INTEGRATED NUTRITION AND MORTALITY SMART SURVEY
REPORT
ELBARDE DISTRICT, BAKOOL REGION,
SOMALIA
NOVEMBER 2019
ACKNOWLEDGEMENTS
Action against Hunger (AAH), would like to acknowledge all the supports provided during the preparations, training and field activities of the survey, which includes but not limited to: ➢ Technical and logistical supports provided by Elbarde Municipality and the Ministry of Health in South West state of Somalia, facilitations during the training and field work. ➢ We would like to acknowledge the roles of the assessment teams including the team leaders, enumerators and community field guides and all the parents/caregivers who provided valuable information to the survey team, and participated the assessment. ➢ Assessment Information Management Working Group (AIMWG) members for the technical inputs and validations. ➢ Appreciation also goes to SIDA, for the generous financial supports to conduct this nutrition and mortality survey.
This survey was implemented with the financial assistance from the SIDA. The views expressed herein should not be taken, in any way, to reflect the official opinion of SIDA.
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Table of contents ACKNOWLEDGEMENTS ...... 2
Table of contents ...... 3
List of tables ...... 4
List of Figures ...... 5
1. INTRODUCTION ...... 10
1.1. Background ...... 10
1.2. Justifications ...... 10
2.0. Overall objective: ...... 11
2.1. Specific objectives ...... 11 3.0. METHODOLOGY ...... 11
3.1. Survey Design ...... 11
3.2. Study Population ...... 11
3.3. Geographic target area and population group ...... 11
3.4. Sample size calculation ...... 11
3.5. Cluster Sampling Strategy ...... 13
The survey employed a two stage cluster sampling technique where ...... 13
3.6. Variables collected ...... 14
3.7. Case Definitions and inclusion Criteria ...... 14 3.8. Data Management and Survey Teams...... 17
3.8.1. Survey Teams ...... 17 3.9. Quality Assurance ...... 17 3.10. Data Analysis and Reporting ...... 18 4.0. SURVEY RESULTS ...... 18
4.1. Demographic Characteristics ...... 18
4.2. Anthropometric results (based on WHO standards 2006) ...... 19
4.2.1. Prevalence of Acute Malnutrition ...... 19 4.2.2. Ditribution of prevalance of acute malnutrition by age ...... 20 4.2.3. Prevalence of Acute Malnutrition based on MAUC ...... 21 4.2.4. Prevalence of Underweight ...... 22 4.2.5. Ditribution of underweight by age ...... 23 4.2.6. Prevalence of Stunting ...... 23 4.3 Infant and Young Child Feedings...... 24
4.4. Mortality results (retrospective over x months/days prior to interview) ...... 25
4.5 Children’s morbidity ...... 26
4.5. 1.Health Seeking Behavior ...... 26 4.5.2. Vitamin A supplementation, Vaccination and deworming Results ...... 26 4.6. Programme coverage (Proxy IMAM Coverage) ...... 27
4.7. Maternal Malnutrition ...... 27
4.7.1. Physical Status for Mothers ...... 27 4.7.2. Maternal nutrition and Multiple Micronutrient supplementations ...... 28 4.8. Water Sanitation and Hygiene (WASH) ...... 28
4.9. Food Security and Livelihood ...... 28
4.9.1. Dietary diversity ...... 28
5.0. Discussion ...... 30
6.0. RECOMMENDATIONS AND PRIORITIES ...... 31
7. REFERENCES ...... 32
8.0. Annexes ...... 33
8.1. Survey Questionnaire ...... 33
8.2. Sampling Frame ...... 38
8.3. Plausibility check for: Elbarde SMART Survey 2019.as ...... 39
8.4. Report for Evaluation of Enumerators ...... 40
8.5. Calendar of Events for SMART Survey, October, 2019 ...... 42
List of tables Table 1: Summary Findings ...... 8
Table 2: Summary Recommendation ...... 9
Table 3: Anthropometric and Mortality Sample Size Calculation ...... 12
Table 4 : Culculating Number of Households per team per day ...... 13
Table 5: Weight-for-height (WHZ), children 6-59 months ...... 15
Table 6: Cut offs points of the Height for Age index (HAZ) and Weight for Age (WAZ) ...... 15
Table 7: MUAC Cut offs, children 6-59 months ...... 15
Table 8: Caregiver level of Education...... 19
Table 9: Distribution of age and sex of sample ...... 19
Table 10: Prevalence of acute malnutrition based on weight-for-height z-scores (and/or oedema) and by sex ...... 20
Table 11: Prevalence of acute malnutrition by age, based on weight-for-height z-scores and/or oedema ...... 21
Table 12: Prevalence of acute malnutrition based on MUAC cut off's (and/or oedema) and by sex ...... 21
Table 13: Prevalence of underweight based on weight-for-age z-scores by sex ...... 22
Table 14: Prevalence of underweight by age, based on weight-for-age z-scores ...... 23
Table 15: Prevalence of stunting based on height-for-age z-scores and by sex ...... 23
Table 16: Prevalence of stunting by age based on height-for-age z-scores ...... 24
Table 17: IYCF Indicators ...... 25
Table 18: Vaccination coverage: BCG for 6-59 months and measles for 9-59 months ...... 27
Table 19: Maternal nutrition and Multiple Micronutrient supplementations ...... 28
Table 20: WASH indicators ...... 28
Table 21: Changes on Food prices before and after the rains ...... 29
Table 22: House hold Dietary Diversity Scores and reduced Coping Strategies Index based on IPC Version 3...... 29
Table 23: Recommendations ...... 31
List of Figures Figure 1: Livelihood map of southern inland pastoral (Elbarde-In red) ...... 10
Figure 2: Elabarde Population ages sex distribution ...... 18
Figure 3 : Observed distribution of acute malnutrition by WHZ ...... 20
Figure 4: Distribution Malnutrition (MUAC) by age group...... 21
Figure 5: Observed distribution of underweight W/A ...... 22
Figure 6: Observed distribution of stunting by WAZ ...... 24
Figure 7: Disease prevalence among children under five ...... 26
Figure 8: Food consumed by households ...... 28
Figure 9: Coping Strategies Index ...... 29
ACRONYMS AND ABBREVIATIONS AAH Action Against Hunger AIMWG Assessment and Information Management Working Group ARI Acute Respiratory Infections AWD Acute Watery Diarrhea BCG Bacillus Calmette-Goerrin CDR Crude Death Rate DEFF Design Effect ENA Emergency Nutrition Assessment EPI Expended Program on Immunization FSNAU Food Security and Nutrition Analysis Unit GAM Global Acute Malnutrition HAZ Height for Age Z – Scores HDDS Household Dietary Diversity Scores HH Household IDP Internally Displaced Persons IPC Integrated Phase Classifications IYCF Infant and Young Child Feeding MM Millimeter MOH Ministry of Health MUAC Mid Upper Arm Circumference ODK Open Data Kit OTP Outpatient Therapeutic Program PPS Probability Proportionate to Size rCSI Reduced Coping Strategies Index SAM Severe Acute Malnutrition SIDA Swedish International Development Agency SC Stabilization Center SD Standard deviation SMART Standardized Methods of Assessment in Relief and Transitions SRCS Somali Red Crescent Society TSFP Target Supplementary Feeding Program U5DR Under Five Death Rates UNICEF United Nations Children’s Fund WASH Water Sanitation and Hygiene WAZ Weight for Age Z –Scores WFP World Food Program WHO World Health Organization WHZ Weight for Height Z- Scores
EXECUTIVE SUMMARY Action Against Hunger (AAH) has been implementing key humanitarian interventions in Somalia during the last three decades, with programing in; integrated health and nutrition services through health centers, mobile teams and stabilization center, Water sanitation and Hygiene (WASH), food security and livelihood (FSL) in Bakool Region (Elbarde and Hudur Districts) Action Against Hunger conducted integrated nutrition SMART survey in November 2019 in Elbarde District to assess the nutrition status among children 6 – 59 months, and the women of child bearing age (15 – 49) years among other indicators. A two - stage cluster sampling methodology was employed, where first stage a total of 33 clusters were sampled, using ENA for SMART software 9th July 2015 version, with probability proportionate to size (PPS). The second stage involved random selection of 430 households (33 clusters*13 households per cluster) using simple random sampling method. A total of 504 children were included in the sample and anthropometric indicators (Weight, Height and MUAC) taken. The findings indicated a Global Acute Malnutrition (GAM) by Weight for Height of 20.4% (16.1 – 25.5 95% CI) and Severe Acute Malnutrition (SAM) of 5.0% (2.7 – 8.8 95% CI). The combined GAM weight for height and MUAC indicated 26 %( 22.2-30.0 95% CI). The findings indicate critical and persisted high acute malnutrition, since November 2018, where GAM of 20.3% (16.2 – 25.1 95% CI) was reported. The mortality findings from a 93 day recall period indicated low level with crude death rate CDR of 0.15 (0.05–0.47)/10,000/day and under five death rate U5DR of 0.40 (0.10 – 1.64)/10,000/day which are below the WHO thresholds 1 person/10,000/days and 2 person/10,000/day for CDR and UDMR respectively. The survey findings further indicated 26.7% of children reported illness two weeks prior the assessment, mostly Acute Watery Diarrhea (AWD 37.9%) and Fever/suspect malaria (30.8%). The coverages of measles and BCG immunizations were low (32.6%) and (71.9%) respectively similar to November 2018 BCG coverage (76.1%) and measles (36.3%) results and far below the recommended Sphere coverage (>95%) and WHO (>80%). Very low vitamin A supplementation (13.5%) and deworming (12.0%) was also recorded, reflecting 2018 coverage whose vitamin A (8.9%) and deworming (13.0%). In conclusion, the nutrition status in Elbarde District remains critical with no improvement compared with 2018. The contributing factors to high malnutrition include high morbidity and worsened household food security due to poor market access due to heavy rains for more than 5 weeks. During post Gu’ 2019, Elbarde district population was mapped as stressed phase (IPC phase 2)1, but the current data is showing deterioration because of increased food prices after road inaccessibility. A summary of key survey findings from other indicators and recommendations are shown in table 1 and 2.
1 FSNAU, 2019: FSNAU Post Gu 2019 Integrated Phase Classifications.
Table 1: Summary Findings # Indicators Number % (CI) 1 Prevalence of Global Acute Malnutrition 103 20.4% (16.1 – 25.6 95% CI) (WHZ) All 2 Prevalence of Global Acute Malnutrition 57 23.0% (17.4-29.6 95% CI) (WHZ) Boys Prevalence of Global Acute Malnutrition 46 18.0% (13.1-24.2 95% CI) (WHZ) Girls 3 Prevalence of Moderate Acute Malnutrition 78 15.5% (12.0-19.7 95% CI) (WHZ) 4 Prevalence of Severe Acute Malnutrition 25 5.0% (2.7 - 8.8 95% CI ) (WHZ) 5 Prevalence of GAM MUAC (All) 64 12.6% ( 9.3 – 16.8) Prevalence of MAM MUAC (All) 10.4% ( 7.7-14.1 95% CI) Prevalence of SAM MUAC (All) 11 2.2% (1.2 – 3.9) 6 Prevalence of Combined GAM (WHZ and 26 %( 22.2-30.0 95% CI). MUAC ) 7 Prevalence of Stunting (All) 64 14.7% (10.1 – 21.1) 8 Severe Stunting (All) 16 3.7% (2.0 – 6.8) 9 Prevalence of Underweight (All) 105 22.4% (17.2 – 28.6) 10 Severe Underweight (All) 30 6.4% (3.4 – 11.8) Death Rates 11 Crude Death Rate/10,000/day 3 0.15 (0.05 – 0.47) 12 Under five Death Rates/10,000/day 3 0.40 (0.10 – 1.64)
Morbidities 13 Child Illness prior two weeks (All) 136 26.7% (17.6 – 35.8) Acute Watery Diarrhea 64 11.5% (5.8 – 17.2) Fever (suspected Malaria) 52 9.3% (5.2 – 13.4) ARI 23 4.1% (1.3 – 6.9) Bloody stool 9 1.6% (0.5 – 2.7) Immunization and supplementation Coverages 14 BCG vaccination (with scars) 366 71.9% (61.1 – 82.6) Measles Vaccination 166 32.6% (20.9 – 44.3) Vitamin A supplementations 25 13.5% ( 5.1 – 22.0)
Table 2: Summary Recommendation No. Key Findings Recommendations By WHO. 1. High prevalence of acute Malnutrition at Continuation of the Ongoing management of Severe and moderate Ministry of Health and 20.4% (16.1 – 25.6 95% CI) categorized as acute malnutrition (OTP, SC and TSFPs) as well as treatment Action Against Hunger and critical and high prevalence of Underweight /management of communicable diseases (especially AWD and Fever) other partners at 22.4% (17.2 – 28.6) and expending these services to areas that have not been covered (like Qurac-jome area). 2 Low immunization and supplementation Demand generation activities to increase utilization of Ministry of Health and coverage. health/immunization services to improve immunization, Deworming and Action Against Hunger and Immunization coverages are below the vitamin supplementation coverages. other partners international standards (sphere >95%); Such activities include: Very low vitamin A supplementations Mass campaign, scaling up using CHWs, 32.6% (20.9 – 44.3) Improve on documentation of immunization and supplementation Deworming: 12.0% (2.8 – 21.3) 3 Suboptimal IYCF practices Promotion of positive behaviors on child care practices and strengthen Ministry of Health and Low continued breastfeeding at one year the IYCF activities Action Against Hunger and (12 -15 months) and only 11.1%, continued other partners breastfeeding at two years (20 – 23 months). 4 Limited access to safe drinking water and Improve the access to safe drinking water through construction of Ministry of Health and the need for improved WASH practices protected water sources. Action Against Hunger and Access to safe drinking water:30.0% (16.6- other partners 43.4) Construct new household latrines and promote positive hygiene Household Access to latrines: 46.1 %( 33.1- practices including hand washing practices. 59.1%) 5 High proportion of the population are still Address short term food insecurity issue with programs like Ministry of Health and practicing high-reduced coping strategies. Like cash voucher or cash for work, as well as a long term plan on Action Against Hunger and Households consuming from low dietary chronic food insecurity. other partners diversityn32.9% while 51.9% of households employing high coping strategies.
1. INTRODUCTION 1.1. Background Action Against Hunger has been a key humanitarian actor in Somalia since May 1992 providing an array of services in Nutrition, Health, Food Security and Livelihood, Water Sanitation and Hygiene across 3 Regions; Bakool, Nugal and Banaadir . Elbarde is one of the districts in Bakool region in Southern Somalia and is located in the northern side of the region, where majority of its population are pastoralists (figure 1). AAH runs key live saving health and nutrition services in Elbarde, including the treatment of communicable diseases, OTP, TSFP and SC programs for the town and the 29 villages, through Elbarde health center and mobile teams. AAH also has food security activities in Elbarde district, including conditional and unconditional cash and WASH interventions like construction and rehabilitation of barkeds, rehabilitation of shallow Figure 1: Livelihood map of southern inland pastoral (Elbarde-In red) wells, water treatments and construction of latrines. 1.2. Justifications The recurrent droughts of last decade had resulted to loss of productive assets and increasing household food insecurity throughout Somalia. Bakool region is among the most affected areas, where beside the climatic shocks, conflict has worsened the situation due to limitation of road accessibilities to main markets, thus affecting the food prices and the overall livelihood status. AAH had conducted SMART nutrition and mortality survey in November 2018 with critical nutrition situation. The November 2019 SMART survey was planned to assess the current nutrition status, compare the previously conducted surveys and further understand the challenges and the intervention gaps that need further improvement and provide the relevant recommendations. The study area in this survey was Elbarde district which is mainly pastoral population.
2.0. Overall objective: To assess acute malnutrition rates amongst children 6-59 months and retrospective mortality rates amongst the population.
2.1. Specific objectives a. To estimate the prevalence of acute malnutrition amongst children aged 6-59 months. b. To assess the retrospective crude and under five mortality rates in the selected locations. c. To assess the coverage of vitamin A supplementation amongst children aged 6-59 months. d. To assess measles immunization coverage amongst children aged 9-59 months. e. To assess the coverage of immunization of polio and BCG amongst children aged 6-59 months f. To estimate the prevalence of common child illnesses in the target locations amongst children under 5 years two weeks prior to the survey. g. To assess water, sanitation and hygiene practices at the household level. h. To estimate levels of key food security and livelihood indicators of HDDS2, FCS3 and CSI4.
3.0. METHODOLOGY 3.1. Survey Design The survey applied a two stage cluster sampling with the clusters selected using the probability proportionate to population size (PPS). The sampling frame constituted sections of the town and list of the villages. 3.2. Study Population The target populations for the survey were children aged 6 – 59 months for the anthropometric component, and women of reproductive age between 15 – 49 years for the maternal health indicators. 3.3. Geographic target area and population group The geographical coverage of the survey was limited only to Elbarde district populations, where the primary respondents for the survey was mothers and/or care takers of children for both household and child questionnaire.
3.4. Sample size calculation The survey sample size was calculated based on key parameters for the primary outcomes (mortality and GAM) in line with current SMART guidance. The table below represent the
2HDDS: Household Dietary Diversity Score 3 FCS: Food Consumption Score 4 CSI: Coping Strategy Index
sample size calculations for both the anthropometric and mortality components. Using the Emergency Nutrition Assessment (ENA) software; July 9th, 2015 version.
Table 3: Anthropometric and Mortality Sample Size Calculation Total number of people accessible in Approximately 48,1925 Elbarde Type of population Rural, Resident/newly settled Parameters for Anthropometry Value Assumptions based on context Estimated Prevalence of GAM (%) 20 Point estimate of SMART Survey of November 2018 used. Secondary data review indicates no major changes in context. ± Desired Precision 5 Less precision required for high GAM >= 20%; precision determined by objectives of this assessment attributed to multi-indicators Design Effect (if applicable) 1.7 SMART survey November, 2018 design effects. Children to be included 455 As calculated from ENA Average HH Size 6 SMART Survey, November 2018 % Children under- 5 20 Based on WHO polio population estimates ACF SMART survey in 2018. % Non-response Households 3 Experience during the November 2018 SMART Survey/to cater for unforeseen circumstances Households to be included 430 As calculated from ENA Parameters for Mortality Value Assumptions based on context Estimated Death Rate/ 10,000/day 0.3 November SMART Survey results ± Desired Precision /10,000/day 0.3 SMART guidelines with death rate < 1 0; Design Effect (if applicable) 1.7 November 2018 SMART survey Recall Period in Days 93 22nd August 2019 Population to be included 2208 As calculated from ENA Average HH size 6 SMART Survey November 2018 % Non-response Households 2 Experience during the November 2018 SMART Survey/to cater for unforeseen circumstances Households to be included 376 As calculated from ENA **Higher household numbers from Anthropometric component of 429 to be used in cluster assignment.
5 WHO Polio Population Estimates
3.5. Cluster Sampling Strategy. The survey employed a two stage cluster sampling technique where; Stage one: cluster selection using updated sampling frame (list of villages in the study location and their population), which was entered into ENA for SMART software 9th July 2015. It is important to note that only secure and accessible areas were eventually included in the sampling frame, few villages near the border of Hudur District were excluded from the sampling due to security. The number of clusters assigned based on the number of households a team can visit in a day as per calculations in the table 4. Table 4 : Culculating Number of Households per team per day Departure from Office 7:00 AM a. Daily morning Briefings 30 minutes b. Travel to clusters 45 minutes c. Introduction and HH list development 45 minutes d. Lunch break 30 minutes e. Total Time from one HH to another 10 minutes f. Travel back to base 45 minutes Total time taken 205 minutes Arrival back to Base 5:00 PM Total Available time in a day 10 hrs (600 minutes) Available time for work 600 - 205 minutes= 395minutes Time taken to complete one household 30 minutes Number of households per team per day Total available time per day/Time taken to complete one household =395/30 =13.2 households =13households per team.
Stage two entailed random sampling 13 households per cluster from an updated list of households. These were the households visited by the survey team. A household was defined as number of people living together and sharing a common cooking pot. Polygamous families were defined based on the same, if each wife has her own pot, even if living in the same compound, this will be treated as different households. The village guide and the elders supported the teams in updating the list of households. Household selection techniques: For clusters with more than 250HHs, segmentation was used to select one portion of the cluster that will represent the cluster. This was done using probability proportionate to size (PPS). In all selected households, children under 5 years (based on immunization card or calendar of events) were included in the anthropometric survey. In households without children 6-59 months, other variables (mortality, Food Security, WASH,..) were collected. All children in the age range of 6-59 months were included in the anthropometric, immunization and health
components. However, only children 9-59 months were assessed for measles immunization coverage as per WHO guidelines and immunization schedule.
3.6. Variables collected Age: Age of the child was recorded based on a combination of child health cards and mothers’/caretakers’ recall of the child’s birth date, using calendar of events for Elbarde town that was developed in collaboration with the survey teams. Sex: The gender of the child whether a male or female was recorded Bilateral Edema: normal thumb pressure was applied on the top part of both feet for 3 seconds Weight: Children were weighed when wearing minimal or light clothing. Weight was taken using Electronic scales, reading the nearest 0.1 Length/Height: children were measured bareheaded and barefooted using wooden UNICEF height boards with a precision of 0.1cm. Children under the age of two years measured while lying down and those over two years while standing upright. Mid Upper Arm Circumference (MUAC): MUAC of children taken at the midpoint of the upper left arm using a MUAC tape and the nearest 0.1cm was recorded. Retrospective Morbidity of Children: Conducted, based on mother’s recall for all children (6-59 months) to assess the prevalence of common diseases, 2 weeks recall period has been taken for Diarrhea, fever and pneumonia, while the recall period for the measles based on last 30 days. Vaccination Status and Coverage: For all children 6-59 months, information on Oral polio Vaccine and measles vaccination was collected using the recall from caregivers. Vitamin A supplementation status: For all children aged 6-59 months, information on Vitamin A supplementation was collected based on mother/caregiver’s recall again. Information on whether the child had received supplementation in the last 6 months has been collected. Vitamin A capsule samples was also shown to mothers to support in recall. Household water source: This indicator is aimed to understand the main water source of the households and whether they get from protected or unprotected source. Sanitation: Information on household accessibility to a toilet/latrine and the type of the latrine they use.
3.7. Case Definitions and inclusion Criteria Anthropometry Acute malnutrition (Weight-for-height Z score (WHZ) Acute malnutrition in children 6-59 months can be expressed by using two indicators: Weight- for Height (WHZ) or Mid-Upper Arm Circumference (MUAC) as described below. A child’s nutritional status is estimated by comparing it to the WHZ curves of a reference population. These curves have a normal shape and are characterized by the median weight (value separating the population into two groups of the same size) and its Z scores
Table 5: Weight-for-height (WHZ), children 6-59 months Weight-for-height index (W/H) Nutritional status WFH -2.0 Z scores None/Mild Children 6-59 WFH - 3.0 and <-2.0 Z scores ,No oedema Moderate acute malnutrition months WFH <-3.0 Z scores and/or oedema Severe acute malnutrition
Chronic malnutrition (Height-for-age Z score (HAZ) The HAZ measure indicates if a child of a given age is chronically malnourished (stunted). This index reflects the nutritional history of a child rather than his/her current nutritional status. The height-for-age index of a child from the studied population expressed in Z-score (HAZ). The HAZ cut-off points in table 6. Underweight (weight-for-age Z score (WAZ)) Underweight indicates the weight of the child compared to his age as expressed by the Weight- for-Age index and in Z-scores. Table 6 show underweight classes with their cut-off points.
Table 6: Cut offs points of the Height for Age index (HAZ) and Weight for Age (WAZ) Stunting Underweight Indicator (Height for Age -HAZ) (Weight for Age-WAZ) Global HFA < -2 S Z scores WFA< -2 Z scores Moderate HFA < -2 and ≥ -3 Z scores WFA < -2 and ≥ -3 Z scores Severe HFA < -3 Z scores WFA < -3 Z scores
Mid-Upper Arm Circumference (MUAC) The mid-upper arm circumference is a reliable indicator of the muscular status of the child and mainly used to identify children with a risk of mortality. In settings where height and weight measurement is not feasible, MUAC can be used as a screening tool for identifying severely malnourished children for management6 In the field the criterion below was used to determine the status of children and appropriate referrals done based on the respective cut-offs (table7). Table 7: MUAC Cut offs, children 6-59 months Target group WHO thresholds Nutritional status 125≤135mm None /mild Children 6-59 months 11.5≤125mm Moderate acute malnutrition <11.5mm Severe acute malnutrition
6 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5983511/
Nutritional bilateral pitting oedema Nutritional bilateral pitting oedema is one of the most severe clinical forms of severe acute malnutrition. In the field children with bilateral oedema was automatically categorized as being severely malnourished, regardless of their WHZ.
Mortality The mortality indicators included all households, regardless of the presence of children. All members of the household were listed using the household definition. Crude death rate (CDR) Number of persons in the total population that dies over a defined period.
Under-5 death rate (U5DR) The probability for those children aged 0-5 years to die during a specific time interval. Calculated as:
Health Immunization status (BCG and Measles) and vitamin A supplementation Mothers/caregivers of all children 6-59 were asked if children received all the necessary vaccinations. The vaccinations asked were; Bacillus Calmette–Guerin (BCG) and Measles for children 9-59 months while Vitamin A supplementation in the last six months was asked for children aged 6-59 months. If the vaccination card was not be available to confirm, then recall of the caregiver was considered. BCG vaccination was confirmed by checking the scar on the child upper arm (left/right while Vitamin A samples were shown to caregivers. Morbidity Mothers/caregivers of children (0-59) months were asked if children had experienced any illness in the 14 days prior the day of the survey. Acute respiratory infection (ARI), fever, malaria, measles and diarrhea was recorded when symptoms matched the case definition were described by the caregiver.
Water Sanitation and Hygiene (WASH) Household respondents were asked about the source of drinking water and distance taken to reach the source. The distance to water, or time to collect water, is often the main constraint of access to water, and associated with the quantity of water used. The caregivers were also asked on what occasions they wash their hands and what they use to wash their hands to determine
the hand washing practices and observe the availability and types of toilet facilities used. This also included availability of waste disposal pits in the compound among others.
Infant and Young child feeding (IYCF) The IYCF indicators used in the measurement of IYCF practices asked to the mothers/caregivers of children aged 0-23 months are as follows among others: Other variables collected included other contextual household information to include household livelihood, foods consumed and sources, coping mechanism during food stress times, animals owned and relief food aid received by households. Other contextual information captured in the questionnaire are; water sanitation and hygiene, and infant young child nutrition indicators.
3.8. Data Management and Survey Teams. 3.8.1. Survey Teams Number of Teams: Action Against Hunger as the lead in the survey overseen the actual field level implementation of the survey from final review of protocol, enumerator selection, training, data collection, supervision, analysis and reporting. The survey encompassed 6 teams comprising of one team leader, two measurers and a village guide. Details on Field Supervision: Action Against Hunger and Ministry of Health jointly conducted regular supervision with the teams to ensure that the data collection proceeds as expected. Data entry procedures: Data was collected on mobile platform (Open Data Kit) to allow direct entry and submission to central repository online. The survey used ODK (Android application) for data collection and ONA (online platform) as the repository for the data. Entire survey questionnaire uploaded; Cluster control form was also used. 3.9. Quality Assurance The following measures were put in place by Action Against Hunger to ensure good quality work. a) Engaged qualified personnel while ensuring and enabling environment for operation. b) Ensured adherence to protocol and standards of quality survey implementation to include: • That the training of survey teams across all study locations are done using standardised material. • Undertook standardisation test as part of the training; taking appropriate steps thereafter based on performance of the survey teams. • Appropriate calibration of survey equipment. • Daily debriefing with the teams giving feedback geared at improving the quality of the measurements and congratulate the teams for job well done • Plausibility checks undertaken on daily basis, as data streams in. c) Anthropometry data was auto analysed using ENA software anthropometry section. The same software used to analyse the mortality data.
An updated calendar of events was used in estimating the ages of children; when documented proof of age is lacking.
3.10. Data Analysis and Reporting The survey data was analysed using ENA for SMART software July 2015 version, especially for both the anthropometric and mortality components. Additional data captured during the survey, such as food security, immunization, morbidity, and micronutrient variables were analysed using EPI Info. Statistical methods consisting of point prevalence calculations for each of the variables disaggregated by sex.
4.0. SURVEY RESULTS
A total of 428 households were interviewed translating to 99.7% response rate. 4.1. Demographic Characteristics This population proportions for Elabrde indicate 51% were Male while female were 49% indicating a sex ration of 1:1. The age specific sex proportions are as shown in figure 2.
Figure 2: Elabarde Population ages sex distribution
Education Level The survey findings indicated a very low literacy level among care-givers with 75.2% (323 out of 428) did not go to school, while 16.5% went to Koranic school, 5.1% at primary school and only 1.4% to secondary school as shown in table 5. The low literacy level is likely because majority of
the population are pastoralists who frequently move from one location to another, then may not have access to schools. Table 8: Caregiver level of Education SN Education Level Number Proportion (CI) 1 Didn't go to school 323 75.2% (65.5 – 85.0)
2 Religious & Koranic school 71 16.5% (9.7 – 23.3) 3 Primary school 22 5.1% (1.4 – 8.8) 4 Secondary school 6 1.4% (0..1 – 2.6) 5 Technical Schools 3 0.7% (0.0 – 1.4) 6 University 1 0.2% (0.0 – 0.7) 7 Don’t Know 2 .4% (0.0 – 1.4) Total 428 100%
Residential Status and housing condition Majority of assessed households were permeant residents and only one household has reported as refugee, but the rest were residents (99.7%) with only one household being refugee. Observation of housing conditions indicated 57.3%, 24.9%, 12.8% and 4.8% of houses were made of Buul, Issb Bricks, Mud Bricks and plastic Sheet Walls respectively.
4.2. Anthropometric results (based on WHO standards 2006) A total of 508 children 6-59 from 429 households were taken anthropometric measurement with distribution of boys (49.2%) and girls (50.8%) indicating boys girls ration of 1.0. Other age distributions are shown in table 9.
Table 9: Distribution of age and sex of sample Boys Girls Total Ratio AGE (mo) no. % no. % no. % Boy:girl 6-17 74 52.1 68 47.9 142 28.0 1.1 18-29 55 47.8 60 52.2 115 22.6 0.9 30-41 45 44.1 57 55.9 102 20.1 0.8 42-53 44 48.9 46 51.1 90 17.7 1.0 54-59 32 54.2 27 45.8 59 11.6 1.2 Total 250 49.2 258 50.8 508 100.0 1.0
4.2.1. Prevalence of Acute Malnutrition The survey results indicates a prevalence of Global Acute Malnutrition (GAM-WHZ) at 20.4 % (16.1 – 25.5), with Severe Acute malnutrition (SAM-WHZ) of 5.0 % (2.7 – 8.8) indicating sustained critical acute malnutrition compared to November 2018 SMART results, where a critical GAM and SAM of 20.3% and 6.1% respectively. The prevalence of combined GAM (WHZ and MUAC) was 26 %( 22.2-30.0 95% CI). The results further indicated that boys were more malnourished than girls through not statistically significant as shown in table 10.
Table 10: Prevalence of acute malnutrition based on weight-for-height z-scores (and/or oedema) and by sex All Boys Girls n = 504 n = 248 n = 256 Prevalence of global malnutrition (103) 20.4 % (57) 23.0 % (46) 18.0 % (<-2 z-score and/or oedema) (16.1 - 25.5 95% C.I.) (17.4 - 29.6 95% (13.1 - 24.2 95% C.I.) C.I.) Prevalence of moderate malnutrition (78) 15.5 % (38) 15.3 % (40) 15.6 % (<-2 z-score and >=-3 z-score, no (12.0 - 19.7 95% C.I.) (10.7 - 21.4 95% (11.6 - 20.7 95% oedema) C.I.) C.I.) Prevalence of severe malnutrition (25) 5.0 % (19) 7.7 % (6) 2.3 % (<-3 z-score and/or oedema) (2.7 - 8.8 95% C.I.) (4.3 - 13.4 95% (0.8 - 6.4 95% C.I.) C.I.)
The normal distribution curve figure 3, shows the distribution of malnutrition is skewed to the left, compared to the WHO Standard. The reason is that the surveyed children have higher malnutrition level than the reference population. The results further indicates mean of -1.11 and standard deviations of ±1.09.
Figure 3 : Observed distribution of acute malnutrition by WHZ 4.2.2. Ditribution of prevalance of acute malnutrition by age Analysis of acute malnutrtion by age group, indcate age group (6 – 17 months) have shown the highest SAM cases at 7.1% and older age group (54 – 59 months) have shown lower SAM cases 1.7%. Malnutrtion among the younger age group can be attributed to weaning gaps where children are not given adequate complematary feeding. The results further found out that older age cohorts of (42 -53) and (54 – 59), have higher moderate malnutrition, 20.2% and 23.7% respectively. Table 11 is showing the prevalence of acute malnutrition by age, based on weight for height z scores and/or oedema.
Table 11: Prevalence of acute malnutrition by age, based on weight-for-height z-scores and/or oedema Severe wasting Moderate wasting Normal Oedema (<-3 z-score) (>= -3 and <-2 z-score ) (> = -2 z score) Age Total No. % No. % No. % No. % (mo) no. 6-17 140 10 7.1 24 17.1 106 75.7 0 0.0 18-29 115 5 4.3 10 8.7 100 87.0 0 0.0 30-41 101 5 5.0 12 11.9 84 83.2 0 0.0 42-53 89 4 4.5 18 20.2 67 75.3 0 0.0 54-59 59 1 1.7 14 23.7 44 74.6 0 0.0 Total 504 25 5.0 78 15.5 401 79.6 0 0.0
4.2.3. Prevalence of Acute Malnutrition based on MAUC A further analysis of malnutrition by Mid Upper hand Circumference (MUAC) <125 mm and /or odema indicated a GAM of 12.6%, with Severe MUAC <115 mm and/or oedema 2.2%. This is lower than the November 2018 SMART results where GAM by MUAC result (17.1%) higher the SAM cases (1.7%) reported last year. Boys and girls were equally malnourished with boys 12.4 % (8.0 - 18.8 95% C.I) and 12.8 % (8.8 - 18.2 95% C.I) for girls as shown in table 12.
Table 12: Prevalence of acute malnutrition based on MUAC cut off's (and/or oedema) and by sex All Boys Girls n = 508 n = 250 n = 258 Prevalence of global malnutrition (64) 12.6 % (31) 12.4 % (33) 12.8 % (< 125 mm and/or oedema) (9.4 - 16.6 95% (8.0 - 18.8 95% (8.8 - 18.2 95% C.I.) C.I.) C.I.) Prevalence of moderate malnutrition (53) 10.4 % (28) 11.2 % (25) 9.7 % (< 125 mm and >= 115 mm, no oedema) (7.7 - 14.1 95% (7.4 - 16.6 95% (6.2 - 14.8 95% C.I.) C.I.) C.I.) Prevalence of severe malnutrition (11) 2.2 % (3) 1.2 % (8) 3.1 % (< 115 mm and/or oedema) (1.2 - 3.9 95% (0.3 - 5.2 95% (1.6 - 5.8 95% C.I.) C.I.) C.I.)
Figure 4 shows the distribution of Malnutrition by MUAC. The findings indicates that children aged 6-17 months are more malnourished compared to other age cohorts.
Figure 4: Distribution Malnutrition (MUAC) by age group.
4.2.4. Prevalence of Underweight Underweight is a composite indicator affected by both wasting and stunting. The result is shows high prevalence of underweight 22.4 % (17.2 - 28.6 95% C.I.) with severe cases of 6.4 % (3.4 - 11.8 95% C.I.). The results further found that boys were more underweight than girls as shown in table 13. Table 13: Prevalence of underweight based on weight-for-age z-scores by sex All Boys Girls n = 469 n = 232 n = 237 Prevalence of underweight (105) 22.4 % (64) 27.6 % (41) 17.3 % (<-2 z-score) (17.2 - 28.6 95% C.I.) (20.9 - 35.4 95% (12.1 - 24.0 95% C.I.) C.I.) Prevalence of moderate (75) 16.0 % (47) 20.3 % (28) 11.8 % underweight (12.5 - 20.3 95% C.I.) (14.9 - 27.0 95% (8.1 - 17.0 95% C.I.) (<-2 z-score and >=-3 z-score) C.I.) Prevalence of severe (30) 6.4 % (17) 7.3 % (13) 5.5 % underweight (3.4 - 11.8 95% C.I.) (3.8 - 13.7 95% C.I.) (2.4 - 12.1 95% C.I.) (<-3 z-score)
Figure 5, shows, weight for age Z-scores for children compared to reference population indicate a negative shift. The mean and standard deviation was -1.28 and ±1.07 respectively.
Figure 5: Observed distribution of underweight W/A
4.2.5. Ditribution of underweight by age Analysis of underweight by age group indicates that children aged 30 to 41 months and 6 – 17 Months were affected by underweight with 8.3% and 7.2% respectively as shown in table 14. Table 14: Prevalence of underweight by age, based on weight-for-age z-scores
Severe Moderate Normal Oedema underweight underweight (> = -2 z score) (<-3 z-score) (>= -3 and <-2 z- score ) Age (mo) Total no. No. % No. % No. % No. % 6-17 125 9 7.2 19 15.2 97 77.6 0 0.0 18-29 109 6 5.5 20 18.3 83 76.1 0 0.0 30-41 96 8 8.3 11 11.5 77 80.2 0 0.0 42-53 84 2 2.4 21 25.0 61 72.6 0 0.0 54-59 55 5 9.1 4 7.3 46 83.6 0 0.0 Total 469 30 6.4 75 16.0 364 77.6 0 0.0
4.2.6. Prevalence of Stunting Stunting is measured by a height-for-age z-score of more than 2 standard deviations below the World Health Organization (WHO) Child Growth Standards median7. Based on WHO classifications, the current stunting is showing low prevalence level (14.7%), with severe stunting cases of 3.7%. This is categorized under medium stunting8 Table 14 is showing the prevalence of stunting based on height for age z- scores by sex.
Table 15: Prevalence of stunting based on height-for-age z-scores and by sex All Boys Girls n = 434 n = 213 n = 221 Prevalence of stunting (64) 14.7 % (34) 16.0 % (30) 13.6 % (<-2 z-score) (10.0 - 21.3 95% (10.9 - 22.7 95% (8.4 - 21.3 95% C.I.) C.I.) C.I.) Prevalence of moderate stunting (48) 11.1 % (26) 12.2 % (22) 10.0 % (<-2 z-score and >=-3 z-score) (7.6 - 15.9 95% (7.8 - 18.5 95% (6.2 - 15.5 95% C.I.) C.I.) C.I.) Prevalence of severe stunting (16) 3.7 % (8) 3.8 % (8) 3.6 % (<-3 z-score) (2.0 - 6.8 95% (1.8 - 7.7 95% (1.7 - 7.6 95% C.I.) C.I.) C.I.)
7 World Health Organization 2018, reducing stunting in children 8 https://www.who.int/nutrition/team/prevalence-thresholds-wasting-overweight-stunting-children- paper.pdf
Figure 6 shows, height for age Z-scores for children compared to reference population. The findings shows a negative shift with mean and standard deviation was -0.90 and ±1.03 respectively
Figure 6: Observed distribution of stunting by WAZ
A further analysis of stunting by age indcate age 18 to 29 months are overally more stunted (19.6%) as shown in table 15.
Table 16: Prevalence of stunting by age based on height-for-age z-scores
Severe stunting Moderate stunting Normal (<-3 z-score) (>= -3 and <-2 z-score ) (> = -2 z score) Age (mo) Total no. No. % No. % No. % 6-17 118 1 0.8 16 13.6 101 85.6 18-29 97 7 7.2 12 12.4 78 80.4 30-41 88 3 3.4 7 8.0 78 88.6 42-53 82 4 4.9 8 9.8 70 85.4 54-59 49 1 2.0 5 10.2 43 87.8 Total 434 16 3.7 48 11.1 370 85.3
4.3 Infant and Young Child Feedings Infant and Young Child Feedings (IYCF) indicators require higher sample size than the SMART. A few indicators were included the SMART assessment to have an understanding of the status. Infant and Young child questions were asked to caregivers of children aged 6-23 months. The survey findings indicate that children 6 – 23 months currently breastfeeding were 29.3%, continued breastfeeding after one year (12 -15 months) was 28.5% and only 11.1% did continue breastfeeding up to two years (20 – 23 months)9.
9 WHO and UNICEF, 2007, Indicators for assessing infant and young child feeding practices
The results further indicated that 38.2% of introduce complementary foods after six months (beside the breastmilk), while 28.9% start when the child is between four to six months. The proportion of mothers who put child to breast within the first hour (1hr) and two (2hrs) after births were (38.2%) and (31.2%) respectively. There was noted variations on meal frequency per day for children 6 – 23 months, with two meals (45.4%), one meal (18.8%), three meals (16.7%) and more than three meals (5.3%). Other infant and young child indicators are shown in table
Table 17: IYCF Indicators
IYCF Indicators # % (CI) Breast Feeding Currently Breastfeeding 34 29.3% (16.6 – 41.9) Breastfeeding Continue breastfeeding up to one year 16 28.5% (13.2 – 43.9) Continue breastfeeding up to two years 2 11.1% (0.0 – 28.0) starts complementary After six months 164 38.2% (27.7 – 48.7) feeding Food/drinks for 4 – 6 months 124 28.9% (18.3 – 38.2) younger children Less than 3 months 14 3.2% (0.4 – 6.0) Less than 2 months 30 6.9% (2.1 – 11.8) Not yet 19 4.4% (0.5 – 8.3) Do not know 71 18.1 (12.6 – 23.7) At what age child should After 6 months 154 35.8% (24.7 – 47.0) given liquids other than 4 -6 months 134 31.2% (20.2 – 42.2) breast milk Less than 3 months 17 3.9% (0.8 – 7.0) Less than 2 months 30 6.9% (0.9 – 13.0) Not yet 18 4.1% (0.4 – 7.9) Don’t Know 56 13.0% (6.8 – 19.2) Within 1 hour 164 38.2% (27.5– 48.9) Put younger child to With 2 hours 134 31.2% (20.9 – 41.1) breast after birth Within 1 day 14 3.2% (1.0 – 5.5) Within 3 days 14 3.2% (0.04 – 6.4)) Do not know 103 24% (17.2 – 30.8) Meals given to 6 – 23 One meal/day 81 18.8% (9.0 – 9.8) months children per day Two meals/Day 195 45.4% (33.6 – 57.2) Three meal/Day 72 16.7% (9.0 24.5) More than three meals/day 23 5.3% (0.8 – 9.8) Other 58 3.5% (7.0 – 20.0)
4.4. Mortality results (retrospective over x months/days prior to interview) The retrospective crude death rate of previous 93 days findings show Crude Death rate (CDR) of 0.15/10,000/day, while the under-five death rate (U5DR) was 0.40/10,000/day. The current mortality result are below the WHO emergency threshold of 1 death/10 000/day and 2
deaths/10 000/day for U5MR and CMR respectively. Reported causes of mortality were Acute Watery Diarrhoea (AWD) and Lower Respiratory Infections (LRI).
4.5 Children’s morbidity Caregivers of children were asked whether their children were sick two weeks prior to the survey. The findings showed 26.7% (17.6 – 35.8 95% C.I.) of children were sick proper to the survey. Majority of the reported causes of child morbidity was acute watery diarrhea (47.1%), Fever or suspected malaria (38.2%) and acute respiratory infection ARI (16.9%) among other diseases as shown in figure 7. The current morbidity result is close to same level the morbidity reported in November 2018 Survey (28.6%), and this could be among the contributing factors for the critical acute malnutrition level.
Disease prevance among children under five
Toothache 0.7 Stomachache 2.9 Skininfection 4.4
Eyeinfection 7.3
Blood stool/dysentry 6.6 Disease ARI/cough 16.9
Malaria/fever 38.2
Diarrhoea 47.1 0 10 20 30 40 50 prevalence 4.5. 1.Health Seeking Behavior Figure 7: Disease prevalence among children under five
Caregivers were asked where they sought care for their children when they were sick. The findings indicate (48.5%) of caregivers reported that they did not take the child to anywhere during the recent illness, which is a big concern and only 33.8% took the child to health facilities while other 12.5% use to private pharmacies and 2.4% used traditional treatments.
4.5.2. Vitamin A supplementation, Vaccination and deworming Results Vitamin A is essential to support rapid growth and to help combat infections. Inadequate intakes of vitamin A may lead to vitamin A deficiency, which can cause visual impairment in the
form of night blindness and may increase the risk of illness and death10. Based on the survey result, vitamin A supplementation coverage during the past 6 months was very low at (13.5%). This was comparable to 2018 which with a coverage a coverage (8.9%). The coverage of Measles and BCG was also assessed. The findings indicated an improvement from 2018 coverage though below the WHO threshold of above 80%. The Proportion of children who received deworming was low at (12.0%) which was comparable to 2018 results as shown in table 19.
Table 18: Vaccination coverage: BCG for 6-59 months and measles for 9-59 months
Antigen SMART Nov 2018 SMART 2019 BCG(scar) 26.4% 71.9% (61.1-82.6%) Measles Card 22.3% 24.1(13.2-35.0) Recall 13.0% 32.6(20.9-44.3%)
Vit A 8.9% 13.5% Polio card 24.2% Recall 51.9% Deworming 13% 12.0% (2.8 – 21.3)
4.6. Programme coverage (Proxy IMAM Coverage) The survey assessed coverage of children in Integrated Management of Acute Malnutrition (IMAM) program. Though SMART methodology does not assess program coverage, the findings are proxy and can be used indicatively. The analysis showed that few children were malnourished were in programs with 3.1% in supplementary feeding programs and 3.7% in therapeutic feeding program. Thought there could be issues of access specially the areas where service is in gap (like Qurac-jome), there is a need to promote and encourage the community on service utilizations. 4.7. Maternal Malnutrition 4.7.1. Physical Status for Mothers The survey team took MUAC measurement for mothers aged 15 to 49 years at the sampled households. The physiological status of the 314 mothers were non-pregnant none lactating (32.4%), during the assessment, while more than half of them were lactating (59.2%).
10 WHO, 2011, Guideline: Vitamin A supplementation for infant’s 1–5 months of age. Geneva, World Health Organization.
4.7.2. Maternal nutrition and Multiple Micronutrient supplementations Malnutrition among pregnant and lactating mothers with MUAC <21.0cm was 6.6%. Majority of mothers did not take Multiple Micronutrient supplementations, as only 23.8% of mothers reported that they had received it during the last pregnancy with 93.3% consuming for less than 60 days as shown in table 19. Table 19: Maternal nutrition and Multiple Micronutrient supplementations Indicators Status Number Proportion (CI) Maternal Malnutrition N MAUC <21.0cm 14 6.6% (3.2 – 9.9) Received Multiple Micronutrients Yes 75 23.8% (12.3 – 35.4) during last pregnancy How many days take (Multiple Less than 30 days 24 32.0% (21.7 – 42.2) Micronutrients) 30 – 59 days 46 61.3% (47.5 – 75.1) ≥ 60 Days 5 6.6%% (1.4 – 11.8)
4.8. Water Sanitation and Hygiene (WASH) Access to save source of drinking water is low (30.0%), and the majority of households were getting water from unprotected sources, while access to latrine is also low (46.1%) and indicting low latrines utilization. Majority of households were not practicing hand washing in most of critical times as shown in table 20. Table 20: WASH indicators SN Indicators Number Proportion (CI) 1 Access to safe drinking water sources 129 30.0% (16.6 – 43.4) 2 Latrines at the HH 198 46.1% (33.1 – 59.1) 3 Hand washing after taking children to the toilet 62 14.4% ((3.4 – 25.5) 4 Hand washing after the toilet 181 42.1% (29.2 – 55.1) 5 Hand washings before cooking 83 19.3% (11.5 – 27.1) 6 Hand washings before eating 286 66.6% (54.5 – 78.8) 4.9. Food Security and Livelihood 4.9.1. Dietary diversity Households were asked about the foods consumed the last one week. The findings indicated a household dietary diversity of 4.8 which is categorized as moderate between 3-5 food groups. Majority of households consumed from cereals, oils sugar and condiments. About 50% of households consumed milk. There was noted low consumption of vegetables, fruits, meat, legumes, fish and tubers.
Food consumed by Households 100.0 90.0 80.0 70.0 60.0 50.0 40.0 30.0 20.0 % of households of% households 10.0 0.0
Food Groups Figure 8: Food consumed by households
4.9.2. Household Coping Mechanism Based on FSNAU post Gu’ 2019 food security analysis and phase classifications, the population of Elbarde district (Southern Inland Pastoral) were in stressed phase (IPC phase II). However, the current AAH assessment result is showing that 67.1% of households are consuming ≥4 food groups, which means that one third of households have low dietary diversity (<4 food groups). More than half of households (51.2%) are also practicing high reduced coping strategies (≥10)11 and other significant proportion (37.0%) are also using Figure 9: Coping Strategies Index medium (4- 9) reduced coping strategies, the current HDDS and rCSI are showing deteriorated food security situation, which can be due to worsened road access, during October and early November 2019, due to heavy rains, and this has resulted increased food prices as shown in table 21.
Table 21: Changes on Food prices before and after the rains Commodity Before rain After rain Rice (50 kg bag) $ 32 $ 40 Sugar (50 kg bag) $ 32 $ 40 Wheat flour (50 kg bag) $ 30 $ 36 Pasta (10 kg) $ 7.5 $ 9
Table 22: House hold Dietary Diversity Scores and reduced Coping Strategies Index based on IPC Version 3.
IPC phase Food Groups N % (CI) HDDS 1-2 5-12 219 51 (36.9 - 65.1) 3 3-4 153 35.6 (23.5 - 47.7) 4-5 0-2 57 13.2 (2.9 - 23.5) IPC phase scores N % (CI) rCSI 1 0 - 3 51 11.8 (8.3 - 15.4) 2 4 - 18 302 70.3 (64.6 - 79.1) 3,4,5 ≥19 76 17.7 (13.3 - 22.0)
Regarding the IPC rule of 20%, the current result of HDDS (35.6%) is showing crisis phase (IPC phase 3), while for rCSI majority of households (70.3%) are showing stressed phase (IPC phase 2)12
11 WFP, 2012,calculation of household food security outcome indicators, Afghanistan
12 IPC version 3; Acute Food Security reference table
5.0. Discussion The survey findings indicated a high prevalence of Global Acute Malnutrition (GAM) of 20.4% (16.1 – 25.5) with Severe Acute Malnutrition (SAM) rate of 5.0% (2.7 –8.8) categorised as critical situation. The current result shows sustained critical nutrition situation compared to November 2018 AAH SMART survey with GAM of 20.3% and SAM of 6.1%. Boys were more malnutrition (23.0%) than girls (18.0%) but not statistically significant (P Value (0.225).A further analysis of age cohort mostly affected by malnutrition indicates ages 6-17 which could be attributed to sub-optimal complementary feeding. There is need to look into the possible causes of high malnutrition among ages 42 to 59 months. The sustained critical nutrition status is likely due to mixed factors that are negatively influencing the situation which includes the high morbidity levels with 26.7% of children being sick two weeks prior to survey date. A further analysis also showed 47.1% and, 38.2% of children suffered from diarrhoea and fever/malaria. The high morbidities of AWD and fever is likely because of the recent rains as use of unsafe water and increased malaria cases might happen during the rainy season. Majority of households are accessing water from unprotected (70%) source and there could be likelihood of increased disease, especially AWD cases. The other possible cause of malnutrition deteriorated food insecurity due reduced market accesses after more than a month continued rain has blocked all the roads, which resulted significant increase of food prices. Low dietary diversity scores (DDS) of 4.8, and adaption of high rCSI is another indication of vulnerability as more than 30% of households have low dietary diversity (<4 FGs), while more than half of them are practicing high rCSI. Low coverage of health services like immunizations, vitamin A supplementations and deworming, as well as, limited access to safe drinking water (30.0%) and household latrines (46.1%) and poor child care practices might also attribute to worsen the situation. Qurac-jome and surround villages had no access to health/nutrition services during the recent months due to intervention gaps and currently the children registered at the nutrition programs were very low, as only 3.1% were in OTP program and 3.7% in TSFP Crude and under five death rates are within the acceptable ranges. Current CDR of 0.15 and U5DR of 0.40 are showing almost similar to 2018 result (CRD 0.26) and the main cause of death were AWD and respiratory infections.
CONCLUSIONS Therefore, continuation of the current activities and upscaling further interventions are very crucial to mitigate and prevent further deteriorated situation. There is need to also have a detailed understanding of high malnutrition rates among ages 6-17 and 42 to 59 months to have a targeted programing.
6.0. RECOMMENDATIONS AND PRIORITIES
To address the high malnutrition among children under five, continuation of current ongoing humanitarian interventions are very crucial. The following recommendations have been put forward to complement the on-going interventions.
Table 23: Recommendations Findings Descriptions Recommendations Critical Acute malnutrition and high GAM 20.4% (16.1 – 25.5) • Continue the Ongoing management of Severe prevalence of Underweight MUAC <125mm 12.6% (9.4 – 16.6) and moderate acute malnutrition (OTP, SC and Underweight 22.4% (17.2 – 28.6) TSFPs). • Treatment/management of communicable diseases (especially AWD, Fever and ARI). Low health service coverages Measles immunizations (32.6%) • Demand generations to increase utilization of Immunization coverages are below the BCG coverage (71.9%) health/immunization services. international standards (sphere >95%). Vitamin A supplementations (13.5%) • Conduct immunization outreach and mobile Very low vitamin A supplementations activities to reach areas with no access to Deworming 12.0% health services Suboptimal IYCF practices • Breast feeding 29.3% • Promotion of positive behaviours on child care • Continue breastfeeding up to 1 practices and strengthen the IYCF activities. year (28.5%) • Continue breastfeeding up to 2 years (11.1%) Limited access to safe drinking water and • Access to safe drinking water (30%) • Improve the access to safe drinking water the need for improved WASH practices • Majority of households do not have through availability of protected water sources latrines (53.9%) • Construction of latrines • Hygiene promotions High proportion of the population are still High rCSI (51.2%) • Food Security interventions (like cash voucher practicing high-reduced coping strategies. DD ≥ 4 Food groups (67.1%) or cash for work). Low HH dietary diversity scores • Improve road accesses, through cash for work
7. REFERENCES
1. IPC Global partner, 2010, The Integrated Phase Classification Technical Manual
2. FSNAU, 2019: FSNAU Post Gu 2019 Integrated Phase Classifications. 3. World Health Organization 2018, reducing stunting in children 4. WHO and UNICEF, 2007, Indicators for assessing infant and young child feeding practices 5. WHO, 2011, Guideline: Vitamin A supplementation for infants 1–5 months of age. Geneva, World Health Organization 6. WHO, https://www.who.int/elena/titles/deworming/en/ 7. WFP, 2012,calculation of household food security outcome indicators, Afghanistan 8. IPC version 3; Acute Food Security reference table
8.0. Annexes 8.1. Survey Questionnaire
District District Clusterno Cluster number Hhno HH number Teamno Team number Enumcode Enter your enumerator code Geopoint Module Latitude Latitude Longitude Longitude Consent Module Hello my name is [MY NAME]. I work for (Action Against Hunger ) nutrition project and we are currently conducting a data collection exercise in the communities supported by (name of project). You were selected by chance to participate into this survey and your participation is completely voluntary and confidential. There will be nothing done against you should you refuse to participate in this interview. The purpose of this interview is to get your views on the services we are providing and help identify ways how we can improve our processes. The information you share will only be used for the purpose mentioned above and will not be used against you anywhere and no additional benefit will be provided to you personally as a result of your participation in this interview. This interview will last approximately between 15 to 20 minutes.
Do you consent to participate the survey?
Con
Noconsent Would you mind telling us why you do not feel able to proceed with the questionnaire? Household Status Module HHSTATUS Displacement status of the HH. NoMealAdults How many meals did adults in the household eat yesterday? NoMealKids How many meals did children in the household eat yesterday? Dietary Diversity Module Foods eaten yesterday Kindly list all the food items that were eaten by members of this household yesterday Nthdd (day or night). Labdd - DdCEREALS Cereals and cereal products eaten DdMILK Milk and milk products ddORANGEVEG Vitamin A rich vegetables and tubers ddGREENVEG Dark green leafy vegetables ddOTHERVEG Other vegetables ddVITAFRUIT Vitamin A rich fruits ddOTHERFRUIT Other fruit ddFLESHMEAT Meat and Poultry ddORGANMEAT Organ meat ddEGGS Eggs ddFISH Fish
ddBEANS Legumes, nuts and seeds ddTUBERS White roots and tubers ddOIL Oils and Fats ddSUGAR Sweets ddCONDIMENTS Coffee, tea and Spices Food Consumption Module Foods eaten in the past 7 days How many days in the last seven days did your household consume Ntfcs Labfcs - fcsCEREALS Cereals and cereal products eaten fcsMILK Milk and milk products fcsORANGEVEG Vitamin A rich vegetables and tubers fcsGREENVEG Dark green leafy vegetables fcsOTHERVEG Other vegetables fcsVITAFRUIT Vitamin A rich fruits fcsOTHERFRUIT Other fruit fcsFLESHMEAT Meat and Poultry fcsORGANMEAT Organ meat fcsEGGS Eggs fcsFISH Fish fcsBEANS Legumes, nuts and seeds fcsTUBERS White roots and tubers fcsOIL Oils and Fats fcsSUGAR Sweets fcsCONDIMENTS Coffee, tea and Spices In the past 7 days, if there have been times when you did not have enough food or money CSI Module to buy food, how often has your household had to: csiLess Consume to less preferred (low quality, less expensive) foods? csiReduce Reduce the portion size/quantity consumed at meal times (Beekhaamis)? csiFewer Reduce number of meals per day? csiBorrow Borrow food on credit from another household (Amaah)? csiAdult Restrict consumption of adults in order for small children to eat? csiCredit Borrow food on credit from the shop/market (Deyn)? csiDonateReli Rely on food donations from relatives (Qaraabo)? csiDonateClan Rely on food donations from the clan/community (Kaalmo)? csiFoodAid Seek or rely on food aid from humanitarian agencies? csiEatOther Send household members to eat elsewhere? csiBeg Beg for food (Tuugsi/dawarsi)? csiSkipDay Skip entire days without eating (Qadoodi)? csiSpoiltFood Consume spoilt or left-over foods csiHunt Rely on hunting for food (ugaarsi)? csiMilkLess Reduce home milk consumption and sell more of milk produced? csiWeakStock Consume weak un-saleable animals (caateysi)? csiMilkStop Stop all home milk consumption and sell all milk produced?
csiCommAid Community identified your household as in need of food and fives support? (Qaraan) csiSeedEat Consume seeds meant for future planting? csiInmatCRops Consume immature crops (fruits or cereals)? csiWildFood Consume wild foods? Eating unacceptable/prohibited foods (animal skins, grass & roots, clotted blood, tree csiProhibFood leaves, warthogs) Mortality Module Currently Living in the Household Id How many household members are currently living in this household? name_hh_l Household Member Name: sex_hh_l Sex of ${name_from_earlier}: age_hh_l Age (in years) of ${name_from_earlier}: join_hh_l Did ${name_from_earlier} join on or after ${recall_start}? born_hh_l Was ${name_from_earlier} born on or after ${recall_start}? Mortality Module Members who Left the Household id_left name_left Household Member Name: sex_left Sex of ${exit_member_name}: age_left Age (in years) of ${exit_member_name}: join_left Did ${exit_member_name} join on or after ${recall_start}? born_left Was ${exit_member_name} born on or after ${recall_start}? Mortality Module Members who Died id_died How many household members have died since ${recall_start}? name_died Household Member Name: sex_died Sex of ${died_member_name}: age_died Age (in years) of ${died_member_name}: join_died Did ${died_member_name} join on or after ${recall_start}? born_died Was ${died_member_name} born on or after ${recall_start}? cause_died What was the cause of death of ${died_member_name}? location_died Where did ${died_member_name} die? Specify_Loc Mortality Pregancny Module pregrant_woman Was anyone in the household pregnant from ${recall_start}? number_pregnant How many household members were pregnant? caretaker_asses Mother/Carer Agewomengte15 What is the age of the mother or primary caregiver in years? How many of the children in this household under 5 are you the mother of or currently nokidlte5 the primary carer for? Are you a mother or a carer of a child or children in this household who is currently under MumCarer 5 years old? Edumax What is your highest level of education? MumCarerMUAC Mother / primary caregiver’s MUAC (cm) Record to the nearest 0.1 cm physStatus What is the physiological status of the mother? During your last pregnancy did you receive multiple micronutrient/Iron/at all? TabsLastPreg
If Yes, for how many days did you take these tablets? DayTaken IYCF Module Children 0 - 23 Months iycf_child How many children 6 - 23 months old are currently in the household? IYCF_NAME Name of Child lt5Sex What is the child sex? lt5AgeMths What is the child's age in months? Bfeed Is this child currently being breastfed? Bmilk1223 Was this child given any breastmilk yesterday? Did this child eat any solid, semi-solid or soft foods yesterday? Eat0812m NoEat0623 How many times did the child eat solids, semi solids and soft food yesterday? Please tell me everything that the child ate yesterday during the day or night (whether at home or outside the home). Think about when the child first woke up yesterday. Did the child eat anything at that time? Keep probing ‘Anything else?’ until the respondent says ‘nothing else.’ If nothing else was given when the child first got up, ask: What did the child do after that? Did the child eat anything at that time? If yes, ask: Please tell me everything the child ate at that time. Probe: ‘Anything else?’ until respondent says ‘nothing else.’ If respondent mentions mixed dishes like a sauce or stew, probe: What ingredients were in that MIXED DISH? Probe: ‘Anything else?’ Until respondent says ‘nothing else.’
As the respondent recalls each food, select Yes for food in the food group list on next screen. ntDD feed623 Feeding 6-23 mths Labinffeed - infGrains Grains, roots and tubers infLegNut Legumes and nuts infDairy Dairy products infMeatrOffel Meats infEgg Eggs infVitAVeg Vitamin A rich vegetables infFruit Other fruits and vegetables infOils Oils and fats infRUTF Child fed RUTF Children 6 - 59 Months Module lt5total How many children under 5 years old are currently in the household? id_child Child ID child_name Name of Child lt5Sex What is the child sex? dob_child Date of Birth of Child lt5AgeMths What is the child's age in months? age_determine How was age determined Wt0659m Weight (kg) to the nearest 0.1kg Ht0659m Height (cm) to the nearest 0.1cm
Oedema Oedema present in child OedemaPhoto If yes, Please take a picture of the oedema test and submit to confirm. MUAN0659m MUAC (cm) to the nearest 0.1 KidNutProg Is this child currently registered in any nutrition programme? (must see card) VitA659mth Has this child received Vitamin A within the last 6 months? Worm1259mth Has this child received a deworming tablet within the last 6 months? MeasleVac Has the child been vaccinated against measles? BCGScar Does have a BCG scar? Plio Has child received the Polio vaccine? IllL2Wks Has child been ill during the last 2 weeks? (If YES), What kind of illness? Use case definitions (If more than one illness is mentioned, take the prominent illness to avoid recording signs and symptoms of the same problem). WhatIll0659 PlaceTreat Where did you take the child for treatment? School Module How many Males in the household aged 5-14 years are currently enrolled in school? Must MALE5_14yrsSCH be no more than ${Males5yrs} How many Females in the household aged 5-14 years are currently enrolled in school? FEMALE5_14yrsSCH Must be no more than ${Females5yrs}
LITERATE How many people in the household (5 years & above?) can read and write? WASH Module
WASHMAINWATERSOURCE What is the main source of drinking water for your household? HANDWASHING Yesterday (within last 24 hours) at what instances did you wash your hands? If the caregiver washes her hands, then probe further; what did you use to wash your USEWASHHANDS hands? DEFECATION Where do household members usually defecate? RELOCATIONPLANS Do you plan to move your household in the next 3 months? MOVING If moving, why? CELLYN Do you have access to a mobile phone CELLOWNED Is the phone your personal phone? END Interview
8.2. Sampling Frame Geographical unit Population size Cluster Elbarde town 19800 1,RC,2,3,4,5,6,7,8,9,10,11,12,RC,13 Ato 3900 RC,14,15 Gargar IDPs 900 16 Wargarweyne IDPs 300 Biyo fadhi 390 17 Hiiray 480 Qabsay 420 Salkudhooble 1200 18 Danshoot 660 19 Gahaydhlay IDP 138 Ayeeyo 330 Ondhere 570 20 Lanbar 540 Garidab 636 21 Xamudhgob 516 Figta 1500 22 Abesaale 2160 23,24 Haarcad 660 Higlole 570 25 Ceelcali 516 Habarey 750 26 Buq 540 Elmagad 1410 27 Qurucjome 6300 28,29,30,RC,31 Bananay IDP 210 Ceel Lahelaye 390 Cimilow 360 32 Libaaxle 270 Kheyra haboon 300 Naagafaal 288 Dharkeynley 330 33 Ceelkuusow 468 Dhagaxtuur 390
8.3. Plausibility check for: Elbarde SMART Survey 2019.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 (0.6 %)
Overall Sex ratio Incl p >0.1 >0.05 >0.001 <=0.001 (Significant chi square) 0 2 4 10 0 (p=0.723)
Age ratio(6-29 vs 30-59) Incl p >0.1 >0.05 >0.001 <=0.001 (Significant chi square) 0 2 4 10 4 (p=0.036)
Dig pref score - weight Incl # 0-7 8-12 13-20 > 20 0 2 4 10 0 (5)
Dig pref score - height Incl # 0-7 8-12 13-20 > 20 0 2 4 10 0 (7)
Dig pref score - MUAC Incl # 0-7 8-12 13-20 > 20 0 2 4 10 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 0 (1.09)
Skewness WHZ Excl # <±0.2 <±0.4 <±0.6 >=±0.6 0 1 3 5 0 (-0.02)
Kurtosis WHZ Excl # <±0.2 <±0.4 <±0.6 >=±0.6 0 1 3 5 0 (-0.19)
Poisson dist WHZ-2 Excl p >0.05 >0.01 >0.001 <=0.001 0 1 3 5 0 (p=0.151)
OVERALL SCORE WHZ = 0-9 10-14 15-24 >25 4 %
The overall score of this survey is 4 %, this is excellent.
There were no duplicate entries detected.
8.4. Report for Evaluation of Enumerators
Weight:
Precision: Accuracy: No. +/- No. +/- Sum of Square Sum of Square Precision Accuracy [W1-W2] [Enum.(W1+W2)- (Superv.(W1+W2)] Supervisor 76.05 2/1 Enumerator 1 0.11 OK 84.10 OK 3/5 3/6 Enumerator 2 0.01 OK 69.08 OK 0/1 2/4 Enumerator 3 0.01 OK 66.28 OK 1/0 2/5 Enumerator 4 0.11 OK 89.30 OK 2/1 2/6 Enumerator 5 0.08 OK 67.37 OK 3/2 3/4 Enumerator 6 0.03 OK 67.54 OK 2/1 4/4 Enumerator 7 0.10 OK 63.55 OK 0/2 4/5 Enumerator 8 0.07 OK 87.08 OK 0/4 5/4 Enumerator 9 0.05 OK 71.66 OK 0/2 3/6 Enumerator 10 4583.32 POOR 3995.67 POOR 3/1 2/5 Enumerator 11 0.15 OK 72.48 OK 3/3 4/5 Enumerator 12 0.00 OK 133.09 OK 0/0 4/5 Enumerator 13 0.04 OK 68.61 OK 2/2 4/4 Enumerator 14 0.04 OK 133.09 OK 0/1 3/6 Enumerator 15 0.11 OK 87.88 OK 2/3 4/5 Enumerator 16 0.07 OK 69.08 OK 0/4 3/6 Enumerator 17 10424.40 POOR 10633.30 POOR 1/0 3/3 Enumerator 18 4108.92 POOR 4206.03 POOR 0/9 4/5
Height:
Precision: Accuracy: No. +/- No. +/- Sum of Square Sum of Square Precision Accuracy [H1-H2] [Enum.(H1+H2)- Superv.(H1+H2)]
Supervisor 24.73 3/5 Enumerator 1 14.83 OK 64.52 OK 3/5 7/3 Enumerator 2 0.18 OK 47.57 OK 5/1 6/4 Enumerator 3 0.02 OK 38.25 OK 1/1 7/3 Enumerator 4 20.70 OK 51.21 OK 3/5 7/3 Enumerator 5 49.01 OK 59.02 OK 0/2 6/4 Enumerator 6 0.20 OK 39.65 OK 5/4 7/2 Enumerator 7 24.82 OK 100.61 POOR 3/2 8/2 Enumerator 8 0.15 OK 51.34 OK 2/7 5/5 Enumerator 9 0.25 OK 34.62 OK 0/1 5/5 Enumerator 10 4045.02 POOR 3571.23 POOR 1/6 6/3 Enumerator 11 14.18 OK 104.47 POOR 5/3 4/6 Enumerator 12 1.87 OK 382.14 POOR 1/4 3/7 Enumerator 13 1.55 OK 38.32 OK 7/2 7/3 Enumerator 14 0.02 OK 432.55 POOR 2/0 2/8 Enumerator 15 6.61 OK 62.34 OK 2/5 5/5
Enumerator 16 0.17 OK 40.60 OK 0/6 5/4 Enumerator 17 4603.33 POOR 4419.82 POOR 1/3 4/5 Enumerator 18 154.97 POOR 238.04 POOR 3/6 3/7
MUAC:
Precision: Accuracy: No. +/- No. +/- Sum of Square Sum of Square Precision Accuracy [MUAC1-MUAC2] [Enum.(MUAC1+MUAC2)- Superv.(MUAC1+MUAC2]
Supervisor 1487.63 5/5 Enumerator 1 Error Error 4/4 5/5 Enumerator 2 39.00 OK 3570.91 OK 7/0 2/8 Enumerator 3 5.00 OK 2916.51 OK 1/1 3/7 Enumerator 4 946.00 OK 2861.31 OK 6/4 8/2 Enumerator 5 1.00 OK 4396.91 OK 1/0 4/6 Enumerator 6 19.00 OK 1824.91 OK 5/0 5/5 Enumerator 7 10317.30 POOR 11182.40 POOR 3/1 4/6 Enumerator 8 407.00 OK 2737.51 OK 2/3 7/3 Enumerator 9 8.00 OK 7663.51 POOR 0/2 4/6 Enumerator 10 20249.00 POOR 17278.90 POOR 1/2 7/3 Enumerator 11 142.00 OK 2660.11 OK 3/1 7/3 Enumerator 12 887.00 OK 2545.71 OK 8/1 7/3 Enumerator 13 73.00 OK 1900.11 OK 4/2 5/5 Enumerator 14 51.00 OK 2419.51 OK 1/6 8/2 Enumerator 15 54.00 OK 2366.11 OK 1/2 6/4 Enumerator 16 32.00 OK 7390.91 POOR 1/4 2/8 Enumerator 17 3553.36 POOR 4496.15 POOR 1/1 5/5 Enumerator 18 15.00 OK 2877.71 OK 5/2 7/3
8.5. Calendar of Events for SMART Survey, October, 2019 Sanadka Miilaadi Hijri Season 2019 2018 2017 2016 2015 2014 January Jamadul Awal/ Ban Jilaal 10 22 34 46 58 hore Doorashaddii Farmaajo February Jamadul Akhir/ Ban Jilaal 9 21 33 45 57 dambe March Rajab/Awosman Jilaal 8 20 32 44 56 Xilligii uu daacuunku dilaacay, Koonfurta Somalia April Shacbaan Gu’ 7 19 31 43 55
May Ramadan/Soon Gu’ 6 18 30 42 54 Bilow Ramadan June Shawaal Soonfur Gu’ 5 17 29 41 53 Ramadan/Ciid Al-fidri Ramadan/Ciid Al-fidri Ramadan Bilow Ramadan July Dulqacda/ Sidataal Xagaa 4 16 28 40 52 Maalinta Xoriyadda Maalinta Xoriyadda Cid Al-fidri Ramadan/ Ciid Al- Maalinta fidri Xoriyadda Maalinta Xoriyadda August Dul xijaha/ Carafo Xagaa 3 15 27 39 51 Ciid Al-Adxa September Muxaram/ Sako Xagaa 2 14 26 38 50 Ciid Al-Adxa Ciid Al-Adxa October Safar Deyr 1 13 25 37 49 Qaraxii Soobbe Ciid Al-Adxa Doorashaddii Xudur November Rabiicul Deyr - 12 24 36 48 Awal/Mowliid December Rabiicu Thaani/ Deyr - 11 23 35 47 59 Malmadoone