. Among children 6-59 months with reported diarrhoea, the most commonly sought care was at a clinic or hospital 57.0% [47.7-65.8] followed by other care 19.7% [12.2-30.1] (see table 50 below). In 12.2% [8.5-17.2] of cases no care was sought. Among children 6-59 months with a reported cough with fever, care was most commonly sought at a clinic or hospital 64.8% [58.3-70.9] (see table 51 below). In 18.8% [14.2-24.3] of cases no care was sought for a cough with fever. Among children 6-59 months with a reported fever without a cough, care was most commonly sought was at a clinic or hospital 46.1% [37.2-55.3] (see table 52 below). In 29.3% [20.2-40.4] of cases no care sought.
Table 51: MS Two-week Recall of Care-seeking Behaviour for Children 6-59 Months with Diarrhoea
All New Arrivals Old Arrivals Care-seeking for Children (n=458) (n=399) (n=50) 6-59 months with Diarrhoea N % 95% CI N % 95% CI N % 95% CI
Clinic or hospital 261 57.0 [47.7-65.8] 239 60.0 [49.5-69.5] 21 42.0 [30.6-54.3] Community or traditional 13 2.8 [1.6-5.1] 13 3.3 [1.8-5.8] 0 0.0 - healer Pharmacy 38 8.3 [56.0-12.1] 26 6.5 [4.2-9.9] 9 18.0 [8.7-33.5]
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Other care 90 19.7 [12.2-30.1] 77 19.3 [11.2-31.2] 9 18.0 [7.7-36.7]
No care sought 56 12.2 [8.5-17.2] 44 11.0 [7.7-15.6] 11 22.0 [110-39.1]
Table 52: MS Two-week Recall of Care-seeking Behaviour for Children 6-59 Months with Cough
All New Arrivals Old Arrivals Care-seeking for Children (n=640) (n=547) (n=83) 6-59 months with Cough N % 95% CI N % 95% CI N % 95% CI
Clinic or hospital 415 64.8 [58.3-70.9] 355 65.0 [57.7-71.5] 56 67.5 [55.1-77.8] Community or traditional 17 2.7 [1.5-4.6] 16 2.9 [1.7-5.1] 0 0.0 - healer Pharmacy 64 10.0 [7.4-13.4] 49 9.0 [6.3-12.7] 14 17.0 [10.1-26.7]
Other care 24 3.8 [2.1-6.8] 21 3.8 [2.0-7.4] 2 2.4 [0.1-8.8]
No care sought 120 18.8 [14.2-24.3] 106 19.4 [14.3-25.8] 11 13.3 [8.5-20.0]
Table 53: MS Two-week Recall of Care-seeking Behaviour for Children 6-59 Months with Fever
All New Arrivals Old Arrivals Care-seeking for Children (n=280) (n=253) (n=20) 6-59 months with Fever N % 95% CI N % 95% CI N % 95% CI
Clinic or hospital 129 46.1 [37.2-55.3] 116 42.5 [33.6-52.0] Community or traditional 5 1.8 [0.1-4.8] 5 1.8 [0.1-4.9] healer Inadequate sample size for Pharmacy 44 15.7 [10.9-22.1] 37 13.6 [9.1-19.7] disaggregation Other care 20 7.1 [3.3-14.8] 19 7.0 [3.1-15.0]
No care sought 82 29.3 [20.2-40.4] 76 27.8 [18.6-39.4]
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RESULTS Nayapara Refugee Camp November 20th - 27th 2017
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3.3 Nayapara Refugee Camp 3.3.1 Data Quality
In total, among the 584 households surveyed in Nayapara Refugee Camp the teams attempted to survey 408 children 6-59 months. Eight children not present at the time of interview were not located after revisiting. Furthermore, the height data from 2 children were excluded from the analyses per WHO flags, which contributed to the overall percentage of flagged data of 0.5%, well below the SMART methodology recommendation of less than 5.0%. The overall anthropometric analysis utilizes the data from 400 children. In terms of data quantity, a sufficient number of households and children were surveyed. According to the SMART methodology, a minimum of 80% of the sample size must be achieved to ensure data quality. For this survey, 80.8% of planned households and 103% of planned children 6-59 months were surveyed (see Table 53 below), above the SMART methodology cut-off. In total, the survey teams surveyed 584 households of 714 attempted, equaling a NRR of 18%.
Table 54: NYP Households and Children 6-59 months Planned vs. Surveyed
Percentage Planned Children 6-59 Percentage Planned Households Surveyed / Children 6-59 Months Surveyed / Households Surveyed Planned Months Surveyed Planned 723 584 80.8% 388 400 103%
The standard deviation (SD) of WHZ (See table 54) was 0.84, the SD of HAZ was 1.03, and the SD of WAZ was 0.89, all three of which fall within the normal range of 0.8 and 1.2. This indicates an adequate distribution of data around the mean and data of good quality. However, the WHZ SD lost points because it approached 0.80 and was considered “acceptable” by the ENA Plausibility score (see table 55). Other statistical tests administered to test the distribution of the sample included:
Shapiro-Wilk test for normal (Gaussian) distribution of the data, which indicated that WHZ (p=0.674) and HAZ (p=0.576) and WAZ (p=0.781) were all normally distributed. The Skewness coefficient (-0.15) which indicates the distribution of malnutrition in the population was symmetrical (>-0.2 and <0.2) and was considered “excellent” by the ENA Plausibility score. The Kurtosis coefficient (0.00) which indicates the “tails” of data in the distribution were as expected. This wasonsidered “excellent” by the ENA Plausibility score.
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Table 55: NYP Median z-score ± Standard Deviation for WHZ, HAZ, and WAZ
Unavailable Excluded z-scores Excluded z-scores Index N Median z-score ± SD Design Effect z-scores (SMART flags) % (SMART flags) WHZ (6-59 months) 398 -1.09 ± 0.84 1.00 8 2 0.5% HAZ (6-59 months) 392 -1.87 ± 1.03 1.00 8 8 2.0% WAZ (6-59 months) 400 -1.78 ± 0.89 1.00 8 0 0.0%
The sex-ratio between boys and girls 6-59 months was satisfactory at 1.23 boys/girls (p=0.038) indicating that there exists a statistical excess of boys. Upon examination of the data there appears to be an overrepresentation of boys from 30-41 months (sex-ratio = 1.25 boys/girls) and 54-59 months (sex-ratio=1.37 boys/girls) (see table 57 below). This affected the score, with the overall the distribution of sex considered “acceptable” by the ENA Plausibility score. Concerning age, among children 6-59 months included in the sample, only 40% had exact birthdays as confirmed by supportive documentation. The age-ratio between the categories of 6- 29 months and 30-59 months was satisfactory at 0.72 (p=0.102) as this falls near the desired value of 0.85 as recommended by the SMART methodology. Overall, the distribution of age was considered “excellent” by the ENA Plausibility score. Digit preference scores for weight was considered “excellent” while height and MUAC were considered “good” by the ENA Plausibility score with the scores of 6, 12, and 10, respectively. The overall data quality score was 18%, which is considered a survey of “acceptable” quality by the ENA Plausibility score. This final score is best interpreted, however, with an understanding of the context and surveyed population. The WHZ SD is an indicator of the distribution of data around the mean, and seeing a more compressed spread of data around the mean can be attributed to the homogeneity of a population. The Plausibility report is presented in Annex 14.
Table 56: NYP Overall Data Quality per ENA Plausibility Check
Criteria SD Flagged Sex-ratio Age-ratio Digit Pref. Weight
Observed 0.84 0.5% (p=0.038) (p=0.102) 6 Desired 0.8-1.2 < 5% (p>0.05) (p>0.05) < 13 Score Acceptable Excellent Acceptable Excellent Excellent
Criteria Digit Pref. Height Digit Pref. MUAC Skewness Kurtosis Overall Score
Observed 12 10 -0.15 0.00 18 Desired < 13 < 13 < ± 0.6 < ± 0.6 < 15 Score Good Good Excellent Excellent Acceptable
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3.3.2 Demography and Mortality
During the planning stages of the assessment, the average household size was estimated to be 5.4 persons per household and the proportion of children less than five years of age in the population was estimated to be 18.4%. Following the analysis of the data the average household size was determined to be 6.4 persons per household and the proportion of children less than five years of age was found to be 15.0% for the sample surveyed (see table 56 below). Disaggragation of households by refugee status shows that registered refugees had larger households than new arrivals (7.0 vs 5.6 persons per household), yet new arrivals had a greater percentage of pregnant and lactating women (9.1% vs. 5.4%) and children under five years (19.1% vs. 12.1%). These demographic differences may be influenced by the availability of family planning services within Nayapara Refugee Camp.
Table 57: Demographics of Nayapara Refugee Camp
All Households Registered Refugees New Arrivals Population Subset N % 95% CI N % 95% CI N % 95% CI All Household Members* 3,093 100.0 - 1,746 56.5 - 1,206 40.0 - Average HH size, mean (SD) 6.4 (2.6) 7.0 (2.7) 5.6 (2.2) All, <5 years 464 15.0 [13.8-16.3] 211 12.1 [10.6-13.7] 230 19.1 [17.0-21.4] All, 5-10 years 613 19.8 [18.5-21.3] 329 18.8 [17.1-20.8] 249 20.7 [18.5-23.0] All, 11-17 years 656 21.2 [19.8-22.7] 419 24.0 [22.1-26.1] 216 18.0 [16.0-20.2] All, 18-59 years 1,264 40.9 [39.2-42.6] 730 41.8 [33.5-44.1] 479 39.7 [37.0-42.5] All, ≥60 years 96 3.1 [2.6-3.8] 57 3.3 [2.5-4.2] 32 2.7 [1.9-3.7] Female 1,580 51.1 [49.3-52.8] 883 50.6 [48.2-52.9] 629 52.2 [49.3-55.0] Women, 15-49 Years 754 24.4 [22.9-25.9] 443 25.4 [23.4-27.5] 281 23.3 [21.0-25.8] Pregnant and lactating women 217 7.0 [6.2-8.0] 95 5.4 [4.5-6.6] 110 9.1 [7.6-10.9] Pregnant women 67 2.2 [1.7-2.7] 32 1.8 [1.3-2.6] 32 2.7 [1.9-3.7] Lactating women 150 4.9 [4.2-5.7] 63 3.6 [2.8-4.6] 78 6.5 [5.2-8.0] Lactating w/child < 6 months 52 1.7 [1.3-2.2] 24 1.4 [0.9-2.0] 28 2.3 [1.6-3.3] Lactating w/child > 6 months 98 3.2 [2.6-3.9] 39 2.2 [1.6-3.0] 50 4.2 [3.2-5.4] Number of days to arrive from Question not asked of registered households 6.1 days (5.6) Myanmar, mean (SD) *Demographics include all current household members, regardless of presence at time of interview
Of the 400 children 6-59 months of age included in the anthropometric analyses, 181 were from registered refugee households, 197 were from new arrival households, and 21 were from old
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arrival households. One child was missing an arrival date and therefore was not included in disaggregated analyses. The distribution of age of children 6-59 months demonstrates relatively equal representation of children 6-23 months and children 24-59 months (see Figure 15 below). The distribution shows distinct peaks at 37 and 39 months as well as slight peaks at 11, 24, and 54 months.
Figure 15: NYP Age Distribution of Children 6-59 months
18
16
14
12
10
8
6 NumberChildren of 4
2
0 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 Age in Months
Table 58: NYP Distribution of Age and Sex, Children 6-59 months
Age Category Boys Girls Total Ratio (months) boy : girl N % N % N % 6-17 47 52.2 43 47.8 90 22.1 1.1 18-29 43 53.1 38 46.9 81 19.9 1.1 30-41 60 55.6 48 44.4 108 26.5 1.3 42-53 46 53.5 40 46.5 86 21.1 1.1 54-59 29 67.4 14 32.6 43 10.5 2.1 Total 225 55.1 183 44.9 408 100.0 1.2
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The Crude Death Rate (CDR) for Nayapara Refugee Camp was 0.75 [0.56-1.01], well above the CDR Emergency Threshold of 0.4 for the South Asian Region per Sphere Standards. The under five Death Rate (UDR) for Nayapara Refugee Camp was 0.80 [0.37-1.73] falling just below the Emergency Threshold of 0.9 for the South Asian Region per Sphere Standards.
3.3.3 Prevalence of Acute Malnutrition by WHZ
The prevalence of acute malnutrition by WHZ was based on the analysis of 398 children, after the exclusion of two children per SMART flags or 0.5% of the data. The distribution curve of figure 16 below illustrates the distribution of the WHZ for the surveyed sample (the red curve) in comparison with the WHO 2006 reference population (the green curve). There were no identified cases of oedema in Nayapara Refugee Camp. The WHZ mean is -1.09 with a standard deviation of ± 0.84 (the standard deviation falls between 0.8 and 1.2 indicating data of good quality). The red curve representing the surveyed population is shifted to the left of the reference population, demonstrating that the acute malnutrition status of the surveyed population is inferior. The reduced spread of the population curve was likely influenced by the homogeneity of the population. The prevalence of acute malnutrition global and severe per WHZ are presented in table 58 below:
Figure 16: NYP Distribution of the WHZ of the Sample Compared to the WHO 2006 Reference
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The prevalence of GAM among children 6-59 months in Nayapara Refugee Camp per WHZ was 14.3% [11.2-18.1] just below the WHO emergency cut-off of 15% and falling in the category of “serious”, as is the lower confidence interval of 11.2% (see table 58 below). This prevalence was slightly higher among new arrivals than registered refugees (15.8% vs. 12.2%), a difference which was not found to be statistically significant. The prevalence of MAM in Nayapara Refugee Camp was 13.1% [10.1-16.7] and was also slightly higher among new arrivals than registered refugees (13.8% vs. 11.6%), but also not found to be statistically significant. The prevalence of SAM in Nayapara Refugee Camp was 1.3% [0.5-2.9] which was also slightly higher in the new arrivals than the registered refugees (2.0% vs. 0.6%), although not statistically significant. Upon disaggregation of the prevalence of GAM into age categories, children 6-23 months had a higher prevalence of GAM than children 24-59 months (24.8% vs. 10.6%). There was a statistically significant association between age and GAM per WHZ (OR 2.78 [95% CI 1.58-4.89]) (p=0.001). This suggests that children under two years of age are more susceptible to acute malnutrition than children 24-59 months in Nayapara Refugee Camp. Results from all 2x2 statistical analyses for Nayapara Refugee Camp are available in Annex 3.
Table 59: NYP Prevalence of Acute Malnutrition in Nayapara Refugee Camp per WHZ and/or Oedema, WHO Reference 2006
Moderate Acute Severe Acute Global Acute Malnutrition Children 6-59 months N Malnutrition Malnutrition N % 95% CI N % 95% CI N % 95% CI All 398 57 14.3 [11.2-18.1] 52 13.1 [10.1-16.7] 5 1.3 [0.5-2.9] Registered 181 22 12.2 [8.2-17.7] 21 11.6 [7.7-17.1] 1 0.6 [0.1-3.1] New Arrivals 196 31 15.8 [11.4-21.6] 27 13.8 [9.6-19.3] 4 2.0 [0.8-5.1] Children 6-23 months 117 29 24.8 [17.8-33.3] 23 19.7 [13.5-27.8] 6 5.1 [2.4-10.7] Children 24-59 months 283 30 10.6 [7.5-14.7] 29 10.2 [7.2-14.3] 1 0.4 [0.1-2.0]
Regarding acute malnutrition by WHZ among children 6-59 months as disaggregated by sex, the prevalence of GAM was higher for boys than girls in Nayapara Refugee Camp (18.7% vs. 8.9%). There was a statistically significant association between sex and prevalence of GAM (OR 2.35 [95% CI 1.27-4.34]) (p=0.006) (see table 59 below). The prevalence of MAM was also higher for boys than girls (17.4% vs. 7.8%), with a statistically significant association between sex and prevalence of MAM (OR 2.47 [95% CI 1.29-4.73] (p=0.007). The prevalence of SAM was also higher for boys than girls (1.4% vs. 1.1%), yet this difference was not found to be statistically significant. These results suggest that boys 6-59 months in Nayapara Refugee Camp were more vulnerable to acute malnutrition than girls.
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Table 60: NYP Prevalence of Acute Malnutrition by Sex per WHZ and/or Oedema, WHO Reference 2006
Moderate Acute Severe Acute Global Acute Malnutrition Children 6-59 months Malnutrition Malnutrition N % 95% CI N % 95% CI N % 95% CI All 57 14.3 [11.2-18.1] 52 13.1 [10.1-16.7] 5 1.3 [0.5-2.9] (n=398) Boys 41 18.7 [14.1-24.4] 38 17.4 [12.9-22.9] 3 1.4 [0.5-3.9] (n=219) Girls 16 8.9 [5.6-14.0] 14 7.8 [4.7-12.7] 2 1.1 [0.3-4.0] (n=179)
Regarding acute malnutrition by WHZ among children 6-59 months as disaggregated by age category, the prevalence of SAM was highest among the 18-29 month category (3.8%) followed by the 6-17 month category (2.4%) (see table 60 below). No SAM cases were reported in children older than 29 months in Nayapara Refugee Camp. The prevalence of MAM was highest among the 6-17 month category (20.2%), while, the age category with the lowest MAM prevalence was the 42-53 month category (9.3%). Overall, the age category with the highest percentage of children who were not acutely malnourished was the 42-53 month category (90.7%). These findings suggest that the younger age categories are more vulnerable to acute malnutrition.
Table 61: NYP Prevalence of Acute Malnutrition by Age per WHZ and/or Oedema, WHO Reference 2006
Severe Acute Moderate Acute Not Acutely Edema Malnourished Malnutrition Malnourished Age (months) Total N % N % N % N % 6-17 84 2 2.4 17 20.2 65 77.4 0 0.0 18-29 80 3 3.8 10 12.5 67 83.8 0 0.0 30-41 106 0 0.0 10 9.4 96 90.6 0 0.0 42-53 80 0 0.0 8 9.3 78 90.7 0 0.0 54-59 42 0 0.0 7 16.7 35 83.3 0 0.0 Total 398 5 1.3 52 13.1 341 85.7 0 0.0
3.3.4 Prevalence of Acute Malnutrition by MUAC
The prevalence of acute malnutrition in children 6-59 months of age per MUAC was lower than the prevalence per WHZ, discussed in greater detail in section 3.3.5. The prevalence of GAM in Nayapara Refugee Camp per MUAC was 7.0% [4.9-9.9] which, according to the IPC Classification falls under “Alert-Serious” (see table 61 below). The prevalence of GAM per MUAC Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 95
was higher for new arrivals than registered refugees (9.6% vs. 4.4%), but this difference was not found to be statistically significant. The prevalence of MAM in Nayapara Refugee Camp per MUAC was 5.3% [3.5-7.9], and this prevalence was somewhat higher among new arrivals than registered refugees (7.1% vs. 3.3%), although this was not found to be statistically significant. The prevalence of SAM in Nayapara Refugee Camp per MUAC was 1.8% [0.9-3.6], with a slightly higher prevalence among new arrivals than registered refugees (2.5% vs. 1.1%), although this was not found to be statistically significant. When disaggregated by age category, children 6-23 months had a much higher prevalence of GAM per MUAC than children 24-59 months (18.8% vs. 2.1%). There was a statistically significant association between age and GAM per MUAC (OR 10.7 [95% CI 4.21-27.2]) (p=0.001). This suggests that children 6-23 months were more than ten times as likely to suffer from acute malnutrition than children 24-59 months in Nayapara Refugee Camp as determined by MUAC.
Table 62: NYP Prevalence of Acute Malnutrition by MUAC
Moderate Acute Severe Acute Global Acute Malnutrition Children 6-59 months N Malnutrition Malnutrition N % 95% CI N % 95% CI N % 95% CI All 400 28 7.0 [4.9-9.9] 21 5.3 [3.5-7.9] 7 1.8 [0.9-3.6] Registered 181 8 4.4 [2.3-8.5] 6 3.3 [1.5-7.0] 2 1.1 [0.3-3.9] New Arrivals 197 19 9.6 [6.3-14.6] 14 7.1 [4.3-11.6] 5 2.5 [1.1-5.8] Children 6-23 months 117 22 18.8 [12.8-26.8] 15 12.8 [7.9-20.1] 7 6.0 [2.9-11.8] Children 24-59 months 283 6 2.1 [1.0-4.5] 6 2.1 [1.0-4.5] 0 0.0 -
The prevalences of acute malnutrition per MUAC as disaggregated by age category (see figure 17 below) demonstrate that the highest prevalence of GAM, MAM, and SAM per MUAC were within the youngest age category of 6-17 months. All seven SAM cases per MUAC were in this category, giving it a SAM prevalence of 8.1%, and a MAM prevalence of 14.0% (overall GAM prevalence of 22.1%). In contrast, no cases of acute malnutrition were identified in the age categories of 42-53 months and 54-59 months by MUAC.
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Figure 17: NYP Prevalence of Acute Malnutrition by Age per MUAC
3.3.5 Prevalence of Acute Malnutrition WHZ vs. MUAC
The prevalence of acute malnutrition among children 6-59 months was notably different as identified by WHZ and MUAC in Nayapara Refugee Camp. The prevalence of GAM was twice as high per WHZ (14.3% vs. 7.0%) and the prevalence of MAM was more than twice as high per WHZ (13.1% vs. 5.3%). However, the prevalence of SAM was slightly higher as identified per MUAC than WHZ (1.8% vs. 1.3%). As demonstrated in figure 18 below, overall, 57 cases of GAM were identified per WHZ and 26 cases of GAM were identified per MUAC. Of the 57 cases, 71.9% (41) of them were not identified as GAM according to MUAC. When disaggregated by age category, the difference in GAM per WHZ of children 6-23 months vs. 24-59 months (24.8% vs. 10.6%) was statistically significant with an odds ratio of 2.78.The difference in GAM per MUAC of children 6-23 months vs. 24-59 months (18.8% vs. 2.1%) was also statistically significant, but with an odds ratio of 10.69. This disparity between numbers of identified cases and odds ratios for children 6-23 months was likely influenced by MUAC’s known bias towards identifying acute malnutrition in younger and small children50.
50 Briend A, Golden MH, Grellety Y, Prudhon C, Hailey P. (1995) Use of mid-upper-arm circumference for nutritional screening of refugees Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 97
Figure 18: NYP Prevalence of Acute Malnutrition WHZ vs. MUAC
3.3.6 Low MUAC in Women
Low MUAC in women was defined as a mid-upper arm circumference below 210mm for the purposes of this assessment. The results from Nayapara Refugee Camp indicated a prevalence of low MUAC among women 15-49 years of 3.5% [2.3-5.1] (see table 62 below). This prevalence was very similar between new arrival women and registered women (3.4% vs. 3.7%). Low MUAC for all pregnant and lactating women in the sample regardless of population subset was 3.8%, but this was not statistically significant compared to the rest of the women in the sample. The average MUAC for the women in Nayapara Refugee Camp was 257mm.
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Table 63: NYP Low MUAC in Women 15-49 Years
MUAC <210mm Women 15-49 years N N % [95% CI] All 693 24 3.5 [2.3-5.1] Registered Refugees 402 15 3.7 [2.3-6.1] New Arrivals 262 9 3.4 [1.8-6.5] PLW 212 8 3.8 [1.9-7.4]
Women 15-49 years N Mean MUAC (SD)
All 693 257mm (34.58)
3.3.7 Low MUAC in Infants
The cut off for low MUAC for infants 0-5 months was assessed at <115mm, <110mm, and <105mm for this assessment (see table 63 below). Within Nayapara Refugee Camp it was found that 42.3% of infants 0-5 months were <115mm, 23.1% were <110mm, and 15.4% were <105mm. The mean MUAC measurement of infants 0-5 months was 118mm.
Table 64: NYP Low MUAC in Infants 0-5 Months
Infants 0-5 months Low MUAC (n=52) N % [95% CI] MUAC <115mm 22 42.3 [29.3-56.4] MUAC <110mm 12 23.1 [13.3-36.9] MUAC <105mm 8 15.4 [7.7-28.4] Infants 0-5 months N Mean MUAC (SD) All 52 118mm (13.2)
3.3.8 Prevalence of Chronic Malnutrition
The prevalence of chronic malnutrition among children 6-59 months in Nayapara Refugee Camp was 44.4% [39.5-49.3], above the WHO cut-off of 40% indicating it is of critical public health significance (see table 64 below). This global prevalence was very similar among new arrivals and registered refugees (44.3% vs. 44.7%). The prevalence was also similar among new arrivals and registered refugees for moderate chronic malnutrition (31.4% vs. 33.0%), and severe chronic malnutrition (12.9% vs. 11.7%). These persistently high prevalences of chronic
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malnutrition speak to the long-term malnutrition context in both Rakhine State as well as Nayapara Refugee Camp.
Table 65: NYP Prevalence of Chronic Malnutrition by HAZ, WHO Reference 2006
Global Chronic Moderate Chronic Severe Chronic Children 6-59 months N Malnutrition Malnutrition Malnutrition N % 95% CI N % 95% CI N % 95% CI All 392 174 44.4 [39.5-49.3] 125 31.9 [27.5-36.7] 49 12.5 [9.6-16.1] Registered 179 80 44.7 [37.6-52.0] 59 33.0 [26.5-40.1] 21 11.7 [7.8-17.3] New Arrivals 194 86 44.3 [37.5-51.4] 61 31.4 [25.3-38.3] 25 12.9 [8.9-18.3]
3.3.9 Prevalence of Underweight
The prevalence of underweight among children 6-59 months in Nayapara Refugee Camp was 40.8% [36.0-45.6], well above the WHO cut-off of 30%, indicating it is of critical public health significance (see table 65 below). This prevalence was slightly higher among new arrivals than registered refugees (42.6% vs. 38.7%), as was moderate underweight (33.5% vs. 31.5%), and severe underweight (9.1% vs. 7.2%), although these differences were not statistically significant. As this malnutrition indicator acts as a composite score between acute and chronic malnutrition, it speaks to both the long-term and short-term effects of malnutrition on the population in Rakhine State and within Nayapara Refugee Camp.
Table 66: NYP Prevalence of Underweight by WAZ, WHO Reference 2006
Global Underweight Moderate Underweight Severe Underweight Children 6-59 months N N % 95% CI N % 95% CI N % 95% CI All 400 163 40.8 [36.0-45.6] 129 32.3 [27.9-37.0] 34 8.5 [6.1-11.6] Registered 181 70 38.7 [31.9-45.9] 57 31.5 [25.2-38.6] 13 7.2 [4.2-11.9] New Arrivals 197 84 42.6 [35.9-49.6] 66 33.5 [27.3-40.4] 18 9.1 [5.9-14.0]
3.3.10 Prevalence of Anaemia
Anaemia was measured among all children 6-59 months once consent was granted. The overall prevalence of anaemia was 46.6% [41.8-51.6] within Nayapara Refugee Camp, well above the WHO cut-off of 40% for a significant public health concern (see table 66 below). This prevalence was slightly higher among new arrivals than registered refugees (48.7% vs. 46.1%), although this was not statistically significant. When the sample was disaggregated by age, the Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 100
prevalence of anaemia was notably higher among children 6-23 months than children 24-59 months (65.0% vs. 39.0%). There was a statistically significant association between age and anaemia (OR 2.90 [95% CI 1.85-4.54]) (p=0.001). This suggests that children 6-23 months were nearly 3 times as likely to suffer from anaemia than children 24-59 months in Nayapara Refugee Camp. No cases of severe anaemia were identified. Overall, these findings indicate that nearly half of the children 6-59 months were suffering from anaemia in Nayapara Refugee Camp, with children under two years the most vulnerable.
Table 67: NYP Prevalence of Anaemia in Children 6-59 months per WHO
All Registered New Arrivals Children 6-59 months (n=399) (n=180) (n=197) N % 95% CI N % 95% CI N % 95% CI Any Anaemia 186 46.6 [41.8-51.6] 83 46.1 [38.9-53.5] 96 48.7 [41.8-55.7] (Hb<11.0 g/dL) Mild Anaemia 124 31.1 [26.7-35.8] 62 34.4 [27.8-41.7] 59 30.0 [23.9-36.7] (Hb 10.0 to <11.0 g/dL) Moderate Anaemia 62 15.5 [12.3-19.5] 21 11.7 [7.7-17.3] 37 18.8 [13.9-24.9] (Hb 7.0 to <10.0 g/dL) Severe Anaemia 0 0.0 - 0 0.0 - 0 0.0 - (Hb <7.0 g/dL)
Any Anaemia 76 65.0 [55.9-73.1]
(Hb<11.049) g/dL)
23 23
- Mild Anaemia 47 40.2 [31.7-49.3]
(Hb(n=3 10.0 to <11.0 g/dL) Moderate(n Anaemia
months 29 24.8 [17.8-33.4] (Hb 7.0 to <10.0 g/dL)
Children 6 Children Severe Anaemia
(n=117) 0 0.0 - (Hb <7.0(n= g/dL) Inadequate sample size for disaggregation Any Anaemia
) 110 39.0 [33.5-44.9] (Hb<11.0 g/dL)
59 - Mild Anaemia 77 27.3 [22.4-32.8]
(n=282 (Hb 10.0 to <11.0 g/dL) Moderate Anaemia 33 11.7 [8.4-16.0] (Hb 7.0 to <10.0 g/dL)
Children 24 Children
months Severe Anaemia 0 0.0 - (Hb(n= <7.0 g/dL)
3.3.11 Prevalence of Morbidity
The prevalence of diarrhoea among children 6-59 months per two-week recall was 34.3% [30.0-39.1] within Nayapara Refugee Camp (see table 67 below). This was notably higher among new arrivals than registered refugees (40.7% vs. 26.9%). There was a statistically significant association between arrival subset and prevalence of diarrhoea (OR 1.87 [95% CI 1.21-2.87])
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(p=0.005). This suggests that new arrival children 6-59 months were nearly twice as likely to suffer from diarrhoeal disease than registered refugees. The prevalence of diarrhoea was also higher for children 6-23 months than children 24-59 months (47.9% vs. 28.6%). There was a statistically significant association between age and prevalence of diarrhoea (OR 2.30 [95% CI 1.48-3.57]) (p=0.001). This suggests that children 6-23 months are more than twice as likely to suffer from diarrhoeal disease than children 24-59 months. The prevalence of acute respiratory infection with fever among children 6-59 months per two-week recall was 50.3% [45.4-55.1] within Nayapara Refugee Camp. The rates were similar between new arrivals and registered refugees (50.3% vs. 50.5%). The prevalence of ARI was also higher among children 6-23 months than children 24-59 months (55.4% vs. 48.1%), however this was not found to be statistically significant. The prevalence of fever without cough among children 6-59 months per two-week recall was 16.9% [13.6-20.9] within Nayapara Refugee Camp. The rates were somewhat higher among new arrivals than registered refugees (19.6% vs. 15.6%), although this was not found to be statistically significant. The rates were also slightly higher in children 6-23 months than children 6-59 months (18.2% vs. 16.4%), a difference which was also not found to be statistically significant. The morbidity indicators suggest that new arrivals and children under two are more vulnerable to diarrhoeal disease, and may be more vulnerable to other communicable diseases in Nayapara Refugee Camp. Table 68: NYP Two-week Prevalence of Diarrhoea, Cough, and Fever in Children 6-59 Months
All Registered New Arrivals Children 6-59 months (n=408) (n=186) (n=199) N % 95% CI N % 95% CI N % 95% CI
Diarrhoea 140 34.3 [30.0-39.1] 50 26.9 [21.0-33.7] 81 40.7 [34.1-47.7]
Children 6-23 months (n=121) 58 47.9 [39.2-56.8] Inadequate sample size for disaggregation Children 24-59 months (n=287) 82 28.6 [23.6-34.1] Acute Respiratory Infection with 205 50.3 [45.4-55.1] 94 50.5 [43.4-57.7] 100 50.3 [43.3-57.2] Fever Children 6-23 months (n=121) 67 55.4 [46.4-64.0] Inadequate sample size for disaggregation Children 24-59 months (n=287) 138 48.1 [42.3-53.9]
Fever without Cough 69 16.9 [13.6-20.9] 29 15.6 [11.0-21.6] 39 19.6 [14.6-25.7]
Children 6-23 months (n=121) 22 18.2 [12.3-26.1] Inadequate sample size for disaggregation Children 24-59 months (n=287) 47 16.4 [12.5-21.1]
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3.3.12 IYCF Indicators
It is important to note when interpreting the IYCF indicators from this assessment, that the survey sample sizes were calculated based on anticipated prevalences of GAM for children 6-59 months. The sample size and precision were not calculated for IYCF indicators, leading to lower precision and larger confidence intervals for some of the results. The IYCF results of this survey should therefore be interpreted with caution and in consideration of the width of their associated confidence intervals. Within Nayapara Refugee Camp, 97.7% [94.0-99.2] of children 0-23 months had been breastfed at some point prior to the survey date, and this rate was similar among new arrivals and registered refugees (96.9% vs. 98.6%) (see table 68 below). The timely initiation of breastfeeding is defined as “the provision of mother’s breast milk to infants within one hour of birth” per the WHO. Of the caregivers interviewed in Nayapara Refugee Camp with a child 0-23 months, 48.5% [41.1-56.1] reported that breastfeeding had been initiated within one hour of birth, 42.1% between one and 24 hours after birth, and 8.8% more than 24 hours after birth. The prevalence of timely initiation of breastfeeding was statistically significantly (P=0.0129) higher among registered refugees than new arrivals (59.4% vs. 39.8%) a difference which was likely influenced by the accessibility of supportive IYCF services within the camp. Of the caregivers interviewed with an infant 0-5 months, 72.2% [58.4-82.8] reported exclusively breastfeeding the infant the day preceding the survey. Of the caregivers interviewed with a child 12-15 mnths, 96.4% [76.3-99.6] reported continued breastfeeding of the child until one year of age. Of the caregivers interviewed with a child 20-23 months, 66.7% [42.7-84.3] reported continued breastfeeding of the child until one year of age. Of the caregivers interviewed with an infant 6-8 months, 94.7% [66.2-99.4] reported the infant was being fed complementary foods. This indictor should be interpreted with caution, however, because of the small sample size (n=19). Minimum dietary diversity was reported as 15.7% [10.2-23.4] among children 6-23 months. This was slightly higher among new arrivals than registered refugees (14.9% vs. 13.3%). Minimum meal frequency was reported as 65.3% [56.3-73.3] among children 6-23 months. This was slightly higher among new arrivals than registered refugees (65.7% vs. 62.2%). Minimum acceptable diet was reported as 15.7% [10.2-23.4] among children 6-23 months. This was slightly higher among new arrivals than registered refugees (14.9% v. 13.3%).
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Table 69: NYP Infant and Young Child Feeding Indicators
Infants and Young Children 0-23 All Registered New Arrivals months (n=175) N % 95% CI N % 95% CI N % 95% CI Ever breastfed 171 97.7 [94.0-99.2] 69 98.6 [90.4-99.8] 93 96.9 [90.7-99.0] Infants 0-23 months (n=175) Timely initiation of breastfeeding 83 48.5 [41.1-56.1] 41 59.4 [47.4-70.4] 37 39.8 [30.3-50.1] Infants 0-23 months (n=171) Exclusive breastfeeding 39 72.2 [58.4-82.8] Infants 0-5 months (n=54) Cont. breastfeeding at one year 27 96.4 [76.3-99.6] Children 12-15 months (n=28) Inadequate sample size for disaggregation Cont. breastfeeding at two years 14 66.7 [42.7-84.3] Children 20-23 months (n=21) Introd. of complementary Foods 18 94.7 [66.2-99.4] Infants 6-8 months (n=19) Minimum dietary diversity 19 15.7 [10.2-23.4] 6 13.3 [6.0-26.9] 10 14.9 [8.2-25.8] Children 6-23 months (n=121) Minimum meal frequency 79 65.3 [56.3-73.3] 28 62.2 [47.2-75.2] 44 65.7 [53.4-76.1] Children 6-23 months (n=121) Minimum acceptable diet 19 15.7 [10.2-23.4] 6 13.3 [6.0-26.9] 10 14.9 [8.2-25.8] Children 6-23 months (n=121)
Overall, children 6-23 months in Nayapara Refugee Camp scored poorly on all IYCF indicators. Figure 19 below shows the frequency of liquids or beverages consumed during the 24 hours preceeding the survey for two age groups: infants 0-5 months and children 6-23 months. This indicator aimed to look at what could be displacing breastmilk. Among infants 0-5 months, an age where exclusive breastfeeding is crucial for optimal health, the beverages most frequently consumed were water (37.8%) thin porridge (9.6%), and milk (8.1%). Fewer infants 0-5 months consumed formula (3.7%), other (3.7%), and juice (1.9%). No infants 0-5 months reported having consumed tea or coffee, yogurt, or broth during the 24-hour recall. Among children 6-23 months, an age where complementary foods in addition to continued breastfeeding are advised, the beverages most frequently consumed in the 24 hours preceeding the survey were water (94.2%), thin porridge (54.6%), and juice (18.2%). Fewer children were reported to have consumed other beverages at 9.9%, milk at 7.4%, tea or coffee at 4.1%, formula at 3.3%, yogurt at 2.5%, and broth at 1.7%. A complete list of the beverages considered in each category is available in Annex 6. Additionally, there is a common practice in parts of Myanmar and Bangladesh where a newborn is fed a sweet beverage (sweetened with sugar or honey) just after birth. It is thought that giving the child such a drink will cause the child to speak sweetly later in life. Caregivers were specifically asked about this practice for children 0-23 months. In Nayapara Refugee Camp, 58.9% of caregivers reported having given their newborn a sweet drink shortly after birth.
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Figure 19: NYP 24-Hour Recall of Consumption of Liquids in Children 6-23 Months
24-Hour Recall Consumption of Liquids
Infants 0-5 months (n=54) Children 6-23 months (n=120)
3.7% Other 9.9%
Tea or Coffee 4.1% 9.6% Thin Porridge 54.6%
Yogurt 2.5%
Broth 1.7% 1.9% Juice 18.2% 8.1% Milk 7.4% 3.7% Infant Formula 3.3% 37.8% Water 94.2% 0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0% 90.0% 100.0%
Figure 20 below shows categories of food consumed with the highest frequency in the 24 hours preceeding the survey. The most commonly consumed food group was “grain” at 78.5% and the least commonly consumed food group was “dairy” at 0.8%. The high rate of grain consumption was consistent with the general food distributions WFP had been providing to the population which consisted mainly of rice, and the low dairy intake likely has a cultural component. The “meat/fish” category was the second most commonly consumed food group at 46.3%, which was likely influenced by the fishing livelihoods in the region. The consumption frequencies of food category between new arrival children and registered refugee children 6-23 months were very similar, with new arrivals consuming slightly more from the grain category (82.1% vs. 75.6%) and vitamin A rich fruits and vegetables category (49.3% vs. 42.2%). A complete list of the food items in each category is available in Annex 6.
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Figure 20: NYP 24-Hour Recall of Food Group Consumption in Children 6-23 Months
24-hour Recall Consumption of Food Groups
90% 82.10% 78.5% 80% 75.6%
70%
60% 49.30% 50% 44.4% 46.3% 43.8% 43.30% 42.2% 40%
30% 24.4% 24.4% 23.1% 22.40% 18.2% 20% 14.90% 9.00% 10% 5.8% 0.8% 1.50% 0.0% 0.0% 0% Grain Legume Dairy Meat/Fish Egg VitA Fruit Veg Other Fruit Veg All Registered New Arrivals
3.3.13 Receipt of Services
Measles vaccination coverage was assessed by documentation or household recall. Among children 6-59 months, the measles vaccination coverage was 88.0% [84.5-90.8] within Nayapara Refugee Camp (see table 69 below). This was similar among registered refugees and new arrivals (88.7% vs. 86.9%). This similarity in coverage is most likely reflecting the measles campaign which was conducted in Nayapara Refugee Camp Nov 20th-22nd, 2017, during the first three days of the survey. Meanwhile, the rate of measles immunisations evidenced by a vaccination card was 44.6% [39.8-49.5], higher than expected likely because of the recent campaign, as the percentage was very similar for registered refugees and new arrivals (44.1% vs. 43.2%). OCV coverage was assessed by household recall. Among all persons over one year of age, the OCV coverage was determined to be 87.3% [86.0-88.4] in Nayapara Refugee Camp. This coverage was slightly higher among registered refugees than new arrivals (89.8% vs. 83.2%), as well as registered and new arrival children 12-59 months (98.8% vs. 91.8%), and registered and new arrival persons ≥5 years (88.8% vs. 81.6%).
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The receipt of GFD indicator is defined as any household from which a household member has received at least one bag of rice since August 25th, 2017. Per this operational definition, 86.4% [81.7-90.1] of new arrival households recieved GFD. This question was not asked of registered refugee households as they were not eligible for this distribution. At the time of the assessment, 27 children were identified as SAM. Only 3 children were found to be enrolled in the OTP. Among the registered population 12.5% of the children were enrolled in the OTP, while among the new arrivals only 10.5% were enrolled in the OTP. Looking at the children eligible for enrollment in BSFP, a total of 82 children were found eligible. However only 47 children were enrolled in the BSFP at the time of the assessment with 69.4% of the registered population and only 25.0% of the new arrival population enrolled. Lastly, 110 children 6-23 months were identified eligible for MNP. However only 18 children had received MNP at time of the assessment with 34.2% of the registered population and only 3.3% of the new arrival population were enrolled.
Table 70: NYP Receipt of Immunizations and Food/Nutrition Assistance
Measles Vaccination All Registered New Arrivals (recall since August 25, 2017) N % 95% CI N % 95% CI N % 95% CI Confirmed by vaccination card or caregiver 359 88.0 [84.5-90.8] 165 88.7 [83.3-92.5] 173 86.9 [81.5-91.0] Children 6-59 months (n=408) Children 6-23 months 103 85.1 [77.6-90.4] 40 88.9 [75.8-95.3] 55 82.1 [70.9-89.6] (n=121) Children 24-59 months 256 89.2 [85.0-92.3] 125 88.7 [82.2-93.0] 118 89.4 [82.8-93.6] (n=287) Confirmed by vaccination card 182 44.6 [39.8-49.5] 82 44.1 [37.1-51.3] 86 43.2 [36.5-50.2] Children 6-59 months (n=408) Confirmed by caregiver 177 43.4 [38.6-48.3] 83 44.6 [37.6-51.9] 87 43.7 [37.0-50.7] Children 6-59 months (n=408) Not vaccinated 46 11.3 [8.5-14.7] 20 10.8 [7.0-16.1] 25 12.6 [8.6-18.0] Children 6-59 months (n=408) Unknown 3 0.7 [0.2-2.3] 1 0.5 [0.0-3.7] 1 0.5 [0.0-3.5] Children 6-59 months (n=408) Oral Cholera Vaccine N % 95% CI N % 95% CI N % 95% CI (recall since August 25, 2017) All persons ≥ 1 year of age 2,620 87.3 [86.0-88.4] 1,531 89.8 [88.3-91.2] 963 83.2 [80.9-85.2] (n=3,002) Children 12-59 months 355 95.2 [92.5-97.0] 168 98.8 [95.4-99.7] 167 91.8 [86.8-95.0] (n=373) Persons ≥ 5 years of age 2,265 86.2 [84.8-87.4] 1,363 88.8 [87.1-90.3] 796 81.6 [79.0-83.9] (n=2,629) Food Assistance N % 95% CI N % 95% CI N % 95% CI
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Receipt of GFD since August 25, 2017 Registered refugees not included in GFDs 223 86.4 [81.7-90.1] New arrival households (n=258) Current OTP enrollment 3 11.1 [3.4-31.1] 1 12.5 [1.5-57.3] 2 10.5 [2.4-36.0] Children 6-59 months (n=27) Current BSFP enrollment 47 57.3 [46.2-67.7] 25 69.4 [52.4-82.5] 15 25.0 [36.4-37.0] Children 6-23 months (n=82) Receipt of MNP since August 25, 2017 18 16.4 [10.5-24.6] 14 34.2 [20.9-50.4] 2 3.3 [0.8-12.6] Children 6-59 months (n=110)
3.3.14 Care-seeking Behaviour
Assessing care-seeking behaviour is another method for understanding a population’s preferences and access to services. Care-seeking behaviour was reported by the caregivers whose child had shown symptoms of diarrhoea, ARI, or fever within the two-week recall period. Among children 6-59 months with reported diarrhoea, care was most commonly sought at a clinic or hospital (63.6% [55.2-71.2]) (see table 70 below). In 16.4% [11.1-23.6] of cases no care was sought for symptoms of diarrhoea. Among children 6-59 months with a reported cough with fever, care was most commonly sought at a clinic or hospital (72.7% [66.1-78.4]) (see table 71 below). In 14.2% [10.0-19.7] of cases no care was sought for symptoms of ARI. Among children 6-59 months with a reported fever without a cough, care was most commonly sought care at a clinic or hospital (60.9% [48.7-71.9]), followed by the local pharmacy (18.8% [11.1-30.1] ) and no care sought (18.8% [11.1-30.1]) (see table 72 below).
Table 71: NYP Two-week Recall of Care-seeking Behaviour for Children 6-59 Months with Diarrhoea
All Registered New Arrivals Care-seeking for Children (n=140) (n=50) (n=81) 6-59 months with Diarrhoea N % 95% CI N % 95% CI N % 95% CI
Clinic or hospital 89 63.6 [55.2-71.2] 30 60.0 [45.8-72.7] 53 65.4 [53.4-75.1] Community or traditional 0 0.0 - 0 0.0 - 0 0.0 - healer Pharmacy 10 7.1 [3.9-12.9] 5 10.0 [4.2-22.1] 4 4.9 [1.8-12.6]
Other care 18 12.9 [8.2-19.6] 8 16.0 [8.1-29.1] 9 11.1 [5.8-20.1]
No care sought 23 16.4 [11.1-23.6] 7 14.0 [6.8-26.8] 15 18.5 [11.4-28.6]
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Table 72: NYP Two-week Recall of Care-seeking Behaviour for Children 6-59 Months with Cough
All Registered New Arrivals Care-seeking for Children (n=205) (n=94) (n=100) 6-59 months with Cough N % 95% CI N % 95% CI N % 95% CI
Clinic or hospital 149 72.7 [66.1-78.4] 72 76.6 [67.0-84.1] 72 72.0 [62.4-80.0] Community or traditional 4 1.9 [0.7-5.1] 2 2.1 [0.5-8.0] 1 1.0 [0.01-6.9] healer Pharmacy 18 8.8 [5.6-13.6] 10 10.6 [5.8-18.7] 6 6.0 [2.7-12.8]
Other care 5 2.4 [1.0-5.8] 2 2.1 [0.1-8.2] 3 3.0 [0.1-9.0]
No care sought 29 14.2 [10.0-19.7] 8 8.5 [4.2-16.2] 18 18.0 [11.6-26.9]
Table 73: NYP Two-week Recall of Care-seeking Behaviour for Children 6-59 Months with Fever
All Registered New Arrivals Care-seeking for Children (n=69) (n=29) (n=39) 6-59 months with Fever N % 95% CI N % 95% CI N % 95% CI
Clinic or hospital 42 60.9 [48.7-71.9] 13 44.8 [27.7-63.3] 28 71.8 [55.5-83.9] Community or traditional 1 1.5 [0.2-10.0] 1 3.5 [0.5-21.6] 0 0.0 - healer Pharmacy 13 18.8 [11.1-30.1] 9 31.0 [16.7-50.2] 4 10.3 [3.8-24.8]
Other care 0 0.0 - 0 0.0 - 0 0.0 -
No care sought 13 18.8 [11.1-30.1] 6 20.7 [9.4-39.6] 7 18.0 [8.6-33.6]
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4. DISCUSSION 4.1. The Malnutrition Landscape
The findings from the three cross-sectional population representative SMART surveys presented in this report aimed to illustrate the nutrition context for the Rohingya population residing in the Ukhia and Teknaf Upazilas of Cox’s Bazar, Bangladesh. The results of key malnutrition indicators and the respective cut-offs utilized during this assessment are presented in table 73 below. Throughout this comparative discussion, it should be noted that the makeshift survey represents a much larger proportion (720,902 or 92%) of the overall Rohingya population in the assessment than the population within Kutupalong Refugee Camp (24,499 or 3%) or Nayapara Refugee Camp (38,997 or 5%). As such, the data speaks only to their designated survey areas, and cannot be averaged without threatening an accurate representation of the populations. 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. Chronic malnutrition in children 6-59 months was above the 40% critical threshold, underweight malnutrition in children 6-59 months was above the 30% critical threshold, and anaemia in children 6-59 months was above the 40% threshold for high public health significance for all surveys. Indicators of low MUAC for women 15-49 years and infants 0-5 months although inferential, are of concern. Compared to established WHO malnutrition cut-offs, the malnutrition status of the Rohingya at the time of survey constitutes emergency levels of malnutrition in need of nutritional support. Although there exist contextual differences between the three surveys and different population subsets within each survey, 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 74: Comparison of Malnutrition Indicators and Cut-offs Across all Three Surveys
Kutupalong Makeshift Nayapara Cut-offs Population Interpretation Oct 22-28 Oct 29-Nov 20 Nov 20-27 Global Acute Malnutrition Critical / Emergency ≥ 15% 24.3% 19.3% 14.3%
WHZ Global Acue [19.5-29.7] [16.7-22.2] [11.2-18.1] Children 6-59 Malnutrition Serious months ≥ 10% - <15% Global Acute 5.9% 8.6% 7.0% Malnutrition Alert-Serious [3.7-9.4] [6.8-10.7] [4.9-9.9] MUAC 6-10.9%51
51 IPC classification Acute Malnutrition Addendum 2016
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Global Acute
Malnutrition Acceptable <6%52 Global Chronic 43.4% 44.1% 44.4% Malnutrition Critical / Emergency [37.6-49.4] [40.7-47.5] [39.5-49.3] ≥ 40% Global Underweight 45.0% 41.3% 40.8% Critical / Emergency ≥ 30% [39.1-51.0] [37.5-45.1] [36.0-45.6] 47.9% 47.9% 46.6% High Public Health Hb<11.0 g/dL ≥ 40% [41.9-54.0] [44.1-41.7] [41.8-51.6] Significance Women 15-49 7.3% 8.7% 3.2% MUAC < 210mm* of concern years [5.2-10.1] [6.7-11.1] [2.1-4.7] Infants 0-5 31.6% 25.8% 23.1% MUAC < 110mm* of concern months [18.4-48.6] [19.2-33.7] [13.3-36.9] *MUAC <210 mm for women 15-49 and < 110mm for infants 0-5 are proposed / inferential thresholds One of the most striking findings from the emergency assessment results is the difference in the prevalence of GAM among children 6-59 months in Kutupalong Refugee Camp 24.3% [19.5-29.7] versus the Makeshift Settlements 19.3% [16.7-22.2] versus Nayapara Refugee Camp 14.3% [11.2-18.1]. The original assumption was that the malnutrition context would be worse outside of Kutupalong Refugee Camp, due to fewer established services and infrastructure. This assumption proved to be incorrect. However, there may be a temporal factor to the displacement which has influenced these results. Figure 21 below demonstrates the overall population of Rohingya Refugees in Ukhia and Teknaf during the assessment as reported by the ISCG. It is worth noting the rapid increase of Rohingya between October 17th and 18th, just prior to the start of data collection in Kutupalong Refugee Camp. Although officially the ISCG reports a fairly consistent camp size for both Kutupalong and Nayapara for the duration of the assessment, reports from the survey teams and other humanitarian actors during data collection confirm that many of these very new arrivals were circulating through the official camps. Often arriving first in Kutupalong Refugee Camp where they could rest and access emergency services after an average 8-day journey on foot, before being quickly shifted to the Makeshift Settlements. This is consistent with the very high non-response rates in both Kutupalong (28%) and Nayapara (18%). This recent circulation of new arrivals through the official camps likely overwhelmed the existing resources, and would have put particular strain on registered refugees if they were sharing their limited rations as insight from key informants suggests.
52 IPC classification Acute Malnutrition Addendum 2016 Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 111
Figure 21: The Population Influx of Rohingya Refugees during the Emergency Assessment Total Population of Rohingya in Ukhia & Teknaf* 740,000
735,000 734,903
730,000 (732,652) NYP Data 725,000 Collection Begins 720,000
715,000 (718,277) MS Data Collection Begins 710,000
Rohingya Population (713,425) KTP Data 705,000 Collection Begins
700,000 698,727 695,000 12-Oct 17-Oct 22-Oct 27-Oct 01-Nov 06-Nov 11-Nov 16-Nov 21-Nov 26-Nov 01-Dec
Source: ISCG Situation Updates: Rohingya Refugee Crisis, Cox's Bazar
*Excluding Rohingya within the host communities The second most striking finding may be the differences in determining cases of acute malnutrition among children 6-59 months between WHZ and MUAC. In Kutupalong Refugee Camp, 76.9% of the children 6-59 months identified as GAM by WHZ were not identified as GAM by MUAC, in the Makeshift Settlements this was 68.5%, and in Nayapara Refugee Camp this was 71.9%. Furthermore, all three surveys found a statistically significant association between children 6-23 months and GAM per MUAC, with an OR of 10.3 in Kutupalong Refugee Camp, an OR of 13.8 in the Makeshift Settlements, and an OR of 10.7 in Nayapara Refugee Camp. In other words, children 6-23 months were 10 to 13 times more likely to be considered GAM by MUAC than children 24-59 months, thereby potentially overlooking cases of acute malnutrition in children older than two years. This is consistent with MUAC having a known bias towards identifying younger and smaller children as malnourished. Given that in Bangladesh the protocol for referring children 6-59 to treatment for acute malnutrition is based on MUAC, this assessment provides evidence for the need to also include WHZ as a part of treatment referral protocols. Measuring MUAC in infants 0-5 months was included in this assessment for ongoing research purposes. There has been increasing interest in recent years in determining an appropriate cut- off for this age group using MUAC for admission into CMAM-I or SC treatment services. The cut- off for infant low MUAC of <110mm has been proposed by Mwangome et al., whose study on infants in Gambia found infants 0-5 months with a MUAC <110mm had a risk of death nearly 10 times higher than well-nourished infants (hazard ratio=9.5)53. The same cut-off has been
53 Mwangome et al. (2012) Mid-upper arm circumference at age of routine infant vaccination to identify infants at elevated risk of death: a retrospective cohort study in the Gambia
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supported by Chand et al., whose study on infants in India found that MUAC <110mm was the best performing cut-off with high sensitivity and specificity54. The results of this assessment identified the proportion of infants 0-5 months <110mm MUAC as 31.6% in Kutupalong Refugee Camp, 25.8% in the Makeshift Settlements, and 23.1% in Nayapara Refugee Camp, suggesting this proportion of infants 0-5 months were in need of treatment for acute malnutrition. Prevalence of total anemia among children 6-59 months was above the WHO threshold of public health significance (40%) in all three surveys, including among registered refugees, unregistered arrivals (pre-Aug 25), and new arrivals (post-Aug 25). Anemia is measured as an indicator of micronutrient deficiency. Taken together with evidence of poor dietary diversity, high prevalence of diarrheoeal disease, and limited access to health care facilities these data provide evidence of high anemia among children that may indicate high prevalence of micronutrient deficiency diseases. Other causes of anemia besides iron-deficiency, however should be considered as well, given previous studies in Bangladesh indicating high iron content in the water and high prevalence of thalassemia.55
4.2. Underlying Causes of Malnutrition
The Rohingya fled one context of poor malnutrition and arrived in another. The food insecurity context in Rakhine State (as discussed in this report’s introduction) is characterized by extremely high rates of poverty and a deterioration of household food security in recent years. A marginalized population generally reliant on agriculture, fishing, and raising livestock in Rakhine State, the Rohingya fled with very few belongings to Bangladesh, where their status bars them from income generating activities. Often relying on dry food assistance from WFP (consisting of rice and lentils) it is unsurprising that only 8.3% of children 6-23 months in the Makeshift Settlements were achieving minimum dietary diversity (see table 74 below), and that grains were the most commonly consumed food group. The WASH context in Rakhine State is very underdeveloped, with much of the population relying on unimproved sources of drinking water and unimproved toilet facilities. In Ukhia and Teknaf, the rapid influx of refugees into the pre-existing camps and rapid expansion beyond them meant water points and sanitation facilities were built hastily, and poor drainage increases risks of diarrhoeal and other waterborne disease. This likely contributed to the two-week recall of diarrhoea in children 6-59 months that ranged from 34.3% in Nayapara Refugee Camp to 41.3% in the Makeshift Settlements. Health services in Rakhine State are poorly developed and pose additional barriers to access for the Rohingya population. The influx into Bangladesh severely strained existing health services, and overcrowding in the camps has likely contributed to disease outbreaks among the most vulnerable. This was demonstrated by the high two-week recall of acute respiratory infection in children 6-59 months of 57.7% in the Makeshift Settlements as well as the two-week recall of Fever in children 6-59 months of 37.5% in Kutupalong Refugee Camp. Although it would
54 Chand et al. (2015) Mid-upper arm circumference for detection of severe acute malnutrition in infants aged between one and six months 55 Merrill RD, Shamim AA, Ali H, et al. High prevalence of anemia with lack of iron deficiency among women in rural Bangladesh: a role for thalassemia and iron in groundwater. Asia Pac J Clin Nutr. 2012;21(3):416-24. Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 113
take an in-depth assessment to understand the barriers to access of health services in these settings, of the cases identified during the assessment, only 50.0% and 55.8% of caregivers in Kutupalong Refugee Camp whose child 6-59 months had diarrhoea or ARI respectivley sought care in a clinic or hospital. Meanwhile only 46.1% of caregivers sought care for a child 6-59 months with fever in a clinic or hospital in the Makeshift Settlements. Alternatively, many caregivers reported relying on local pharmacies or foregoing treatment altogether. The two-week recall of morbidities in Nayapara was found to be lower. This could possibly have been affected by the timing of the assessment as Nayapara was done later, so there might have been more health services established. Also, in Teknaf the number of refugees arriving was lower compared to Ukhia and therefore there might have been less pressure on existing resources. In addition morbidity indicators suggest that new arrival children 6-59 months are more susceptible to diarrhoeal disease and acute respiratory infection, and that children under two years may have been more vulnerable to communicable diseases in Kutupalong Refugee Camp. While morbidity indicators collected in Makeshift Settlements suggest that children under two were more susceptible to diarrhoeal disease compared to children 24-59 months, and that new arrival children were more likely to suffer from a fever without a cough. In Nayapara new arrival children 6-59 months were nearly twice as likely to suffer from diarrhoeal disease than registered refugees. Anaemia prevalences among children between 6-59 months were > 40% and considered high according to WHO cut-offs for both Rohingya population residing in Bangladesh and the Rohingya population who newly arrived from Myanmar. The high anaemia prevalences are likely to be caused by poor consumption of minimum acceptable diet by this age group, high prevalence of diarrhoeal diseases, access to health care or other factcors. However this assessment did not look at the causality of anaemia. Even though this assessment looked at heamoglobin levels only, this might also be an indication of other micro-nutrient deficiencies. All IYCF indicators from previous assessments in Rakhine State suggested a context with inadequate breastfeeding and complementary feeding practices. Add to that the stress of forced migration and overcrowded conditions in the camps and the IYCF status of infants and young children was of serious concern. This assessment found breastfeeding to be widely practiced, but the rates of exclusive breastfeeding to be very low in some places, with just 56.1% of infants 0- 5 months exclusively breastfed and timely initiation of breastfeeding practiced with just 42.9% of children 0-23 months in the Makeshift Settlements to 82.1% of infants 0-5 months exclusively breastfed and timely initiation of breastfeeding practiced in 69.6% of children 0-23 months in Kutupalong Refugee Camp. The protection context was not a specified objective of this assessment, but the side effects of violence and trauma on caregivers and caregiving practices should not be overlooked. This topic is worthy of greater attention in the Rohingya context.
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Table 75: Comparison of Key Indicators and Across all Three Surveys
Kutupalong Makeshift Nayapara Indicator Population Oct 22-28 Oct 29-Nov 20 Nov 20-27 Minimum dietary 9.8% 8.3% 15.7% diversity [5.3-11.7] [5.2-13.0] [10.2-23.4] Minimum meal Children 6-23 53.9% 61.2% 65.3% frequency months [44.1-63.5] [54.6-67.5] [56.3-73.3] Minimum adequate 8.8% 6.4% 15.7% diet [4.6-16.2] [3.8-10.4] [10.2-23.4] Timely initiation of Children 0-23 69.6% 42.9% 48.5% breastfeeding months [61.3-76.7] [35.6-50.4] [41.1-56.1] Infants 0-5 82.1% 56.1% 72.2% Exclusive breastfeeding months [66.0-91.5] [45.1-66.4] [58.4-82.8] Cont. breastfeeding at Children 12- 97.3% 96.4% 100% one year 15 months [89.2-99.2] [76.3-99.6] Two-week recall 40.5% 41.3% 34.3% diarrhoea [35.1-46.1] [36.5-47.2] [30.0-39.1] Two-week recall 55.7% 57.7% 50.3% ARI [50.1-61.1] [52.7-62.4] [45.4-55.1] Two-week recall 37.5% 25.2% 16.9% fever Children 6-59 [32.3-43.1] [20.5-30.6] [13.6-20.9] Care-seeking in clinic or months 50.4% 57.0% 63.6% hospital for diarrhoea [41.6-59.2] [47.7-65.8] [55.2-71.2] Care-seeking in clinic or 55.8% 64.8% 72.7% hospital for ARI [48.2-63.1] [58.3-70.9] [66.1-78.4] Care-seeking in clinic or 50.0% 46.1% 60.9% hospital for fever [40.9-59.1] [37.2-55.3] [48.7-71.9]
4.3 Receipt of Services
Determining measles coverage was confounded by a measles campaign running concurrently with the assessment. The first measles campaign was conducted from 16th September- 4th October. The follow up measles campaign was conducted from November 18th to 30th (specifically in Nayapara Refugee Camp Nov 20th-22nd, during the first three days of data collection for the third survey) which may explain why the measles vaccination coverage was 88.0% among children 6-59 months in Nayapara Refugee Camp compared to 55.0% and 45.3% for Kutupalong and Makeshift Settlements respectively (see table 75 below). This may have been an underestimation at the time, if households were surveyed prior to their children being vaccinated. OCV coverage was 88.5% for all persons over 1 year of age in the Makeshift Makeshift Settlements, and was similar in Nayapara Refugee Camp and lower in Kutupalong Refugee Camp. This was likely influenced by the cholera campaign, of which the first round was conducted from October 10-18th , 2017 in all persons over 1 year of age and a second round from November 4-9th, 2017 in children 12-59 months.
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Assessing coverage of GFD was limited to asking eligible households if at least one person had received a food distribution. Only about half (52.5%) of eligible households in Kutupalong Refugee Camp had received at least one food distribution while the greatest coverage was 86.4% of eligible households in Nayapara Refugee Camp. The lower rate in Kutupalong may have been due to swift population movements through the camp, where although eligible, households may have been surveyed prior to receipt of food assistance. The rate of OTP enrollment among children 6-59 months identified with SAM was highest in the makeshift settlements at 16.7%. The enrollment rate of children 6-23 months in the Blanket Supplementary Feeding Programme in Nyapara and Kutupalong camps were the highest with 57.3%%. The results are impacted by the influx of refugees and limited number of nutrition service points available at the time of the assessment.
Table 76: Comparison of Key Indicators and Across all Three Surveys
Kutupalong Makeshift Nayapara Indicator Population Oct 22-28 Oct 29-Nov 20 Nov 20-27 Measles vaccination Children 6-59 55.0% 45.3% 88.0% coverage months [49.4-60.5] [38.5-52.3] [84.5-90.8] Cholera vaccination All persons ≥ 78.1% 88.5% 87.3% coverage 1 year of age [69.7-79.1] [84.0-91.9] [86.0-88.4] Receipt of a general Eligible 52.5% 82.7% 86.4% food distribution Households [44.7-50.2] [75.0-87.6] [81.7-90.1] Children 6-59 11.1% 16.7% 11.1% OTP enrollment months [9.3-62.6] [8.2-31.0] [3.4-31.1] Children 6- 57.3% 11.6% 57.3% BSFP enrollment 23/ 6-59 [45.7-68.2] [7.5-17.7] [46.2-67.7] months Children 6- 44.7% 10.0% 16.4% Receipt of MNP 23/ 6-59 [34.3-55.6] [6.9-14.3] [10.5-24.6] months
4.4 Limitations of the Assessment
The Rohingya crisis is a challenging context in which to conduct a lengthy assessment, due to rapid population movement and a complex sampling strategy. One key limitation of this assessment was the evolving population figures of survey areas. Population estimates relied on during planning may have increased or decreased once survey teams arrived for data collection. Therefore, there may exist a slight overrepresentation or underrepresentation within the sampling frame, particularly in the makeshift survey which was conducted using a cluster-sampling and the assessment was implemented among a growing population over thirty days. During the planning stages of the Makeshift Settlement survey in particular, we were expected to survey three times as many new arrival households as old arrival households (540,452/180,450 = 3.0) per ISCG population estimates from Oct 26th, 2017. The final proportion of new arrival to Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 116
old arrival households was twice that (5,249/859 = 6.1). There is some concern that incentives for assistance were causing households to portray themselves as having arrived after August 25th, 2017, and there were accounts from survey teams of households that had split into two households in order to increase household eligibility for services. Documentation evidencing exact dates of birth for children 6-59 months was low, particularly among the new arrival households who fled Rakhine State without time to gather personal effects. Similarly this might be the case for women 15-49 years as they might not know their exact date of birth. This likely reduced the precision of collected age data. The prevalence differences in malnutrition cannot be entirely understood without an in-depth analysis of the underlying causes of malnutrition, including the socio-economic context, food security and livelihoods environment, as well as market analyses. This report provides a general overview and analysis of the context as it stood in Cox’s Bazar from October 22nd to November 27th, 2017. 5. Conclusion and Recommendations
The Emergency Nutrition Assessment was conducted in Cox’s Bazar, Bangladesh from October 22nd to November 27th, 2017, with the aim of determining the nutrition status of all Rohingya living in Kutupalong Refugee Camp, Nayapara Refugee Camp, and the Makeshift Settlements. The findings from the Kutupalong Refugee Camp and Makeshift Settlements surveys indicated the prevalence of acute malnutrition among all children 6-59 months exceeded the 15% WHO emergency threshold, while Nayapara Refugee Camp fell just under it. All three surveys indicated that more than 2 in 5 of children 6-59 months suffered from chronic malutrition, exceeding the WHO threshold for a critical/emergency situtaion All three surveys indicated that nearly half of children 6-59 months suffered from anaemia, exceeding the WHO threshold for a high public health significance. Data from the two-week recall of symptoms consistent with diarrhoeal disease, acute respiratory infection, and fever indicated a high disease burden in children 6-59 months. IYCF practices were concerning with poor minimum acceptable diets for children 6-23 months and exclusive breastfeeding rates dangerously low. Furthermore, nearly all indicators once disaggregated between refugees arriving after August 25th and other refugees suggested a poorer nutrition status among new arrivals, likely aggravated by the week-long journey from Rakhine State, lack of knowledge of or proximity to services upon arrival, and lack of resources in general. The findings indicate a serious public health and nutrition emergency among the Rohingya children of Cox’s Bazar. This suggests a critical need to ensure all Rohingya children benefit from ongoing multi-sectoral efforts to scale up the emergency response including nutrition treatment programmes, nutrition prevention programmes, access to micronutrient dense foods, basic health services, IYCF support, improved access to safe water and sanitation, appropriate shelter, and the provision of psychosocial support. The recommendations drawn from the findings of this assessment are the following:
Scaling-up treatment of SAM among children 6-59 months Establishment of C-MAMI services for infants 0-5 months
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Assessment of the need to expand services for the treatment of SAM and/or MAM among children ≥5 years Scaling-up of TSFPs for the treatment of MAM among children 6-59 months Scaling-up of BSFPs for the prevention of acute malnutrition in children 6-59 months Advocacy for the use of both WHZ and MUAC as enrollment criteria for acute malnutrition in children 6-59 months Scaling-up of services supporting optimal IYCF practices to focus on timely initiation of breastfeeding and introductioin of complementary feeding Scaling-up of psychosocial support and MHCP targeting caregivers of children under 5 yearsAdvocacy for food voucher programmes to increase household consumption of iron-rich and vitamin-A rich foods and dietary diversity Multi-sectoral inquiry into the feasibility of providing emergency cash-transfers to households with children less than five years old Immunisation of all new arrivals at entry points for measles, OCV and Polio Close monitoring of immunisation coverage and disease burden to mitigate outbreaks Scaling-up of WASH infrastructure and activities to support the provision of safe drinking water and appropriate sanitation facilities Where feasible, creation of small-scale IGAs in order to support household dietary consumption Improved outreach and messaging for services to ensure newly-arrived refugees are not facing barriers due to poor communication of available services Follow-up assessment to monitor the evolution of nutritional status and enrollment into services in 6 months’ time
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Annex 1: Kutupalong Results of 2x2 Tests of Statistical Significance per Epi Info Software
Odds Ratio Chi Squared Fisher Exact Statistical Exposure/Outcome [95% CI] 2 tailed P 2 tailed P Significance New Arrival/GAM 1.34 [0.76-2.34] P=0.383 P=0.320 no 6-23/GAM 1.65 [0.93-2.95] P=0.118 P=0.096 no New Arrival/MAM 1.55 [0.82-2.93] P=0.234 P=0.195 no Registered/SAM 1.15 [0.45-2.96] P=0.958 P=0.815 no Boys/GAM 1.56 [0.88-2.78] P=0.126 P=0.152 no Boys/MAM 1.44 [0.75-2.78] P=0.355 P=0.326 no Boys/SAM 1.58 [0.61-4.09] P=0.475 P=0.484 no Registered/GAM MUAC 1.05 [0.38-2.92] P=0.999 P=0.999 no 6-23/GAM MUAC 10.3 [2.85-37.14] P=0.001 P=0.001 yes NA Women/low MUAC 3.06 [1.49-6.28] P=0.003 P=0.003 yes PLW/low MUAC 1.68 [0.82-3.43] P=0.210 P=0.188 no New Arrival/GCM 1.33 [0.82-2.17] P=0.300 P=0.265 no New Arrival/GU 0.79 [0.49-1.30] P=0.426 P=0.383 no New Arrival/Anaemia 1.33 [0.81-2.18] P=0.311 P=0.263 no 6-23 months/Anaemia 1.71 [1.02-2.88] P=0.056 P=0.049 no/yes New Arrival/diarrhoea 2.41 [1.51-3.84] P=0.001 P=0.001 yes 6-23 months/diarrhoea 1.45 [0.90-2.35] P=0.163 P=0.139 no New Arrival/ARI 1.96 [1.24-3.09] P=0.005 P=0.004 yes 6-23 months/ARI 1.25 [0.77-2.03] P=0.423 P=0.393 no New Arrival/fever 1.21 [0.76-1.92] P=0.489 P=0.481 no 6-23 months/fever 1.37 [0.84-2.23] P=0.251 P=0.213 no
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Annex 2: Makeshift Settlements Results of 2x2 Tests of Statistical Significance per Epi Info Software
Odds Ratio Chi Squared Fisher Exact Statistical Exposure/Outcome [95% CI] 2 tailed P 2 tailed P Significance Old Arrival/GAM 1.03 [0.66-1.61] P=0.972 p=0.909 no 6-23/GAM 2.57 [1.89-3.50] P=0.001 P=0.001 yes Old Arrival/MAM 1.06 [0.66-1.70] P=0.913 P=0.807 no New Arrival/SAM 1.09 [0.38-3.14] P=0.999 P=0.999 no Boys/GAM 1.13 [0.83-1.53] P=0.485 P=0.443 no Boys/MAM 1.13 [0.82-1.57] P=0.496 P=0.460 no Boys/SAM 1.05 [0.52-2.11] P=0.999 P=0.999 no New Arrival/GAM MUAC 2.77 [1.10-6.94] P=0.036 P=0.022 yes 6-23/GAM MUAC 13.8 [7.81-24.41] P=0.001 P=0.001 yes NA Women/low MUAC 2.67 [1.22-5.82] P=0.015 P=0.008 yes PLW/low MUAC 1.56 [1.07-2.27] P=0.027 P=0.026 yes New Arrival/GCM 1.04 [0.73-1.50] P=0.885 P=0.854 no Old Arrival/GU 1.03 [0.71-1.47] P=0.964 P=0.926 no Old Arrival/Anaemia 1.10 [0.77-1.56] P=0.675 P=0.650 no 6-23 months/Anaemia 2.22 [1.72-2.89] P=0.001 P=0.001 yes New Arrival/diarrhoea 1.37 [0.95-1.97] P=0.113 P=0.103 no 6-23 months/diarrhoea 1.51 [1.17-1.95] P=0.002 P=0.002 yes New Arrival/ARI 1.00 [0.71-1.43] P=0.999 P=0.999 no 6-23 months/ARI 1.06 [0.82-1.37] P=0.656 P=0.704 no New Arrival/fever 2.26 [1.38-3.69] P=0.001 P=0.001 yes 6-23 months/fever 1.17 [0.88-1.55] P=0.323 P=0.302 no
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Annex 3: Nayapara Results of 2x2 Tests of Statistical Significance per Epi Info Software
Odds Ratio Chi Squared Fisher Exact Statistical Exposure/Outcome [95% CI] 2 tailed P 2 tailed P Significance New Arrival/GAM 1.36 [0.75-2.45] P=0.382 P=0.374 no 6-23/GAM 2.78 [1.58-4.89] P=0.001 P=0.001 yes New Arrival/MAM 1.22 [0.66-2.24] P=0.633 P=0.541 no New Arrival/SAM 3.75 [0.42-33.87] P=0.417 P=0.374 no Boys/GAM 2.35 [1.27-4.34] P=0.009 P=0.006 yes Boys/MAM 2.47 [1.29-4.73] p=0.008 p=0.007 yes Boys/SAM 1.23 [0.20-7.44] P=0.999 P=0.999 no New Arrival/GAM MUAC 2.31 [0.98-5.41] P=0.077 P=0.070 no 6-23/GAM MUAC 10.69 [4.21-27.2] P=0.001 P=0.001 yes REG Women/low MUAC 1.09 [0.47-2.53] P=0.999 P=0.999 no PLW/low MUAC 1.12 [0.47-2.65] P=0.974 P=0.823 no Registered/GCM 1.01 [0.67-1.53] P=0.999 P=0.999 no New Arrival/GU 1.18 [0.78-1.78] P=0.497 P=0.464 no New Arrival/Anaemia 1.11 [0.74-1.67] P=0.685 P=0.680 no 6-23 months/Anaemia 2.90 [1.85-4.54] P=0.001 P=0.001 yes New Arrival/diarrhoea 1.87 [1.21-2.87] P=0.006 P=0.005 yes 6-23 months/diarrhoea 2.30 [1.48-3.57] P=0.001 p=0.001 yes Registered/ARI 1.01 [0.68-1.51] P=0.999 P=0.999 no 6-23 months/ARI 1.34 [0.87-2.05] P=0.216 P=0.194 no New Arrival/fever 1.32 [0.78-2.24] P=0.370 P=0.350 no 6-23 months/fever 1.13 [0.65-1.98] P=0.764 P=0.666 no
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Annex 4: Survey Team Training Schedule
Integrated SMART Survey Training agenda Venue: Hotel Beach Way, Kolatoli, Cox’s Bazar Duration: 15 Oct-19 Oct 2017 Day Time Topic Method Facilitator 15- 9:00-9:20 o Introduction and registration Discussion FC/HoDs/PMs Oct SMs/Partners 9:20 – 10:00 o Expectation! Presentation and ACF and others o Ground rules! discussion o Survey and training Questionnaire objectives o Pre-test 10:00-10:45 o Programme overview in Presentation and Nutrition Sector Registered Camp and Makeshift discussion Coordinator / site. Programmeme manager – ACF Tea break (15 minutes) 11:00-11:30 Basic concept Presentation and Survey Manager(SM)/ o Food and nutrition discussion o Types of malnutrition and o Assessment of nutritional status/detection of malnutrition o Referral system of malnourished Children
11:30-12:00 Survey methodology Presentation and CDC/Survey Manager(SM) o Survey Area discussion o Target Population o Objectives of the survey 12:00-1:00 Survey methodology Presentation, CDC/Survey o Sampling procedure- Simple exercises and Manager(SM)/ Others Random Sampling and selection discussion of targeted HHs. Lunch + Prayer (60 minutes) 2:00-3:45 o Sampling procedure- Cluster Presentation, CDC/Survey Manager(SM) Sampling and selection of exercises and targeted HHs. discussion o Cluster control form Tea break (15 minutes) 4:00-5:00 Discussion on different sections of Presentation, Survey Manager(SM)/ the questionnaire exercise and CDC o Consent Form discussion o Importance of different sections of the questionnaire.
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o Demographic Information/ HH definition o Mortality o Demography Exercise Tea break (15 minutes) 16-October 2017 2 9:00-11:00 Recap Session of previous Day Discussion, role Survey Manager(SM) o Anthropometry : Procedures - play weight, height, MUAC, oedema, and o Referral procedures o Age estimation/even calendar Tea break (15 minutes) 11:15-1:00 Questionnaire: Discussion, practice UNHCR/Programme o Haemoglobin measurement Manager/Survey o Practice measurement Manager-ACF
Lunch + Prayer (60 minutes) 2:00- 2:45 Questionnaire: Discussion, role Survey Manager(SM)/ o Morbidity Module play Partners
2:45-3:45 Questionnaire: Survey Manager(SM)/ o IYCF Module- (0-23m) Partners Tea break (15 minutes) 4:00-4:30 IYCF Module-Food Groups (6-23m) Discussion, role Survey Manager(SM) play 4:30-5:00 Role Play and Group Work Question and Survey Manager(SM) answer
17-Oct 2017 3 9:00 – 11:00 Recap Session of previous Day Discussion, role Survey Manager(SM) o Role Play and group Exercise play Tea break (15 minutes) 11:15-1:00 Adaptation of the survey Discussion, role CartONG questionnaire in electronic device/ play Soft ware o Introduction to KoBO Collect data collection tools o Access different menu of Apps.
Lunch + Prayer (60 minutes) 2:00-3:30 Adaptation of the survey questionnaire Discussion, CartONG in electronic device/ Soft ware demonstration o Covering different sections of questionnaire o Process of Data synchronize o Maintenance and Trouble shooting
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Tea break (15 minutes) 3:45-5:00 Adaptation of the survey questionnaire Discussion, Teams o Practical exercise on tablet device demonstration data collection 18-Oct-2017 4 9:00 – 1:00 Recap Session of previous Day Brief presentation Survey Manager and o Practical Exercise and on site, practical others o Standardisation test –Part-1 exercise Lunch + Prayer (60 minutes) 2:00 – 3:00 o Standardisation test –Part-2 practical exercise Survey Manager and others 3:00 – 3:30 Survey tips Discussion Survey Manager and o Daily field work completion others procedures (Team leader check list) o Consent form o Brief on different format, check list and bill voucher. Tea break (15 minutes) 3:45-4:30 o Procedure of Financial management, Discussion Survey Manager and keeping proper documentation with others justification. 4:30 – 5:00 o Post Test Question and All answer Tea break (15 minutes) 19-Oct-2017 5 9:00-1:00 Field exercise Practice Survey Manager and others Travelling + Lunch (120 minutes) 3:00-4:00 Feedback session on field findings. Survey Manager and others 4:00-5:00 Team building, Job responsibility and Discussion Survey Manager and Administrative brief and preparation for others the next day. The End
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Annex 5: Makeshift Settlements Cluster Determination
Estimated Settlement Clusters Population Size
Kutupalong MS 123985 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18
19,20,21,22,23,24,RC,25,RC,26,27,28,29,RC,30,31,32,33, Kutupalong 252767 RC,34,35,36,37,38,39,RC,40,41,42,43,44,45,46,47,48,49, Expansion Zone 50
Balukhali MS 65000 51,52,53,54,55,56,57,58,59,60 Thangkhali 28200 61,62,63,64 Hakimpara 55000 65,RC,66,67,68,69,70,71 Jamtoli 46311 72,73,74,75,76,RC,77 Moynarghona 21400 78,79,80 Chakmarkul 10500 81,82 Shamlapur 22700 RC,RC,83 Unchiprang 30100 84,85,86,87 Leda MS 22700 88,89,90,91 Nayapara Outside / 42239 92,93,94,RC,95,96 MS
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Annex 6: Survey Questionnaire
Emergency Health and Nutrition Survey-2017 (OCT-NOV)
Household Level Questionnaire (খানার তথ্য)
1.0 Name of Enumerator (তথ্য সংগ্রহকারীর নাম) 1.1 Date (তারিখ): 1.2 Team (টিম): (Valid answers: Numbers between 1 and 8) 1.3 Survey Area (জররপ এলাকা) 1= Kutupalong Refugee Camp/嗁তুপালং শরণাথ্ী কযাম্প 2 = Nayapara Refugee Camp/ নযাপাডা শরণাথ্ী কযাম্প
3 = Outside of Refugee Camp কযাম্পম্পর বাইম্পর
1.4 BLOCK (ব্লক) 1.5 CLUSTER (ক্লাস্টাি) (Relevant if 1.3 is 3 (outside of camp); Valid answers: Numbers between 1 and 100) 1.6 HOUSEHOLD (খানা) 1.7 GPS Coordinate (Note: Push the 'Record Location' button when the accuracy of the GPS measure is less than 25 m.) 1.8 Hello, My name is______, We are working with 1 = Consent (সম্মরত) ______organization. We are here to gather 2 = Refuse (end survey)/ অস্বীকার (জররপ রশম্পে) information related to nutrition, child feeding practices, and 3 = Absent (end survey) /অনুপরস্থ্রত(জররপ রশম্পে) child health of the Rohingya people in Cox’s Bazar. If there are any women (aged 15-49 years) or children under five years old in the household we would like to take some measurements to assess their nutritional status. All personal information will be kept confidential. Please note that it is not currently known what actions if any will be taken after the results of the survey are finalized. This information will not directly affect what humanitarian assistance is given to you or your family. The questions will take about 20-25 minutes. Do you have any questions? May I begin?
হযাম্পলা, আমার নাম হল ______, আমরা ______প্ররতষ্ঠাম্পনর সাম্পথ্ কাজ কররি। আমরা ক বাজাম্পর ররারহঙ্গা রলাম্পকম্পের পুরি, রশশুরশ া চচচা, এবং রশশু স্বাস্থ্য সম্পরকচত এক綿 জররপ পররচালনা কররি। আপনার খানা綿 এই জররপ কাম্পজর জনয এক綿 রনবচারচত পররবার।
- আপনার পররবাম্পর পাাঁচ বিম্পরর নীম্পচ রকান রশশু এবং ১৫ ৪৯ বির মরহলা থ্াকম্পল আমরা তাম্পের পুরির অবস্থ্া মূলযাযন করার জনয রকিু পররমাপ Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 126
রনম্পত চাই। সমস্ত বযরিগত তথ্য রগাপন রাখা হম্পব।জররম্পপর ফলাফল巁রল চূডান্ত করার পম্পর রকানও পেম্প প রনওযা হম্পব রকনা এ সম্পরকচত রকান
তথ্য আমরা জারন না। এই তথ্য綿 আপনাম্পক বা আপনার পররবাম্পরর কাম্পি মানরবক সহাযতা প্রোন করা সরাসরর প্রভারবত করম্পব না। সা াৎকার রনম্পত ২0-২৫ রমরনট সময লাগম্পব। আপরন রক রকিু জানম্পত চান? আরম রক শু쇁 করম্পত পারর?
Note: A household will only be marked absent after at least two re-visits to the household have been made.( রকান খানাম্পত পর পর েুইবার পররেশচম্পনর পরও খানা সেসয পাওযা না রগম্পল বারড綿
জরীম্পপ অনুপরস্থ্রত বম্পল রবম্পবরচত হম্পব।)
1.9 When did the household arrive in Bangladesh? 1 = Registered refugees(রনবরিত শরণাথ্ী) (Note: Select the best answer. If household members did not 2 = Unregistered – Prior to October 2016(অ রনবরিত - all arrive at the same time, select the option that is most অম্পটাবর 2016 এর আম্পগ) accurate for a majority of the household members) 3 = Unregistered – October 2016 to August 25, 2017(অ খানা綿 কখন বা廬লাদেদে আদে? রনবরিত - অম্পটাবর 2016 রথ্ম্পক ২5 আগস্ট, 2017) (দনাট: সেরা উত্তর ননববাচন ক쇁ন। যনে পনরবাদরর েেেয েকল 4 = Unregistered – August 25 2017 to present(অ রনবরিত - একই েমদ আদেন না, তাহদল বানর েেেযদের ে廬খযাগনরদের 25 আগস্ট 2017 রথ্ম্পক বতচমান) জনয েবদচদ উপযুক্ত নবকল্প綿 ননববাচন ক쇁ন)
List all of the household members that are currently living in this household. (বতচমাম্পন এই পররবার এ বসবাসকারী সকল সেসযম্পের তারলকা ক쇁ন) (Programmemed on tablet as a repeat group) 2.1 First name of the household member (পররবাম্পরর সেম্পসযর প্রথ্ম নাম) Note: First name only. Name will not be retained in the final data set. Name is only collected to aid in recall during data collection. (রনাট: শুধুমাত্র প্রথ্ম নাম। নাম চূডান্ত তথ্য রসট রাখা হম্পব না। রেটা সংগ্রম্পহর সময স্মরণ করার জনয রকবল নাম সংগ্রহ করা হম্পব)
2.2 Age in years (বযস-বছর) Note: Children aged 0-11 months should be recorded as ‘0’ years রনাট: 0-11 মাস বযসী রশশুম্পের '0' বির রহসাম্পব ররকেচ ক쇁ন।
2.3 Sex (রলঙ্গ) 1 = Male (পু쇁ে) 2 = Female (মরহলা) 2.4 Did [Name] join the household since the end of Ramadan (June 25, 2017)? 1 = Yes (হযাাঁ) [নাম] রক রমজান (25 রশ জুন, ২017) রশে হওযার পর রথ্ম্পক পররবাম্পরর 2 = No (না) সাম্পথ্ র াগ হম্পযম্পি?
2.5 Was [Name] born since the end of Ramadan (June 25, 2017)? 1 = Yes (হযাাঁ) [নাম] রক রমজান (25 রশ জুন, ২017) রশে হওযার পর জন্ম গ্রহন কম্পরম্পি? 2 = No (না) (Relevant: Age in years = 0) 2.6 Is [Name] currently pregnant or lactating? 1= Pregnant/ (গভচবতী) Note: If a women is pregnant and lactating, select pregnant 2= Lactating (with child less than 6 months) [নাম] রক বতচমাম্পন গভচবতী বা স্তনযোনকারী? (েুগ্ধোনকারী, 6 মাম্পসর কম বযসী রশশু) Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 127
দ্রিবয: রে এক綿 মরহলা একই সাম্পথ্ গভচবতী এবং েুগ্ধোনকারী হয, তম্পব 3 = Lactating (with child 6 months or older) গভচবতী মরহলা綿 রনবচাচন ক쇁ন (েুগ্ধোনকারী, 6 মাস বা তার রবশী বযসী রশশু) (Relevant: Women between the ages of 15-49 years) 4= Neither pregnant nor lactating (গভচবতীও না বা েুগ্ধোনকারীও না) 8 = Don’t Know (জারন না) 2.7 Did [Name] receive the oral cholera vaccine since arriving in Bangladesh? 1 = Yes – by finger mark(হযাাঁ - আঙুম্পলর রচহ্ন Note: Show the vaccine vial. Check for finger mark on left little finger. দ্বারা) ? বাংলাম্পেম্পশ আসার পর [নাম] রক মুম্পখ কম্পলরা 綿কা রনম্পযম্পি/ম্পখম্পযম্পি 2 = Yes – by recall (হযাাঁ –অনুসরন দ্বারা) দ্রিবয: ভযাকরসন ভাযাল রেখান/ বাম আঙুল উপর আঙুম্পলর মাকচ পরী া 3 = No (না)
ক쇁ন। 8 = Don’t know(জারননা)
(Relevant: Age in years doesn’t equal 0) 2.8 Were you able to check [Name]’s finger for a mark? আঙুল এ োগ আম্পিরকনা 1 = Yes – present at the time of visit (হযাাঁ, প চম্পব ণ ক쇁ন। আঙুল এ োগ আম্পি) Note: Observation. Do not read aloud 2 = No – not present at the time of visit (না, (Relevant: Age in years doesn’t equal 0) আঙুল এ োগ নাই) List all of the household members that left this household since the end of Ramadan (June 25, 2017). রমজান (25 রশ জুন, ২017) রশে হওযার পর রথ্ম্পক পররবার রথ্ম্পক ারা চম্পল রগম্পযম্পি তাম্পের তারলকা ক쇁ন। (Programmed on tablet as a repeat group) 3.1 First name of the household member (পররবাম্পরর সেম্পসযর প্রথ্ম নাম) Note: First name only. Name will not be retained in the final data set. Name is only collected to aid in recall during data collection. (রনাট: শুধুমাত্র প্রথ্ম নাম । নাম চূডান্ত তথ্য রসট রাখা হম্পবনা।রেটা সংগ্রম্পহর সময স্মরণ করার জনয রকবল নাম সংগ্রহ করা হম্পব)
3.2 Age in years (বযস-বছর) Note: Children aged 0-11 months should be recorded as ‘0’ years রনাট: 0-11 মাস বযসী রশশুম্পের '0' বির রহসাম্পব ররকেচ ক쇁ন।
3.3 Sex (রলঙ্গ) 1 = Male (পু쇁ে) 2 = Female) মরহলা( 3.4 Did [Name] join the household since the end of Ramadan (June 25, 2017)? 1 = Yes (হযাাঁ) [নাম] রক রমজান (25 রশ জুন, ২017) রশে হওযার পর রথ্ম্পক পররবাম্পরর 2 = No (না) সাম্পথ্ র াগ হম্পযম্পি?
3.5 Was [Name] born since the end of Ramadan (June 25, 2017)? 1 = Yes (হযাাঁ) [নাম] রক রমজান (25 রশ জুন, ২017) রশে হওযার পর জন্ম গ্রহন 2 = No (না) কম্পরম্পি? (Relevant: Age in years = 0) List all of the household members that died since the end of Ramadan June 25, 2017) রমজান (25 রশ জুন, ২017) রশে হওযার পর পররবার এর ারা মারা রগম্পযম্পি তাম্পের তারলকা ক쇁ন। (Programmed on tablet as a repeat group) 4.1 First name of the household member (পররবাম্পরর সেম্পসযর প্রথ্ম নাম) Note: First name only. Name will not be retained in the final data set. Name is only collected to aid in recall during data collection. (রনাট: শুধুমাত্র প্রথ্ম নাম । নাম চূডান্ত তথ্য রসট রাখা হম্পব না।রেটা সংগ্রম্পহর সময স্মরণ করার জনয রকবল নাম সংগ্রহ করা হম্পব)
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4.2 Age in years (বযস-বছর) Note: Children aged 0-11 months should be recorded as ‘0’ years রনাট: 0-11 মাস বযসী রশশুম্পের '0' বির রহসাম্পব ররকেচ ক쇁ন।
4.3 Sex (রলঙ্গ) 1 = Male (পু쇁ে) 2 = Female) মরহলা( 4.4 Did [Name] join the household since the end of Ramadan (June 25, 2017)? 1 = Yes (হযাাঁ) [নাম] রক রমজান (25 রশ জুন, ২017) রশে হওযার পর রথ্ম্পক পররবাম্পরর 2 = No (না) সাম্পথ্ র াগ হম্পযম্পি?
4.5 Was [Name] born since the end of Ramadan (June 25, 2017)? 1 = Yes (হযাাঁ) [নাম] রক রমজান (25 রশ জুন, ২017) রশে হওযার পর জন্ম গ্রহন 2 = No (না) কম্পরম্পি? (Relevant: Age in years = 0)
Women Level Questionnaire
Anthropometry of women of reproductive age (15-49 Yrs) ৫৯ বছর বেী-১৫(মনহলাদের েরীর বৃত্তী পনরমাপ) Note: Complete the following module for all women in the household between 15 and 49 years of age ১৫ থেকে ৪৯ বছকেে মকযে পরেবাকেে সব নােীকেে জনে রনকনাক্ত মরিউল綿 সম্পন্ন ে쇁ন (Programmed on tablet as a repeat group) 5.1 Age (Years) (বযস-বির) (Valid responses: 15 to 49) 5.2 MUAC (mm) )মুযাক-রমরম) 5.3 Are you currently pregnant or lactating? )আপরন রক বতচমাম্পন 1= Pregnant/ (গভচবতী) গভচবতী বা 駁গ্ধোনোেী?) 2= Lactating (with child less than 6 Note: If a women is pregnant and lactating, select pregnant months) (েুগ্ধোনকারী, 6 মাম্পসর কম দ্রিবয: রে এক綿 মরহলা গভচবতী হয এবং গভচবতী হয, তম্পব বযসী রশশু) গভচবতী মরহলা綿 রনবচাচন ক쇁ন 3 = Lactating (with child 6 months or older) (েুগ্ধোনকারী, 6 মাস বা তার রবশী বযসী রশশু) 4= Neither pregnant nor lactating (গভচবতীও না বা েুগ্ধোনকারীও না) 8 = Don’t Know (জারন না)
Child Level Questionnaire
Anthropometry and Anaemia ০-৫ মাে বেী নে�দের েরীর বৃত্তী পনরমাপ Note: Complete the following module for all children in the household between 0-59 months (Programmed on tablet as a repeat group)
6.1 [Name]’s sex (রশশুর (নাম) রলঙ্গ) 1 = Male (পু쇁ে) 2 = Female) মরহলা(
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6.2 Do you know [Name]’s day, month and year of birth? (আপরন রক 1 = Yes (হাাঁ) (নাম)রশশুর জন্ম রেন, মাস এবং জন্ম সন জাম্পনন?) 2 = No (না) (skip to 5.4) 6.3 [Name]’s date of birth (রশশুর জন্ম তাররখ)- (Day/Month/Year)/ (Age on months calculated on tablet from survey date and DOB) (রেন/ মাস/বির) 6.4 [Name]’s age in months / (রশশুর বযস মাম্পস) Note: Estimate using event calendar. (ঘটনাপণরির মাধযম্পম বযস রবর ক쇁ন) 6.5 Weight (Kg) ±0.1kg (ওজন ±0.1 রকরজ) Note: The child must be weighed naked. Remove diapers, necklaces and other items that could increase the weight before measuring. REMINDER: Always record weight with one digit after the decimal point. (Relevant for age between 6 and 59 months; valid responses between 0.1 and 54) 6.6 Height or Length56(cm) 0.1 cm )উচ্চতা বা দেঘচয + 0.1 রসরম ( Note: Height measurement standing when child is ≥24 months (height proxy ≥87 cm) and lying down when child is < 24 months (< 87 cm) (Relevant for age between 6 and 59 months; valid responses between 30 and 155) 6.7 Record measurement taken: length or height ) দেঘচয বা উচ্চতা) 1 = Length (দেঘচয) 2= Height (উচ্চতা) 6.8 MUAC (mm) )মুযাক-রমরম) (If MUAC<115, prompt a note: “Please complete the referral form. This child has severe acute malnutrition.”) ( রে MUAC <115, রনাট ক쇁ন: "অনুগ্রহ কম্পর ররফাম্পরল ফমচ綿 পূরণ ক쇁ন। এই রশশু綿র 巁쇁তর অপুরি আম্পি।")
6.9 Does [Name] have bilateral oedema that is swelling with pitting oedema in 1 = Yes (হযাাঁ) both feet? 2 = No ( না) )উভয পাম্পযর পাতায ইরেমা আম্পি) (If yes, prompt a note: “Notify your supervisor and have him/her confirm whether or not the child has oedema. Children with oedema should be referred for treatment”) 6.10 Is [Name] currently enrolled in a therapeutic feeding program for 1 = Yes (হযাাঁ) treatment of severe acute malnutrition? )বতচমাম্পন রশশু綿 রক 巁쇁তর 2 = No (না) তীব্র অপুরি রচরকৎসার জনয রকানও রফরেং রপ্রাগ্রাম্পম তারলকাভুি হম্পযম্পি?) 8 = Don’t Know (জারন না)
(Note: Show package of RUTF) (Relevant for age between 6 and 59 months) 6.11 Is [Name] currently enrolled in a blanket or supplemental feeding 1 = Yes (হযাাঁ) program? 2 = No (না) ) নে�綿 [নাম] রক বতচ মাম্পন 뇍াংম্পকট বা সম্পূরক বা সুরজ রপ্রাগ্রাম্পম 8 = Don’t Know (জারন না) তারলকাভুি হম্পযম্পি?)
(Note: Show package of CSB) (Relevant for age between 6 and 59 months) 6.12 Since the influx of new arrivals (August 25, 2017) has [Name] received any 1 = Yes (হযাাঁ) micronutrient powders? 2 = No (না) ( , (নতুন আগমম্পনর পম্পর আগস্ট ২5 ২017) রথ্ম্পক রশশু綿 [নাম] রক রকান 8 = Don’t Know (জারন না) মাইম্পরারনউরিম্পযন্ট 巁াঁম্পডা (পুরস্টকনা) রখম্পযম্পি?)
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(Note: Show package of MNP) (ম্পনাট: MNP বা পুরস্টকনার পযাম্পকট রেখান) (Relevant for age between 6 and 59 months) 6.13 Since the influx of new arrivals (August 25, 2017) has anyone in the 1 = Yes (হযাাঁ) household received a bag of rice as part of a food distribution? 2 = No (না) ( ( , নতুন আগমম্পনর পম্পর আগস্ট ২5 ২017) রথ্ম্পক পররবাম্পরর রকউ রক চাম্পলর 8 = Don’t Know (জারন না) এক綿 বযাগ/ বস্তা রপম্পযম্পিন?) (Note: Show 25kg bag of rice. If the household purchased the food the market, select “no”) (ম্পনাট: চাম্পলর 25 রকরজ বযাগ রেখান। রে গৃহস্থ্ারলর বাজাম্পর খােয綿 রকনা হয তম্পব "না" রনবচাচন ক쇁ন) 6.14 Does the caregiver consent to having [Name]’s haemoglobin measured? 1 = Yes (হযাাঁ) (রহম্পমাম্পলারবন মাপার অনুমরত রেওযা হম্পযম্পি?) 2 = No (না) 6.15 Haemoglobin measurement (g/dL) (রহম্পমাম্পলারবন পররমাপ – গ্রাম/রেএল) (Relevant for age between 6 and 59 months AND 6.14 response is Yes (1); valid responses between 1 and 23)
Child Morbidity 7.1 In the past two weeks, has [Name] had diarrhoea? (গত েুই সপ্তাম্পহ 1 = Yes (হযাাঁ) রশশু綿র (নাম) রক োযররযা হম্পযরিল? 2 = No (না) Skip to 7.3) Note: Diarrhoea is defined as the passage of three or more loose or 8 = Don’t Know (জারন না) (Skip to liquid stools in a day (োযররযা -রেম্পন রতন বা এর অরধক পাতলা বা 7.3) পারন ুি পাযখানা) (Relevant for age between 6 and 59 months) 7.2 Was [Name] taken for treatment / medical care since the time the 1 = Yes – at a clinic/hospital ( হযাাঁ - diarrhoea started? রিরনক বা হাসপাতাল) রশশু綿র (নাম) রক োযররযার জনয রকান রচরকৎসা রনম্পযরিল?) 2 = Yes –community / traditional healer (গ্রাম্পমর োিার বা করবরাজ) Note: Do not read answer choices allowed. ( উত্তর পম্পড শুনাম্পনা 3 = No (না) ) াম্পবনা 8 = Don’t Know (জারন না) 7.3 In the past two weeks, has [Name] had cough with rapid or 1 = Yes (হযাাঁ) difficulty breathing AND a fever? (গত েুই সপ্তাম্পহ রশশু綿র (নাম) রক 2 = No (না) (Skip to 7.5) একই সাম্পথ্ জর, দ্রত কারশ বা শ্বাস কি হম্পযরিল? 8 = Don’t Know (জারন না) (Skip to 7.5)
(Relevant for age between 6 and 59 months) 7.4 Was [Name] taken for treatment / medical care since the time the 1 = Yes – at a clinic/hospital ( হযাাঁ - cough started? রিরনক বা হাসপাতাল) (রশশু綿র (নাম) রক জর, দ্রত কারশ বা শ্বাস কির জনয রকান রচরকৎসা 2 = Yes –community / traditional রনম্পযরিল?) healer (গ্রাম্পমর োিার বা করবরাজ) 3 = No (না) Note: Do not read answer choices allowed. ( উত্তর পম্পড শুনাম্পনা 8 = Don’t Know (জারন না) াম্পবনা)
7.5 In the past two weeks, has [Name] had a fever BUT NO cough? 1 = Yes (হযাাঁ) (গত েুই সপ্তাম্পহ রশশু綿র (নাম) রক শুধু জর হম্পযরিল (কারশ িাডা)?) 2 = No (না) (Skip to 7.7) 8 = Don’t Know (জারন না) (Skip to 7.7) (Relevant for age between 6 and 59 months)
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7.6 Was [Name] taken for treatment / medical care since the time the 1 = Yes – at a clinic/hospital ( হযাাঁ - fever started? রিরনক বা হাসপাতাল) রশশু綿র (নাম) রক জর এর জনয রকান রচরকৎসা রনম্পযরিল?) 2 = Yes –community / traditional healer (গ্রাম্পমর োিার বা করবরাজ) Note: Do not read answer choices allowed.( উত্তর পম্পড শুনাম্পনা 3 = No (না) ) াম্পবনা 8 = Don’t Know (জারন না) 7.7 Since the influx of new arrivals (August 25, 2017) has [Name] 1 = Yes by card (হযাাঁ কােচ ) received a measles injection? Measles is a shot given in the upper 2 = Yes by recall (হযাাঁ (মা স্মরণ) arm to prevent him/her from getting measles. ( নতুন আগমম্পনর পর 3 = No (না) ( ) ?) ২৫রশ অগাস্ট ২০১৭ এর পর রশশু綿ম্পক রকান হাম্পমর 綿কা রেযা হম্পযম্পি 8 = Don’t Know (জারন না) (বাহুর উপম্পরর অংম্পশ হাম্পমর 綿কা রেযা হয?)
Note: Interviewer should describe the campaign. The children of vaccinated children were marked. Vitamin A (small red or blue capsules given orally was also given at the same time). ) কযাদেইন এর বর্বনা নেন- সযমন হাদমর 綿কার নেন লাল এব廬 নীল র廬 এর নিটানমন এ কযাপেুল খাওাদনা হদনছল(
(Relevant for age between 6 and 59 months)
Infant and Young Child Feeding (IYCF) Practices (০-২৩ মাস বযসী রশশুর খােযাভাস)
8.1 Has [Name] ever been breastfed? 1 = Yes (হযাাঁ) (নাম) তাম্পক রক কখনও বুম্পকর েুধ খাইম্পযম্পিন? 2 = No (না) (Relevant for age between 0 and 23 months) 8 = Don’t Know (জারন না) 8.2 How long after delivery was [Name] put to the breast? 1 = Less than one hour (১
জম্পন্মর কত ণ পম্পর (নাম) তাম্পকবুম্পকর েুধ রেযা হম্পযরিল? ঘণ্টার কম) (Relevant for age between 0 and 23 months) 2 = Between 1 to 23 hours (১- ২৩ ঘণ্টার মম্পধয) 3 = More than 24 hours (২৪ ঘণ্টার রবরশ) 8 = Don’t Know (জারন না) 8.3 On the day of birth, did [Name] receive a sweet drink with honey or 1 = Yes (হযাাঁ) sugar water? রশশু綿 [নাম] রক জম্পন্মর রেন, মধু বা রচরনর রচরনর পারন 2 = No (না) পান কম্পররিল?) 8 = Don’t Know (জারন না)
8.4 Was [Name] breastfed yesterday during the day or at night? 1 = Yes (হযাাঁ) (Skip to 8.7) গতকাল রেম্পন অথ্বা রাম্পত (নাম) তাম্পক রক বুম্পকর েুধ খাওযাম্পনা 2 = No (না) / Stop Feeding হম্পযরিল? (খাওযাম্পনা বি কম্পরম্পি (Relevant for age between 0 and 23 months) 8 = Don’t Know ((জারন না) (Skip to 8.7) 8.5 When did [Name] stop breastfeeding? (রশশু綿 কখন বুম্পকর েুধ খাওযা বি 1 = Before arrival in কম্পরম্পি?) Bangladesh / Before the recent influx (August 25, 2017)
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(বাংলাম্পেম্পশ আগমম্পনর পূম্পবচ বা ২৫ রশ আগম্পস্টর পূম্পবচ) (Skip to 8.7)
2= Since arrival in Bangladesh / Since the recent influx (August 25, 2017) (বাংলাম্পেম্পশ আগমম্পনর পর বা ২৫ রশ আগম্পস্টর পর)
8.6 What was the main reason [Name] stopped breastfeeding? (রশশু綿 1 = Lack of privacy for (নাম) বুম্পকর েুধ খাওযা বি করার মূল কারন রক?) breastfeeding (রগাপনীযতার অভাব) Note: Do not read the answer choices aloud. Select the best answer. 2 = Stress (রেস) (উত্তর পম্পড শুনাম্পনা াম্পবনা- সম্পবচাত্তম উত্তর綿 রনবচাচন ক쇁ন) 3 = Lack of food (খাম্পেযর অভাব) 4 = Separation of mother and child (মা এবং রশশুর রবম্পেে) 5 = Illness (অসুস্থ্তা) 6 = Other (অনযানয) 8 = Don’t know (জারন না) Now I would like to ask you about the liquids that [Name] may have had yesterday during the day or night. I am interested in whether your child had the item even if it was combined with another food. Yesterday during the day or night did [Name] receive any of the following? (8.6 a-i: Relevant for age between 0 and 23 months) 8.7a Plain Water-পারন 1 = Yes (হযাাঁ) 2 = No (না) 8 = Don’t Know (জারন না) ( 8.7b Infant formula ( Serelack, Lactogen, My boy) রশশু Baby) ফমূচলা র মন- 1 = Yes (হযাাঁ) রসম্পরলাক, লযাটু ম্পজন, মাই বয ইতযারে) 2 = No (না) 8 = Don’t Know (জারন না) , 8.7c Milk such as tinned, powered, or fresh animal milk (綿নজাত েুধ 巁ডা 1 = Yes (হযাাঁ) , েুধ প্রাণীজ েুধ) 2 = No (না) 8 = Don’t Know (জারন না) / 8.7d Juice or juice drinks (Fruit Juice, coconut water etc.) (ফম্পলর রস জুস 1 = Yes (হযাাঁ) / োম্পবর পারন) 2 = No (না) 8 = Don’t Know (জারন না) 8.7e Clear broth (পররষ্কার তুোরপাত) 1 = Yes (হযাাঁ) 2 = No (না) 8 = Don’t Know (জারন না) 8.7f Sour milk or yogurt (Curd) (সুস্বােুেুধ বা েই) 1 = Yes (হযাাঁ) 2 = No (না) 8 = Don’t Know (জারন না) 8.7g Thin porridge (পাতলা জাউ বা সুরজ ইতযারে) 1 = Yes (হযাাঁ) 2 = No (না)
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8 = Don’t Know (জারন না) 8.7h Tea or coffee with milk (েুধ রেম্পয চা বা করফ) 1 = Yes (হযাাঁ) 2 = No (না) 8 = Don’t Know (জারন না) 8.7i Any other water-based liquid (soda, sweet drinks, herbal infusion, 1 = Yes (হযাাঁ) clear tea with no milk, black coffee) (অনয রকানও জলরভরত্তক তরল 2 = No (না) (ম্পসাো, রমরি পানীয, রভেজ উরিে, রকান েুম্পধর সাম্পথ্ পররষ্কার চা, কাম্পলা 8 = Don’t Know (জারন না) করফ)
8.8 Yesterday during the day or night did [name] eat solid or semi-solid 1 = Yes (হযাাঁ) (soft, mushy) food? (গতকাল রেম্পন বা রাম্পত (নাম) রস রক বুম্পকরেুধ 2 = No (না) (Skip to 9.1a) িাডা অনয রকান নরম/ অধচ শি/ শি খাবার রখম্পযরিল?) 8 = Don’t Know (জারন না) (Relevant for age between 0 and 23 months) 8.9 How many times did [Name] eat solid, semi-solid, or soft foods other than liquids yesterday during the day or at night? (হযাাঁ হম্পল, রশশু綿 (নাম) গতকাল রেম্পন এবং রাম্পত (গত ২৪ ঘন্টার মম্পধয) তরল বযারতত সবচম্পমাট কতবার শি, আধা-শি অথ্বা নরম খাবার রখম্পযম্পি?) (Relevant for age between 0 and 23 months)
Now I’d like to ask you about everything that [Name] ate or drank yesterday during the day or night, whether he/she ate it at home or anywhere else. Please include all foods and drinks, any snacks or small meals, as well as all main meals. Remember to include all foods you may have eaten while preparing meals or preparing food for others. (9.1 a-g: Relevant for age between 6 and 23 months) 9.1a Grains, roots, tubers (nan, chapatti, parata, bread, rice, potato) 1 = Yes (হযাাঁ) শসয,রশকড এবং কন্দ ( নান, চাপারত, পম্পরাটা, 쇁綿, ভাত/চাল, আলু) 2 = No (না) 8 = Don’t Know (জারন না) 9.1b Legumes or nuts (lentils) 1 = Yes (হযাাঁ) রশম জাতীয বা বাোম 2 = No (না) 8 = Don’t Know (জারন না) 9.1c Dairy products (milk, yoghurt, cheese) 1 = Yes (হযাাঁ) েুদ্ধজাতীয পণয (েুধ, ইম্পযাগাটচ , পরনর) 2 = No (না) 8 = Don’t Know (জারন না) 9.1d Flesh foods (meat, fish, poultry, liver/organ meat) 1 = Yes (হযাাঁ) মাংসজাতীয খাবার (মাি, মাংস, মুররগর মাংস এবং কৃ ত /করলজা ও অনযানয 2 = No (না) অঙ্গ র মন- হৃেরপণ্ড, রকেরন, রজহবা, অগ্ন্যাশয, মগজ ইতযারে) 8 = Don’t Know (জারন না) 9.1e Egg রেম 1 = Yes (হযাাঁ) 2 = No (না) 8 = Don’t Know (জারন না) 9.1f Vitamin A rich fruits and vegetables (carrot, pumpkin, orange sweet 1 = Yes (হযাাঁ) potato, mango, papaya, dark green leafy vegetables, long beans) 2 = No (না) ( , , - , রভটারমন এ সমৃদ্ধ ফলমূল ও শাকসবরজ গাাঁজর রমরি 嗁মডা কমলা রমরি আলু 8 = Don’t Know (জারন না) আম, রপাঁম্পপ, গাঢ় সবুজ শাক সবরজ, রশম) 9.1g Other fruit and vegetables (banana, apples, pineapple, watermelon , 1 = Yes (হযাাঁ) eggplant, onion, cucumbers, tomatoes) 2 = No (না) 8 = Don’t Know (জারন না) Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 134
অনযানয ফলমূল ও শাকসবরজ (কলা, আম্পপল, আনারস, তরমুজ, রব巁ন, রপাঁযাজ, শসা, টম্পমম্পটা)
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Annex 7: Cluster Control Form
Emergency Health and Nutrition Survey-2017 KTP RC NYP RC MS Site Cluster Control Form Name of Area:______Block /Union: ______Upazila:______Leader Name: ______Mobile No:______Date:______CLUSTER NO: ______TEAM NO: ______Key Informants/Mobile: HH ID Family Household Visit Result Number of Number of Status Number needs to Household Remarks/ HH 1 = Consent eligible eligible Head of HH name (See Note 2 = Refuse (end of eligible be revisited Reason for not serial children children for Code) survey) children revisited YES/NO Measured 3 = Absent (end survey) (6-59m) Measured (0-5m) YES/NO 1 2 3 4 5 6 7 8 9 10 11 12
13
14 15 Note**: Family Status Code: 1 = Registered refugees, 2 = Unregistered – Prior to October 2016, 3 = Unregistered – October 2016 to August 25, 2017, 4 = Unregistered – August 25 2017 to present Note: Households only marked absent after at least two re-visits to the household have been made Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 136
Annex 8: Anthropometric Measurement Form Children Emergency Health and Nutrition Survey-2017 KTP RC NYP RC MS Site Anthropometric Measurement Form Name of Area:______Block /Union: ______Upazila:______Leader Name: ______Mobile No:______Date:______CLUSTER NO: ______TEAM NO: ______Key Informant/ Mobile: HH/MRC Child Oedema MUAC Comments/ Date of No ID Sex Age Weight Height (Y/N) (mm) HB Reason for HH Serial Name of child Birth (dd- (M/F) (month) (kg) (cm) (g/dl) not mm-yyyy) Measured
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Annex 9: Anthropometric Measurement Form Women
Emergency Health and Nutrition Survey -2017 MUAC Measurement Form (15-49 Yrs.) Name of Area: ______Block/Union: ______Upazila:______Leader Name: Mobile:______DATE : ______CLUSTER NO: ______TEAM NO:______Are you Comments/ currently Age Reason for Household Household Women ID MUAC (mm) pregnant (month) not /MRC NO Serial or Measured lactating?
Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 138
1= Pregnant 2= Lactating (with child less than 6 months 3 = Lactating (with child 6 months or older) 4= Neither pregnant nor lactating 8 = Don’t Know Note: If a women is pregnant and lactating, select pregnant
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Annex 10: Event Calendar
Month 2012 2013 2014 2015 2016 2017 Winter session, Eid- Winter session, Winter session, Winter session, Eid-E- Winter session, E-miladunnobi Eid-E-miladunnobi, Eid-E-miladunnobi miladunnobi, English New Jan ==(E-Safor, S- Rabiul Natioznal Election (Family Photo,school Year’s Day Winter session (Poush-Magh) Au Wall Nat Taw-Tabo 58 /// 46 vaccine campaign) 33 21 9 Dway OTP-6 (Conflict in Du Chee reopening Family Yar Tan) End of winter, maghi End of Winter/// End of Winter End of Winter purnima (*E-Rabiul (Family Photo,school Mother Language Feb End of winter, Eid- Au wall, S-Safor Pya End of Winter vaccine campaign) Day (Magh-Falgun) E-miladunnobi 57 45 32 20 8 Tho-Tabo Dway Hindu festival Kyauk Pan Do Hervesting time Hervesting time work Hervesting time Hervesting time work work brick field, brick field, work brick field, Hervesting time brick field ((*E-Rabiul (Ended Family photo Birth day of Mar Hervesting time work brick field, Au wall, S-Safor Pya Matric Exam and Bangabandu (Falgun-Chaitra) work brick field 56 Local Upazila 44 31 19 7 Tho-Tabo Dway Hindu (returning card on Independence Day election festival Kyauk Pan Do March 31)
Harvesting time, Harvesting time, Harvesting time, New Harvesting time, Harvesting time, Harvesting time, New year New year day/ year day (Pohela Bangla New year April (Chaitra-Baishakh) New year day New year day 55 day(Pohela 42 Pohela Boishak 30 Boishak). 18 day (Pohela 6 (Pohela Boishak). (Pohela Boishak). Boishak). (End of hot season ) Boishak). Summer, Summer, Summer, Summer, Cyclone Summer, Buddho May (Baishakh-Jaishtha) Summer 54 41 Buddho purnima 29 Buddho purnima 17 Buddho purnima 5 mohashen purnima Shab-e-Barat Start of long rainy Start of long rainy Start of long rainy Start of long rainy Shobe-e Qadar & June Start of long rainy session, buddho session, Shab-e- session, session, Jummatul bida/ (Jaishtha-Ashar) session. 53 40 28 16 4 purnima Barat Shab-e-Barat Shab-e-Barat Eid-ul Fitr Start of Ramadan, Eid-ul fitor, Rainy Eid-ul fitor, Rainy Rainy session July Start of Ramadan, Eid-ul fitor, Rainy Jonmastomi, Rainy session session (Ashar-Srabon) Rainy session. 52 session 39 27 15 3 session. Rainy Session, Rainy Session, Rainy Session, 2 Janmashtami Janmashtami Janmashtami Aug Eid-ul fitor, Rainy Eid-ul fitor, Rainy Rainy Session, National Mourning (Srabon-Vadro) session session 51 Janmashtami 38 26 14 Day (Recent Conflict) Monsha Puja end End of the long End of the long rainy Eid Ul Adha Sept end of the long rainy End of the long 1 of the long rainy rainy session/ session/ Durgapuja (Vadro-Ashshin) session 50 rainy session 37 25 13 session. Eid-ul Azha, Eid-ul Azha, (Dashami) Durga Puja, Durga Puja, Durga Puja, Eid-ul Azha, Durga Eid-ul Azha, Durga 0 Oct , Go brick field up to Moharram Moharram Moharram Puja, Go brick field Puja, Go brick field nd (Ashshin-Kartik) march. 49 36 24 ( 2 recent 12 up to march. up to march. Conflict) Start working in salt Harvesting time, Harvesting time, Start Nov Start working in salt Start working in salt field. Start working in working in salt field, (Kartik-Agrahayan) field, Moharram 48 field, Moharram 35 23 11 salt field, Christmas, Starting Christmas, Starting Christmas, Starting Christmas, Starting Christmas, Starting Dec (Agrahayon-Pous) Winter Winter Winter 59 Winter 47 Winter 34 22 10
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Month 2012 2013 2014 2015 2016 2017 Winter session, Eid-E- Winter session, Winter session, Eid- Winter session, Eid- Winter session, miladunnobi Eid-E-miladunnobi, E-miladunnobi E-miladunnobi, English New Jan ==(E-Safor, S- Rabiul Au National Election (Family Photo,school Year’s Day Winter session (Poush-Magh) Wall Nat Taw-Tabo 59 /// 47 vaccine campaign) 34 22 10 Dway OTP-6 reopening (Conflict in Du Chee Family photo) Yar Tan) End of winter, maghi End of Winter/// End of Winter End of Winter purnima (*E-Rabiul Au (Family Photo,school Mother Language Feb End of winter, Eid-E- wall, S-Safor Pya Tho- End of Winter vaccine campaign) Day (Magh-Falgun) miladunnobi 58 46 33 21 9 Tabo Dway Hindu festival (Kyauk Pan Do) Hervesting time work Hervesting time work Hervesting time Hervesting time work brick field, (Ended brick field, work brick field, brick field ((*E-Rabiul Hervesting time Mar Hervesting time work brick field, Family photo Matric Birth day of Au wall, S-Safor Pya (Falgun-Chaitra) work brick field 57 Local Upazila 45 Exam and (returning 32 20 Bangabandu 8 Tho-Tabo Dway Hindu election card on March 31) Independence Day festival (Kyauk Pan Do)
Harvesting time, Harvesting time, Harvesting time, New Harvesting time, Harvesting time, Harvesting time, New New year New year day/ year day (Pohela Bangla New year April (Chaitra-Baishakh) New year day year day (Pohela 56 day(Pohela 44 Pohela Boishak (End 31 Boishak). 19 day (Pohela 7 (Pohela Boishak). Boishak). Boishak). of hot season ) Boishak). Summer, Summer, Summer, Summer, Cyclone Summer, Buddho May (Baishakh-Jaishtha) Summer 55 42 Buddho purnima 30 Buddho purnima 18 Buddho purnima 6 mohashen purnima Shab-e-Barat Start of long rainy Start of long rainy Start of long rainy Start of long rainy Shobe-e Qadar & June Start of long rainy session, buddho session, Shab-e- session, session, Jummatul bida/ (Jaishtha-Ashar) session. 54 41 29 17 5 purnima Barat Shab-e-Barat Shab-e-Barat Eid-ul Fitr Start of Ramadan, Eid-ul fitor, Rainy Eid-ul fitor, Rainy Rainy session July Start of Ramadan, Eid-ul fitor, Rainy Jonmastomi, Rainy session session (Ashar-Srabon) Rainy session. 53 session 40 28 16 4 session. Rainy Session, Rainy Session, Rainy Session, Janmashtami Janmashtami Janmashtami
Aug Eid-ul fitor, Rainy Eid-ul fitor, Rainy Rainy Session, National
(Srabon-Vadro) session session 52 Janmashtami 39 27 15 Mourning 3 Day (Recent Conflict in Myanmar) Monsha Puja end of End of the long rainy End of the long rainy Eid Ul Adha Sept end of the long rainy End of the long 2 the long rainy session/ session/ Durgapuja (Vadro-Ashshin) session 51 rainy session 38 26 14 session. Eid-ul Azha, Eid-ul Azha, (Dashami) Durga Puja, Durga Puja, Durga Puja, 1 Eid-ul Azha, Durga Eid-ul Azha, Durga Moharram Moharram Moharram Oct , Go brick field up to nd Puja, Go brick field Puja, Go brick field ( 2 recent (Ashshin-Kartik) march. 50 37 25 13 up to march. up to march. Conflict in Myanmar) Harvesting time, Harvesting time, Start Start working in salt Start working in 0 Nov Start working in salt Start working in salt working in salt field, Harvesting time, field. salt field, (Kartik-Agrahayan) field, Moharram 49 36 field, 24 12 Start working in Moharram salt field, Christmas, Starting Christmas, Starting Christmas, Starting Christmas, Starting Christmas, Starting Dec (Agrahayon-Pous) Winter Winter Winter Winter 48 Winter 35 23 11
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Annex 11: Referral Form
Emergency Health and Nutrition Survey-2017 Referral Form DATE OF REFER:______Team Number:______Cluster HH No ______Camp Name: ______Block Name:______Block Leader Name: ______
Type: Children Pregnant Lactating
Name:______Mother Name/ Husband Name:______Age:______
Sex: Female Male
Measurement: Height:______cm; Weight:______kg, MUAC:______mm; Edema Yes No
Haemoglobin Level (g/dl):______
Referral Centre:______
Remarks:______
______Team Leader Name and Signature
Emergency Health and Nutrition Survey-2017 Referral Form DATE OF REFER:______Team Number:______Cluster HH No ______Camp Name: ______Block Name:______Block Leader Name: ______
Type: Children Pregnant Lactating
Name:______Mother Name/ Husband Name:______Age:______
Sex: Female Male
Measurement: Height:______cm; Weight:______kg, MUAC:______mm; Edema Yes No
Haemoglobin Level (g/dl):______
Referral Centre:______
Remarks:______Team Leader Name and Signature Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 143
Annex 12: Kutupalong Refugee Camp Plausibility Check
Plausibility check for: BD_102017_ACF_Kutupalong_Complete.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 (0.4 %)
Overall Sex ratio Incl p >0.1 >0.05 >0.001 <=0.001 (Significant chi square) 0 2 4 10 0 (p=0.100)
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=0.660)
Dig pref score - weight Incl # 0-7 8-12 13-20 > 20 0 2 4 10 0 (6)
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 0 (7)
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 (1.11)
Skewness WHZ Excl # <±0.2 <±0.4 <±0.6 >=±0.6 0 1 3 5 1 (-0.23)
Kurtosis WHZ Excl # <±0.2 <±0.4 <±0.6 >=±0.6 0 1 3 5 1 (-0.21)
Poisson dist WHZ-2 Excl p >0.05 >0.01 >0.001 <=0.001 0 1 3 5 0 (p=)
OVERALL SCORE WHZ = 0-9 10-14 15-24 >25 7 %
The overall score of this survey is 7 %, this is excellent.
There were no duplicate entries detected.
Percentage of children with no exact birthday: 35 %
Anthropometric Indices likely to be in error (-3 to 3 for WHZ, -3 to 3 for HAZ, -3 to 3 for Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 144
WAZ, from observed mean - chosen in Options panel - these values will be flagged and should be excluded from analysis for a nutrition survey in emergencies. For other surveys this might not be the best procedure e.g. when the percentage of overweight children has to be calculated):
Line=81/ID=5: WHZ (-4.468), Height may be incorrect Line=135/ID=5: HAZ (1.448), Age may be incorrect Line=261/ID=4: HAZ (1.585), Age may be incorrect
Percentage of values flagged with SMART flags:WHZ: 0.4 %, HAZ: 0.7 %, WAZ: 0.0 %
Age distribution:
Month 6 : #### Month 7 : ###### Month 8 : ####### Month 9 : #### Month 10 : #### Month 11 : ###### Month 12 : ###### Month 13 : ##### Month 14 : ###### Month 15 : ####### Month 16 : ###### Month 17 : ##### Month 18 : ###### Month 19 : ## Month 20 : ### Month 21 : ### Month 22 : #### Month 23 : #### Month 24 : ## Month 25 : ###### Month 26 : #### Month 27 : ##### Month 28 : ###### Month 29 : ####### Month 30 : ############# Month 31 : ##### Month 32 : # Month 33 : ###### Month 34 : #### Month 35 : #### Month 36 : ####### Month 37 : ####
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Month 38 : ############ Month 39 : ##### Month 40 : ### Month 41 : ### Month 42 : ########## Month 43 : ## Month 44 : ## Month 45 : ### Month 46 : ###### Month 47 : ### Month 48 : ########### Month 49 : ##### Month 50 : ### Month 51 : ### Month 52 : ## Month 53 : ####### Month 54 : ####### Month 55 : #### Month 56 : ###### Month 57 : #### Month 58 : ##### Month 59 : #
Age ratio of 6-29 months to 30-59 months: 0.81 (The value should be around 0.85).: p-value = 0.660 (as expected)
Statistical evaluation of sex and age ratios (using Chi squared statistic):
Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 40/34.3 (1.2) 29/28.1 (1.0) 69/62.4 (1.1) 1.38 18 to 29 12 26/33.5 (0.8) 25/27.4 (0.9) 51/60.9 (0.8) 1.04 30 to 41 12 40/32.5 (1.2) 28/26.5 (1.1) 68/59.0 (1.2) 1.43 42 to 53 12 29/31.9 (0.9) 27/26.1 (1.0) 56/58.0 (1.0) 1.07 54 to 59 6 13/15.8 (0.8) 12/12.9 (0.9) 25/28.7 (0.9) 1.08 ------6 to 59 54 148/134.5 (1.1) 121/134.5 (0.9) 1.22
The data are expressed as observed number/expected number (ratio of obs/expect)
Overall sex ratio: p-value = 0.100 (boys and girls equally represented) Overall age distribution: p-value = 0.377 (as expected) Overall age distribution for boys: p-value = 0.275 (as expected) Overall age distribution for girls: p-value = 0.981 (as expected) Overall sex/age distribution: p-value = 0.068 (as expected)
Digit preference Weight:
Digit .0 : ########################### Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 146
Digit .1 : ############################# Digit .2 : ################## Digit .3 : ########################### Digit .4 : ############################### Digit .5 : ############################# Digit .6 : ##################### Digit .7 : ############################## Digit .8 : #################################### Digit .9 : #####################
Digit preference score: 6 (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) p-value for chi2: 0.357
Digit preference Height:
Digit .0 : ####################### Digit .1 : ############################### Digit .2 : ################################### Digit .3 : ################################## Digit .4 : ############################# Digit .5 : ########################### Digit .6 : ########################### Digit .7 : ########################## Digit .8 : ################## Digit .9 : ###################
Digit preference score: 7 (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) p-value for chi2: 0.278
Digit preference MUAC:
Digit .0 : ####################### Digit .1 : #################################### Digit .2 : ######################## Digit .3 : ###################### Digit .4 : ################################ Digit .5 : ###################### Digit .6 : ########################### Digit .7 : #################### Digit .8 : ############################# Digit .9 : ##################################
Digit preference score: 7 (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) p-value for chi2: 0.310
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Evaluation of Standard deviation, Normal distribution, Skewness and Kurtosis using the 3 exclusion (Flag) procedures
. no exclusion exclusion from exclusion from . reference mean observed mean . (WHO flags) (SMART flags) WHZ Standard Deviation SD: 1.12 1.12 1.11 (The SD should be between 0.8 and 1.2) Prevalence (< -2) observed: 24.5% 24.5% 24.3% calculated with current SD: 26.6% 26.6% 25.9% calculated with a SD of 1: 24.1% 24.1% 23.7%
HAZ Standard Deviation SD: 1.15 1.15 1.11 (The SD should be between 0.8 and 1.2) Prevalence (< -2) observed: 43.1% 43.1% 43.4% calculated with current SD: 42.0% 42.0% 42.7% calculated with a SD of 1: 40.9% 40.9% 41.8%
WAZ Standard Deviation SD: 1.01 1.01 1.01 (The SD should be between 0.8 and 1.2) Prevalence (< -2) observed: 45.0% 45.0% 45.0% calculated with current SD: 45.7% 45.7% 45.7% calculated with a SD of 1: 45.7% 45.7% 45.7%
Results for Shapiro-Wilk test for normally (Gaussian) distributed data: WHZ p= 0.143 p= 0.143 p= 0.190 HAZ p= 0.079 p= 0.079 p= 0.140 WAZ p= 0.104 p= 0.104 p= 0.104 (If p < 0.05 then the data are not normally distributed. If p > 0.05 you can consider the data normally distributed)
Skewness WHZ -0.28 -0.28 -0.23 HAZ 0.30 0.30 0.20 WAZ 0.05 0.05 0.05 If the value is: -below minus 0.4 there is a relative excess of wasted/stunted/underweight subjects in the sample -between minus 0.4 and minus 0.2, there may be a relative excess of wasted/stunted/underweight subjects in the sample. -between minus 0.2 and plus 0.2, the distribution can be considered as symmetrical. -between 0.2 and 0.4, there may be an excess of obese/tall/overweight subjects in the sample. -above 0.4, there is an excess of obese/tall/overweight subjects in the sample
Kurtosis WHZ -0.13 -0.13 -0.21 HAZ -0.09 -0.09 -0.28 WAZ -0.46 -0.46 -0.46 Kurtosis characterizes the relative size of the body versus the tails of the distribution. Positive kurtosis indicates relatively large tails and small body. Negative kurtosis indicates relatively large body and small tails. If the absolute value is: -above 0.4 it indicates a problem. There might have been a problem with data collection or sampling. -between 0.2 and 0.4, the data may be affected with a problem. -less than an absolute value of 0.2 the distribution can be considered as normal.
Are the data of the same quality at the beginning and the end of the clusters? Evaluation of the SD for WHZ depending upon the order the cases are measured within each Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 148
cluster (if one cluster per day is measured then this will be related to the time of the day the measurement is made).
Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3
(when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points)
Analysis by Team
Team 1 2 3 4 5 6 n = 38 49 50 36 43 53 Percentage of values flagged with SMART flags: WHZ: 0.0 0.0 0.0 0.0 0.0 1.9 HAZ: 0.0 2.0 0.0 0.0 0.0 1.9 WAZ: 0.0 0.0 0.0 0.0 0.0 0.0 Age ratio of 6-29 months to 30-59 months: 0.65 0.96 0.92 0.80 0.95 0.61 Sex ratio (male/female): 1.11 1.04 1.17 1.57 1.69 1.04 Digit preference Weight (%): .0 : 11 14 12 6 9 8 .1 : 8 16 2 6 16 15 .2 : 5 2 8 11 2 11 .3 : 16 10 10 11 14 2 .4 : 11 10 18 8 7 13 .5 : 13 8 12 14 9 9 .6 : 8 4 8 17 7 6 .7 : 13 14 14 8 9 8 .8 : 13 16 10 8 16 15 .9 : 3 4 6 11 9 13 DPS: 13 17 14 11 14 14 Digit preference score (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) Digit preference Height (%): .0 : 3 8 6 3 5 23 .1 : 13 10 8 11 16 11 .2 : 16 8 6 11 12 25 .3 : 13 12 20 6 19 6 .4 : 13 14 12 8 9 8 .5 : 21 8 4 14 7 9 .6 : 11 12 8 8 12 9 .7 : 8 12 14 14 5 6 .8 : 3 6 12 11 5 4 .9 : 0 8 10 14 12 0 DPS: 21 8 15 12 16 25 Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 149
Digit preference score (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) Digit preference MUAC (%): .0 : 11 2 16 6 7 9 .1 : 13 10 12 17 12 17 .2 : 13 10 6 8 7 9 .3 : 5 6 8 11 5 13 .4 : 21 10 20 8 12 2 .5 : 3 8 8 11 12 8 .6 : 5 10 10 11 16 8 .7 : 11 8 4 6 9 8 .8 : 8 20 8 3 12 11 .9 : 11 14 8 19 9 15 DPS: 17 15 15 16 10 14 Digit preference score (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) Standard deviation of WHZ: SD 0.95 1.16 1.05 1.07 1.08 1.31 Prevalence (< -2) observed: % 30.6 22.0 22.2 30.2 28.3 Prevalence (< -2) calculated with current SD: % 32.5 21.3 17.9 32.1 32.1 Prevalence (< -2) calculated with a SD of 1: % 29.9 20.1 16.4 30.8 27.2 Standard deviation of HAZ: SD 1.30 1.24 0.86 0.89 1.09 1.24 observed: % 42.1 44.9 37.2 30.2 calculated with current SD: % 41.7 49.2 38.7 27.6 calculated with a SD of 1: % 39.2 49.1 37.6 23.0
Statistical evaluation of sex and age ratios (using Chi squared statistic) for:
Team 1:
Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 6/4.6 (1.3) 4/4.2 (1.0) 10/8.8 (1.1) 1.50 18 to 29 12 1/4.5 (0.2) 4/4.1 (1.0) 5/8.6 (0.6) 0.25 30 to 41 12 6/4.4 (1.4) 2/3.9 (0.5) 8/8.3 (1.0) 3.00 42 to 53 12 4/4.3 (0.9) 4/3.9 (1.0) 8/8.2 (1.0) 1.00 54 to 59 6 3/2.1 (1.4) 4/1.9 (2.1) 7/4.1 (1.7) 0.75 ------6 to 59 54 20/19.0 (1.1) 18/19.0 (0.9) 1.11
The data are expressed as observed number/expected number (ratio of obs/expect)
Overall sex ratio: p-value = 0.746 (boys and girls equally represented) Overall age distribution: p-value = 0.431 (as expected) Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 150
Overall age distribution for boys: p-value = 0.391 (as expected) Overall age distribution for girls: p-value = 0.521 (as expected) Overall sex/age distribution: p-value = 0.112 (as expected)
Team 2:
Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 9/5.8 (1.6) 4/5.6 (0.7) 13/11.4 (1.1) 2.25 18 to 29 12 5/5.7 (0.9) 6/5.4 (1.1) 11/11.1 (1.0) 0.83 30 to 41 12 3/5.5 (0.5) 4/5.3 (0.8) 7/10.7 (0.7) 0.75 42 to 53 12 6/5.4 (1.1) 8/5.2 (1.5) 14/10.6 (1.3) 0.75 54 to 59 6 2/2.7 (0.7) 2/2.6 (0.8) 4/5.2 (0.8) 1.00 ------6 to 59 54 25/24.5 (1.0) 24/24.5 (1.0) 1.04
The data are expressed as observed number/expected number (ratio of obs/expect)
Overall sex ratio: p-value = 0.886 (boys and girls equally represented) Overall age distribution: p-value = 0.568 (as expected) Overall age distribution for boys: p-value = 0.525 (as expected) Overall age distribution for girls: p-value = 0.651 (as expected) Overall sex/age distribution: p-value = 0.223 (as expected)
Team 3:
Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 4/6.3 (0.6) 9/5.3 (1.7) 13/11.6 (1.1) 0.44 18 to 29 12 5/6.1 (0.8) 6/5.2 (1.2) 11/11.3 (1.0) 0.83 30 to 41 12 8/5.9 (1.4) 4/5.0 (0.8) 12/11.0 (1.1) 2.00 42 to 53 12 7/5.8 (1.2) 2/5.0 (0.4) 9/10.8 (0.8) 3.50 54 to 59 6 3/2.9 (1.0) 2/2.5 (0.8) 5/5.3 (0.9) 1.50 ------6 to 59 54 27/25.0 (1.1) 23/25.0 (0.9) 1.17
The data are expressed as observed number/expected number (ratio of obs/expect)
Overall sex ratio: p-value = 0.572 (boys and girls equally represented) Overall age distribution: p-value = 0.964 (as expected) Overall age distribution for boys: p-value = 0.737 (as expected) Overall age distribution for girls: p-value = 0.319 (as expected) Overall sex/age distribution: p-value = 0.147 (as expected)
Team 4:
Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 4/5.1 (0.8) 4/3.2 (1.2) 8/8.4 (1.0) 1.00 18 to 29 12 7/5.0 (1.4) 1/3.2 (0.3) 8/8.1 (1.0) 7.00 30 to 41 12 6/4.8 (1.2) 4/3.1 (1.3) 10/7.9 (1.3) 1.50 42 to 53 12 4/4.7 (0.8) 3/3.0 (1.0) 7/7.8 (0.9) 1.33 54 to 59 6 1/2.3 (0.4) 2/1.5 (1.3) 3/3.8 (0.8) 0.50 ------6 to 59 54 22/18.0 (1.2) 14/18.0 (0.8) 1.57
Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 151
The data are expressed as observed number/expected number (ratio of obs/expect)
Overall sex ratio: p-value = 0.182 (boys and girls equally represented) Overall age distribution: p-value = 0.933 (as expected) Overall age distribution for boys: p-value = 0.692 (as expected) Overall age distribution for girls: p-value = 0.716 (as expected) Overall sex/age distribution: p-value = 0.188 (as expected)
Team 5:
Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 11/6.3 (1.8) 2/3.7 (0.5) 13/10.0 (1.3) 5.50 18 to 29 12 5/6.1 (0.8) 3/3.6 (0.8) 8/9.7 (0.8) 1.67 30 to 41 12 7/5.9 (1.2) 4/3.5 (1.1) 11/9.4 (1.2) 1.75 42 to 53 12 4/5.8 (0.7) 6/3.5 (1.7) 10/9.3 (1.1) 0.67 54 to 59 6 0/2.9 (0.0) 1/1.7 (0.6) 1/4.6 (0.2) 0.00 ------6 to 59 54 27/21.5 (1.3) 16/21.5 (0.7) 1.69
The data are expressed as observed number/expected number (ratio of obs/expect)
Overall sex ratio: p-value = 0.093 (boys and girls equally represented) Overall age distribution: p-value = 0.361 (as expected) Overall age distribution for boys: p-value = 0.115 (as expected) Overall age distribution for girls: p-value = 0.535 (as expected) Overall sex/age distribution: p-value = 0.006 (significant difference)
Team 6:
Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 6/6.3 (1.0) 6/6.0 (1.0) 12/12.3 (1.0) 1.00 18 to 29 12 3/6.1 (0.5) 5/5.9 (0.9) 8/12.0 (0.7) 0.60 30 to 41 12 10/5.9 (1.7) 10/5.7 (1.8) 20/11.6 (1.7) 1.00 42 to 53 12 4/5.8 (0.7) 4/5.6 (0.7) 8/11.4 (0.7) 1.00 54 to 59 6 4/2.9 (1.4) 1/2.8 (0.4) 5/5.7 (0.9) 4.00 ------6 to 59 54 27/26.5 (1.0) 26/26.5 (1.0) 1.04
The data are expressed as observed number/expected number (ratio of obs/expect)
Overall sex ratio: p-value = 0.891 (boys and girls equally represented) Overall age distribution: p-value = 0.075 (as expected) Overall age distribution for boys: p-value = 0.248 (as expected) Overall age distribution for girls: p-value = 0.290 (as expected) Overall sex/age distribution: p-value = 0.034 (significant difference)
Evaluation of the SD for WHZ depending upon the order the cases are measured within each cluster (if one cluster per day is measured then this will be related to the time of the day the measurement is made).
Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 152
Team: 1
Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3
(when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points)
Team: 2
Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3
(when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points)
Team: 3
Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3
(when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points)
Team: 4
Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3
(when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points)
Team: 5
Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3
(when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points)
Team: 6
Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3
(when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points)
(for better comparison it can be helpful to copy/paste part of this report into Excel)
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Annex 13: Makeshift Settlements Plausibility Check
Plausibility check for: BAN_112017_ACF_Makeshift_6-59.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 (0.1 %)
Overall Sex ratio Incl p >0.1 >0.05 >0.001 <=0.001 (Significant chi square) 0 2 4 10 2 (p=0.051)
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=0.781)
Dig pref score - weight Incl # 0-7 8-12 13-20 > 20 0 2 4 10 0 (3)
Dig pref score - height Incl # 0-7 8-12 13-20 > 20 0 2 4 10 2 (8)
Dig pref score - MUAC Incl # 0-7 8-12 13-20 > 20 0 2 4 10 0 (4)
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 0 (0.93)
Skewness WHZ Excl # <±0.2 <±0.4 <±0.6 >=±0.6 0 1 3 5 0 (-0.15)
Kurtosis WHZ Excl # <±0.2 <±0.4 <±0.6 >=±0.6 0 1 3 5 0 (0.13)
Poisson dist WHZ-2 Excl p >0.05 >0.01 >0.001 <=0.001 0 1 3 5 1 (p=0.020)
OVERALL SCORE WHZ = 0-9 10-14 15-24 >25 5 %
The overall score of this survey is 5 %, this is excellent.
There were no duplicate entries detected.
Missing or wrong data:
WEIGHT: Line=1/ID=3, Line=23/ID=4, Line=50/ID=4, Line=188/ID=9, Line=266/ID=6, Line=317/ID=3, Line=332/ID=3, Line=340/ID=7, Line=343/ID=5, Line=357/ID=5,
Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 154
Line=422/ID=3, Line=461/ID=5, Line=541/ID=4, Line=567/ID=3, Line=609/ID=5, Line=612/ID=4, Line=618/ID=8, Line=624/ID=8, Line=637/ID=3, Line=708/ID=5, Line=739/ID=8, Line=840/ID=4, Line=867/ID=9, Line=965/ID=9, Line=1009/ID=8 HEIGHT: Line=1/ID=3, Line=23/ID=4, Line=50/ID=4, Line=188/ID=9, Line=266/ID=6, Line=317/ID=3, Line=332/ID=3, Line=340/ID=7, Line=343/ID=5, Line=357/ID=5, Line=422/ID=3, Line=461/ID=5, Line=541/ID=4, Line=567/ID=3, Line=609/ID=5, Line=612/ID=4, Line=618/ID=8, Line=624/ID=8, Line=637/ID=3, Line=668/ID=3, Line=708/ID=5, Line=739/ID=8, Line=840/ID=4, Line=867/ID=9, Line=965/ID=9, Line=1009/ID=8
Percentage of children with no exact birthday: 80 %
Anthropometric Indices likely to be in error (-3 to 3 for WHZ, -3 to 3 for HAZ, -3 to 3 for WAZ, from observed mean - chosen in Options panel - these values will be flagged and should be excluded from analysis for a nutrition survey in emergencies. For other surveys this might not be the best procedure e.g. when the percentage of overweight children has to be calculated):
Line=47/ID=6: WAZ (1.484), Weight may be incorrect Line=63/ID=6: HAZ (1.388), Age may be incorrect Line=71/ID=4: WHZ (-4.688), WAZ (-5.506), Weight may be incorrect Line=76/ID=6: HAZ (1.637), Age may be incorrect Line=87/ID=6: HAZ (-5.457), Age may be incorrect Line=197/ID=4: HAZ (-4.924), Age may be incorrect Line=239/ID=3: HAZ (1.314), Age may be incorrect Line=247/ID=9: HAZ (-5.672), WAZ (-5.517), Age may be incorrect Line=256/ID=3: HAZ (-4.860), Age may be incorrect Line=287/ID=7: HAZ (-5.807), Height may be incorrect Line=337/ID=3: HAZ (-5.097), Age may be incorrect Line=369/ID=5: HAZ (-5.154), Age may be incorrect Line=523/ID=3: HAZ (1.706), Height may be incorrect Line=579/ID=6: HAZ (1.415), Age may be incorrect Line=607/ID=3: HAZ (-4.870), Age may be incorrect Line=788/ID=5: HAZ (2.663), WAZ (1.230), Age may be incorrect Line=818/ID=6: HAZ (1.354), Age may be incorrect Line=961/ID=5: HAZ (1.288), WAZ (1.226), Age may be incorrect
Percentage of values flagged with SMART flags:WHZ: 0.1 %, HAZ: 1.5 %, WAZ: 0.5 %
Age distribution:
Month 6 : ################## Month 7 : ##########################
Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 155
Month 8 : ##################### Month 9 : ################# Month 10 : ######################## Month 11 : ########################## Month 12 : ################### Month 13 : ################## Month 14 : ########################## Month 15 : ############# Month 16 : ###################### Month 17 : ##################### Month 18 : ######################################## Month 19 : ##################### Month 20 : ######### Month 21 : ######## Month 22 : ############### Month 23 : ################ Month 24 : ############# Month 25 : ############################################ Month 26 : #################################### Month 27 : ######################## Month 28 : ####################### Month 29 : ################ Month 30 : ################################# Month 31 : ################### Month 32 : ###### Month 33 : ####### Month 34 : ############## Month 35 : ############ Month 36 : ########################## Month 37 : ############################################### Month 38 : ######################## Month 39 : ##################### Month 40 : ########################### Month 41 : ##################### Month 42 : ####################### Month 43 : ############ Month 44 : ####### Month 45 : ########### Month 46 : ############## Month 47 : #################### Month 48 : ################ Month 49 : ############################### Month 50 : ############################## Month 51 : ################# Month 52 : ################### Month 53 : ###################
Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 156
Month 54 : ############################# Month 55 : ########################## Month 56 : ############## Month 57 : ########## Month 58 : ########################## Month 59 : ############### Month 60 : #
Age ratio of 6-29 months to 30-59 months: 0.86 (The value should be around 0.85).: p-value = 0.781 (as expected)
Statistical evaluation of sex and age ratios (using Chi squared statistic):
Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 135/136.7 (1.0) 117/121.6 (1.0) 252/258.2 (1.0) 1.15 18 to 29 12 127/133.2 (1.0) 137/118.5 (1.2) 264/251.8 (1.0) 0.93 30 to 41 12 142/129.1 (1.1) 116/114.9 (1.0) 258/244.0 (1.1) 1.22 42 to 53 12 115/127.1 (0.9) 103/113.1 (0.9) 218/240.2 (0.9) 1.12 54 to 59 6 70/62.9 (1.1) 51/55.9 (0.9) 121/118.8 (1.0) 1.37 ------6 to 59 54 589/556.5 (1.1) 524/556.5 (0.9) 1.12
The data are expressed as observed number/expected number (ratio of obs/expect)
Overall sex ratio: p-value = 0.051 (boys and girls equally represented) Overall age distribution: p-value = 0.459 (as expected) Overall age distribution for boys: p-value = 0.470 (as expected) Overall age distribution for girls: p-value = 0.356 (as expected) Overall sex/age distribution: p-value = 0.020 (significant difference)
Digit preference Weight:
Digit .0 : ############################################## Digit .1 : ########################################################## Digit .2 : ##################################################### Digit .3 : ################################################ Digit .4 : ########################################################## Digit .5 : ############################################################ Digit .6 : ######################################################## Digit .7 : ############################################################ Digit .8 : #################################################### Digit .9 : ######################################################
Digit preference score: 3 (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) p-value for chi2: 0.651
Digit preference Height: Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 157
Digit .0 : ################## Digit .1 : ############################################### Digit .2 : ########################################### Digit .3 : ############################################# Digit .4 : ################################### Digit .5 : ############################# Digit .6 : ####################################### Digit .7 : ######################################## Digit .8 : ###################################### Digit .9 : #############################
Digit preference score: 8 (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) p-value for chi2: 0.000 (significant difference)
Digit preference MUAC:
Digit .0 : ################################################ Digit .1 : ######################################################## Digit .2 : ########################################################## Digit .3 : ############################################################## Digit .4 : ############################################## Digit .5 : ################################################ Digit .6 : ########################################################## Digit .7 : ############################################################# Digit .8 : ########################################################### Digit .9 : ###############################################
Digit preference score: 4 (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) p-value for chi2: 0.203
Evaluation of Standard deviation, Normal distribution, Skewness and Kurtosis using the 3 exclusion (Flag) procedures
. no exclusion exclusion from exclusion from . reference mean observed mean . (WHO flags) (SMART flags) WHZ Standard Deviation SD: 0.94 0.94 0.93 (The SD should be between 0.8 and 1.2) Prevalence (< -2) observed: calculated with current SD: calculated with a SD of 1:
HAZ Standard Deviation SD: 1.15 1.15 1.08 (The SD should be between 0.8 and 1.2) Prevalence (< -2) observed: 44.2% 44.2% 44.1% Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 158
calculated with current SD: 42.5% 42.5% 42.0% calculated with a SD of 1: 41.4% 41.4% 41.4%
WAZ Standard Deviation SD: 0.93 0.93 0.91 (The SD should be between 0.8 and 1.2) Prevalence (< -2) observed: calculated with current SD: calculated with a SD of 1:
Results for Shapiro-Wilk test for normally (Gaussian) distributed data: WHZ p= 0.018 p= 0.018 p= 0.037 HAZ p= 0.057 p= 0.057 p= 0.024 WAZ p= 0.081 p= 0.081 p= 0.083 (If p < 0.05 then the data are not normally distributed. If p > 0.05 you can consider the data normally distributed)
Skewness WHZ -0.19 -0.19 -0.15 HAZ 0.07 0.07 0.10 WAZ -0.11 -0.11 -0.10 If the value is: -below minus 0.4 there is a relative excess of wasted/stunted/underweight subjects in the sample -between minus 0.4 and minus 0.2, there may be a relative excess of wasted/stunted/underweight subjects in the sample. -between minus 0.2 and plus 0.2, the distribution can be considered as symmetrical. -between 0.2 and 0.4, there may be an excess of obese/tall/overweight subjects in the sample. -above 0.4, there is an excess of obese/tall/overweight subjects in the sample
Kurtosis WHZ 0.23 0.23 0.13 HAZ 0.35 0.35 -0.27 WAZ 0.28 0.28 -0.22 Kurtosis characterizes the relative size of the body versus the tails of the distribution. Positive kurtosis indicates relatively large tails and small body. Negative kurtosis indicates relatively large body and small tails. If the absolute value is: -above 0.4 it indicates a problem. There might have been a problem with data collection or sampling. -between 0.2 and 0.4, the data may be affected with a problem. -less than an absolute value of 0.2 the distribution can be considered as normal.
Test if cases are randomly distributed or aggregated over the clusters by calculation of the Index of Dispersion (ID) and comparison with the Poisson distribution for:
WHZ < -2: ID=1.32 (p=0.020) WHZ < -3: ID=0.85 (p=0.857) GAM: ID=1.32 (p=0.020) SAM: ID=0.85 (p=0.857) HAZ < -2: ID=1.36 (p=0.012) HAZ < -3: ID=1.09 (p=0.249) WAZ < -2: ID=1.50 (p=0.001) WAZ < -3: ID=1.62 (p=0.000)
Subjects with SMART flags are excluded from this analysis.
The Index of Dispersion (ID) indicates the degree to which the cases are aggregated into certain clusters (the degree to which there are "pockets"). If the ID is less than 1 and p > 0.95 it indicates that the cases are UNIFORMLY distributed among the clusters. If the p value is between 0.05 and 0.95 the cases appear to be randomly distributed among the clusters, if ID is higher than 1 Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 159
and p is less than 0.05 the cases are aggregated into certain cluster (there appear to be pockets of cases). If this is the case for Oedema but not for WHZ then aggregation of GAM and SAM cases is likely due to inclusion of oedematous cases in GAM and SAM estimates.
Are the data of the same quality at the beginning and the end of the clusters? Evaluation of the SD for WHZ depending upon the order the cases are measured within each cluster (if one cluster per day is measured then this will be related to the time of the day the measurement is made).
Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 01: 0.96 (n=95, f=0) ####### 02: 0.87 (n=92, f=0) ### 03: 1.04 (n=93, f=0) ########## 04: 0.97 (n=95, f=1) ####### 05: 1.01 (n=96, f=0) ######### 06: 0.92 (n=90, f=0) ##### 07: 0.97 (n=87, f=0) ####### 08: 0.87 (n=77, f=0) ### 09: 0.88 (n=70, f=0) ### 10: 0.89 (n=62, f=0) #### 11: 0.92 (n=59, f=0) ##### 12: 0.93 (n=45, f=0) ###### 13: 1.04 (n=35, f=0) OOOOOOOOOO 14: 0.90 (n=28, f=0) OOOO 15: 0.82 (n=22, f=0) O 16: 0.78 (n=17, f=0) 17: 0.76 (n=10, f=0) 18: 0.93 (n=06, f=0) ~~~~~ 19: 0.86 (n=04, f=0) ~~
(when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points)
Analysis by Team
Team 1 2 3 4 5 6 n = 216 172 177 179 199 170 Percentage of values flagged with SMART flags: WHZ: 0.5 0.0 1.1 1.1 3.1 7.6 HAZ: 2.3 1.2 0.6 1.7 4.7 9.5 WAZ: 0.5 1.2 1.1 1.1 3.6 7.6 Age ratio of 6-29 months to 30-59 months: 0.71 0.76 0.86 0.86 1.16 0.89 Sex ratio (male/female): 0.88 1.39 1.01 0.95 1.65 1.07 Digit preference Weight (%): .0 : 9 5 9 9 12 5 .1 : 7 11 14 10 11 10 .2 : 11 8 7 11 8 13 .3 : 11 8 11 8 6 9
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.4 : 8 12 12 10 10 12 .5 : 10 13 12 13 9 9 .6 : 12 8 13 7 9 13 .7 : 8 14 9 14 11 10 .8 : 10 13 7 10 11 6 .9 : 13 10 6 8 11 11 DPS: 5 9 8 7 6 8 Digit preference score (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) Digit preference Height (%): .0 : 3 6 11 6 4 1 .1 : 13 10 9 16 13 18 .2 : 11 14 14 10 12 10 .3 : 10 11 19 14 10 10 .4 : 11 8 9 8 12 9 .5 : 9 9 5 8 9 7 .6 : 12 17 6 8 12 9 .7 : 11 8 9 12 9 18 .8 : 13 10 14 8 10 7 .9 : 7 6 6 10 8 11 DPS: 10 11 14 10 8 16 Digit preference score (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) Digit preference MUAC (%): .0 : 4 5 11 12 11 11 .1 : 9 11 11 10 5 17 .2 : 15 11 12 7 8 10 .3 : 14 8 14 12 13 6 .4 : 12 10 6 6 12 4 .5 : 6 8 11 10 10 8 .6 : 9 12 9 11 11 12 .7 : 11 14 9 12 7 16 .8 : 10 17 10 7 15 5 .9 : 10 6 6 12 7 11 DPS: 10 11 8 7 10 14 Digit preference score (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) Standard deviation of WHZ: SD 0.90 0.93 0.93 0.84 0.94 1.08 Prevalence (< -2) observed: % 25.3 Prevalence (< -2) calculated with current SD: % 25.2 Prevalence (< -2) calculated with a SD of 1: % 23.7 Standard deviation of HAZ: SD 1.07 1.25 0.93 1.23 1.09 1.26 observed: % 37.7 44.0 42.4 55.4 41.8
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calculated with current SD: % 34.1 43.5 39.9 51.5 40.7 calculated with a SD of 1: % 33.1 41.9 37.7 51.7 38.4
Statistical evaluation of sex and age ratios (using Chi squared statistic) for:
Team 1:
Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 26/23.4 (1.1) 23/26.7 (0.9) 49/50.1 (1.0) 1.13 18 to 29 12 14/22.8 (0.6) 27/26.0 (1.0) 41/48.9 (0.8) 0.52 30 to 41 12 25/22.1 (1.1) 27/25.2 (1.1) 52/47.4 (1.1) 0.93 42 to 53 12 27/21.8 (1.2) 26/24.8 (1.0) 53/46.6 (1.1) 1.04 54 to 59 6 9/10.8 (0.8) 12/12.3 (1.0) 21/23.1 (0.9) 0.75 ------6 to 59 54 101/108.0 (0.9) 115/108.0 (1.1) 0.88
The data are expressed as observed number/expected number (ratio of obs/expect)
Overall sex ratio: p-value = 0.341 (boys and girls equally represented) Overall age distribution: p-value = 0.591 (as expected) Overall age distribution for boys: p-value = 0.230 (as expected) Overall age distribution for girls: p-value = 0.947 (as expected) Overall sex/age distribution: p-value = 0.139 (as expected)
Team 2:
Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 25/23.2 (1.1) 10/16.7 (0.6) 35/39.9 (0.9) 2.50 18 to 29 12 18/22.6 (0.8) 21/16.3 (1.3) 39/38.9 (1.0) 0.86 30 to 41 12 26/21.9 (1.2) 14/15.8 (0.9) 40/37.7 (1.1) 1.86 42 to 53 12 17/21.6 (0.8) 20/15.5 (1.3) 37/37.1 (1.0) 0.85 54 to 59 6 14/10.7 (1.3) 7/7.7 (0.9) 21/18.4 (1.1) 2.00 ------6 to 59 54 100/86.0 (1.2) 72/86.0 (0.8) 1.39
The data are expressed as observed number/expected number (ratio of obs/expect)
Overall sex ratio: p-value = 0.033 (significant excess of boys) Overall age distribution: p-value = 0.891 (as expected) Overall age distribution for boys: p-value = 0.427 (as expected) Overall age distribution for girls: p-value = 0.231 (as expected) Overall sex/age distribution: p-value = 0.008 (significant difference)
Team 3:
Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 16/20.6 (0.8) 27/20.4 (1.3) 43/41.1 (1.0) 0.59 18 to 29 12 23/20.1 (1.1) 16/19.9 (0.8) 39/40.0 (1.0) 1.44 Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 162
30 to 41 12 18/19.5 (0.9) 22/19.3 (1.1) 40/38.8 (1.0) 0.82 42 to 53 12 20/19.2 (1.0) 17/19.0 (0.9) 37/38.2 (1.0) 1.18 54 to 59 6 12/9.5 (1.3) 6/9.4 (0.6) 18/18.9 (1.0) 2.00 ------6 to 59 54 89/88.5 (1.0) 88/88.5 (1.0) 1.01
The data are expressed as observed number/expected number (ratio of obs/expect)
Overall sex ratio: p-value = 0.940 (boys and girls equally represented) Overall age distribution: p-value = 0.994 (as expected) Overall age distribution for boys: p-value = 0.687 (as expected) Overall age distribution for girls: p-value = 0.319 (as expected) Overall sex/age distribution: p-value = 0.138 (as expected)
Team 4:
Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 19/20.2 (0.9) 16/21.3 (0.7) 35/41.5 (0.8) 1.19 18 to 29 12 23/19.7 (1.2) 25/20.8 (1.2) 48/40.5 (1.2) 0.92 30 to 41 12 18/19.1 (0.9) 21/20.2 (1.0) 39/39.2 (1.0) 0.86 42 to 53 12 12/18.8 (0.6) 15/19.9 (0.8) 27/38.6 (0.7) 0.80 54 to 59 6 15/9.3 (1.6) 15/9.8 (1.5) 30/19.1 (1.6) 1.00 ------6 to 59 54 87/89.5 (1.0) 92/89.5 (1.0) 0.95
The data are expressed as observed number/expected number (ratio of obs/expect)
Overall sex ratio: p-value = 0.709 (boys and girls equally represented) Overall age distribution: p-value = 0.016 (significant difference) Overall age distribution for boys: p-value = 0.156 (as expected) Overall age distribution for girls: p-value = 0.189 (as expected) Overall sex/age distribution: p-value = 0.012 (significant difference)
Team 5:
Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 33/28.8 (1.1) 23/17.4 (1.3) 56/46.2 (1.2) 1.43 18 to 29 12 30/28.1 (1.1) 21/17.0 (1.2) 51/45.0 (1.1) 1.43 30 to 41 12 29/27.2 (1.1) 12/16.4 (0.7) 41/43.6 (0.9) 2.42 42 to 53 12 23/26.8 (0.9) 12/16.2 (0.7) 35/42.9 (0.8) 1.92 54 to 59 6 9/13.2 (0.7) 7/8.0 (0.9) 16/21.2 (0.8) 1.29 ------6 to 59 54 124/99.5 (1.2) 75/99.5 (0.8) 1.65
The data are expressed as observed number/expected number (ratio of obs/expect)
Overall sex ratio: p-value = 0.001 (significant excess of boys) Overall age distribution: p-value = 0.214 (as expected) Overall age distribution for boys: p-value = 0.599 (as expected) Overall age distribution for girls: p-value = 0.270 (as expected) Overall sex/age distribution: p-value = 0.001 (significant difference)
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Team 6:
Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 16/20.4 (0.8) 18/19.0 (0.9) 34/39.4 (0.9) 0.89 18 to 29 12 19/19.9 (1.0) 27/18.5 (1.5) 46/38.5 (1.2) 0.70 30 to 41 12 26/19.3 (1.3) 20/18.0 (1.1) 46/37.3 (1.2) 1.30 42 to 53 12 16/19.0 (0.8) 13/17.7 (0.7) 29/36.7 (0.8) 1.23 54 to 59 6 11/9.4 (1.2) 4/8.8 (0.5) 15/18.1 (0.8) 2.75 ------6 to 59 54 88/85.0 (1.0) 82/85.0 (1.0) 1.07
The data are expressed as observed number/expected number (ratio of obs/expect)
Overall sex ratio: p-value = 0.645 (boys and girls equally represented) Overall age distribution: p-value = 0.169 (as expected) Overall age distribution for boys: p-value = 0.396 (as expected) Overall age distribution for girls: p-value = 0.093 (as expected) Overall sex/age distribution: p-value = 0.017 (significant difference)
Evaluation of the SD for WHZ depending upon the order the cases are measured within each cluster (if one cluster per day is measured then this will be related to the time of the day the measurement is made).
Team: 1
Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 01: 1.02 (n=16, f=0) ######### 02: 0.78 (n=16, f=0) 03: 1.20 (n=16, f=0) ################# 04: 0.76 (n=16, f=0) 05: 0.90 (n=16, f=0) #### 06: 0.92 (n=15, f=0) ##### 07: 0.91 (n=16, f=0) ##### 08: 0.90 (n=15, f=0) #### 09: 0.55 (n=15, f=0) 10: 0.93 (n=14, f=0) ###### 11: 1.15 (n=14, f=0) ############### 12: 0.52 (n=12, f=0) 13: 0.73 (n=10, f=0) 14: 1.16 (n=07, f=0) OOOOOOOOOOOOOOO 15: 0.82 (n=06, f=0) O 16: 0.46 (n=03, f=0) 17: 0.55 (n=02, f=0)
(when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points)
Team: 2
Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 01: 0.96 (n=14, f=0) ####### 02: 1.07 (n=15, f=0) ########### 03: 0.89 (n=15, f=0) #### 04: 0.95 (n=15, f=0) ###### 05: 0.83 (n=15, f=0) # 06: 0.74 (n=15, f=0) Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 164
07: 0.76 (n=13, f=0) 08: 0.95 (n=12, f=0) ###### 09: 0.57 (n=10, f=0) 10: 1.32 (n=09, f=0) ###################### 11: 0.52 (n=10, f=0) 12: 1.34 (n=07, f=0) OOOOOOOOOOOOOOOOOOOOOOO 13: 1.53 (n=04, f=0) OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO 14: 0.92 (n=03, f=0) ~~~~~ 15: 0.96 (n=03, f=0) ~~~~~~~ 16: 0.59 (n=03, f=0) 17: 1.53 (n=02, f=0) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18: 0.26 (n=02, f=0)
(when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points)
Team: 3
Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 01: 1.01 (n=16, f=0) ######### 02: 0.77 (n=15, f=0) 03: 1.21 (n=16, f=0) ################# 04: 1.19 (n=16, f=1) ################ 05: 1.08 (n=16, f=0) ############ 06: 1.01 (n=16, f=0) ######### 07: 0.57 (n=14, f=0) 08: 0.92 (n=14, f=0) ##### 09: 0.79 (n=12, f=0) 10: 0.75 (n=10, f=0) 11: 0.70 (n=10, f=0) 12: 0.93 (n=07, f=0) OOOOOO 13: 0.58 (n=05, f=0) 14: 0.62 (n=04, f=0) 15: 0.90 (n=03, f=0) ~~~~ 16: 0.78 (n=02, f=0)
(when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points)
Team: 4
Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 01: 0.70 (n=16, f=0) 02: 0.83 (n=15, f=0) # 03: 0.89 (n=16, f=0) #### 04: 0.81 (n=16, f=0) 05: 1.00 (n=16, f=0) ######### 06: 1.07 (n=15, f=0) ########### 07: 0.65 (n=15, f=0) 08: 0.86 (n=14, f=0) ### 09: 0.58 (n=10, f=0) 10: 0.69 (n=09, f=0) 11: 1.15 (n=07, f=0) OOOOOOOOOOOOOOO 12: 0.80 (n=07, f=0) 13: 1.09 (n=06, f=0) OOOOOOOOOOOO 14: 0.34 (n=05, f=0) 15: 0.89 (n=03, f=0) ~~~~ 16: 1.42 (n=03, f=0) ~~~~~~~~~~~~~~~~~~~~~~~~~~ 17: 0.13 (n=02, f=0)
(when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points)
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Team: 5
Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 01: 0.88 (n=16, f=0) ### 02: 0.82 (n=16, f=0) # 03: 0.68 (n=16, f=0) 04: 1.16 (n=15, f=0) ############### 05: 1.02 (n=16, f=0) ######### 06: 0.72 (n=13, f=0) 07: 1.36 (n=14, f=0) ######################## 08: 0.80 (n=13, f=0) 09: 1.08 (n=13, f=0) ############ 10: 0.72 (n=12, f=0) 11: 0.73 (n=10, f=0) 12: 1.39 (n=07, f=0) OOOOOOOOOOOOOOOOOOOOOOOOO 13: 1.34 (n=07, f=0) OOOOOOOOOOOOOOOOOOOOOOO 14: 0.72 (n=06, f=0) 15: 0.52 (n=06, f=0) 16: 0.46 (n=06, f=0) 17: 0.78 (n=04, f=0) 18: 0.11 (n=02, f=0)
(when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points)
Team: 6
Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 01: 1.06 (n=17, f=0) ########### 02: 0.99 (n=15, f=0) ######## 03: 1.25 (n=14, f=0) ################### 04: 0.96 (n=17, f=0) ####### 05: 1.16 (n=17, f=0) ############### 06: 1.08 (n=16, f=0) ############ 07: 1.23 (n=15, f=0) ################## 08: 0.72 (n=09, f=0) 09: 1.34 (n=10, f=0) ####################### 10: 0.80 (n=08, f=0) 11: 1.26 (n=08, f=0) OOOOOOOOOOOOOOOOOOOO 12: 0.54 (n=05, f=0) 13: 1.29 (n=03, f=0) ~~~~~~~~~~~~~~~~~~~~~ 14: 0.15 (n=03, f=0)
(when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points)
(for better comparison it can be helpful to copy/paste part of this report into Excel)
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Annex 14: Nayapara Refugee Camp Plausibility Check
Plausibility check for: BAN_112017_ACF_Nayapara_6-59.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 (0.5 %)
Overall Sex ratio Incl p >0.1 >0.05 >0.001 <=0.001 (Significant chi square) 0 2 4 10 4 (p=0.038)
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=0.102)
Dig pref score - weight Incl # 0-7 8-12 13-20 > 20 0 2 4 10 0 (6)
Dig pref score - height Incl # 0-7 8-12 13-20 > 20 0 2 4 10 2 (12)
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 10 (0.84)
Skewness WHZ Excl # <±0.2 <±0.4 <±0.6 >=±0.6 0 1 3 5 0 (-0.15)
Kurtosis WHZ Excl # <±0.2 <±0.4 <±0.6 >=±0.6 0 1 3 5 0 (0.00)
Poisson dist WHZ-2 Excl p >0.05 >0.01 >0.001 <=0.001 0 1 3 5 0 (p=)
OVERALL SCORE WHZ = 0-9 10-14 15-24 >25 18 %
The overall score of this survey is 18 %, this is acceptable.
There were no duplicate entries detected.
Missing or wrong data:
WEIGHT: Line=1/ID=5, Line=2/ID=5, Line=3/ID=4, Line=4/ID=6, Line=5/ID=12, Line=6/ID=4, Line=7/ID=11, Line=8/ID=5 Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 167
HEIGHT: Line=1/ID=5, Line=2/ID=5, Line=3/ID=4, Line=4/ID=6, Line=5/ID=12, Line=6/ID=4, Line=7/ID=11, Line=8/ID=5
Percentage of children with no exact birthday: 60 %
Anthropometric Indices likely to be in error (-3 to 3 for WHZ, -3 to 3 for HAZ, -3 to 3 for WAZ, from observed mean - chosen in Options panel - these values will be flagged and should be excluded from analysis for a nutrition survey in emergencies. For other surveys this might not be the best procedure e.g. when the percentage of overweight children has to be calculated):
Line=37/ID=3: HAZ (1.303), Age may be incorrect Line=39/ID=4: WHZ (-4.310), Height may be incorrect Line=51/ID=8: HAZ (1.279), Age may be incorrect Line=56/ID=6: HAZ (-4.885), Age may be incorrect Line=64/ID=4: WHZ (-4.172), HAZ (1.829), Height may be incorrect Line=68/ID=4: HAZ (2.642), Age may be incorrect Line=70/ID=3: HAZ (1.471), Age may be incorrect Line=85/ID=5: HAZ (1.848), Age may be incorrect Line=137/ID=3: HAZ (1.852), Age may be incorrect
Percentage of values flagged with SMART flags:WHZ: 0.5 %, HAZ: 2.0 %, WAZ: 0.0 %
Age distribution:
Month 6 : ## Month 7 : ######## Month 8 : ######### Month 9 : #### Month 10 : ### Month 11 : ############ Month 12 : #### Month 13 : ####### Month 14 : ########## Month 15 : ########## Month 16 : ######### Month 17 : ############ Month 18 : ##### Month 19 : ### Month 20 : ### Month 21 : ###### Month 22 : ####### Month 23 : #######
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Month 24 : ########## Month 25 : ####### Month 26 : ########## Month 27 : ########## Month 28 : ######### Month 29 : #### Month 30 : ###### Month 31 : ###### Month 32 : ######## Month 33 : ####### Month 34 : ######### Month 35 : ######## Month 36 : ######## Month 37 : ################ Month 38 : ##### Month 39 : ############### Month 40 : ####### Month 41 : ############ Month 42 : ########## Month 43 : ## Month 44 : ### Month 45 : #### Month 46 : ##### Month 47 : ############# Month 48 : ### Month 49 : ##### Month 50 : ######## Month 51 : ########## Month 52 : ########### Month 53 : ########### Month 54 : ############ Month 55 : ######### Month 56 : ###### Month 57 : ######## Month 58 : ##### Month 59 : ### Month 60 : ##
Age ratio of 6-29 months to 30-59 months: 0.72 (The value should be around 0.85).: p-value = 0.102 (as expected)
Statistical evaluation of sex and age ratios (using Chi squared statistic):
Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 47/52.2 (0.9) 43/42.5 (1.0) 90/94.7 (1.0) 1.09 18 to 29 12 43/50.9 (0.8) 38/41.4 (0.9) 81/92.3 (0.9) 1.13 30 to 41 12 60/49.3 (1.2) 48/40.1 (1.2) 108/89.5 (1.2) 1.25
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42 to 53 12 46/48.5 (0.9) 40/39.5 (1.0) 86/88.0 (1.0) 1.15 54 to 59 6 29/24.0 (1.2) 14/19.5 (0.7) 43/43.5 (1.0) 2.07 ------6 to 59 54 225/204.0 (1.1) 183/204.0 (0.9) 1.23
The data are expressed as observed number/expected number (ratio of obs/expect)
Overall sex ratio: p-value = 0.038 (significant excess of boys) Overall age distribution: p-value = 0.239 (as expected) Overall age distribution for boys: p-value = 0.265 (as expected) Overall age distribution for girls: p-value = 0.492 (as expected) Overall sex/age distribution: p-value = 0.011 (significant difference)
Digit preference Weight:
Digit .0 : ######################### Digit .1 : ################################################### Digit .2 : ############################################### Digit .3 : #################################### Digit .4 : ############################################ Digit .5 : ###################################### Digit .6 : ##################################### Digit .7 : ########################################## Digit .8 : ################################### Digit .9 : #############################################
Digit preference score: 6 (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) p-value for chi2: 0.194
Digit preference Height:
Digit .0 : ############### Digit .1 : ############################################## Digit .2 : ##################################################### Digit .3 : ####################################################### Digit .4 : #################################################### Digit .5 : ################## Digit .6 : ########################################## Digit .7 : ###################################################### Digit .8 : ################################## Digit .9 : ###############################
Digit preference score: 12 (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) p-value for chi2: 0.000 (significant difference)
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Digit preference MUAC:
Digit .0 : ############################ Digit .1 : ################################################## Digit .2 : ########################################## Digit .3 : ############################################################# Digit .4 : ############################# Digit .5 : ##################### Digit .6 : ################################################## Digit .7 : ########################################### Digit .8 : ########################################## Digit .9 : ##################################
Digit preference score: 10 (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) p-value for chi2: 0.000 (significant difference)
Evaluation of Standard deviation, Normal distribution, Skewness and Kurtosis using the 3 exclusion (Flag) procedures
. no exclusion exclusion from exclusion from . reference mean observed mean . (WHO flags) (SMART flags) WHZ Standard Deviation SD: 0.87 0.87 0.84 (The SD should be between 0.8 and 1.2) Prevalence (< -2) observed: calculated with current SD: calculated with a SD of 1:
HAZ Standard Deviation SD: 1.13 1.13 1.03 (The SD should be between 0.8 and 1.2) Prevalence (< -2) observed: 43.8% 43.8% 44.4% calculated with current SD: 43.3% 43.3% 44.8% calculated with a SD of 1: 42.4% 42.4% 44.6%
WAZ Standard Deviation SD: 0.89 0.89 0.89 (The SD should be between 0.8 and 1.2) Prevalence (< -2) observed: calculated with current SD: calculated with a SD of 1:
Results for Shapiro-Wilk test for normally (Gaussian) distributed data: WHZ p= 0.024 p= 0.024 p= 0.674 HAZ p= 0.000 p= 0.000 p= 0.576 WAZ p= 0.781 p= 0.781 p= 0.781 (If p < 0.05 then the data are not normally distributed. If p > 0.05 you can consider the data normally distributed)
Skewness WHZ -0.32 -0.32 -0.15 HAZ 0.48 0.48 0.11 WAZ -0.01 -0.01 -0.01 If the value is: -below minus 0.4 there is a relative excess of wasted/stunted/underweight subjects in the sample -between minus 0.4 and minus 0.2, there may be a relative excess of wasted/stunted/underweight Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 171
subjects in the sample. -between minus 0.2 and plus 0.2, the distribution can be considered as symmetrical. -between 0.2 and 0.4, there may be an excess of obese/tall/overweight subjects in the sample. -above 0.4, there is an excess of obese/tall/overweight subjects in the sample
Kurtosis WHZ 0.47 0.47 0.00 HAZ 0.95 0.95 -0.05 WAZ 0.10 0.10 0.10 Kurtosis characterizes the relative size of the body versus the tails of the distribution. Positive kurtosis indicates relatively large tails and small body. Negative kurtosis indicates relatively large body and small tails. If the absolute value is: -above 0.4 it indicates a problem. There might have been a problem with data collection or sampling. -between 0.2 and 0.4, the data may be affected with a problem. -less than an absolute value of 0.2 the distribution can be considered as normal.
Are the data of the same quality at the beginning and the end of the clusters? Evaluation of the SD for WHZ depending upon the order the cases are measured within each cluster (if one cluster per day is measured then this will be related to the time of the day the measurement is made).
Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3
(when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points)
Analysis by Team
Team 1 2 3 4 5 6 n = 74 80 60 53 65 76 Percentage of values flagged with SMART flags: WHZ: 0.0 3.8 1.7 1.9 6.6 1.3 HAZ: 2.7 5.1 1.7 5.8 6.6 2.6 WAZ: 0.0 2.6 1.7 1.9 6.6 0.0 Age ratio of 6-29 months to 30-59 months: 0.54 0.78 0.88 0.66 0.81 0.73 Sex ratio (male/female): 1.18 1.00 0.88 2.12 1.32 1.38 Digit preference Weight (%): .0 : 5 9 2 12 8 3 .1 : 15 15 17 12 5 12 .2 : 8 9 17 13 11 13 .3 : 9 14 5 4 8 11 .4 : 11 13 5 12 8 16 .5 : 7 10 12 13 8 8 .6 : 11 4 8 4 15 13 .7 : 11 10 15 8 13 7 .8 : 12 8 5 12 10 7 Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 172
.9 : 11 8 14 12 13 12 DPS: 9 11 18 11 10 13 Digit preference score (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) Digit preference Height (%): .0 : 0 8 14 2 0 0 .1 : 12 14 5 10 16 11 .2 : 12 15 7 27 10 11 .3 : 15 10 20 8 8 20 .4 : 19 14 5 2 23 12 .5 : 5 4 3 10 3 3 .6 : 9 10 8 6 16 12 .7 : 12 9 14 21 7 20 .8 : 9 9 10 10 7 7 .9 : 5 6 14 6 10 7 DPS: 17 12 17 25 22 20 Digit preference score (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) Digit preference MUAC (%): .0 : 0 6 7 12 13 7 .1 : 12 12 14 19 11 9 .2 : 11 14 8 13 8 8 .3 : 11 18 17 13 15 17 .4 : 11 9 3 4 8 7 .5 : 0 3 0 13 11 7 .6 : 18 10 14 8 13 12 .7 : 16 5 8 12 8 14 .8 : 9 9 27 2 7 9 .9 : 12 14 2 4 5 11 DPS: 18 15 26 17 10 11 Digit preference score (0-7 excellent, 8-12 good, 13-20 acceptable and > 20 problematic) Standard deviation of WHZ: SD 0.85 0.79 0.83 0.88 0.88 0.99 Prevalence (< -2) observed: % Prevalence (< -2) calculated with current SD: % Prevalence (< -2) calculated with a SD of 1: % Standard deviation of HAZ: SD 1.11 1.11 1.05 1.19 0.99 1.28 observed: % 40.5 51.3 44.1 30.8 50.0 calculated with current SD: % 37.4 52.0 41.8 34.7 45.1 calculated with a SD of 1: % 36.0 52.2 41.4 32.1 43.8
Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 173
Statistical evaluation of sex and age ratios (using Chi squared statistic) for:
Team 1:
Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 10/9.3 (1.1) 5/7.9 (0.6) 15/17.2 (0.9) 2.00 18 to 29 12 6/9.0 (0.7) 5/7.7 (0.7) 11/16.7 (0.7) 1.20 30 to 41 12 10/8.8 (1.1) 11/7.5 (1.5) 21/16.2 (1.3) 0.91 42 to 53 12 9/8.6 (1.0) 10/7.3 (1.4) 19/16.0 (1.2) 0.90 54 to 59 6 5/4.3 (1.2) 3/3.6 (0.8) 8/7.9 (1.0) 1.67 ------6 to 59 54 40/37.0 (1.1) 34/37.0 (0.9) 1.18
The data are expressed as observed number/expected number (ratio of obs/expect)
Overall sex ratio: p-value = 0.486 (boys and girls equally represented) Overall age distribution: p-value = 0.376 (as expected) Overall age distribution for boys: p-value = 0.845 (as expected) Overall age distribution for girls: p-value = 0.313 (as expected) Overall sex/age distribution: p-value = 0.173 (as expected)
Team 2:
Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 7/9.3 (0.8) 9/9.3 (1.0) 16/18.6 (0.9) 0.78 18 to 29 12 8/9.0 (0.9) 11/9.0 (1.2) 19/18.1 (1.0) 0.73 30 to 41 12 13/8.8 (1.5) 6/8.8 (0.7) 19/17.5 (1.1) 2.17 42 to 53 12 6/8.6 (0.7) 10/8.6 (1.2) 16/17.3 (0.9) 0.60 54 to 59 6 6/4.3 (1.4) 4/4.3 (0.9) 10/8.5 (1.2) 1.50 ------6 to 59 54 40/40.0 (1.0) 40/40.0 (1.0) 1.00
The data are expressed as observed number/expected number (ratio of obs/expect)
Overall sex ratio: p-value = 1.000 (boys and girls equally represented) Overall age distribution: p-value = 0.930 (as expected) Overall age distribution for boys: p-value = 0.376 (as expected) Overall age distribution for girls: p-value = 0.820 (as expected) Overall sex/age distribution: p-value = 0.217 (as expected)
Team 3:
Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 6/6.5 (0.9) 9/7.4 (1.2) 15/13.9 (1.1) 0.67 18 to 29 12 7/6.3 (1.1) 6/7.2 (0.8) 13/13.6 (1.0) 1.17 30 to 41 12 4/6.1 (0.7) 9/7.0 (1.3) 13/13.2 (1.0) 0.44 42 to 53 12 10/6.0 (1.7) 7/6.9 (1.0) 17/12.9 (1.3) 1.43 54 to 59 6 1/3.0 (0.3) 1/3.4 (0.3) 2/6.4 (0.3) 1.00 ------6 to 59 54 28/30.0 (0.9) 32/30.0 (1.1) 0.88
The data are expressed as observed number/expected number (ratio of obs/expect) Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 174
Overall sex ratio: p-value = 0.606 (boys and girls equally represented) Overall age distribution: p-value = 0.354 (as expected) Overall age distribution for boys: p-value = 0.312 (as expected) Overall age distribution for girls: p-value = 0.589 (as expected) Overall sex/age distribution: p-value = 0.102 (as expected)
Team 4:
Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 5/8.4 (0.6) 6/3.9 (1.5) 11/12.3 (0.9) 0.83 18 to 29 12 9/8.1 (1.1) 1/3.8 (0.3) 10/12.0 (0.8) 9.00 30 to 41 12 10/7.9 (1.3) 5/3.7 (1.3) 15/11.6 (1.3) 2.00 42 to 53 12 8/7.8 (1.0) 4/3.7 (1.1) 12/11.4 (1.0) 2.00 54 to 59 6 4/3.8 (1.0) 1/1.8 (0.6) 5/5.7 (0.9) 4.00 ------6 to 59 54 36/26.5 (1.4) 17/26.5 (0.6) 2.12
The data are expressed as observed number/expected number (ratio of obs/expect)
Overall sex ratio: p-value = 0.009 (significant excess of boys) Overall age distribution: p-value = 0.817 (as expected) Overall age distribution for boys: p-value = 0.734 (as expected) Overall age distribution for girls: p-value = 0.405 (as expected) Overall sex/age distribution: p-value = 0.017 (significant difference)
Team 5:
Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 11/8.6 (1.3) 6/6.5 (0.9) 17/15.1 (1.1) 1.83 18 to 29 12 5/8.4 (0.6) 7/6.3 (1.1) 12/14.7 (0.8) 0.71 30 to 41 12 13/8.1 (1.6) 8/6.1 (1.3) 21/14.3 (1.5) 1.63 42 to 53 12 3/8.0 (0.4) 4/6.0 (0.7) 7/14.0 (0.5) 0.75 54 to 59 6 5/3.9 (1.3) 3/3.0 (1.0) 8/6.9 (1.2) 1.67 ------6 to 59 54 37/32.5 (1.1) 28/32.5 (0.9) 1.32
The data are expressed as observed number/expected number (ratio of obs/expect)
Overall sex ratio: p-value = 0.264 (boys and girls equally represented) Overall age distribution: p-value = 0.107 (as expected) Overall age distribution for boys: p-value = 0.079 (as expected) Overall age distribution for girls: p-value = 0.851 (as expected) Overall sex/age distribution: p-value = 0.018 (significant difference)
Team 6:
Age cat. mo. boys girls total ratio boys/girls ------6 to 17 12 8/10.2 (0.8) 8/7.4 (1.1) 16/17.6 (0.9) 1.00 18 to 29 12 8/10.0 (0.8) 8/7.2 (1.1) 16/17.2 (0.9) 1.00 30 to 41 12 10/9.6 (1.0) 9/7.0 (1.3) 19/16.7 (1.1) 1.11 42 to 53 12 10/9.5 (1.1) 5/6.9 (0.7) 15/16.4 (0.9) 2.00 Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 175
54 to 59 6 8/4.7 (1.7) 2/3.4 (0.6) 10/8.1 (1.2) 4.00 ------6 to 59 54 44/38.0 (1.2) 32/38.0 (0.8) 1.38
The data are expressed as observed number/expected number (ratio of obs/expect)
Overall sex ratio: p-value = 0.169 (boys and girls equally represented) Overall age distribution: p-value = 0.891 (as expected) Overall age distribution for boys: p-value = 0.521 (as expected) Overall age distribution for girls: p-value = 0.773 (as expected) Overall sex/age distribution: p-value = 0.128 (as expected)
Evaluation of the SD for WHZ depending upon the order the cases are measured within each cluster (if one cluster per day is measured then this will be related to the time of the day the measurement is made).
Team: 1
Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3
(when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points)
Team: 2
Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3
(when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points)
Team: 3
Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3
(when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points)
Team: 4
Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3
(when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points)
Team: 5
Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3
Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 176
(when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points)
Team: 6
Time SD for WHZ point 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3
(when n is much less than the average number of subjects per cluster different symbols are used: 0 for n < 80% and ~ for n < 40%; The numbers marked "f" are the numbers of SMART flags found in the different time points)
(for better comparison it can be helpful to copy/paste part of this report into Excel)
Action Against Hunger / Emergency Nutrition Assessment / Cox’s Bazar, Bangladesh / Oct - Nov 2017 177