NURITION AND FOOD SECURITY SURVEILLANCE:
NORTH EAST NIGERIA – EMERGENCY SURVEY NOVEMBER 2019
FINAL REPORT
Acknowledgments This survey was carried out by the National Bureau of Statistics (NBS) in coordination with the National Population Commission (NPopC), the Federal Ministry of Health (FMOH), and the Nigeria Nutrition in Emergency Working Group (NiEWG).
Financial support was provided by the Government of Nigeria, United Nations Children’s Fund (UNICEF), and the United Kingdom Agency for International Development (UKAID). Technical support was provided by the Centers for Disease Control and Prevention (CDC) and UNICEF through NBS.
Additional information about this survey may be obtained by contacting UNICEF Nigeria or the Northeast Nigeria Nutrition Sector Coordinator Simon Karanja: [email protected] or Adamu Yerima: [email protected].
Executive Summary
The Boko Haram conflict was declared to be a state of emergency at the beginning of 2012 by the government of Nigeria. In May 2013, the area under the state of emergency was extended to include all of Adamawa, Borno and Yobe states in North-eastern Nigeria. The insurgency and political violence had caused mass population displacement. According to the International Organization of Migration’s (IOM) August 2019 report, there were 1,483,566, 200,011 and 131,597 internally displaced persons (IDPs) in Borno, Adamawa and Yobe states respectively.
Given the emergency situation as well as recently increases in access to newly liberated areas since the emergency declaration, a series of repeated surveys were organized with the primary objective of providing representative estimates for prevalence of acute malnutrition among children 6 to 59 months (by weight-for-height and MUAC), as well as mortality rate in North East Nigeria to inform the ongoing emergency response. Information on nutritional status of women of reproductive age, prevalence of common child health morbidities, access to health services and health status among children, and infant feeding.
The first round of repeated surveys was conducted in October-November 2016, the second round in February-March 2017, the third round in July-August 2017, the fourth round in November-December 2017, the fifth round in April-May 2018 and the sixth round conducted jointly with WFP for both nutrition and food security (JANFSA) in October 2018, seventh round in May-June 2019.
These surveys were carried out by the National Bureau of Statistics (NBS) in coordination with the National Population Commission (NPC), the Federal Ministry of Health (FMOH), and the Nigeria Nutrition in Emergency Working Group (NiEWG). Financial support was provided by the Government of Nigeria, United Nations Children’s Fund (UNICEF), and the United Kingdom Agency for International Aid (UKAID). Technical support was provided by the Centers for Disease Control and Prevention (CDC) and UNICEF through NBS.
Methodology
Cross-sectional household surveys were carried out using a two-stage cluster sampling design consistent with the SMART methodology. The survey area consisted of 65 LGAs within the three states of Adamawa, Borno and Yobe. The 65 LGAs were divided into 10 domains: 2 in Adamawa (North and South), 3 in Yobe (North, Central and South) and 5 in Borno state (North, South, Central, East, and MMC/Jere). Domains were created considering livelihood zones, geographic proximity and socio-cultural homogeneity1. Results are representative at the level of the domain, a grouping of LGAs.
Clusters were selected using probability proportional to size (PPS) sampling. The primary sampling unit (PSU) for Yobe and Adamawa domains were based on Enumeration Areas (EAs) from the 2006 census frame. Estimated populations for each EA are 2019 populations projected from the 2006 census. Given recent large-scale population movement, an updated sampling frame was built for Borno. Population estimates from the August 2019 polio campaign micro plan as well as Village Tracking System population estimates by settlement were used for settlements2.
1 Famine Early Warning Systems Network (FEWSNET). Nigeria Livelihood Zones. 2014. Available at: http://www.fews.net/west-africa/nigeria/livelihood-zone-map/may-2014
2 Nigeria - DTM Round 28 Report (August 2019). Available at; https://displacement.iom.int/system/tdf/reports/Nigeria_DTM_Round_28_Report_August%202019.pdf?file=1&type=node &id=6616
Sample size was calculated to ensure adequate precision for estimates of global acute malnutrition (GAM) and crude mortality rate (CMR). A sample of 600 households, 30 clusters of 20 households, was selected per domain. Within selected clusters, all households were listed and selected using systematic random sampling. Enumerators received a four-days training including a full standardization and field test.
Results Data collection took place between September 15 and October 22, 2019. Four of the LGAs in Borno (Abadam, Guzamala, Kukawa and Marte) were determined by state level actors to be inaccessible at the time of this survey. All ten domains were accessible and all inaccessible areas in were excluded a priori. Prevalence of GAM in children 6 to 59 months was 11.3% in Yobe, 8.1% in Borno, and 7.2% in Adamawa. Prevalence of GAM exceeded the WHO Crisis Classification threshold for serious (10%) in all the domains in Yobe state (Central Yobe, Southern Borno, and Northern Yobe) and East Borno in Borno state. Prevalence of GAM was highest in Central Yobe both by weight-for-height and/or oedema (13.8%), and by MUAC (4.1%).
Crude mortality was highest in Southern Adamawa 0.41 while under-five mortality rates was highest in both Northern Borno 1.02). Crude and under-five mortality rates remained below emergency threshold of 1 death / 10,000 people / day & 2 deaths in children under five / 10,000 children under five / day in any of the domains. By domain, crude mortality rate ranged from 0.2-0.41 total deaths / 10,000 people / day. Under five mortality rates ranged from 0.1 to 1.02 deaths in children under five / 10,000 children under five / day.
Overall, data quality was excellent in all 10 domains according to SMART methodology classifications.
Breastfeeding practices were assessed as a measure of infant and young child feeding (IYCF). The proportion of children who continued breastfeeding at one year was over 90% in all three states, but then steadily declined; continued breastfeeding at two years (assessed among children aged 20-23 months) ranged from 31.1 - 40.9% by state.
Prevalence of acute among adolescent girls (15 to 19 years) was 29.5% and among adult women (20 to 49 years) was 5.9%. The rates of acute malnutrition is 5 times higher among the adolescent compared to the adult women.
Recommendations: Based on the NFSS Round 8 findings, the following actions are recommended:
Prevention: 1. UNICEF and WHO to continue support for SPHCDA to strengthen the routine provision of vitamin A and deworming through the EPI at health facilities, and in regular campaigns. UNICEF to assist in developing communication strategies to improve the uptake of vitamin A and deworming both in routine programming, and campaigns. 2. Health Sector to ensure 100% coverage of measles vaccination to ensure 100% herd immunity is achieved. 3. WHO, UNICEF and health sector partners to strengthen management of common childhood illnesses, such as diarrhoea, at accessible at the household level and primary health centers. 4. WFP to continue strengthening its ongoing humanitarian response (nutrition and food or cash assistance), which may be attributable in contributing to the documented decrease in acute malnutrition.
Response: 5. Improve coverage of effective nutrition intervention e.g. targeting them in Mother to Mother Support groups, aimed at improving the nutritional status of adolescent girls. 6. Nutrition Sector partners to adopt tested and innovative methods to improve the coverage and quality of infant and young child feeding (IYCF), and use of micronutrient powder (MNP), including establishing Father-to-Father Groups, Mother-to-Mother Support Groups, Care Models, and engagement of Community Nutrition Mobilisers to distribute MNPs.
Funding 7. Donors to support Nutrition Sector partners to scale-up nutrition prevention and treatment response in areas with persistent high levels of GAM including Central, Northern and Southern Yobe, and East Borno.
Monitoring and Evaluation: 8. Nutrition Sector to plan and carry out systematic SMART methodology nutrition surveys in LGAs, and to seek donor funding for regularization of these surveys.
Coordination: 9. OCHA to support the Nutrition Sector to involve the ISWG and specifically the WASH and Food Security in the planning, implementation, analysis, and dissemination of results. This is to ensure the SMART results are relevant to the other sectors. 10. OCHA to support the adoption of GAM results as a cross cutting outcome for all sectors.
Table of Contents
Acknowledgments i Executive Summary ii Table of Contents 5 List of Tables 7 List of Figures 8 List of Acronyms 9 1 Introduction 11 1.1 Justification 11 1.2 Objectives 12 2. Methodology 13 2.1 First Stage Sampling 13 2.2 Second Stage Sampling 14 2.3 Sample Size Calculation 14 2.4 Case Definitions and Inclusion Criteria 18 2.5 Training and Supervision 19 2.6 Data Analysis 20 3. Results 21 3.1 Final Sample and Data Quality 21 3.2 Anthropometric results: 24 3.2.1 Acute Malnutrition (WHZ and/or Bilateral Oedema) 25 3.2.2 Acute Malnutrition (MUAC) and/or Bilateral Oedema 28 3.2.3 Underweight 32 3.2.4 Chronic Malnutrition (Stunting) 34 3.3 Mortality results 37 3.4 Infant and Young Child Feeding 37 3.5 Child Health 44 3.5.1 Measles Vaccination Coverage 44 3.5.2 Diarrhoea, Oral Rehydration Therapy and Zinc Supplementation 47 3.5.3 Acute Respiratory Infection (ARI) and Treatment 49 3.5.4 Fever, Prevention of Malaria, and Antimalarial Treatment 51 3.6 Maternal Nutrition 56 3.6.1 Minimum Dietary Diversity for Women 58 3.7 Public Health Interventions that Prevents against Malnutrition 60 3.7.1 Deworming, Vitamin A and Micronutrient Powder (MNP) 60 3.7.2 Specialised Nutritious Foods 62 3.8 Water, Sanitation and Hygiene (WASH) 63 4. Discussion: 66 5. Conclusion and Recommendations 73 6. References 75
7. Annexes 77 Annex 1: Local Government Areas and Estimated Accessible Population, by Survey Domain 77 Annex 3. Maps of Local Government Areas, by Survey Domain 79 Annex 4. List of nutrition indicators and definitions 80 Annex 5: Calendar of Local Events 84 Annex 6: Selected Clusters 86 Annex 7: Plausibility Checks 98
List of Tables TABLE 1: SURVEY DOMAINS...... 13 TABLE 2 ANTHROPOMETRY AND MORTALITY SAMPLE SIZE INPUTS...... 16 TABLE 3 NUMBER OF HOUSEHOLDS PER CLUSTER IN EACH DOMAIN ...... 17 TABLE 4 NUMBER OF CLUSTERS AND HOUSEHOLDS SAMPLED BY DOMAIN ...... 17 TABLE 5 FINAL SAMPLE OF HOUSEHOLDS, WOMEN AND CHILDREN, BY DOMAIN ...... 21 TABLE 6 DISTRIBUTION OF AGE AND SEX OF SAMPLE, BY DOMAIN ...... 22 TABLE 7 SUMMARY OF CHILD ANTHROPOMETRY DATA QUALITY ...... 23 TABLE 8 PROPORTION OF CHILDREN WITH COMPLETE DATA OF BIRTH, AGE REPORTED IN MONTHS OR MISSING, BY DOMAIN AND TEAM ...... 24 TABLE 9 PREVALENCE OF ACUTE MALNUTRITION BY WEIGHT-FOR-HEIGHT Z-SCORES (AND/OR OEDEMA) AND BY SEX, CHILDREN 0-59 MONTHS, BY STATE AND DOMAIN ...... 26 TABLE 10 PREVALENCE OF ACUTE MALNUTRITION BY AGE, BY WEIGHT-FOR-HEIGHT Z-SCORES AND/OR OEDEMA, CHILDREN 6-59 MONTHS, BY DOMAIN ...... 27 TABLE 11 PREVALENCE OF ACUTE MALNUTRITION BY MUAC (AND/OR OEDEMA) IN CHILDREN 6-59 MONTHS, AND BY SEX, STATE AND DOMAIN ...... 30 TABLE 12: PREVALENCE OF ACUTE MALNUTRITION BY MUAC AND/OR OEDEMA IN CHILDREN 6-59 MONTHS, BY AGE, BY DOMAIN ...... 31 TABLE 13 PREVALENCE OF UNDERWEIGHT BY WEIGHT-FOR-AGE Z-SCORES IN CHILDREN 0-59 MONTHS, BY SEX, BY STATE AND DOMAIN ...... 33 TABLE 14: PREVALENCE OF STUNTING BASED ON HEIGHT-FOR-AGE Z-SCORES IN CHILDREN 0-59 MONTHS, BY SEX, BY STATE AND DOMAIN ...... 35 TABLE 15: MEAN Z-SCORES, DESIGN EFFECTS AND EXCLUDED SUBJECTS, BY DOMAIN ...... 36 TABLE 16: MORTALITY RATES BY STATES AND DOMAIN ...... 37 TABLE 17: PERCENT OF CHILDREN 0-59 MONTHS WHO WERE EXCLUSIVELY BREASTFED, EARLY INITIATION OF BREASTFEEDING, BY SEX, AGE, STATE AND DOMAIN ...... 39 TABLE 18: EXCLUSIVE, PREDOMINANTLY, AND CONTINUED BREASTFEEDING PRACTICES BY AGE, SEX, SURVEY DOMAIN AND STATE ...... 41 TABLE 19: PERCENTAGE OF INFANTS AGE 6-8 MONTHS WHO RECEIVED SOLID, SEMI-SOLID, OR SOFT FOODS DURING THE PREVIOUS DAY, BY SEX, SURVEY DOMAIN AND STATE ...... 43 TABLE 20: PERCENTAGE OF CHILDREN AGE 6-23 MONTHS WHO RECEIVED APPROPRIATE LIQUIDS AND SOLID, SEMI- SOLID, OR SOFT FOODS THE MINIMUM NUMBER OF TIMES OR MORE DURING THE PREVIOUS DAY, BY BREASTFEEDING STATUS, BY SEX, STATE, AND DOMAIN ...... 44 TABLE 21: PERCENTAGE OF CHILDREN AGE 12-59 MONTHS VACCINATED AGAINST MEASLES, BY STATE AND DOMAIN .. 46 TABLE 22 PERCENTAGE OF CHILDREN AGE 0-59 MONTHS WITH DIARRHOEA IN THE PREVIOUS TWO WEEKS WHO RECEIVED ORAL REHYDRATION SALTS (ORS) OR ZINC, BY SEX, AGE, STATE AND DOMAIN ...... 48 TABLE 23: PERCENTAGE OF CHILDREN AGE 0-59 MONTHS WITH SYMPTOMS ARI IN THE PREVIOUS TWO WEEKS WHO RECEIVED ANTIBIOTICS, BY SEX, AGE, STATE AND DOMAIN ...... 50 TABLE 24: PERCENTAGE OF CHILDREN AGE 0-59 MONTHS WITH FEVER IN THE LAST TWO WEEKS WHO WERE TESTED FOR MALARIA USING RAPID DIAGNOSTIC TEST (RDT) AND/OR RECEIVED ANTI-MALARIAL, BY SEX, AGE, STATE AND DOMAIN ...... 52 TABLE 25: HOUSEHOLDS OWNERSHIP OF MOSQUITO NETS, BY STATE AND DOMAIN ...... 54 TABLE 26: PERCENTAGE OF CHILDREN AGE 0-59 MONTHS RECEIVING SEASONAL MALARIA CHEMOPREVENTION AND PERCENT WHO SLEPT UNDER A MOSQUITO NET THE NIGHT BEFORE THE SURVEY, BY SEX, AGE, STATE AND DOMAIN ...... 55 TABLE 27: ACUTE MALNUTRITION BY MUAC AMONG WOMEN OF REPRODUCTIVE AGE (15-49 YEARS), BY AGE, STATE AND DOMAIN ...... 57 TABLE 28: DIETARY DIVERSITY AMONG WOMEN OF REPRODUCTIVE AGE (15-49 YEARS), BY AGE, STATE AND DOMAIN ...... 59 TABLE 29: PERCENTAGE OF CHILDREN RECEIVING VITAMIN A, ANTHELMINTHIC DRUG, AND MNP IN THE PAST 6 MONTHS BY SEX, AGE AND LOCATION ...... 61 TABLE 30: PERCENTAGE OF HOUSEHOLDS RECEIVING SUPER CEREAL IN THE LAST THREE MONTHS, BY STATE AND DOMAIN ...... 62 TABLE 31: PERCENTAGE OF HOUSEHOLDS TREATING THEIR DRINKING WATER BY TREATMENT METHOD, BY STATE AND DOMAIN ...... 64 TABLE 32: PERCENTAGE OF HOUSEHOLDS WHERE A PLACE FOR HANDWASHING WAS OBSERVED AND AVAILABILITY OF SOAP AND/OR WATER, BY STATE AND DOMAIN ...... 65
List of Figures FIGURE 1: PERCENTAGE OF CHILDREN AGE 12-59 MONTHS VACCINATED AGAINST MEASLES, BY DOMAIN ...... 47 FIGURE 2: GAM TRENDS FROM 2016 TO 2019...... 67
List of Acronyms ACT Artemisinin-based Combination Therapy ANC Antenatal Care ARI Acute Respiratory Infection CI Confidence Interval CMAM Community-based Management of Acute Malnutrition EA Enumeration Areas ENA Emergency Nutrition Assessment EPI Expanded Programme on Immunisation FGON Federal Government of Nigeria FMOH Federal Ministry of Health GAM Global Acute Malnutrition HAZ Height-for-Age Z-score HH Household IPT Intermittent Preventive Treatment ITN Insecticide Treated Net IYCF Infant and Young Child Feeding KAP Knowledge, Attitudes and Practice LGA Local Governmental Area MAM Moderate Acute Malnutrition MDG Millennium Development Goals MNCHW Maternal Newborn and Child Health Week MICS Multiple Indicator Cluster Survey MUAC Mid-Upper Arm Circumference NBS National Bureau of Statistics NCHS National Center for Health Statistics NDHS Nigeria Demographic and Health Survey NIS Nutrition Information System NMCSP National Malaria Control Strategic Plan NNHS National Nutrition and Health Survey NPopC National Population Commission NSHDP National Strategic Health Development Plan NSPAN National Strategic Plan of Action for Nutrition ORS Oral Rehydration Salts ORT Oral Rehydration Therapy PHC Primary Health Care PPS Probability Proportional to Size PSU Primary Sampling Unit RDT Rapid Diagnostic Testing SAM Severe Acute Malnutrition SD Standard Deviation SMART Standardized Monitoring and Assessment of Relief and Transition SOML Saving One Million Lives SP Sulphadoxine Pyrimethamine UNHCR United Nations High Commission for Refugees
UNICEF United Nations Children's Fund USAID United States Agency for International Development VAD Vitamin A Deficiency WASH Water, Sanitation and Hygiene WAZ Weight-for-Age Z-score WB World Bank WHZ Weight for Height Z-score WFP World Food Programme WHO World Health Organization
1 Introduction The Boko Haram insurgency has caused mass population displacement throughout the North East Nigeria since 2012, when the government declared a state of emergency secondary to the conflict. According to the International Organization of Migration’s (IOM) Displacement Tracking Matrix (DTM) round XXVIII (August 2019) report, there are 2,018,513 internal displaced persons (IDPs) spread across Borno, Adamawa and Yobe states. This represents a nominal increase of 2.0% or 38,477 persons in comparison to 1,980,036 IDPs identified in ION DTM Round XXVII (May 2019). The conflict and displacement has resulted in disrupted livelihoods, food insecurity, and population overcrowding, in turn increasing the risks for malnutrition and mortality in affected populations.
With the emergency situation in North East Nigeria, and access to newly liberated areas, a series of repeated surveys were organized with the primary objective to provide representative estimates for prevalence of acute malnutrition among children under five years, the nutritional status of women, prevalence of common child health morbidities, access to health services and health status among children, status of infant feeding, and mortality rates to inform the ongoing emergency response.
The round of repeated surveys known collectively as the Nutrition and Food Security Surveillance (NFSS) were carried out as follows: Round 1 October-November 2016 Round 2 February-March 2017 Round 3 July-August 2017 Round 4 November-December 2017 Round 5 April-May 2018 Round 6 October 20183 Round 7 May-June 2019
The results of the NFSS are only representative of accessible areas in the three states at the time of their undertaking. The situation may be worse in inaccessible and newly accessible LGAs. The July 2018 Bama SMART survey showed a higher GAM in areas where newly arrived children 6 to 59 months were living (37.5%) compared to 7.8% for children 6 to 59 months living in the camp for a longer period. The new arrival screening data is also suggestive of a critical nutrition situation in inaccessible areas.
Currently, there is limited nutrition data available at the LGA level, which is the level of program implementation. The only available LGA results are SMART nutrition surveys conducted by Nutrition Sector partners within their operational areas. Recently, a sentinel surveillance system has been initiated in 23 accessible LGAs of Borno. The data is collected on quarterly basis from 75,591 households within the accessible wards. A dashboard showing the sentinel surveillance findings will be functional by April 2020.
1.1 Justification
In early 2016, the Federal Government of Nigeria declared the Boko Haram conflict in Northeastern Nigeria as a state of emergency. In May 2017, the state of emergency area was extended to include Adamawa, Borno and Yobe states. The conflict has continued and impacted the population’s freedom of movement, livelihoods, markets, and access to humanitarian assistance in Northeast Nigeria, as well as the neighbouring border countries of Niger, Chad,
3 UNICEF/WFP Joint Approach for Nutrition and Food Security Assessment (JANFSA) in Borno, Yobe and Adamawa states, October 2018.
and Cameroon.
In Nigeria, the humanitarian response is mainly focused in Borno, Yobe and Adamawa states. Information on the nutrition situation since April 2016 remains limited. Small-scale SMART nutrition surveys and larger Emergency Food Security Assessments (EFSA) surveys have been carried out. While these surveys provide the most reliable information on the current nutrition situation in the Northeast, there were too few to provide a detailed analysis of the nutrition situation across the whole of the three states. Presently, the NFSS remains the most comprehensive and regular source of the nutrition situation.
In 2016, UNICEF and Nutrition Sector partners established the NFSS, which intends to contribute to existing nutrition information from: i. repeated cross-sectional surveys on standardized groupings of LGAs; ii. exhaustive MUAC screening of children 6-59 months coming from newly accessible areas, iii. flexible integrated and timely (FIT) sentinel surveillance in Borno state and iv. real-time CMAM programme and stocks data to ensure that all children with acute malnutrition have access to appropriate management.
The findings in this report represent Round 8 of a series of planned, repeated cross-sectional surveys.
1.2 Objectives The overall goal of this survey is to establish the extent and the severity of acute malnutrition and determine the contributing factors of malnutrition in Northeast Nigeria to inform the ongoing emergency response.
The specific objectives of the survey were as follows: 1. Determine all-cause mortality among the general population (crude death rate) and among children 6 to 59 months (under-five death rate); 2. Determine the prevalence of acute malnutrition among children 0 to 59 months of age using WHZ and bilateral oedema and among children 6 to 59 months using Middle Upper Arm Circumference (MUAC); 3. Determine the prevalence of chronic malnutrition and underweight among children 0 to 59 months of age; 4. Determine the prevalence of acute malnutrition among women 15 to 49 years of age using MUAC; 5. Assess the prevalence of diarrhoea and use of ORS and zinc among children under-five years in the two weeks preceding the survey; 6. Assess the prevalence of fever and use of antibiotics among children under-five years in the two weeks preceding the survey; 7. Estimate coverage of deworming among children 12 to 59 months of age within the last six months; 8. Determine the coverage of measles immunization among children 12 to 23 months of age; 9. Determine the proportion of children under five with Acute Respiratory Infection (ARI) symptoms and proportion of children with fever who received treatment; 10. Determine the ownership and universal access of mosquito nets, and utilization of mosquito nets by children 0 to 59 months of age; 11. Assess IYCF practices among children 0 to 23 months of age; 12. Assess dietary diversity among women 15 to 49 years of age; 13. Estimate household access to safe water and sanitation facilities.
2. Methodology
This survey, part of the Nigeria Nutrition and Food Security Surveillance System, was designed as cross-sectional household surveys using a two-stage cluster sampling design consistent with the SMART methodology. These methods produce results representative of a groupings of Local Governments Areas (LGAs) as domains. Domains were created considering livelihood zones, geographic proximity, and socio-cultural homogeneity. (Table 1)
The survey area consists of 65 LGAs within Adamawa, Borno and Yobe states. The 65 LGAs were divided into 10 domains: two in Adamawa, three in Yobe and five in Borno. LGAs were grouped as follows:
Table 1: Survey Domains
Domain LGAs Included Demsa, Girie, Guyuk, Lamurde, Numan, Shelleng, Yoa North, 1 Southern Adamawa Ganye, Jada, Mayo-Belwa, Teungo, Fufore, Yola South Gombi, Hong, Madagali, Maiha, Michika, Mubi North, Mubi 2 Northern Adamawa South, Song 3 Northern Borno *Abadam, Mobbar, *Guzamala, Kukawa, Nganzai 4 Southern Borno Askira/Uba, Bayo, Biu, Chibok, Hawul, Kwaya Kusar, Shani 5 East Borno Bama, Dikwa, Gwoza, Kala/Balge, Ngala Damboa, Gubio, Kaga, Konduga, Mafa, Magumeri, *Marte, 6 Central Borno Monguno, 7 MCC/Jere Maiduguri, Jere 8 Central Yobe Bade, Borsari, Geidam, Jakusko Damaturu, Fika, Fune, Gujba, Gulani, Nangere, Potiskum, 9 Southern Yobe Tarmuwa 10 Northern Yobe Karasuwa, Machina, Nguru, Yunusari, Yusufari *LGAs stroked out were inaccessible and were excluded a priori
2.1 First Stage Sampling The sample was selected using a two-stage cluster design. The clusters for each domain were drawn independently using probability proportional to size (PPS) method. For Yobe and Adamawa, clusters were selected from the updated national master sample frame with support from the National Population Commission (NPopC). Estimated populations for each EA were 2019 populations projected from the 2006 census as calculated by NPopC. No EAs were excluded a priori.
Given recent large-scale population movement, an updated sampling frame was built for Borno. Population estimates from the January 2019 polio campaign microplanning, as well as Village Tracking System (VTS) population estimates by settlement were used for settlements. Settlements that had less than 20 households (HHs) were sampled and the remaining HHs supplemented from nearest villages (within a 5 kilometre radius of the selected village). Population estimates for IDP camps were from the latest IOM DTM report available at the time of the survey (DTM Round XXVIII, May 2019).
Several wards were excluded a priori as they were determined to be inaccessible given the ongoing conflict. Accessibility was determined by state level security officers and informed by access during the November 2019 polio campaign. Four of the LGAs (Abadam, Guzamala, Kukawa & Marte) in two domains in Borno (North and Central) were also determined to be inaccessible. Estimates of accessible populations included persons in areas that were only
accessible with a military escort.
In Adamawa State, Gombi and Girei LGAs were erroneously assigned to the wrong sampling domain, i.e. switched from Northern Adamawa to Southern Adamawa, and vice versa. However, this did not affect the required sample size even though Southern Adamawa was over sampled. This only affected the precision of the results rather than the point estimates. Of the originally selected clusters, 12 were either inaccessible or abandoned including two clusters in Southern Adamawa (inaccessible due to flood), six clusters in MMC/Jere (1 abandoned, 5 inaccessible), five clusters in Central Borno (inaccessible), one cluster in Central Yobe (1 abandoned), two clusters in Southern Yobe (inaccessible), and one cluster in Northern Yobe (inaccessible).
2.2 Second Stage Sampling Within selected clusters, households were selected using systematic random selection. With the support of a community leader, teams mapped and listed all households within the cluster. The following definition was used to identify a household4:
“A person or a group of persons, related or unrelated, who live together and share a common source of food and livelihood, and recognize one person as a head”.
In many cases, compounds contained multiple households. Abandoned households were not listed. Household listing was performed using a paper form. Team leaders entered the total number of households in the cluster into the tablet. Sampling interval was automatically calculated on the tablet and displayed along with the random start number.
Households that were absent at the time of the visit were re-visited at least three times before being marked absent. Households in which one or more children 0-59 months of age or women 15-49 years of age were absent at the time of the visit were also re-visited. Households that refused were not replaced.
All eligible children and women were measured. The head of household was the respondent for the household enumeration, mortality questionnaire, and other household level questions (e.g., water and sanitation). For questions about children, the primary caregiver served as the respondent. One women of reproductive age (15-49 years) was randomly selected using the tablet for questions on women’s dietary diversity.
2.3 Sample Size Calculation The sample sizes for anthropometry and mortality were calculated using the ENA for SMART application. Sample size was calculated to ensure accurate GAM prevalence in children 6-59 months as well as crude mortality rate.
Details on the estimated values and source for each parameter are provided in Tables 2.2 and 2.3 The sample size for anthropometry was calculated using GAM prevalence in children aged 6-59 months using an estimated prevalence for each domain from NFSS Round 7 data. The upper confidence interval of the state level estimate was used as a conservative estimate.
The sample size for mortality was calculated with an estimated crude mortality rate (CDR) based on that observed in NFSS Round 7. Estimates used were average deaths per 10,000 population per day, rounded up to the nearest 0.05 deaths. The period of recall covered
4 World Health Organization (WHO). Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. 1995. Available at: http://www.who.int/childgrowth/publications/physical_status/en/
approximately four months, a period of 165 days starting from October 1st, 2018 (Independence Day).
The inputs for the sample size calculations for anthropometry and mortality are included in the table 2.
Table 2 Anthropometry and Mortality Sample Size Inputs Anthropometry sample size inputs Parameters SA NA NB SB EB CB M&J CY SY NY Source Upper confidence interval of estimate Estimated GAM prevalence 10 9 14 13.2 19 14 17.4 17.4 17.7 15.9 from NFSS Round 7 (May 2019) Recommended precision for prevalence Precision 3.5 3 3.5 3.5 4 3.5 4 4 4 4 <10%, 10-15% & 15-20% Conservative estimate from NFSS Round Design effect for WHZ 1.50 1.71 1.50 1.50 1.68 1.50 1.84 1.92 1.94 1.50 7 (May 2019) Number of children to be included 461 651 617 587 676 617 691 721 739 524 Average number of persons per HH 4.9 5.0 4.4 5.5 4.7 4.5 5.5 5.6 5.5 4.6 Estimate from NFSS Round 7 (May 2019) Percent of under five children in total Estimate from NFSS Round 7 (May 2019) 18.1 17 18.3 19.6 18.4 20.8 17.4 20.3 20.9 20.7 population Estimate from emergency surveillance Percent of non-response households 0.4 0.6 0.5 0.3 0.2 0 0.2 0.8 0.8 1.5 (May 2019) Number of HHs to be included 580 856 855 607 870 732 804 711 720 621
Mortality sample size Parameters SA NA NB SB EB CB M&J CY SY NY Source Domain level estimate from NFSS Round Estimated CDR prevalence 0.27 0.07 0.70 0.26 0.32 0.27 0.30 0.34 0.53 0.39 7 – rounded up Recommended precision for CDR Precision 0.3 0.2 0.35 0.3 0.3 0.3 0.3 0.3 0.3 0.3 <1/10,000/day Observed DEFF from NFSS Round 7 (May Design effect for CDR 1.75 1.5 1.5 1.24 2.82 1.31 2.26 1.87 1.5 2.17 2019) – rounded up From 4th June 2019 (Eid el Fitr Karamar Recall period in days 118 118 118 118 118 118 118 118 118 118 Sallah) Number of persons to be included, 3,33 1,861 930 3,038 1,536 3,554 1,393 2,670 2,504 3,131 Number of HHs to interview 3 Average number of persons per HH 4.9 5 4.4 5.5 4.7 4.5 5.5 5.6 5.5 4.6 Estimate from NFSS Round 7 (May 2019) Percent of non-response HHs 0.4 0.6 16.5 0.3 0.2 0 0.2 0.8 0.8 1.5 Estimate from NFSS Round 7 (May 2019) Number of HHs to be included 381 187 694 280 758 310 486 451 574 736
Using the parameters calculated as shown in Table 2 and to have a minimum of 30 clusters per domain, the number of households per clusters for each domain for both mortality and anthropometry are presented in Table 3 below:
Table 3 Number of Households per Cluster in each Domain
Required Anthropometry Mortality # State Domain # HH/Cluste Childre Tota Populatio Total Cluster r n l HH Cluster n HH s Adamawa Southern Adamawa 19 461 580 31 1861 381 21 Adamawa Northern Adamawa 23 651 856 38 930 187 9 Borno Northern Borno 24 617 855 36 3038 694 29 Borno Southern Borno 19 587 607 32 1536 280 15 Borno East Borno 23 676 870 38 3554 758 33 Borno Central Borno 20 617 732 37 1393 310 16 Borno MMC & Jere 23 691 804 35 2670 486 22 Yobe Central Yobe 20 721 711 36 2504 451 23 Yobe Southern Yobe 20 739 720 36 3131 574 29 Yobe Northern Yobe 20 524 621 32 3333 736 37
The highest sample size for anthropometry (using GAM rate) or for mortality (using CMR) was used for the survey to achieve the highest possible precision. Taking the time, the team needs for household listing, household selection, interview, and travel to the EAs into account, it was determined it was possible for each team to complete 24 households or less per cluster per day, which resulted in the following clusters per domain (see the table 4 below).
Table 4 Number of Clusters and Households Sampled by Domain
Households/ Domain Clusters/Domain Household/ Domain Cluster Southern Adamawa 589 31 19 Northern Adamawa 874 38 23 Northern Borno 864 36 24 Southern Borno 608 32 19 Eastern Borno 874 38 23 Central Borno 740 37 20 MMC & Jere 805 35 23 Central Yobe 720 36 20 Southern Yobe 720 36 20 Northern Yobe 740 37 20 Total 356
By domain, data collection was concluded between September 15 and October 22 resulting in recall periods of 193 days in Southern Adamawa, 194 days in Northern Adamawa, 199 days in Southern Borno, 204 days in Central Borno, 207 days in MMC/Jere, 208 in East Borno, 166 days in Central Yobe, 160 days in Southern Yobe, and 168 days recall in Northern Yobe.
2.4 Case Definitions and Inclusion Criteria
A full list of indicators as well as their case definitions and age inclusion are provided as Annex 3. The following is a summary:
- Child Nutrition Acute malnutrition among children age 0-59 months (by weight-for-height and/or oedema); acute malnutrition among children age 6-59 months (by MUAC and/or oedema); underweight, chronic malnutrition among children age 0-59 months.
- Mortality Crude death rate and under-five death rate.
- Child health Measles vaccination coverage among children; proportion of children under five with fever, Acute Respiratory Infection (ARI) and diarrhoea who received an Artemisinin Combined Therapy (ACT), antibiotics, and ORS and zinc respectively; household mosquito net ownership, universal coverage of mosquito net and utilization of mosquito net by under-five children and intermittent preventive treatment in children.
- Public Health Campaigns Deworming among children 12-59 months; coverage of Super Cereal distributions.
- Maternal Nutrition Acute malnutrition among women of reproductive age 15-49 years; dietary diversity among women.
- Water, Sanitation and Hygiene Household water treatment, Presence of water and soap at household handwashing station.
- Food Security Dietary diversity for Women; Household dietary diversity, household food consumption score, reduced coping strategy index, livelihood coping strategy index, income/livelihood source and food assistance
- IYCF Exclusive breastfeeding, early initiation of breastfeeding, complementary feeding, breastfeeding up to 2 years, acceptable minimum meal frequency, children 6-23 months dietary diversity
Age was recorded as exact date of birth if a birth certificate or vaccine card was available. In all other cases, age was estimated in months using a local events calendar. The calendar of local events used during field work is included as Annex 4.
Anthropometry was measured according to the WHO recommendations5. Selected children were weighed without clothes using SECA scales (100g precision). Children were measured on a
5 World Health Organization (WHO). Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. 1995. Available at: http://www.who.int/childgrowth/publications/physical_status/en/
measuring board (precision of 0.1cm). Children less than 87 cm were measured lying down, while those greater than or equal to 87 cm were measured standing up. MUAC was measured using standard UNICEF tapes at the midpoint of the left upper arm of the children (precision of 0.1cm). Bilateral pitting oedema was assessed by the application of normal thumb pressure for at least 3 seconds to both feet.
All the team members were given referral forms and all children found to be acutely malnourished were referred to the nearest treatment programme.
2.5 Training and Supervision
Survey training was organized for 10-13 September 2019 in Maiduguri. The training included three days of theoretical training, a standardization test, and a field test. Training was facilitated by experts from UNICEF and National Bureau of Statistics (NBS), with remote support from the Center for Disease Control and Prevention (CDC).
The training included the following:
- An overview of the survey and its objectives, as well as an introduction to SMART
methods
- Interviewing and general communication skills
- Segmentation and systematic random selection of households
- Consent forms and identification of individuals to measure or interview
- Classroom and practical training on how to complete the questionnaires
- Estimation of age in months and validation using the calendar of local events
- Classroom and practical training on proper anthropometric measurements technique
- The standardization test to assess accuracy and precision of height, weight and MUAC
- The identification and referral of cases of severe acute malnutrition
- Household enumeration, data entry, and transmission of questionnaires using tablets
A pilot test was organized in Maiduguri prior to data collection, in order to assess the tools and evaluate the actual data collection process before deployment of the teams.
Survey staff were selected by the NBS. All selected individuals were current residents of Borno, Yobe, or Adamawa states. Selected individuals were literate in at least English and Hausa. A total of 47 individuals were selected of which 30 were retained as enumerators. Selection was based on performance during the standardization test, field test, and a written examination. The 30 individuals made up fifteen teams, each composed of a measurer and an assistant.
Teams were supervised in the field by three field coordinators, senior staff from the NBS, as well as nine supervisors selected based on performance during the training. Supervisors oversaw no more than two teams. Supervisors were responsible for the daily organisation and supervision of teams' work. The coordinators provided support to supervisors based on need, coordinated
security and movement plans, and targeted additional supervision based on feedback received daily from survey manager.
2.6 Data Analysis Data was entered directly into 3G enabled tablets (Galaxy tab 4 and tab A 7.0) using a questionnaire built in Open Data Kit (opendatakit.org) and transmitted to an ONA online server (ona.io) as soon as connected to a network. The ENA application (version July 9, 2015) was used for analysis of anthropometry and mortality data. Stata (version 14.2) was used for transformation of the data from the ONA output to ENA as well as for analysis of additional indicators.
Tablets were programmed with internal quality checks during field work including a prompt for a re-measurement of potential errors in anthropometric measurements. Enumerators were prompted to re-measure all anthropometric indicators if measurements were outside of the WHO flag criteria: HAZ below –6 or above +6, WAZ below –6 or above +5, WHZ below –5 or above +5, or BMIZ below –5 or above +5). An additional 5% of children were randomly selected for re- measurement. Second measurements were used in the analysis when taken.
For analysis, Z-scores for each child were calculated based on the WHO 2006 growth references population. Extreme values were excluded during analysis based on SMART flag criteria. SMART flags exclude anthropometric indices with -3 to 3 for WHZ, -3 to 3 for HAZ, -3 to 3 for WAZ, from observed mean. The number of values excluded for each indicator are presented in Table 3.2.7.
3. Results
3.1 Final Sample and Data Quality Data collection took place from October 17 to November 20, 2019 in Adamawa, Borno, and Yobe states. Table 5 provides details on the number of clusters completed and sample size for households, children (0-59 months) and women (15-49 years of age) by domain. For children, both the number surveyed, and the number measured are provided as not all children’s caregivers interviewed consented to measurement.
By domain, the number of households surveyed ranged from 540 to 589. Households that were absent upon re-visit or refused were not replaced. Response rates ranged from 96.4% (Northern Adamawa) to 98.4% (Central Yobe). The number of children aged 0-59 months surveyed ranged from 491 to 594. By state, average household size ranged from 5.2-5.6. Children represented 16.6 to 20.2% of household members by state.
Table 5 Final Sample of Households, Women and Children, By Domain
Total number of Average Number children under five percent of of Clusters Number Averag years of age HH women Surveye of HHs e HH members 15-49 d Surveyed Size Surveyed Measured age 0-59 years of months age State Adamawa 67 1,380 5.0 1,166 1,149 17.2 1,519 Borno 172 3,663 4.8 3,201 3,140 18.7 3,623 Yobe 105 2,065 5.4 2,054 2,008 19.0 2,177 Domain Southern Adamawa 36 697 5.0 598 592 17.8 725 Northern Adamawa 31 683 5.1 568 557 16.6 794 Northern Borno 32 702 3.9 494 481 18.7 572 Southern Borno 32 606 5.5 592 588 17.9 717 East Borno 38 869 4.6 791 775 19.9 776 Central Borno 35 687 4.6 615 601 20.2 631 MCC & Jere 35 799 5.4 709 694 16.9 927 Central Yobe 35 689 5.5 685 666 18.7 764 Southern Yobe 34 674 5.6 691 676 18.9 723 Northern Yobe 36 701 5.1 678 666 19.4 690
Additional information on the sample of children measured for nutrition indicators is presented in Tables 5 For each domain, the table presents the age and sex distribution of children 6-59 months of age. Note that some anthropometry indicators were measured among children under six months of age (not shown in Table 5). The sex ratio was not significant (p<0.05) for all domains suggesting the samples were balanced in terms of sex. By domain, the ratio of boys to girls ranged from 0.92-1.29 (Table 6). The ratio of children age 6-23 months to children 30-59 months ranged from 0.72-1.01. This ratio is expected to be 0.85, suggesting the samples had a higher proportion of younger children than expected in Eastern Borno and Central Yobe. The high proportion of younger children may reflect a true deviation of the age structure of the population, possibly due to ongoing displacement in the area or sampling bias.
Table 6 Distribution of Age and Sex of Sample, by Domain Boys Girls Total Ratio Age groups (months) no. (%) no. (%) no. (%) Boy: Girl Southern Adamawa 6-17 49 (41.5) 69 (58.5) 118 (22.1) 0.7 18-29 70 (54.7) 58 (45.3) 128 (24.0) 1.2 30-41 64 (54.2) 54 (45.8) 118 (22.1) 1.2 42-53 60(52.6) 54 (47.4) 114 (21.3) 1.1 54-59 37(66.1) 19 (33.9) 56 (10.5) 1.9 Total 280 (52.4) 254 (47.6) 534 (100) 1.1 Northern Adamawa 6-17 (53) 51.0 (53) 51.0 (104) 20.1 1.0 18-29 (73) 60.8 (73) 60.8 (1200 23.2 1.6 30-41 (74) 52.5 (74) 52.5 (141) 27.2 1.1 42-53 (64) 58.2 (64) 58.2 (110) 21.2 1.4 54-59 (28) 65.1 (28) 65.1 (43) 8.3 1.9 Total (292) 56.4 (292) 56.4 (518) 100.0 1.3 Northern Borno 6-17 (60) 55.0 (60) 55.0 (109) 24.9 1.2 18-29 (48) 47.1 (48) 47.1 (102) 23.3 0.9 30-41 (57) 55.3 (57) 55.3 (103) 23.6 1.2 42-53 (54) 52.9 (54) 52.9 (102) 23.3 1.1 54-59 (12) 57.1 (12) 57.1 (21) 4.8 1.3 Total (231) 52.9 (231) 52.9 (437) 100.0 1.1 Southern Borno 6-17 (55) 50.9 (53) 49.1 (108) 20.3 1.0 18-29 (57) 49.6 (580 50.4 (115) 21.6 1.0 30-41 (61) 42.7 (82) 57.3 (143) 26.9 0.7 42-53 (61) 57.0 (46) 43.0 (107) 20.1 1.3 54-59 (29) 49.2 (30) 50.8 (59) 11.1 1.0 Total (263) 49.4 (269) 50.6 (532) 100.0 1.0 Eastern Borno 6-17 (94) 52.8 (84) 47.2 (178) 25.1 1.1 18-29 (84) 47.7 (92) 52.3 (176) 24.8 0.9 30-41 (62) 39.2 (96) 60.8 (158) 22.3 0.6 42-53 (61) 46.9 (69) 53.1 (1300 18.3 0.9 54-59 (39) 58.2 (28) 41.8 (67) 9.4 1.4 Total (340) 48.0 (369) 52.0 (709) 100.0 0.9 Central Borno 6-17 (84) 60.0 (56) 40.0 (140) 25.5 1.5 18-29 (64) 50.8 (62) 49.2 (126) 23.0 1.0 30-41 (66) 48.9 (69) 51.1 (135) 24.6 1.0 42-53 (56) 52.8 (50) 47.2 (106) 19.3 1.1 54-59 (25) 61.0 (16) 39.0 (41) 7.5 1.6 Total (295) 53.8 (253) 46.2 (548) 100.0 1.2 MMC / Jere 6-17 (760 59.4 (52) 40.6 (128) 19.8 1.5 18-29 (81) 49.4 (83) 50.6 (164) 25.4 1.0
30-41 (72) 47.7 (79) 52.3 (151) 23.4 0.9 42-53 (74) 49.7 (75) 50.3 (149) 23.1 1.0 54-59 (26) 49.1 (27) 50.9 (53) 8.2 1.0 Total (329) 51.0 (316) 49.0 (645) 100.0 1.0 Northern Yobe 6-17 (64) 43.5 (83) 56.5 (147) 24.3 0.8 18-29 (690 45.4 (83) 54.6 (152) 25.1 0.8 30-41 (77) 50.3 (76) 49.7 (153) 25.2 1.0 42-53 (53) 49.5 (54) 50.5 (107) 17.7 1.0 54-59 (27) 57.4 (20) 42.6 (47) 7.8 1.4 Total (290) 47.9 (316) 52.1 (606) 100.0 0.9 Central Yobe 6-17 (70) 43.2 (92) 56.8 (162) 26.1 0.8 18-29 (80) 53.3 (70) 46.7 (150) 24.2 1.1 30-41 (60) 45.8 (71) 54.2 (131) 21.1 0.8 42-53 (75) 55.1 (61) 44.9 (136) 21.9 1.2 54-59 (17) 41.5 (24) 58.5 (41) 6.6 0.7 Total (302) 48.7 (318) 51.3 (620) 100.0 0.9 Southern Yobe 6-17 (64) 46.0 (75) 54.0 (139) 22.3 0.9 18-29 (78) 47.6 (86) 52.4 (164) 26.4 0.9 30-41 (77) 53.8 (66) 46.2 (143) 23.0 1.2 42-53 (76) 56.3 (59) 43.7 (135) 21.7 1.3 54-59 (23) 56.1 (18) 43.9 (41) 6.6 1.3 Total (318) 51.1 (304) 48.9 (622) 100.0 1.0
Table 7 presents a summary of the data quality. Overall, data quality was high. All domains had less than 2.5% of values excluded as outliers (SMART flags). Standard deviation for WHZ for all surveys were within an acceptable range (0.8-1.2). Tests of skewness, kurtosis and Poisson distribution suggests that the WHZ distributions were normal. Statistical tests for rounding, referred to as digit preference, suggest that there was no notable preference for any digit in weight measurements (as if the case when digital scales are used). For height and MUAC, digit preference scores were all good to excellent. All domains had values of 9 or less (excellent or good). Overall, data quality was excellent in all 10 domains according to SMART classifications. Results by indicator are color coded in Table 3.1.3 on a scale from excellent (dark green) to problematic (orange). Full plausibility reports are provided in Annex 6.
Table 7 Summary of Child Anthropometry Data Quality
In addition to the tests presented above, the proportion of children with complete date of birth is an important measure of the quality of age data. For children aged 0-59 months, age was recorded as an exact date of birth if recorded on a birth certificate or vaccination card available at the time of the visit. When unavailable, age in months was estimated using a local events calendar. Table 8 presents the proportion of children for which exact date of birth was available by domain and by team. The proportion of children with documented date of birth varied considerably by domain (range: 6.2 – 46.2%) and by team (range: 2.2- 74.6). This is likely affected by regional differences in the availability of age documentation. Where vital registration and age documentation are poor, measures that include age (such as stunting and underweight) may be affected.
Table 8 Proportion of Children with Complete Data of Birth, Age Reported in Months or Missing, by Domain and Team Age reported in Complete date of Missing (%) months (%) birth (%) Domain Southern Adamawa 48.5 51.5 0 Northern Adamawa 48.3 51.5 0.2 Northern Borno 87.8 12.0 0.2 Southern Borno 56.6 43.4 0 East Borno 69.6 30.0 0.4 Central Borno 79.2 20.5 0.3 MCC & Jere 61.5 38.5 0 Central Yobe 74.6 25.3 0.1 Southern Yobe 76.1 23.6 0.3 Northern Yobe 85.1 14.8 0.1 Team 1 47.2 52.6 0.2 2 72.0 27.5 0.5 3 84.2 15.1 0.7 4 68.3 31.1 0.6 5 62.9 37.1 0.0 6 65.6 34.4 0.0 7 90.5 9.3 0.2 8 67.3 32.7 0.0 9 38.5 61.5 0.0 10 85.5 14.5 0.0 11 83.2 16.8 0.0 12 51.9 48.1 0.0 13 97.3 2.5 0.2 14 53.3 46.7 0.0
3.2 Anthropometric results:
Anthropometric measurements in children were converted into Z-Scores using the 2006 WHO Child Growth Standards.6 Three child malnutrition indicators are presented: acute malnutrition, chronic malnutrition and underweight. Acute malnutrition is most responsive to changes in diet
6 World Health Organization (WHO). 2006. Child Growth Standards. Available at: http://www.who.int/childgrowth/en/
and recent shocks including disease and is the most dangerous form of malnutrition in terms of mortality risk; as such it is the primary indicator of interest in the context of an emergency.
3.2.1 Acute Malnutrition (WHZ and/or Bilateral Oedema)
Tables 9 present prevalence of acute malnutrition by state and domain among children 6-59 months of age based on weight-for-height z-scores and/or oedema, disaggregated by sex. Age disaggregation by domain for children 6-59 months of age is presented in Table 10.
Prevalence of GAM was high in Yobe (11.5%), where the prevalence of SAM was 1.5%. By sampling domain, prevalence of GAM was highest in Central Yobe (13.8%), followed by Southern Yobe (11.1%). Prevalence was higher among boys than girls in all domains with the exception of MMC & Jere and Central Borno. Disaggregation by age showed that prevalence of GAM was highest among children in the younger age cohort of 6-17 months.
Table 9 Prevalence of Acute Malnutrition by Weight-For-Height Z-Scores (and/or Oedema) And by Sex, Children 0-59 Months, By State and Domain Prevalence of moderate acute Prevalence of severe acute Number of Prevalence of global acute malnutrition malnutrition malnutrition children 0- (<, 2 z, score and/or oedema) (<, 2 z, score and >=, 3 z, score, no oedema) (<, 3 z, score and/or oedema) 59 months All Boys Girls All Boys Girls All Boys Girls
State Adamawa (83) 7.2 (54) 8.7 (29) 5.4 (76) 6.6 (50) 8.1 (26) 4.8 (7) 0.6 (4) 0.6 (3) 0.6 1149 [5.5-9.4] [6.3-12.0] [3.7-7.9] [5.1-8.6] [5.9-11.1] [3.3-7.1] [0.3-1.2] [0.2-1.7] [0.2-1.7] Borno (262) 8.1 (150) 8.5 (112) 7.7 (236) 7.2 (134) 7.5 (102) 6.9 (26) 0.9 (16) 1.0 (10) 0.8 3140 [7.0-9.4] [7.2-10.1] [6.3-9.4] [6.2-8.4] [6.2-9.0] [5.6-8.5] [0.6-1.4] [0.6-1.8] [0.4-1.5] Yobe (235) 11.5 (142) 13.8 (93) 9.1 (204) 10.0 (126) 12.4 (78) 7.6 (31) 1.5 (16) 1.4 (15) 1.5 2008 [9.6-13.7] [11.0-17.2] [7.3-11.5] [8.4-12.0] [9.9-15.4] [6.0-9.6] [1.0-2.2] [0.8-2.6] [0.9-2.7] Domain S. Adamawa (43) 7.3 (25) 8.1 (18) 6.3 (39) 6.6 (23) 7.5 (16) 5.6 (4) 0.7 (2) 0.6 (2) 0.7 592 [5.1-10.3] [5.4-12.0] [4.0-10.0] [4.7- 9.2] [5.1-10.9] [3.5- 9.0] [0.3- 1.7] [0.2- 2.5] 0.2- 2.8 N. Adamawa (41) 7.4 (29) 9.2 (12) 5.0 (38) 6.8 (27) 8.5 (11) 4.6 (3) 0.5 (2) 0.6 (1) 0.4 557 [4.9-10.9] [5.5-14.8] [2.5- 9.5] [4.6-10.1] [5.2-13.7] [2.3- 8.8] [0.2- 1.7] [0.2- 2.5] [0.1- 3.1] Northern Borno (45) 9.4 (26) 10.2 (19) 8.4 (38) 7.9 (22) 8.7 (16) 7.0 (7) 1.5 (4) 1.6 (3) 1.3 481 [6.7-12.9] [6.7-15.4] [5.2-13.2] [5.7-10.9] [5.5-13.4] [4.4-11.0] [0.6- 3.3] [0.6- 4.1] [0.4- 4.1] Southern Borno (36) 6.1 (24) 8.2 (12) 4.1 (34) 5.8 (22) 7.5 (12) 4.1 (2) 0.3 (2) 0.7 (0) 0.0 588 [4.1- 8.9] [5.1-12.8] [2.0- 8.1] [3.9- 8.4] [4.5-12.2] [2.0- 8.1] [0.1- 1.4] [0.2- 2.9] {0.0- 0.0] East Borno (78) 10.1 (47) 12.7 (31) 7.7 (74) 9.5 (44) 11.9 (30) 7.4 (4) 0.5 (3) 0.8 (1) 0.2 775 [8.0-12.5] [9.6-16.6] [5.6-10.5] [7.5-12.1] [8.9-15.7] [5.3-10.2] [0.2- 1.4] [0.3- 2.5] [0.0- 1.9] Central Borno (59) 9.8 (30) 9.3 (29) 10.4 (52) 8.7 (27) 8.4 (25) 9.0 (7) 1.2 (3) 0.9 (4) 1.4 601 [7.4-13.0] [6.4-13.3] [7.1-14.9] [6.4-11.6] [5.8-12.0] [5.8-13.5] [0.6- 2.3] [0.3- 2.9] [0.6- 3.5] MMC & Jere (48) 6.9 (24) 6.8 (24) 7.0 (42) 6.1 (20) 5.7 (22) 6.5 (6) 0.9 (4) 1.1 (2) 0.6 694 [5.1- 9.3] [4.8- 9.5] [4.8-10.2] [4.4- 8.3] [3.9- 8.3] [4.4- 9.4] [0.4- 1.9] [0.4- 3.0] [0.1- 2.4] Central Yobe (92) 13.8 (57) 17.2 (35) 10.4 (77) 11.6 (47) 14.2 (30) 9.0 (15) 2.3 (10) 3.0 (5) 1.5 666 [10.7-17.7] [13.4-21.8] [13.4-21.8] [9.0-14.7] [10.8-18.4] [5.8-13.7] [1.3- 4.0] [1.5- 5.9] [0.4- 5.4] Southern Yobe (75) 11.1 (46) 13.1 (29) 9.0 (66) 9.8 (42) 11.9 (24) 7.4 (9) 1.3 (4) 1.1 (5) 1.5 676 [8.2-14.9] [8.7-19.1] [6.2-12.7] [7.2-13.1] [8.1-17.2] [5.1-10.7] [0.7- 2.7] [0.4- 3.1] [0.7- 3.6] Northern Yobe (72) 10.8 (40) 12.5 (32) 9.2 (63) 9.5 (36) 11.3 (27) 7.8 (9) 1.4 (4) 1.3 (5) 1.4 666 [8.3-13.9] [9.4-16.6] [6.4-13.0] [7.2-12.4] [8.2-15.3] [5.3-11.2] [0.7- 2.6] [0.4- 4.0] [0.6- 3.3] The prevalence of oedema is 0.0 % in all domains.
Table 10 Prevalence of Acute Malnutrition by Age, By Weight-For-Height Z-Scores and/or Oedema, Children 6-59 Months, By Domain Severe acute Moderate acute Total Normal Age Groups (months) malnutrition malnutrition Oedema no. (>-2 z score) (<-3 z-score) (>-3 and <-2 z-score) No. (%) No. (%) No. (%) No. (%) Southern Adamawa 6-17 118 (2) 1.7 (11) 9.3 (105) 89.0 0 (0) 18-29 128 (1) 0.8 (12) 9.4 (115) 89.8 0 (0) 30-41 117 (0) 0.0 (5) 4.3 (112) 95.7 0 (0) 42-53 114 (0) 0.0 (3) 2.6 (111) 97.4 0 (0) 54-59 56 (1) 1.8 (20 3.6 (53) 94.6 0 (0) Total 533 (4) 0.8 (33) 6.2 (496) 93.1 0 (0) Northern Adamawa 6-17 99 (1) 1.0 (9) 9.1 (89) 9.9 0 (0) 18-29 120 (0) 0.0 (11) 9.2 (109) 90.8 0 (0) 30-41 139 (0) 0.0 (12) 8.6 (127) 91.4 0 (0) 42-53 110 (1) 0.9 (2) 1.8 (107) 97.3 0 (0) 54-59 43 (0) 0.0 (1) 2.3 (42) 97.7 0 (0) Total 511 (2) 0.4 (35) 6.8 (474) 92.8 0 (0) Northern Borno 6-17 105 (4) 3.8 (11) 10.5 (90) 85.7 0 (0) 18-29 99 (0) 0.0 (5) 5.1 (94) 94.9 0 (0) 30-41 102 (1) 1.0 (5) 4.9 (96) 94.1 0 (0) 42-53 102 (0) 0.0 (6) 5.9 (96) 94.1 0 (0) 54-59 20 (0) 0.0 (3) 15.0 (17) 85.0 0 (0) Total 428 (5) 1.2 (30) 7.0 (393) 91.8 0 (0) Southern Borno 6-17 108 (0) 0.0 (11) 10.2 (97) 89.8 0 (0) 18-29 114 (1) 0.9 (8) 7.0 (105) 92.1 0 (0) 30-41 142 (0) 0.0 (3) 2.1 (139) 97.9 0 (0) 42-53 106 (0) 0.0 (3) 2.8 (103) 97.2 0 (0) 54-59 59 (0) 0.0 (1) 1.7 (58) 98.3 0 (0) Total 529 (1) 0.2 (26) 4.9 (502) 94.9 0 (0) East Borno 6-17 176 (2) 1.1 (29) 16.5 (145) 82.4 0 (0) 18-29 174 (1) 0.6 (14) 8.0 (159) 91.4 0 (0) 30-41 153 (2) 1.3 (5) 3.3 (146) 95.4 0 (0) 42-53 129 (0) 0.0 (6) 4.7 (123) 95.3 0 (0) 54-59 67 (0) 0.0 (5) 7.5 (62) 92.5 0 (0) Total 699 (5) 0.7 (59) 8.4 (535) 90.8 0 (0) Central Borno 6-17 135 (2) 1.5 (24) 17.8 (109) 80.7 0 (0) 18-29 124 (3) 2.4 (16) 12.9 (105) 84.7 0 (0) 30-41 133 (1) 0.8 (4) 3.0 (128) 96.2 0 (0) 42-53 105 (0) 0.0 (5) 4.8 (100) 95.2 0 (0) 54-59 41 (0) 0.0 (1) 2.4 (40) 97.6 0 (0) Total 538 (60 1.1 (50) 9.3 (482) 89.6 0 (0)
MMC / Jere 6-17 123 (3) 2.4 (13) 10.6 (107) 87.0 0 (0) 18-29 159 (1) 0.6 (11) 6.9 (147) 92.5 0 (0) 30-41 150 (0) 0.0 (7) 4.7 (143) 95.3 0 (0) 42-53 147 (1) 0.7 (4) 2.7 (142) 96.6 0 (0) 54-59 53 (0) 0.0 (2) 3.8 (51) 96.2 0 (0) Total 632 (5) 0.8 (37) 5.9 (590) 93.4 0 (0) Central Yobe 6-17 157 (6) 3.8 (25) 15.9 (126) 80.3 0 (0) 18-29 147 (1) 0.7 (20) 13.6 (126) 85.7 0 (0) 30-41 130 (3) 2.3 (15) 11.5 (112) 86.2 0 (0) 42-53 134 (2) 1.5 (6) 4.5 (126) 94.0 0 (0) 54-59 41 (0) 0.0 (2) 4.9 (39) 95.1 0 (0) Total 609 (12) 2.0 (68) 11.2 (529) 86.9 0 (0) Southern Yobe 6-17 137 (5) 3.6 (19) 13.9 (113) 82.5 0 (0) 18-29 163 (2) 1.2 (16) 9.8 (145) 89.0 0 (0) 30-41 143 (0) 0.0 (16) 11.2 (127) 88.8 0 (0) 42-53 133 (0) 0.0 (7) 5.3 (126) 94.7 0 (0) 54-59 40 (0) 0.0 (1) 2.5 (39) 97.5 0 (0) Total 616 (7) 1.1 (59) 9.6 (550) 89.3 0 (0) Northern Yobe 6-17 145 (4) 2.8 (19) 13.1 (122) 84.1 0 (0) 18-29 149 (2) 1.3 (17) 11.4 (130) 87.2 0 (0) 30-41 153 (2) 1.3 (13) 8.5 (138) 90.2 0 (0) 42-53 107 (1) 0.9 (6) 5.6 (100) 93.5 0 (0) 54-59 46 (0) 0.0 (3) 6.5 (43) 93.5 0 (0) Total 600 (9) 1.5 (58) 9.7 (533) 88.8 0 (0)
3.2.2 Acute Malnutrition (MUAC) and/or Bilateral Oedema
Mid-upper arm circumference in combination with bilateral oedema is commonly used in emergency nutrition programs, including in Nigeria, for diagnosis and referral of children aged 6-59 months. MUAC as a screening tool has been demonstrated to be a better predictor of mortality than any other anthropometric measurement in many studies. Prevalence of acute malnutrition based on MUAC and/or oedema among children aged 6-59 months is presented in Tables 11 and 12.
Prevalence of GAM as assessed by MUAC and/or oedema was highest in Borno (2.8%) followed by Yobe (2.6%) and Adamawa (1.2%). While prevalence of SAM was highest in Yobe (1.0%). By domain prevalence of GAM by MUAC was highest in Central Yobe (4.1%). Prevalence was higher among girls than boys in all domains with the exception of MMC & Jere and Northern Borno. In all domains, the majority of children identified as acutely malnourished by MUAC were under 24 months of age.
MUAC and WHZ are unique indicators for the identification of acutely malnourished children under five and may not detect the same children or correlate7. The difference between GAM
7 https://www.researchgate.net/publication/281204067_Inconsistent_diagnosis_of_acute_malnutrition_by_weight-for- height_and_mid-upper_arm_circumference_Contributors_in_16_cross-
derived from MUAC measurements and GAM derived from WHZ measurements may either suggest that all children with MUAC <125mm are also a WHZ of <2 Z-score or they are a different set of acutely malnourished children.
sectional_surveys_from_South_Sudan_the_Philippines_Chad_and_Bangladesh
Table 11 Prevalence of Acute Malnutrition by MUAC (and/or Oedema) In Children 6-59 Months, And by Sex, State and Domain
Prevalence of global acute Prevalence of moderate acute Prevalence of severe acute malnutrition malnutrition malnutrition
(< 125 mm and >= 115 mm, no Number of children (< 125 mm and/or oedema) (< 115 mm and/or oedema) oedema) 6-59 months All Boys Girls All Boys Girls All Boys Girls
State Adamawa (13) 1.2 (4) 0.6 (9) 1.9 (8) 0.7 (4) 0.6 (4) 0.7 (5) 0.5 (0) 0.0 (5) 1.1 1052 [0.7,2.1] [0.2,2.1] [1.0,3.4] [0.3,1.5] [0.2,2.1] [0.3,1.8] [0.2,1.2] [0.0- 0.0] [0.5,2.7] Borno (77) 2.8 (37) 2.6 (40) 2.9 (54) 1.9 (22) 1.4 (32) 2.3 (23) 0.9 (15) 1.1 (8) 0.6 2863 [2.0,3.7] [1.8,3.8] [2.0,4.3] [1.3,2.8] [0.8,2.5] [1.5,3.6] [0.6,1.4] [0.7,2.0] [0.3,1.3] Yobe (52) 2.6 (15) 1.6 (37) 3.6 (34) 1.6 (10) 1.2 (24) 2.0 (18) 1.0 (5) 0.5 (13) 1.6 1843 [2.0,3.5] [0.9,2.8] [2.6,5.1] [1.1,2.3] [0.6,2.3] [1.3,3.1] [0.6,1.7] [0.2,1.2] [0.9,2.7] Domain S. Adamawa (8) 1.5 (3) 1.1 (5) 2.0 (7) 1.3 (3) 1.1 (4) 1.6 (4) 0.7 (0) 0.0 (1) 0.4 535 [0.7- 3.2] [0.2- 4.6] [0.9- 4.2] [0.6- 3.0] [0.2- 4.6] [0.6- 3.8] [0.3- 1.7] [0.0- 0.0] [0.1- 2.9] N. Adamawa (5) 1.0 (1) 0.3 (4) 1.8 (1) 0.2 (1) 0.3 (0) 0.0 (4) 0.8 (0) 0.0 (4) 1.8 517 [0.4- 2.3] [0.0- 2.7] [0.7- 4.7] [0.0- 1.5] [0.0- 2.7] [0.0- 0.0] [0.3- 2.1] [0.0- 0.0] [0.7- 4.7] Northern Borno (15) 3.4 (10) 4.3 (5) 2.4 (8) 1.8 (4) 1.7 (4) 1.9 (7) 1.6 (6) 2.6 (1) 0.5 437 [2.0- 6.0] [2.3- 8.1] [1.0- 5.7] [0.8- 3.9] [0.6- 4.6] [0.7- 5.2] [0.7- 3.6] [1.0- 6.4] [0.1- 3.5] Southern Borno (5) 0.9 (2) 0.8 (3) 1.1 (4) 0.8 (1) 0.4 (3) 1.1 (1) 0.2 (1) 0.4 (0) 0.0 530 [0.3- 3.4] [0.2- 3.2] [0.2- 7.8] [0.2- 3.6] [0.0- 3.0] [0.2- 7.8] [0.0- 1.5] [0.0- 3.0] [0.0- 0.0] East Borno (21) 3.0 (9) 2.6 (12) 3.3 (16) 2.3 (7) 2.1 (9) 2.5 (5) 0.7 (2) 0.6 (3) 0.8 705 [1.8- 4.9] [1.3- 5.2] [1.9- 5.6] [1.4- 3.8] [0.9- 4.7] [1.4- 4.5] [0.3- 1.6] [0.1- 2.3] [0.3- 2.5] Central Borno (21) 3.8 (8) 2.7 (13) 5.2 (19) 3.5 (7) 2.4 (12) 4.8 (2) 0.4 (1) 0.3 (1) 0.4 548 [2.0- 7.3] [1.1- 6.7] [2.6- 9.9] [1.7- 7.0] [0.8- 6.5] [2.3- 9.6] [0.1- 1.5] [0.0- 2.5] [0.1- 3.0] MMC & Jere (15) 2.3 (8) 2.4 (7) 2.2 (7) 1.1 (3) 0.9 (4) 1.3 (8) 1.2 (5) 1.5 (3) 1.0 643 [1.4- 3.9] [1.2- 4.9] [1.1- 4.4] [0.5- 2.2] [0.3- 2.7] [0.5- 3.3] [0.6- 2.6] [0.7- 3.5] [0.3- 2.9] Central Yobe (25) 4.1 (6) 2.0 (19) 6.0 (16) 2.6 (3) 1.0 (13) 4.1 (9) 1.5 (3) 1.0 (6) 1.9 617 [2.7- 6.0] [0.9- 4.3] [3.8- 9.4] [1.5- 4.5] [0.3- 3.1] [2.4- 6.9] [0.8- 2.6] [0.3- 3.1] [0.9- 3.9] Southern Yobe (14) 2.3 (5) 1.6 (9) 3.0 (7) 1.1 (4) 1.3 (3) 1.0 (7) 1.1 (1) 0.3 (6) 2.0 620 [1.3- 3.8] [0.7- 3.7] [1.6- 5.5] [0.6- 2.2] [0.5- 3.3] [0.3- 2.9] [0.5- 2.5] [0.0- 2.4] [0.9- 4.1] Northern Yobe (13) 2.1 (4) 1.4 (9) 2.8 (11) 1.8 (3) 1.0 (8) 2.5 (2) 0.3 (1) 0.3 (1) 0.3 606 [1.2- 3.8] [0.3- 5.3] [1.5- 5.4] [1.0- 3.3] [0.2- 4.4] [1.2- 5.2] [0.1- 1.3] [0.0- 2.4] [0.0- 2.3]
Table 12: Prevalence of Acute Malnutrition by MUAC and/or Oedema In Children 6-59 Months, By Age, By Domain Severe Moderate wasting Normal Age groups (months) Total no. wasting (>= 115 mm and < Oedema (> = 125 mm) (< 115 mm) 125 mm) No. (%) No. (%) No. (%) No. (%) Southern Adamawa 6-17 118 (1) 0.8 (1) 0.8 (1) 0.8 0 (0) 18-29 129 (0) 0.0 (0) 0.0 (0) 0.0 0 (0) 30-41 118 (0) 0.0 (0) 0.0 (0) 0.0 0 (0) 42-53 114 (0) 0.0 (0) 0.0 (0) 0.0 0 (0) 54-59 56 (0) 0.0 (0) 0.0 (0) 0.0 0 (0) Total 535 (1) 0.2 (1) 0.2 (1) 0.2 0 (0) Northern Adamawa 6-17 103 (4) 3.9 (4) 3.9 (4) 3.9 0 (0) 18-29 120 (0) 0.0 (0) 0.0 (0) 0.0 0 (0) 30-41 141 (0) 0.0 (0) 0.0 (0) 0.0 0 (0) 42-53 110 (0) 0.0 (0) 0.0 (0) 0.0 0 (0) 54-59 43 (0) 0.0 (0) 0.0 (0) 0.0 0 (0) Total 517 (4) 0.8 (4) 0.8 (4) 0.8 0 (0) Northern Borno 6-17 109 (5) 4.6 (5) 4.6 (5) 4.6 0 (0) 18-29 102 (2) 2.0 (2) 2.0 (2) 2.0 0 (0) 30-41 103 (0) 0.0 (0) 0.0 (0) 0.0 0 (0) 42-53 102 (0) 0.0 (0) 0.0 (0) 0.0 0 (0) 54-59 21 (0) 0.0 (0) 0.0 (0) 0.0 0 (0) Total 437 (7) 1.6 (7) 1.6 (7) 1.6 0 (0) Southern Borno 6-17 108 (0) 0.0 (4) 3.7 (104) 96.3 0 (0) 18-29 114 (0) 0.0 (0) 0.0 (114) 100.0 0 (0) 30-41 143 (1) 0.7 (0) 0.0 (142) 99.3 0 (0) 42-53 106 (0) 0.0 (0) 0.0 (1060 100.0 0 (0) 54-59 59 (0) 0.0 (0) 0.0 (59) 100.0 0 (0) Total 530 (1) 0.2 (4) 0.8 (525) 99.1 0 (0) East Borno 6-17 177 (4) 2.3 (13) 7.3 (160) 90.4 0 (0) 18-29 176 (0) 0.0 (3) 1.7 (173) 98.3 0 (0) 30-41 155 (1) 0.6 (0) 0.0 (154) 99.4 0 (0) 42-53 130 (0) 0.0 (0) 0.0 (130) 100.0 0 (0) 54-59 67 (0) 0.0 (0) 0.0 (67) 100.0 0 (0) Total 705 (5) 0.7 (16) 2.3 (684) 97.0 0 (0) Central Borno 6-17 139 (2) 1.4 (13) 9.4 (124) 89.2 0 (0) 18-29 125 (0) 0.0 (4) 3.2 (121) 96.8 0 (0) 30-41 136 (0) 0.0 (1) 0.7 (135) 99.3 0 (0) 42-53 106 (0) 0.0 (0) 0.0 (106) 100.0 0 (0) 54-59 41 (0) 0.0 (1) 2.4 (40) 97.6 0 (0) Total 547 (2) 0.4 (19) 3.5 (526) 96.2 0 (0)
MMC / Jere 6-17 127 (5) 3.9 (5) 3.9 (117) 92.1 0 (0) 18-29 163 (3)1.8 (2) 1.2 (158) 96.9 0 (0) 30-41 151 (0) 0.0 (0) 0.0 (151) 100.0 0 (0) 42-53 149 (0) 0.0 (0) 0.0 (149) 100.0 0 (0) 54-59 53 (0) 0.0 (0) 0.0 (53) 100.0 0 (0) Total 643 (8) 1.2 (7) 1.1 (628) 97.7 0 (0)
Northern Yobe
6-17 147 (2) 1.4 (10) 6.8 (135) 91.8 0 (0) 18-29 152 (0) 0.0 (1) 0.7 (151) 99.3 0 (0) 30-41 153 (0) 0.0 (0) 0.0 (153) 100.0 0 (0) 42-53 107 (0) 0.0 (0) 0.0 (107) 100.0 0 (0) 54-59 47 (0) 0.0 (0) 0.0 (47) 100.0 0 (0) Total 606 (0.3) 0.3 (11) 1.8 (593) 97.9 0 (0) Central Yobe 6-17 161 (8) 5.0 (12) 7.5 (141) 87.6 0 (0) 18-29 149 (1) 0.7 (3) 2.0 (145) 97.3 0 (0) 30-41 131 (0) 0.0 (1) 0.8 (130) 99.2 0 (0) 42-53 135 (0) 0.0 (0) 0.0 (135) 100.0 0 (0) 54-59 41 (0) 0.0 (0) 0.0 (41) 100.0 0 (0) Total 617 (9) 1.5 (16) 2.6 (592) 95.9 0 (0) Southern Yobe 6-17 139 (4) 2.9 (6) 4.3 (129) 92.8 0 (0) 18-29 164 3) 1.8 (1) 0.6 (160) 97.6 0 (0) 30-41 143 (0) 0.0 (0) 0.0 (143) 100.0 0 (0) 42-53 133 (0) 0.0 (0) 0.0 (133) 100.0 0 (0) 54-59 41 (0) 0.0 (0) 0.0 (41) 100.0 0 (0) Total 620 (7) 1.1 (7) 1.1 (606) 97.7 0 (0)
3.2.3 Underweight Underweight refers to the proportion of children with low weight-for-age. The percentage of children who have low weight-for-age can reflect acute malnutrition (low weight-for- height), chronic malnutrition (low height-for-age), or both. Thus, underweight is a composite indicator and may be difficult to interpret. Table 13 presents prevalence of underweight among children 0-59 months by state and domain, disaggregated by sex.
The prevalence of underweight in Yobe (16.8%) was nearly twice that in Adamawa (9.4%). The prevalence of severe underweight in Yobe (3.3%) and Borno (2.8%) exceeded that in Adamawa (1.6%). In all three states, prevalence was higher among boys than girls. By domain, the prevalence of underweight was highest in Central Yobe (19.3%) followed by Central Borno (18.8%), as presented in table 13.
Table 13 Prevalence of Underweight by Weight-For-Age Z-Scores in Children 0-59 Months, By Sex, By State and Domain Prevalence of moderate Number of Prevalence of underweight Prevalence of severe underweight underweight children 0-59 (<-2 z-score) (<-2 z-score and >=-3 z-score) (<-3 z-score) months All Boys Girls All Boys Girls All Boys Girls State Adamawa (110) 9.4 (73) 11.8 (37) 6.6 (91) 7.8 (60) 9.7 (31) 5.5 (19) 1.6 (13) 2.1 (6) 1 1152 [7.5-11.8] [9.1-15.1] [4.4-9.7] [6.1-9.9] [7.3-12.7] [3.5-8.5] [1.0-2.6] [1.2-3.7] [0.4-2.5] Borno (433) 14.5 (271) 17.6 (162) 11.3 (353) 11.7 (225) 14.6 (128) 8.7 (80) 2.8 (46) 3 (34) 2.6 3148 [12.8-16.4] [15.5-19.9] [9.3-13.6] [10.4-13.2] [12.7-16.7] [7.1-10.5] [2.1-3.7] [2.1-4.3] [1.8-3.8] Yobe (338) 16.8 (190) 18.3 (148) 15.2 (273) 13.5 (155) 14.7 (118) 12.1 (65) 3.3 (35) 3.5 (30) 3 2021 [14.2-19.7] [14.7-22.5] [12.4-18.5] [11.3-16.0] [11.6-18.6] [9.8-15.0] [2.4-4.5] [2.3-5.3] [1.8-5.1] Domain S. Adamawa (62) 10.5 (33) 10.7 (29) 10.2 (51) 8.6 (27) 8.7 (24) 8.5 (11) 1.9 (6) 1.9 (5) 1.8 592 [7.6-14.2] [7.4-15.1] [6.2-16.4] [6.1-12.0] [6.1-12.4] [4.8-14.5] [0.9- 3.6] [0.8- 4.5] [0.7- 4.7] N. Adamawa (48) 8.6 (40) 12.6 (8) 3.3 (40) 7.1 (33) 10.4 (7) 2.9 (8) 1.4 (7) 2.2 (1) 0.4 560 [6.1-12.0] [8.6-18.0] [1.7- 6.2] [4.9-10.4] [6.8-15.5] [1.4- 5.8] [0.7- 3.0] [1.0- 5.0] {0.1- 3.0] Northern Borno (65) 13.5 (42) 16.6 (23) 10.0 (59) 12.2 (38) 15.0 (21) 9.2 (6) 1.2 (4) 1.6 (2) 0.9 481 [9.8-18.3] [11.7-23.1] [6.2-15.8] [8.8-16.8] [10.5-21.0] [5.6-14.6] [0.6- 2.7] [0.6- 4.1] [0.2- 3.4] Southern Borno (54) 9.2 (37) 12.6 (17) 5.8 (47) 8.0 (34) 11.6 (13) 4.5 (7) 1.2 (3) 1.0 (4) 1.4 586 [6.3-13.2] [8.7-17.9] [3.0-11.1] [5.5-11.6] [7.9-16.6] [2.3- 8.6] [0.6- 2.4] [0.3- 3.2] [0.5- 3.6] East Borno (103) 13.3 (63) 16.9 (40) 9.9 (83) 10.7 (50) 13.4 (33) 8.1 (20) 2.6 (13) 3.5 (7) 1.7 777 [10.7-16.3] [13.6-20.9] [6.8-14.1] [8.3-13.6] [10.5-17.1] [5.3-12.4] [1.6- 4.0] [2.0- 6.0] [0.9- 3.5] Central Borno (113) 18.8 (66) 20.4 (47) 16.9 (86) 14.3 (49) 15.1 (37) 13.3 (86) 14.3 (49) 15.1 (37) 13.3 602 [1z5.9- [15.1-23.0] [12.2-22.9] [11.6-17.5] [11.1-20.3] [9.6-18.2] [11.6-17.5] [11.1-20.3] [9.6-18.2] 25.7] MMC & Jere (98) 14.0 (63) 17.6 (35) 10.2 (78) 11.1 (54) 15.1 (24) 7.0 (20) 2.9 (9) 2.5 (11) 3.2 701 [11.0-17.6] [14.1-21.9] [6.9-14.8] [8.9-13.9] [12.0-18.8] [4.6-10.4] [1.7- 4.7] [1.3- 4.8] [1.7- 6.0] Central Yobe (130) 19.3 (75) 22.3 (55) 16.4 (105) 15.6 (62) 18.4 (43) 12.8 (25) 3.7 (13) 3.9 (12) 3.6 673 [15.3-24.0] [17.2-28.4] [12.1-21.8] [12.2-19.7] [13.9-24.0] [9.3-17.4] [2.1- 6.5] [1.9- 7.5] [1.9- 6.7] Southern Yobe (113) 16.8 (62) 17.5 (51) 16.0 (90) 13.4 (49) 13.8 (41) 12.9 (23) 3.4 (13) 3.7 (10) 3.1 674 [12.8-21.7] [12.0-24.8] [11.6-21.7] [9.9-17.8] [9.0-20.6] [9.1-17.8] [2.1- 5.5] [1.9- 6.8] [1.3- 7.5] Northern Yobe (95) 14.1 (53) 16.3 (42) 12.0 (78) 11.6 (44) 13.5 (34) 9.7 (17) 2.5 (9) 2.8 (8) 2.3 674 [10.6-18.5] [12.1-21.6] [8.0-17.6] [8.8-15.0] [10.2-17.7] [6.5-14.3] [1.4- 4.4] [1.2- 6.2] [1.1- 4.7]
3.2.4 Chronic Malnutrition (Stunting) Stunting occurs as a result of inadequate nutrition over a longer period. Stunting is assessed by length or height-for-age Z-scores (HAZ). Table 14 presents prevalence of stunting among children 0-59 months by state and domain, disaggregated by sex.
Prevalence of stunting is highest in Yobe (24.8%) and Borno (24.4%) than in Adamawa (19.9%). Based on the WHO classification of malnutrition, prevalence in Adamawa, Yobe and Borno are below serious level of between 30 and 40%. At least one in twenty children in Yobe and Borno are severely stunted (22.9% and 20.4%, respectively). Stunting prevalence is higher (but statistically significant) in boys than girls in all three states. By domain, prevalence was highest in Central Borno (31.5%).
Table 14: Prevalence of Stunting Based on Height-For-Age Z-Scores in Children 0-59 Months, By Sex, By State and Domain Prevalence of stunting Prevalence of moderate stunting Prevalence of severe stunting Number of children 0- (<-2 z-score) (<-2 Z-score and ≥ -3 z-score) (<-3 z-score) 59 months All Boys Girls All Boys Girls All Boys Girls State Adamawa (235) 19.9 (153) 24.1 (82) 15 (186) 15.6 (118) 18.3 (68) 12.3 (49) 4.4 (35) 5.8 (14) 2.7 1140 [16.4-24.1] [19.3-29.5] [11.9-18.8] [12.7-18.9] [14.4-23.0] [9.6-15.5] [3.2-6.0] [4.1-8.1] [1.5-4.7] Borno (699) 24.2 (418) 28.1 (281) 20.1 (520) 18 (311) 21.2 (209) 14.5 (179) 6.3 (107) 6.9 (72) 5.6 3108 [22.0-26.7] [25.0-31.3] [17.7-22.8] [16.1-19.9] [18.6-24.0] [12.5-16.7] [5.1-7.6] [5.4-8.8] [4.4-7.2] Yobe (470) 24.8 (273) 28.5 (197) 21 (348) 18.5 (194) 20.3 (154) 16.7 (122) 6.2 (79) 8.2 (43) 4.2 1989 [20.8-29.2] [23.5-34.1] [17.0-25.5] [15.6-21.9] [16.5-24.7] [13.6-20.4] [4.7-8.2] [6.0-11.0] [2.9-6.2] Domain S. Adamawa (148) 25.3 (90) 29.4 (58) 20.7 (126) 21.5 (75) 24.5 (51) 18.2 (22) 3.8 (15) 4.9 (7) 2.5 586 [20.0-31.3] [22.5-37.4] [15.9-26.6] [17.1-26.7] [18.5-31.7] [14.1-23.1] [2.3- 6.2] [2.9- 8.1] [0.9- 6.5] N. Adamawa (84) 15.2 (61) 19.5 (23) 9.5 (57) 10.3 (41) 13.1 (16) 6.6 (27) 4.9 (20) 6.4 (7) 2.9 554 [10.9-20.7] [13.7-26.9] [6.1-14.5] [7.2-14.4] [8.8-19.0] [3.9-11.0] [3.1- 7.5] [3.9-10.2] [1.4- 5.8] Northern Borno (104) 21.9 (64) 25.4 (40) 17.9 (71) 14.9 (45) 17.9 (26) 11.7 (33) 6.9 (19) 7.5 (14) 6.3 475 [17.8-26.7] [20.3-31.3] [12.9-24.2] [11.6-19.1] [12.9-24.2] [8.2-16.4] [4.7-10.2] [4.6-12.0] [3.6-10.6] Southern Borno (113) 19.7 (66) 22.8 (47) 16.5 (90) 15.7 (51) 17.6 (39) 13.7 (23) 4.0 (15) 5.2 (8) 2.8 574 [14.8-25.6] [16.4-30.9] [11.4-23.2] [11.8-20.5] [12.6-24.1] [9.3-19.8] [2.2- 7.1] [2.7- 9.8] [1.2- 6.7] East Borno (135) 17.5 (81) 21.9 (54) 13.5 (103) 13.4 (57) 15.4 (46) 11.5 (32) 4.2 (24) 6.5 (8) 2.0 770 [14.2-21.4] [17.5-27.1] [10.0-18.0] [10.8-16.5] [12.0-19.6] [8.3-15.8] [2.8- 6.2] [4.1-10.2] [1.0- 3.9] Central Borno (188) 31.5 (111) 34.8 (77) 27.8 (137) 23.0 (82) 25.7 (55) 19.9 (51) 8.6 (29) 9.1 (22) 7.9 596 [25.9-37.8] [27.0-43.4] [22.0-34.4] [18.7-27.9] [19.5-33.1] [15.1-25.6] [5.6-13.0] [5.4-14.8] [4.8-12.8] MMC & Jere (157) 22.7 (95) 26.9 (62) 18.3 (119) 17.2 (75) 21.2 (44) 13.0 (38) 5.5 (20) 5.7 (18) 5.3 691 [19.2-26.7] [22.4-31.9] [14.5-22.9] [14.2-20.7] [17.1-26.1] [9.9-16.9] [4.1- 7.4] [3.7- 8.6] [3.5- 7.9] Central Yobe (153) 23.2 (89) 27.5 (64) 19.1 (112) 17.0 (65) 20.1 (47) 14.0 (41) 6.2 (24) 7.4 (17) 5.1 659 [18.1-29.2] [20.4-35.9] [13.9-25.7] [13.4-21.3] [14.1-27.8] [10.5-18.5] [4.1- 9.4] [5.0-10.8] [2.5-10.0] Southern Yobe (180) 26.9 (106) 30.2 (74) 23.2 (137) 20.4 (76) 21.7 (61) 19.1 (43) 6.4 (30) 8.5 (13) 4.1 670 [20.5-34.4] [22.4-39.4] [16.8-31.1] [15.6-26.4] [15.7-29.0] [14.0-25.6] [4.1- 9.9] [5.3-13.6] [2.2- 7.5] Northern Yobe (136) 20.6 (77) 24.2 (59) 17.3 (101) 15.3 (53) 16.7 (48) 14.0 (35) 5.3 (24) 7.5 (11) 3.2 660 [15.6-26.7] [17.9-31.9] [12.2-23.8] [11.7-19.7] [12.4-22.0] [9.9-19.5] [3.3- 8.3] [4.7-12.0] [1.6- 6.2]
Table 15 present summary statistics for each anthropometric indicator. Mean Z-Scores for all indicators and for all domains are negative, suggesting that the populations assessed were malnourished relative to a WHO reference population.
Standard deviation can be understood as a measure of heterogeneity of the sample as well as data quality. Standard deviations for HAZ, WHZ and WAZ z-scores all fell within ±0.8-1.2 (acceptable levels). Design effects for WHZ z-scores ranged from less than 1.70 for all domains, and less than 1.5 for all domains in Borno, Southern Adamawa and Northern Yobe suggesting relatively low heterogeneity in acute malnutrition.
Z-scores are not available for children that were absent at the time of the visit and children for whom measurements could not be taken, e.g., disability. Z-scores are considered out of range and excluded for analysis if they are more extreme than ±3 SDs from the observed mean of the domain (SMART flags).
Table 15: Mean Z-Scores, Design Effects and Excluded Subjects, By Domain Design z-scores z-scores Mean z- Effect Indicator n not out of scores ± SD (z-score < - available range 2) Weight-for-Height Southern Adamawa 592 -0.35±1.05 1.32 2 4 Northern Adamawa 557 -0.50±1.07 1.68 2 9 Northern Borno 481 -0.80±0.98 1.30 2 11 Southern Borno 588 -0.45±1.02 1.36 2 2 East Borno 775 -0.70±0.99 1.05 8 8 Central Borno 601 -0.69±1.03 1.28 8 6 MMC / Jere 694 -0.60±0.96 1.09 3 12 Northern Yobe 666 -0.75±1.04 1.30 2 10 Central Yobe 676 -0.82±1.05 1.62 4 15 Southern Yobe 666 -0.63±1.06 1.83 8 7 Weight-for-Age Southern Adamawa 592 -0.95±0.92 1.61 1 5 Northern Adamawa 560 -0.86±0.88 1.50 1 7 Northern Borno 481 -1.19±0.80 1.80 1 11 Southern Borno 586 -0.90±0.85 1.95 2 4 East Borno 777 -1.11±0.84 1.28 6 8 Central Borno 602 -1.30±0.91 1.48 8 5 MMC / Jere 701 -1.13±0.89 1.55 3 5 Northern Yobe 673 -1.13±0.89 2.07 1 3 Central Yobe 674 -1.25±0.94 1.98 4 8 Southern Yobe 674 -1.18±0.92 2.28 6 11 Height-for-Age Southern Adamawa 586 -1.31±1.04 2.37 2 10 Northern Adamawa 554 -0.96±1.07 2.50 2 12 Northern Borno 475 -1.24±1.05 1.33 1 18 Southern Borno 574 -1.08±1.04 2.54 2 15 East Borno 770 -1.12±0.98 1.68 8 12 Central Borno 596 -1.47±1.10 2.42 9 10 MMC / Jere 691 -1.25±1.06 1.35 2 16 Northern Yobe 659 -1.12±1.10 2.99 2 16 Central Yobe 670 -1.23±1.10 2.75 4 22 Southern Yobe 660 -1.35±1.05 4.02 5 16
3.3 Mortality results
Crude and under five mortality rates are measures of all-cause mortality occurring during the recall period. Deaths both from conflict as well as natural causes contribute to all-cause mortality. Both CMR and U5MR were below the emergency threshold of 1 death/10,000 population/day and 2 deaths/10,000 population/day, respectively. By domain, CMR was highest in South Adamawa, 0.41 (0.24-0.71 95% CI) while U5MR was highest in Northern Borno 1.02 (0.36-2.85 95% CI). By domain CMR ranged from 0.16-0.41 total deaths / 10,000 people / day, and U5MR ranged from 0.10 to 1.02 deaths in children under five / 10,000 children under five / day. (Table 16)
Under-five mortality rates did not exceed the emergency thresholds in all domains. However, the upper confidence intervals for U5MR in Northern Borno and Southern Adamawa exceeded 2.0, suggesting it is possible that U5MR exceeded emergency thresholds in these domains. Crude mortality rates did not exceed emergency thresholds.
Table 16: Mortality Rates by States and Domain Crude Mortality Rate Under five Mortality Rate Total Number of (deaths in children under (total deaths /10,000 Populatio household five / 10,000 children people / day) n Sampled s under five / day) Design Design Rate [CI] Rate [CI] Effect Effect
State Adamawa 0.27 1.19 0.74 1.22 6,959 1,380 [0.08-0.46] [0.00-1.55] Borno 0.27 1.18 0.57 1.12 17,468 3,663 [0.07-0.47] [0.00-1.30] Yobe 0.23 1.37 0.81 1.27 10,278 2,065 [0.04-0.42] [0.00-1.69] Domain S. Adamawa 0.41 1.28 0.80 1.44 3,463 697 [0.24-0.71] [0.29-2.19] N. Adamawa 0.16 1.10 0.70 1.00 3,496 683 [0.07-0.36] [0.29-1.64] Northern Borno 0.30 1.09 1.02 1.53 2,729 702 [0.15-0.60] [0.36-2.85] Southern Borno 0.30 1.06 0.81 1.06 3,324 606 [0.17-0.54] [0.34-1.90] East Borno 0.24 1.00 0.10 1.00 3,973 869 [0.14-0.42] [0.01-0.81] Central Borno 0.21 1.00 0.42 1.00 3,129 687 [0.10-0.44] [0.14-1.27] MMC & Jere 0.30 1.75 0.53 1.00 4,313 799 [0.15-0.63] [0.20-1.39] Central Yobe 0.20 1.88 0.74 1.17 3,781 689 [0.08-0.51] [0.30-1.83] Southern Yobe 0.22 1.13 0.74 1.11 3,768 674 [0.11-0.44] [0.31-1.79] Northern Yobe 0.31 1.00 0.50 1.00 2,729 702 [0.18-0.51] [0.19-1.33]
3.4 Infant and Young Child Feeding
UNICEF recommends early initiation of breastfeeding whereby an infant is put to the breast
within one hour of birth. Exclusive breastfeeding is recommended for the first six months of life. Continued breastfeeding with appropriate complementary feeding is recommended for up to two years.
Mothers (or caregivers) were asked whether their children aged 0-23 months had ever been breastfed. For all children who had ever been breastfed, mothers (or caregivers) were asked how long after birth did they first put the child to breast and whether the child was breastfed on the day preceding the survey during the day or night. Indicators for continued breastfeeding at one and two years of age are derived from the question regarding breastfeeding during the day preceding the survey, asked to all mothers or caregivers of children 0-23 months. While for exclusive breastfeeding, mothers of children 0-5 months were asked whether the child was given anything other than breast milk during the day preceding the survey. Sample sizes for continued breastfeeding within each domain are small and therefore the confidence intervals around these estimates are wide.
Overall the proportion of children aged 0-23 months who were ever breastfed was over 90% in all three states. By domain, the proportion ever breastfed ranged from 90.7-96.2%. However, less than half of mothers initiated early breastfeeding within one hour of birth: 49.7% in Borno, 44.5% in Adamawa and 46.5% in Yobe. (Table 17)
Table 17: Percent of Children 0-59 Months Who Were Exclusively Breastfed, Early Initiation of Breastfeeding, By Sex, Age, State and Domain Percentage who were Number of Percentage Number of first breastfed: children age who were ever children age 6- Within one Within one 6-23 months breastfed 23 months hour of day of birth ever breastfed birth
Sex Male (1201) 95 1261 (564) 47.2 (426) 35.7 1199 [93.4,96.3] [42.5,51.8] [31.9,39.7] Female (1136) 93.7 1196 (524) 47.8 (397) 35.3 1126 [91.5,95.4] [43.1,52.6] [31.5,39.3] Age in months 0-5 (615) 96.5 635 (338) 55.3 (179) 28.8 615 [93.9,98.0] [49.7,60.8] [24.7,33.3] 6-11 (621) 96.9 642 (261) 41.8 (247) 41.1 621 [95.2,98.1] [36.2,47.5] [35.6,46.8] 12-23 (1091) 91.9 1181 (489) 46.3 (397) 36.1 1089 [89.4,93.9] [41.3,51.3] [32.1,40.4] State Adamawa (399) 95.4 419 (179) 44.5 (151) 37.7 399 [91.3,97.6] [35.1,54.2] [30.1,45.9] Borno (1168) 93.5 1241 (574) 49.7 (393) 33.6 1167 [91.4,95.1] [43.4,56.0] [28.8,38.8] Yobe (760) 94.9 798 (335) 46.5 (279) 36.1 759 [91.9,96.8] [38.6,54.5] [29.9,42.9] Domain S. Adamawa (210) 94.2 223 (100) 47.6 (82) 39.0 210 [85.5,97.8] [35.0,60.6] [28.3,51.0] N. Adamawa (189) 96.4 196 (79) 41.8 (69) 36.5 189 [92.3,98.4] [28.9,55.9] [26.3,48.1] Northern Borno (176) 90.7 194 (82) 46.6 (500 28.4 176 [85.5,94.2] [33.4,60.2] [20.3,38.1] Southern Borno (194) 95.1 204 (78) 40.2 (83) 42.8 194 [86.5,98.3] [27.9,53.9] [32.6,53.6] East Borno (311) 96.0 100 (164) 52.7 (99) 31.8 311 [92.7,97.8] [42.7,62.6] [24.4,40.3] Central Borno (240) 96.0 250 (118) 49.2 (76) 31.7 240 [92.5,97.9] [37.8,60.6] [23.8,40.8] MMC & Jere (247) 96.2 100 (132) 53.7 (85) 34.6 246 [87.2,94.9] [41.2,65.7] [24.9,45.6] Central Yobe (268) 96.1 279 (108) 40.3 (109) 40.7 268 [90.9,98.3] [28.7,53.0] [29.3,53.2] Southern Yobe (242) 94.2 257 (123) 51 (84) 34.9 241 [88.9,97.0] [38.7,63.2] [25.6,45.5] Northern Yobe (2500 95.4 262 (104) 41.6 (86) 34.4 250 [91.2,97.7] [29.8,54.4] [25.9,44.0]
While about 9 in 10 children continued breastfeeding until one year of age, the proportion declined after this. The percent of children 20-23 months who continued breastfeeding at two years was lowest in Borno (21.3%) while in Yobe (35.1%) and Adamawa (29.2%). No significant differences in breastfeeding practices were documented by sex. The percentage of children 0- 6 months exclusively breastfed was highest in Adamawa (52.2%) followed by Borno (45.6%) while Yobe was the lowest at 35.1%. By domain, Southern Yobe had the lowest exclusive breastfeeding rate with 29.9%, while East Borno was the highest with 57.0%. See table 17 for details.
At six months of age, breastmilk alone is no longer sufficient to meet the nutritional demands of an infant. Thus, appropriate complementary feeding should be introduced while breastfeeding is continued until 2 years of age or more. This requires transition from exclusive breastfeeding to complement breastfeeding with family foods at age 6-8 months when children are very vulnerable to being malnourished, and during this time it is important that they receive solid, semisolid, or soft foods. In the context of the survey, mothers (or caregivers) were asked whether their children aged 6-8 months were given solid, semisolid, or soft foods in the 24 hours preceding the survey.
The prevalence of children predominantly breastfed is Borno (96.2%), Yobe (93.4%) and Adamawa (96.4%), clearly indicating that majority of children are breastfed including those who are not exclusively breastfed. The predominantly breastfed differs from exclusive breastfeeding since the infant may also have received water and water-based drinks (sweetened and flavoured water, teas, infusions, etc.), fruit juice and ritual fluids (in limited quantities). With the exception of fruit juice and sugar water, no food-based fluid is considered under this definition.
The results indicate that 66.5% of children 6-8 months in Adamawa received semi-solid, or soft foods the previous day while 59.1% and 52.7% in Borno and Yobe received, respectively. By domain, between 50.0 % in MMC & Jere to 72.4% received semisolid, or soft foods the previous day. No difference in gender was observed. At least half of the children 0-23 months were appropriately breastfed in the 3 states (Table 19).
Table 18: Exclusive, Predominantly, And Continued Breastfeeding Practices by Age, Sex, Survey Domain and State Children age 0-5 months Children age 12-15 months Children age 20-23 months Percent Percent Number of Percent breastfed Number of Percent breastfed Number of exclusively predominantly children 0- (Continued breastfeeding at 1 children 12-15 (Continued breastfeeding at children 20-23 breastfed breastfed* 5 months year) months 2 years) months
Sex Male (155) 44.8 (325) 94.7 343 (241) 89.4 270 (35) 25.5 158 [38.2,51.6] [91.0,97.0] [84.3,92.9] [18.6,34.0] Female (139) 45.9 (282) 94.9 295 (217) 87 251 (38) 25.4 159 [39.4,52.5] [90.8,97.2] [81.7,90.9] [18.4,33.8] State 50 Adamawa (59) 52.2 (108) 96.4 112 (80) 90.0 89 (15) 29.2 [41.9,62.3] [90.5,98.7] [81.5,94.8] [17.8,43.8] 166 Borno (158) 45.6 (304) 94.2 323 (23) 86.8 263 (30) 21.3 [37.6,53.8] [89.2,96.9] [80.2,91.4] [14.6,30.0] 102 Yobe (77) 35.1 (195) 94.3 203 (145) 87.9 169 (28) 35.1 [26.5,44.9] [87.9,97.4] [80.6,92.8] [23.7,48.5] Domain S. Adamawa (35) 55.6 (61) 96.8 63 (33) 89.2 37 (9) 36 25 [41.6,68.7] [87.9,99.2] [69.9,96.7] [17.6,59.7] N. Adamawa (24) 49 (47) 95.9 49 (47) 90.4 52 (6) 24 25 [34.3,63.8] [84.8,99.0] [80.1,95.6] [11.8,42.6] Northern Borno (26) 46.4 (49) 87.5 56 (40) 88.9 45 (3) 14.3 21 [32.4,61.1] [71.8,95.1] [76.4,95.2] [4.6,36.8] Southern Borno (34) 56.7 (58) 96.7 60 (46) 92 50 (6) 24 25 [44.4,68.1] [88.9,99.1] [81.9,96.7] [9.5,48.8] East Borno (45) 57 (75) 94.9 79 (54) 93.1 58 (3) 7.7 39 [43.2,69.7] [87.0,98.1] [83.0,97.4] [1.9,26.1] Central Borno (24) 37.5 (61) 95.3 64 (54) 84.4 64 (4) 11.8 34 [22.3,55.7] [81.1,99.0] [66.4,93.7] [3.8,30.9] MMC & Jere (29) 45.3 (61) 95.3 64 84.8 46 (14) 29.8 47 [29.7,61.9] [81.6,98.9] [73.8,91.7] [17.7,45.5] Central Yobe (28) 43.8 (64) 100 64 (45) 81.8 55 (8) 21.1 38 [29.6,59.0] [65.0,91.6] [9.4,40.5] Southern Yobe (20) 29.9 (61) 91 67 (48) 92.3 52 (15) 51.7 29 [17.8,45.5] [79.8,96.3] [77.7,97.6] [28.9,73.8] Northern Yobe (29) 40.3 (70) 97.2 72 (52) 83.9 62 (5) 14.3 35 [26.2,56.1] [0.7,10.2] [73.8,90.6] [6.1,29.9] *Predominantly breastfed includes children currently breastfeeding who are either exclusively breastfed or receiving plain water and non-milk liquids only
3.4.1 Minimum Dietary Diversity, Minimum Meal Frequency and Minimum Acceptable Diet
Minimum dietary diversity8 is a proxy indicator for the mean micronutrient density adequacy of the diet and is measured by counting the number of food groups a child received in the last 24 hours. Studies have shown that infants and young children who consumed at least four of the seven groups were more likely to have diets that were higher in micronutrient density. Minimum meal frequency9 was developed as a proxy for energy intake of infants and young children. Young children are expected to receive a minimum acceptable diet10, which combines both minimum diet diversity and minimum meal frequency. (Table 19)
Less than 5% of children 6-23 months of age received a minimum acceptable diet in the 24 hours preceding the survey: 3.8% in Adamawa, 3.0% in Yobe and only 0.5% in Borno. By domain, no children 6 to 23 months in Northern Borno and MMC/Jere received a minimum acceptable diet. The domain with the highest proportion of minimum acceptable diets was Southern Yobe with 4.6%. (Table 20). The low rates of minimum acceptable diets can indicate a lack of knowledge by mothers and caregivers on appropriate infant and young child feeding practices.
8 Minimum dietary diversity is defined as receiving foods from at least 4 of 7 food groups: 1) Grains, roots and tubers, 2) legumes and nuts, 3) dairy products (milk, yogurt, cheese), 4) flesh foods (meat, fish, poultry and liver/organ meats), 5) eggs, 6) vitamin-A rich fruits and vegetables, and 7) other fruits and vegetables. 9 Minimum meal frequency among currently breastfeeding children is defined as children who also received solid, semi- solid, or soft foods 2 times or more daily for children age 6-8 months and 3 times or more daily for children age 9-23 months. For non-breastfeeding children age 6-23 months it is defined as receiving solid, semi-solid or soft foods, or milk feeds, at least 4 times. 10 the minimum acceptable diet for breastfed children age 6-23 months is defined as receiving the minimum dietary diversity and the minimum meal frequency, while it for non-breastfed children further requires at least 2 milk feedings and that the minimum dietary diversity is achieved without counting milk feeds.
Table 19: Percentage of Infants Age 6-8 Months Who Received Solid, Semi-Solid, Or Soft Foods During the Previous Day, By Sex, Survey Domain and State Percent 0-23 Percent Number of months Number of receiving solid, children age 6- children children age semi-solid or 8 months appropriately 0-23 months soft foods breastfed
Sex Male (90) 58.0 148 (674) 52.5 1274 [47.5,67.8] [48.9,56.0] Female (104) 57.6 175 (650) 53.4 1204 [47.7,67.0] [49.7,57.1] State Adamawa (33) 66.5 49 (254) 59.7 420 [49.8,79.9] [53.2,65.9] Borno (98) 59.1 159 (671) 51.7 1248 [47.7,69.5] [47.2,56.3] Yobe (63) 52.7 115 (399) 48.6 811 [38.8,66.2] [42.6,54.6] Domain S. Adamawa (21) 72.4 29 (147) 65.6 224 [54.0,85.5] [58.3,72.2] N. Adamawa (12) 60.0 20 (107) 54.6 196 [33.8,81.5] [44.4,64.5] Northern Borno (14) 53.8 26 (101) 51.8 195 [26.8,78.8] [42.6,60.8] Southern Borno (21) 70.0 30 (121) 59 205 [45.6,86.7] [51.7,66.0] East Borno (33) 64.7 51 (189) 58.3 100 [45.8,79.9] [51.2,65.1] Central Borno (17) 65.4 26 (122) 48.2 253 [42.4,82.9] [39.6,56.9] MMC & Jere (13) 50.0 26 (1380 271 100 [29.2,70.8] [41.9,59.9] Central Yobe (220 47.8 46 (143) 50.5 283 [28.2,68.1] [42.3,58.8] Southern Yobe (16) 48.5 33 (124) 47.3 262 [27.3,70.3] [37.7,57.1] Northern Yobe (25) 69.4 36 (132) 49.6 266 [46.5,85.6] [41.9,57.3]
Table 20: Percentage of Children Age 6-23 Months Who Received Appropriate Liquids and Solid, Semi-Solid, Or Soft Foods the Minimum Number of Times or More During the Previous Day, By Breastfeeding Status, By Sex, State, And Domain Number of children age 6- Percent of children who received: 23 months
Minimum Minimum Minimum dietary meal acceptable diversity frequency diet
Sex Male (88) 12.4 (100) 10.5 (16) 1.6 681 [9.1,16.7] [7.9,13.8] [0.8,3.1] Female (100) 14.5 (105) 11 (20) 2.0 673 [10.7,19.4] [8.4,14.3] [1.1,3.8]
State Adamawa (51) 20.8 (57) 15.1 (12) 3.8 243 [13.6,30.5] [10.4,21.4] [1.7,8.3] Borno (85) 9.2 (64) 9.0 (11) 0.5 696 [6.0,13.9] [6.1,13.1] [0.2,1.3] Yobe (52) 13.9 (75) 11.4 (13) 3.0 415 [7.5,24.4] [7.6,16.9] [1.0,8.4] Domain S. Adamawa (29) 22.5 (26) 16.1 (7) 4.3 129 [12.7,36.6] [9.0,27.2] [1.9,9.5] N. Adamawa (22) 19.3 (21) 14.3 (5) 3.4 114 [10.1,33.7] [8.8,22.3] [0.8,12.8] Northern Borno (7) 7.0 (12) 8.6 (0) 0.0 100 [2.7,17.2] [3.1,21.9] Southern Borno (21) 19.3 (18) 12.4 (1) 0.7 109 [9.6,35.0] [5.1,27.1] [0.1,4.6] East Borno (38) 19.5 (19) 7.8 (9) 3.7 195 [8.8,37.7] [4.2,13.9] [1.1,11.3] Central Borno (6) 4.2 (19) 10.1 (1) 0.5 144 [1.3,12.6] [5.9,16.6] [0.1,3.7] MMC & Jere (13) 8.8 (16) 7.7 (0) 0.0 148 [3.5,20.2] [3.2,17.5] Central Yobe (15) 10.1 (28) 12.8 (1) 0.5 149 [3.9,23.7] [6.1,24.8] [0.1,3.2] Southern Yobe (21) 16.8 (190 9.7 (9) 4.6 125 [6.7,36.1] [4.7,19.1] [1.3,14.7] Northern Yobe (16) 11.3 (28) 14.4 (30 1.5 141 [5.3,22.7] [8.6,23.2] [0.4,6.3]
3.5 Child Health
3.5.1 Measles Vaccination Coverage
Measles is a highly contagious viral respiratory tract infection known to be an important cause of death and acute malnutrition among young children particularly in emergency contexts wherein 1 to 5 percent of children with measles may die from complications of the disease11.
11 World Health Organization (WHO). 2007. WHO Fact sheet N°286: Measles. Available at: http://www.who.int/mediacentre/factsheets/fs286/en/
Measles vaccination is one of the immunizations provided as part of the Nigerian Expanded Programme on Immunization (EPI), a program initiated in 1979. A child is considered adequately immunized against measles after receiving only one dose of vaccine (around 9 months of age). Currently, a second dose of measles vaccination has been introduced in Nigeria with implementation staggered and expected to cover the whole country by the end 2020.
An outbreak of measles was recorded in Borno and Yobe states in May of 2019, with 989 (Borno) and measles vaccination campaign has been implemented as part of the Northeast Nigeria humanitarian response.
Mothers were asked to provide vaccination cards and interviewers copied vaccination information from the cards onto the questionnaire. If the child had no vaccination card, the respondent was asked to recall if the vaccine was given to the child.
Overall, measles vaccination coverage among children 12-59 months as determined by observation of vaccination card or maternal recall was 87.3%, 86.0% and 75.9% in Adamawa, Borno and Yobe, respectively (Table 21 and Figure 1). These represent an increase in coverage in Borno and Yobe relative to the estimates from the 2015 National Nutrition Survey (61.1%, 27.9% and 7.1%, respectively). However, coverage in all states is well below the national target of 90% coverage12.
Coverage was lowest in Northern Yobe (70.7%). In Borno, coverage in MMC & Jere (91.4%) and Southern Borno (90.6%) were the highest with that of Northern Borno being the lowest (72.6%). Vaccination coverage was higher among children 24-59 months in all three states. These results indicate that children are not receiving the vaccination promptly at 9 months of age, and a need to continue strengthening routine and supplemental immunization activities.
12 Measles Eradication: Recommendations from a Meeting Cosponsored by the World Health Organization, the Pan American Health Organization, and CDC. MMWR. 1997:46(RR11);1-20.
Table 21: Percentage of Children Age 12-59 Months Vaccinated Against Measles, By State and Domain Children 12-59 months Children 12-23 months Children 24-59 months Percent Number of Percent with Number of Percent with Number of Measles Measles with children Measles Vaccination children age Vaccination children age Vaccination Vaccination Vaccination age 12-23 Vaccination Card Seen 12-59 months Card Seen 24-59 months Card Seen months
State Adamawa (833) 87.3 (222) 23.3 954 (178) 85.0 (60) 30.3 209 (655) 88.0 (162) 23.4 745 [80.5,92.0] [17.9,29.6] [76.0,91.0] [22.4,39.5] [81.6,92.3] [17.7,30.2] Borno (2187) 86.0 (470) 18.5 2543 (508) 84.8 (145) 22.7 596 (1679) 86.3 (325) 14.5 1947 [81.9,89.3] [14.6,23.1] [79.5,88.9] [17.1,29.5] [81.3,90.1] [11.2,18.7] Yobe (1237) 75.9 (306) 18.8 1629 (277) 72.4 (93) 24.6 390 (960) 78.7 (213) 18 1239 [69.1,81.7] [13.9,24.9] [63.6,79.7] [17.6,33.2] [71.5,84.5] [12.8,24.6] Domain S. Adamawa (417) 87.4 (56) 11.7 477 (89) 86.4 (18) 17.5 103 (328) 87.7 (38) 10.2 374 [74.2,94.4] [7.1,18.8] [69.6,94.6] [8.5,32.5] [74.2,94.6] [5.9,16.9] N. Adamawa (416) 87.2 (166) 34.8 477 (89) 84 (42) 39.6 106 (327) 88.1 (124) 33.4 371 [80.3,92.0] [25.6,45.3] [72.3,91.3] [27.9,52.6] [81.4,92.7] [24.3,44.0] Northern Borno (278) 72.6 (31) 8.1 383 (53) 62.4 (10) 11.8 85 (225) 75.5 (21) 7 298 [60.7,81.9] [4.0,15.7] [48.6,74.4] [4.5,27.5] [62.4,85.1] [3.6,13.3] Southern Borno (435) 90.6 (142) 29.6 480 (85) 91.4 (31) 33.3 93 (350) 90.4 (111) 28.7 387 [79.8,95.9] [18.7,43.4] [79.5,96.7] [20.2,49.7] [79.3,95.9] [17.7,43.0] East Borno (544) 89.0 (138) 11 611 (135) 91.8 (44) 29.9 147 (409) 88.1 (94) 20.3 464 [79.4,94.5] [13.5,35.2] [81.5,96.6] [17.5,46.2] [78.1,93.9] [11.7,32.7] Central Borno (399) 81.8 (65) 13.3 488 (104) 81.3 (25) 19.5 128 (295) 81.9 (40) 11.1 360 [69.2,90.0] [7.5,22.6] [66.4,90.5] [10.1,34.4] [69.0,90.2] [6.3,18.9] MMC & Jere (531) 91.4 (94) 16.2 581 (131) 91.6 (35) 24.5 143 (400) 91.3 (59) 13.5 438 [82.7,95.9] [10.0,25.1] [84.0,95.8] [15.0,37.3] [81.2,96.2] [7.9,22.0] Central Yobe (416) 77.6 (115) 21.5 536 (102) 75.6 (34) 25.2 135 (314) 78.3 (81) 20.2 401 [66.0,86.1] [13.0,33.2] [61.6,85.6] [14.1,40.9] [66.2,86.9] [12.3,31.4] Southern Yobe (440) 79.4 (115) 20.8 554 (95) 74.8 (33) 26 127 (345) 80.8 (82) 19.2 427 [68.5,87.3] [13.1,31.3] [60.7,85.1] [15.9,39.5] [69.7,88.5] [11.7,29.8] Northern Yobe (381) 70.7 (76) 14.1 539 (80) 62.5 (26) 20.3 128 (301) 73.2 (50) 12.2 411 [56.5,81.8] [7.1,26.0] [46.5,76.1] [10.1,36.7] [58.7,84.1] [5.9,23.5]
Figure 1: Percentage of children age 12-59 months vaccinated against measles, by domain
3.5.2 Diarrhoea, Oral Rehydration Therapy and Zinc Supplementation
Mothers (or caregiver) were asked whether any of their children under five had diarrhoea at any time during the preceding two weeks. If yes, the mother was asked if the child was given ORS and/or Zinc. ORS includes only commercial varieties, not home formulations. As both the symptoms of diarrhoea and treatment are based on maternal recall, the validity of this indicator may be affected by recall biases.
Two-week prevalence of diarrhoea was highest in Borno (11.2%) followed by Yobe (8.6%) and Adamawa (7.4%). By domain, prevalence was highest in MMC & Jere (14.4%) followed by Central Borno (11.4%). Overall, there was no significant difference between males (9.2%) than females (10.0%). Table 22 shows the percent of children with symptoms of diarrhoea in the two weeks preceding the survey as well as receipt of ORS and/or Zinc among the children with diarrhoea symptoms.
Less than 25% of children with symptoms of diarrhoea in Borno (22.0%) received treatment with both ORS and zinc, this is more than three times the number in Adamawa (6.3%) and nearly six times that in Yobe (4.5%). The proportion of children receiving ORS was higher than the proportion receiving zinc in all three states: Adamawa (23.6% and 6.3%, respectively), Borno (24.6% and 22.0%, respectively) and Yobe (22.6% and 4.5%, respectively). These estimates represent an improvement in clinical management of diarrhoea relative to that observed in the NFSS Round 7, especially in Borno.
By domain, the proportion of children of children with symptoms of diarrhoea receiving ORS ranged from 13.5% (Northern Adamawa) to 61.2% (East Borno). For children receiving zinc, the range was 2.0% (Southern Adamawa) to 27.7% (MMC & Jere).
The finding that coverage of ORS is higher than zinc in children with symptoms of diarrhoea is consistent with findings from previous national surveys as well Rounds 1 to 7 of the NFSS. It could be attributed to greater caregiver knowledge of ORS than zinc supplementation.
Table 22 Percentage of Children Age 0-59 Months with Diarrhoea In the Previous Two Weeks Who Received Oral Rehydration Salts (ORS) Or Zinc, By Sex, Age, State and Domain Number of Had Number of children age 0-59 months Number children age 0- diarrhea with diarrhea in the last two weeks: of 59 months with in the children Oral diarrhoea in last two age 0-59 rehydration Zinc Both the last two weeks months salts (ORS) weeks
Sex Male (298) 9.2 3287 (120) 42.5 (50) 18.8 (43) 15.8 298 [7.6,11.0] [35.2,50.2] [12.4,27.4] [9.9,24.0] Female (290) 10 3129 (101) 40 (45) 17.4 (35) 13.8 290 [8.1,12.3] [32.1,48.4] [10.6,27.1] [7.6,23.6] Age in months 0-5 (17) 3 638 (1) 2.9 (0) 0.0 (0) 0.0 17 [1.7,5.4] [0.4,18.1] [0.0- 0.0] [0.0- 0.0] 6-11 (68) 10.4 646 (23) 37.6 (7) 13.2 (6) 11.2 68 [7.8,13.8] [24.8,52.4] [6.1,26.1] [4.8,23.9] 12-23 (115) 9.6 1195 (46) 42.7 (19) 19.8 (18) 18.5 115 [7.3,12.5] [32.4,53.7] [11.5,31.9] [10.4,30.9] 24-35 (141) 10.4 1425 (55) 43.6 (23) 17.4 (40) 15.2 141 [8.2,13.2] [33.4,54.5] [9.8,29.0] [8.4,26.1] 36-47 (125) 10.3 1271 (52) 45.6 (22) 20.1 (17) 15.1 125 [7.8,13.5] [34.2,57.5] [11.7,32.3] [8.0,26.9] 48-59 (122) 10.7 1235 (44) 40.2 (24) 20.2 (17) 14.4 122 [8.3,13.9] [30.5,50.7] [12.2,31.8] [7.7,25.5] State Adamawa (88) 7.4 1166 (22) 23.6 (8) 10.4 (5) 6.3 88 [5.2,10.5] [15.1,35.0] [5.4,19.0] [2.7,14.1] Borno (318) 11.2 3199 (163) 52.4 (72) 24.6 (64) 22 318 [8.5,14.6] [42.9,61.7] [14.4,38.7] [12.6,35.5] Yobe (182) 8.6 2054 (36) 22.6 (15) 9 (9) 4.5 182 [6.0,12.2] [12.7,36.9] [4.7,16.8] [2.3,8.6] Domain S. Adamawa (51) 8.5 598 (17) 33.3 (1) 2.0 (1) 2.0 51 [5.4,13.3] [20.1,49.8] [0.3,13.1] [0.3,13.1] N. Adamawa (37) 6.5 568 (5) 13.5 (7) 19.4 (4) 10.8 37 [3.8,11.1] [6.3,26.8] [8.5,38.7] [3.9,26.6] Northern Borno (30) 6.1 493 (8) 26.7 (6) 20 (5) 16.7 30 [3.1,11.4] [13.3,46.3] [9.2,38.1] [6.7,35.8] Southern Borno (49) 8.3 592 (19) 38.8 (5) 10.2 (3) 6.1 49 [5.4,12.6] [21.2,59.8] [3.4,26.6] [2.0,17.3] East Borno (67) 8.5 790 (41) 61.2 (15) 22.4 (14) 20.9 67 [5.0,14.1] [42.9,76.8] [11.1,39.9] [10.1,38.4] Central Borno (70) 11.4 615 (32) 45.7 (18) 25.7 (16) 22.9 70 [6.9,18.2] [30.9,61.4] [9.5,53.4] [7.7,51.4] MMC & Jere (102) 14.4 709 (63) 61.8 (28) 27.7 (26) 25.5 102 [9.1,22.0] [45.9,75.5] [11.9,52.0] [11.2,48.3] Central Yobe (61) 8.9 685 (11) 18 (5) 8.2 (5) 8.2 61 [5.0,15.2] [7.8,36.4] [3.6,17.7] [3.6,17.7] Southern Yobe (57) 8.2 691 (16) 28.1 (6) 10.5 (2) 3.5 57 [4.6,14.4] [13.0,50.4] [3.9,25.2] [1.0,12.0] Northern Yobe (64) 9.4 678 (9) 14.1 (4) 6.3 (2) 3.1 64 [5.9,14.8] [6.6,27.4] [1.8,19.3] [0.8,12.0]
3.5.3 Acute Respiratory Infection (ARI) and Treatment
Among children under five years of age, the rates for ARI symptoms during the two weeks preceding the survey were highest in Borno (2.5%), followed by Yobe (1.8%) and Adamawa (1.5%). Nearly half of the children in Adamawa, Borno and Yobe (42.6%, 36.0% and 41.4%, respectively) received antibiotics (see table 23).
Prescription of antibiotics varied greatly by domain. Less than one in five children with symptoms of ARI in Northern Borno (12.5%) received antibiotics compared to three in five children in Southern Adamawa (66.7%) and Northern Yobe (66.7%). These differences do not correspond with major differences in receipt of any medication (including antibiotics as well as paracetamol, aspirin, ibuprofen, and other medications). No major differences in two-week prevalence or receipt of antibiotics were observed by gender. Antibiotic treatment was least prevalent among children aged 0-5 months (20.9%).
Table 23: Percentage of Children Age 0-59 Months with Symptoms ARI in The Previous Two Weeks Who Received Antibiotics, By Sex, Age, State and Domain Number of children age Symptoms Number 0-59 months with Number of of ARI in of symptoms of ARI in the children age 0- the last children last two weeks given: 59 months with two age 0-59 Any symptoms of weeks months medicatio Antibiotics ARI n Sex Male (51) 1.7 3287 (37) 72.9 (19) 32.8 51 [1.1,2.5] [61.6,81.9] [21.6,46.5] Female (63) 2.3 3129 (48) 76.3 (25) 42.4 63 [1.6,3.2] [64.1,85.4] [31.1,54.7] Age in months 0-5 (11) 2 638 (6) 48.4 (3) 20.9 11 [1.1,3.6] [20.2,77.7] [5.3,55.5] 6-11 (10) 1.7 646 (8) 78.9 (4) 40.3 10 [0.9,3.3] [42.2,95.0] [13.5,74.6] 12-23 (19) 1.8 1195 (14) 72.5 (10) 52.2 19 [1.0,3.3] [45.4,89.3] [21.9,81.0] 24-35 (30) 2.1 1425 (24) 80.3 (11) 35.3 30 [1.3,3.2] [58.1,92.3] [21.6,51.8] 36-47 (20) 1.8 1271 (15) 76.8 (7) 32.2 20 [1.1,3.0] [54.3,90.3] [15.5,55.3] 48-59 (24) 2.3 1235 (18)79.5 (9) 42.6 24 [1.2,4.2] [63.3,89.7] [22.6,65.4] State Adamawa (16) 1.5 1166 (9) 54.1 (7) 42.6 16 [0.8,2.8] [22.9,82.4] [14.3,76.9] Borno (65) 2.5 3199 (51) 78.4 (22) 36 65 [1.5,4.0] [68.2,86.0] [25.7,47.7] Yobe (33) 1.8 2054 (25) 71.1 (15) 41.4 33 [0.9,3.3] [55.1,83.1] [22.9,62.7] Domain S. Adamawa (3) 0.5 598 (3) 100 (2) 66.7 3 [0.2,1.5] [9.0,97.6] N. Adamawa (13) 2.3 568 (6) 46.2 (5) 38.5 13 [1.1,4.7] [15.0,80.7] [10.0,77.9] Northern Borno (8) 1.6 493 (1) 12.5 (1) 12.5 8 [0.8,3.5] [1.8,53.3] [1.8,53.3] Southern Borno (7) 1.2 592 (6) 85.7 (3) 42.9 7 [0.5,2.6] [34.7,98.5] [10.6,82.6] East Borno (10) 1.3 790 (10) 100 (3) 30 10 [0.7,2.4] [10.4,61.4] Central Borno (18) 2.9 615 (16) 88.9 (5) 27.8 18 [1.1,7.4] [69.9,96.5] [18.9,38.9] MMC & Jere (22) 3.1 709 (18) 81.8 (10) 45.5 22 [1.4,6.8] [62.7,92.3] [25.6,66.8] Central Yobe (10) 1.5 685 (8) 80 (4) 40 10 [0.7,3.0] [50.2,94.1] [12.4,75.8] Southern Yobe (14) 2 691 (9) 64.3 (5) 35.7 14 [0.8,4.9] [42.9,81.2] [16.0,61.9] Northern Yobe (9) 1.3 678 (8) 88.9 (6) 66.7 9 [0.6,3.1] [40.8,98.9] [23.7,92.8]
3.5.4 Fever, Prevention of Malaria, and Antimalarial Treatment Among all children with symptoms of fever, receipt of antimalarial medications was highest in Borno (40.9%) followed by Yobe (34.5%) and Adamawa (28.9%). However, less than 20% of all children receiving antimalarial treatment received ACT, the first-line treatment for malaria in Nigeria. Receipt of ACT in Yobe (6.5%) was nearly five times that of Adamawa (1.5%) and nearly twice that of Borno (1.5%). The proportion of children receiving ACT varied by domain ranging from 1.5% in 2 domains of Adamawa to 14.5% in East Borno. Table 24 shows the proportion of children receiving any antimalarial medication including SP/Fansidar, Chloroquine, Amodiaquine, Quinine, ACT, or any other anti-malarial.
The use of antimalarial treatment (including ACT) increased with age, from 8.5% among children less than 6 months of age to 39.0% for children above 4 years of age, while antibiotic treatment is quite stable at around (10.4 to 26.1%) for all age cohorts above 5 months. No significant difference was noted between boys and girls receiving appropriate antimalarial drugs.
These findings suggest that despite national programs, adequate clinical management of malaria with first line treatment remains below the national target of 80% as specified in the National Malaria Strategic Plan13.
13 Federal Ministry of Health. 2011. National Policy on Malaria Diagnosis and Treatment.
Table 24: Percentage of Children Age 0-59 Months with Fever in The Last Two Weeks Who Were Tested for Malaria Using Rapid Diagnostic Test (RDT) and/or Received Anti-Malarial, By Sex, Age, State and Domain Number of children age 0-59 months with fever in No. of No. the last two weeks who: children age Had fever children Had blood 0-59 months in the last age 0- taken from Were given Were Were given with fever in two weeks 59 a finger or anti- given ACT antibiotics the last two months heel for malarial weeks testing
Sex Male (373) 11.4 3287 (39) 12.1 (131) 36.9 (16) 3.6 (47) 12.3 373 [9.8,13.4] [7.6,18.5] [30.7,43.6] [2.0,6.3] [8.1,18.1] Female (341) 11.5 3129 (30) 9.7 (116) 37.1 (21) 6.5 (54) 15.9 341 [9.8,13.4] [6.1,15.2] [31.1,43.5] [3.9,10.8] [10.9,22.5] Age in months 0-5 (22) 3.9 638 (1) 6.6 (2) 8.5 (0) 0.0 (1) 5.2 22 [2.4,6.0] [0.9,35.1] [1.8,32.4] [0.7,30.0] 6-11 (53) 7.7 646 (2) 6.2 (13) 29.5 (2) 4.2 (13) 26.1 53 [5.7,10.3] [1.5,21.8] [17.1,45.9] [0.9,17.1] [15.2,41.1] 12-23 (134) 11.0 1195 (14) 13.2 (50) 39.2 (12) 8.2 (18) 12.8 134 [8.9,13.5] [7.5,22.0] [30.8,48.3] [4.2,15.5] [7.9,20.2] 24-35 (183) 13.4 1425 (17) 9.8 (69) 39.8 (7) 3.9 (25) 12.9 183 [11.2,16.0] [5.1,17.9] [31.6,48.5] [1.7,8.5] [8.5,19.1] 36-47 (175) 13.9 1271 (17) 9.2 (60) 36.5 (8) 3.6 (17) 10.4 175 [11.4,16.8] [4.7,17.2] [29.4,44.3] [1.7,7.4] [4.9,20.5] 48-59 (147) 13.0 1235 (18) 14.4 (53) 39.0 (8) 6.2 (27) 18.1 147 [10.5,15.9] [8.9,22.5] [31.8,46.8] [2.9,12.5] [10.7,28.8] State Adamawa (134) 11.6 1166 (10) 7.4 (40) 28.9 (2) 1.5 (21) 14.9 134 [8.8,15.1] [3.6,14.8] [19.9,40.0] [0.4,6.0] [9.0,23.8] Borno (335) 11.4 3199 (937) 12.1 (129) 40.9 (20) 4.9 (40) 11.9 335 [9.3,13.9] [7.8,18.5] [34.6,47.6] [2.6,8.8] [7.0,19.3] Yobe (245) 12 2054 (22) 9.2 (78) 34.5 (15) 6.5 (40) 14.7 245 [9.4,15.2] [4.2,19.1] [27.7,42.0] [2.9,13.9] [9.4,22.4] Domain S. Adamawa (66) 11 598 (5) 7.6 (24) 36.4 (1) 1.5 (14) 21.2 66 [7.2,16.5] [2.3,22.5] [20.3,56.1] [0.2,11.1] [11.7,35.3] N. Adamawa (68) 12 568 (5) 7.4 (16) 23.5 (1) 1.5 (7) 10.3 68 [8.4,16.9] [3.0,17.1] [14.7,35.5] [0.2,9.6] [4.7,21.2] Northern (44) 8.9 493 (3) 6.8 (12) 27.3 (2) 4.5 (2) 4.5 44 Borno [5.9,13.4] [2.2,18.9] [16.6,41.4] [0.7,25.4] [1.2,15.5] Southern (71) 12 592 (13) 18.3 (29) 40.8 (3) 4.2 (17) 23.9 71 Borno [7.7,18.3] [5.5,46.4] [27.5,55.7] [1.3,12.5] [8.3,52.2] East Borno (55) 7 790 (2) 3.6 (17) 30.9 (8) 14.5 (3) 5.5 55 [3.9,12.1] [1.0,11.9] [18.8,46.3] [4.6,37.7] [1.5,17.6] Central Borno (86) 14 615 (4) 4.7 (32) 37.2 (2) 2.3 (8) 9.3 86 [10.0,19.2] [1.4,14.7] [26.1,49.8] [0.5,9.7] [4.1,19.7] MMC & Jere (79) 11.1 709 (15) 19 (39) 49.4 (5) 6.3 (10) 12.7 79 [7.4,16.3] [11.3,30.2] [37.7,61.1] [2.4,15.8] [4.9,29.0] Central Yobe (85)12.4 685 (11) 12.9 (23) 27.1 (4) 4.7 (14) 16.5 85 [8.0,18.8] [4.8,30.3] [15.8,42.3] [1.3,15.6] [5.7,38.9] Southern Yobe (84) 12.2 691 (8) 9.5 (33) 39.3 (6) 7.1 (10) 11.9 84 [8.4,17.3] [2.8,27.9] [30.0,49.4] [2.3,19.9] [5.9,22.5] Northern Yobe (76) 11.2 678 (3) 3.9 (22) 28.9 (5) 6.6 (16) 21.1 76 [7.8,15.9] [1.4,10.4] [17.1,44.6] [1.3,28.1] [11.4,35.6]
Use of mosquito nets, particularly long-lasting insecticide-treated bed nets, is an important preventive measure to reduce incidence of malaria. In order to achieve universal coverage in 2009, Nigeria started the National Malaria Control Strategic Plan (NMCSP) which include a coordinated strategy to deliver two nets to every household across the country. Seasonal malaria chemoprevention (SMC) is recommended by WHO for children during the malaria season in areas of highly seasonal transmission.
Survey respondents were asked whether they possess any type of mosquito net in their household and, if so, how many. The findings are presented in Table 25 For households with children, caregivers were asked whether each child aged 0-59 months had received any pills or syrup to prevent malaria and whether they had slept under a bednet during the night preceding the survey. These findings are presented in Table 26.
The results indicate that more than 80 percent of households in Yobe (81.3%), more than 70 percent of households in Adamawa (73.6%) and 55 percent in Borno (55.1%) possess at least one mosquito net. However, less than half of the households have the recommended number of bednets (one net per two persons) with only 24.7% HHS in Borno, 47.0% HHs in Yobe, and 39.1% HHs in Adamawa. Among children residing in households with bednets, about three in four slept under a bednet during the night preceding the survey with 73.8% in Yobe, and 63.5% in Adamawa. Utilization did not vary notably by age cohort (range: 72.8-75.9%). No significant difference in utilization of bednets was observed by gender. However, there remains a need for both improved coverage of bednets as well as education on utilization given evidence of households where bednets were not currently in use by children.
All caregivers of children aged 0-59 months were asked whether they received seasonal malaria chemoprevention for malaria. In Nigeria, SMC/IPT is generally taken for three days at the beginning of the month. Coverage of SMC was highest in Adamawa (13.2%) followed by Yobe (12.2%) and Borno (11.2%). By domain, coverage ranged from 18.7% (East Borno) to as low as 2.6% (Northern Borno). Coverage was slightly higher among children aged 48-59 months (16.9%, range: 2.5-16.9%). No significant differences in SMC coverage were observed by gender.
Table 25: Households Ownership of Mosquito Nets, By State and Domain
Percent of households with at least: Number of households One Mosquito Net per Two One Mosquito Net Persons
State Adamawa (1017) 73.6 (541) 39.1 1381 [66.7,79.5] [33.3,45.2] Borno (1932) 55.1 (859) 24.7 3661 [49.8,60.3] [21.3,28.3] Yobe (1722) 81.3 (1000) 47.0 2059 [73.8,87.1] [41.1,53.0] Domain S. Adamawa (524) 75.1 (292) 41.8 698 [65.2,82.9] [32.5,51.8] N. Adamawa (493) 72.2 (249) 36.5 683 [62.1,80.4] [29.7,43.8] Northern Borno (295) 42 (141) 20.1 702 [30.1,54.9] [13.1,29.6] Southern Borno (436) 71.9 (219) 36.1 606 [59.8,81.6] [27.1,46.3] East Borno (464) 53.4 (192) 22.1 869 [43.4,63.1] [15.6,30.4] Central Borno (291) 42.4 (133) 19.4 686 [30.8,54.9] [13.2,27.6] MMC & Jere (446) 55.9 (174) 21.8 798 [45.2,66.1] [17.0,27.6] Central Yobe (594) 86.7 (360) 52.6 685 [77.0,92.7] [44.1,60.8] Southern Yobe (520) 77.3 (297) 44.1 673 [64.8,86.3] [34.9,53.8] Northern Yobe (608) 86.7 (343) 48.9 701 [75.3,93.3] [41.1,56.8]
Table 26: Percentage of Children Age 0-59 Months Receiving Seasonal Malaria Chemoprevention and Percent Who Slept Under A Mosquito Net the Night Before the Survey, By Sex, Age, State and Domain Number of children age 0-59 Received Seasonal months who slept under a bed-net Number of Malaria last night: children age Chemoprevention Among children in Among all 0-59 months (SMC) home with at children least on bed-net
Sex Male (396) 12.0 (1966) 58.8 (1913) 81.3 3287 [9.2,15.5] [54.4,63.1] [77.9,84.3] Female (392) 12.4 (1900) 58.4 (1850) 81.9 3129 [9.8,15.5] [53.9,62.7] [78.4,84.9] Age in months 0-5 (18) 2.5 (366) 54.0 (356) 75.6 638 [1.3,4.6] [48.1,59.8] [70.1,80.4] 6-11 (47) 6.4 (369) 55.5 (355) 79.4 646 [4.4,9.1] [49.3,61.6] [73.5,84.2] 12-23 (148) 11.9 (702) 57.2 (687) 82.4 1195 [8.9,15.9] [52.1,62.2] [78.0,86.0] 24-35 (197) 13.7 (879) 60.0 (859) 83.4 1425 [10.7,17.5] [55.1,64.6] [79.8,86.4] 36-47 (171) 13.7 (777) 59.9 (757) 82.8 1271 [10.5,17.8] [55.1,64.6] [78.8,86.2] 48-59 (205) 16.9 (773) 60.9 (7490 82 1235 [13.2,21.3] [56.2,65.4] [77.7,85.6] State Adamawa (147) 13.2 (738) 63.6 (718) 79.1 1166 [8.8,19.4] [55.6,70.9] [72.5,84.5] Borno (386) 11.2 (1561) 47.4 (1501) 79.7 3199 [8.3,14.9] [41.4,53.4] [74.8,83.8] Yobe (256) 12.2 (1568) 73.8 (1545) 84.2 2054 [7.1,20.2] [65.5,80.6] [78.4,88.7] Domain S. Adamawa (50) 8.4 (368) 61.5 (355) 76.5 598 [4.0,16.5] [50.7,71.3] [67.6,83.6] N. Adamawa (97) 17.1 (370) 65.3 (363) 81.2 568 [10.4,26.8] [53.6,75.4] [71.1,88.4] Northern Borno (13) 2.6 (188) 38.1 (182) 74.6 493 [1.0,6.8] [25.9,52.1] [59.4,85.5] Southern Borno (72) 12.2 (400) 67.6 (383) 85.1 592 [5.4,25.1] [52.7,79.6] [72.9,92.4] East Borno (148) 18.7 (384) 48.7 (373) 80.6 790 [9.0,34.9] [36.6,60.8] [72.1,86.9] Central Borno (38) 6.2 (225) 36.6 (217) 72.3 615 [2.9,12.6] [25.4,49.5] [59.1,82.5] MMC & Jere (115) 16.2 (364) 51.3 (346) 83 709 [10.5,24.1] [40.5,62.1] [75.1,88.7] Central Yobe 9.1 (542) 79.2 (532) 86.8 685 [3.9,19.7] [68.7,86.9] [78.7,92.1] Southern Yobe (82) 11.9 (475) 68.8 (468) 81.5 691 [4.9,26.2] [55.3,79.8] [71.4,88.6] Northern Yobe (112) 16.5 (551) 81.4 (545) 88.2 678 [8.5,29.6] [70.5,88.9] [79.1,93.6]
3.6 Maternal Nutrition Malnutrition in women of reproductive age (15 to 49 years) has important implications for both her health, her unborn infant, and that of her children. Malnourished women experience increased susceptibility to infections, slow recovery from illness, and a heightened risk of adverse pregnancy outcomes.
The nutritional status of non-pregnant women of reproductive age was assessed using MUAC. The measurement of MUAC is commonly used as an indicator of malnutrition and wasting in children. MUAC can be used as an indicator of maternal nutritional status in non-pregnant women because of its high correlation with maternal weight and weight-for-height. Increases in MUAC measurement during pregnancy are generally less than 0.5 cm; therefore, the survey used MUAC to also measure undernutrition in pregnant women.
There is no global standard or agreement for MUAC thresholds for pregnant and non-pregnant women (15 to 49 years). Based on the Nigeria FMOH guidance, women with MUAC < 221 mm were classified as acutely malnourished, MUAC between 214 to 221 mm was classified as moderately malnourished, and MUAC less than 214 mm was classified as severely malnourished.
Prevalence of severe malnutrition was highest among women of reproductive age in Yobe (9.7%) followed by Borno (5.9%) and Adamawa (4.6%). Prevalence of acute malnutrition was also highest in Yobe (15.0%). By domain, prevalence of acute malnutrition was highest in Northern and Central Yobe. In adolescent girls (15 to 19 years), the prevalence of acute malnutrition was five times higher than adult women (20 to 49 years) at 29.5% compared to 5.9%. (Table 27).
Table 27: Acute Malnutrition by MUAC Among Women of Reproductive Age (15-49 Years), By Age, State and Domain Number of women age MUAC in millimeters 15-49 years
≤ 221 mm < 214 mm
% % Age Group 15-19 years (514) 29.5 (319) 18.4 1735 [26.8,32.4] [16.0,20.9] 20-49 years (330) 5.9 (177) 3.1 5584 [5.1,6.7] [2.6,3.8] State Adamawa (145) 9.5 (71) 4.6 1519 [7.8,11.5] [3.4,6.4] Borno (373) 10.3 (214) 5.9 3623 [9.1,11.6] [4.9,7.1] Yobe (326) 15 (211) 9.7 2177 [12.8,17.5] [7.9,11.7] Domain S. Adamawa (60) 8.3 (29) 4.0 725 [6.0,11.3] [2.5,6.4] N. Adamawa (85) 10.7 (42) 5.3 794 [8.3,13.7] [3.4,8.1] Northern Borno (70) 12.2 (40) 7.0 572 [9.4,15.8] [4.9,9.9] Southern Borno (58) 8.1 (34) 4.7 717 [6.0,10.9] [2.9,7.7] East Borno (65) 8.4 (28) 3.6 776 [6.7,10.4] [2.4,5.5] Central Borno (74) 11.7 (43) 6.8 631 [9.3,14.6] [4.8,9.7] MMC & Jere (106) 11.4 (69) 7.4 927 [8.8,14.8] [5.3,10.3] Central Yobe (116) 15.2 (74) 9.7 764 [11.6,19.7] [7.0,13.2] Southern Yobe (101) 14 (63) 8.7 723 [10.3,18.7] [5.5,13.4] Northern Yobe (109) 15.8 (75) 10.7 690 [12.4,19.9] [8.4,13.6]
3.6.1 Minimum Dietary Diversity for Women In the context of an emergency, diets can be dominated by one or a few staple foods given constraints on food choices. Poor dietary diversity has been shown to be associated with poor micronutrient adequacy of diets14. In the survey, dietary diversity was measured to assess micronutrient adequacy among women of reproductive age (15 to 49 years). This group is nutritionally vulnerable because of the physiological demands of pregnancy and lactation. The Minimum Dietary Diversity in Women (MDD-W) indicator can be understood as a measure of whether women are receiving adequate amounts of the recommended vitamins and minerals. The MDD-W was developed as a proxy indicator to reflect the micronutrient adequacy of women’s diets, a contrast to the household dietary diversity (HDDS) indicator that measures household-level access to kilo-calories (dietary energy).
One randomly selected woman of reproductive age in each household containing at least one eligible woman was surveyed. Selection was done automatically on the tablets, and sample weights were adjusted accordingly. Women were asked about consumption of different food groups during the day prior to the survey. Foods were then re-categorized into 10 food groups: (1) grains, white roots and tubers, plantains, (2) pulses, (3) nuts and seeds, (4) dairy, (5) meat, poultry and fish, (6) eggs, (7) dark green leafy vegetables, (8) other vitamin A-rich fruits, (9) other vegetables, and (10) other fruits. The MDD-W indicator is a dichotomous indicator of whether a woman has consumed at least five out of the ten defined food groups15.
The proportion of women of reproductive age meeting minimum dietary diversity was highest in Adamawa (47.2%) followed by Borno (34.1%) and Yobe (29.1%). Of the ten food groups assessed, the mean number consumed during the day preceding the survey by women of reproductive age was less than five in all three states with 4.57% in Adamawa, 4.07% in Borno, and 3.98% in Yobe. The proportion of women of reproductive age consuming iron rich foods was lowest in Borno (36.4%) while the proportion consuming vitamin A rich foods was lowest in Adamawa (62.6%).
By domain, the proportions consuming iron rich food, and the proportion consuming vitamin A rich foods were all lowest in East Borno (21.0%), Northern Borno (25.0%) and Northern Adamawa (57.4%). (Table 28). For all domains, the proportion of women consuming Vitamin A rich foods during the day preceding the survey was higher than the proportion consuming iron rich foods.
The proportion of women meeting minimum dietary diversity, consuming iron rich foods, and consuming Vitamin A rich foods were all slightly higher among adolescent girls (15-19 years) than adult women (20-49 years). This was a contrast to the pattern of acute malnutrition as measured by MUAC.
14 Martin-Prevel, Y, Allemand, P, Wiesmann, D, et al. 20015. Moving Forward: On choosing a standard operational indicator for women’s dietary diversity. Available at: http://www.fao.org/3/a-i4942e.pdf
15 Food and Agricultural Organization (FAO) and FHI 360. 2016. Minimum Dietary Diversity for Women: A Guide for Measurement. Rome: FAO. Available at: http://www.fao.org/3/a-i5486e.pdf
Table 28: Dietary Diversity Among Women of Reproductive Age (15-49 Years), By Age, State and Domain Percentage of women 15-49 years: Meeting Minimum Mean number of Consuming Number of Dietary Consuming food groups vitamin A women age Diversity for iron rich foods consumed rich foods 15-49 years Women of yesterday yesterday (of 10) yesterday Reproductive Age (MDD-W)*
Age Group 15-19 years (393) 40.8 (429) 42.2 (67) 63.3 4.20 1109 [34.2,47.8] [37.3,47.1] [58.0,68.2] 20-49 years (1445) 37.7 (1675) 40.3 (2943) 67 4.13 4414 [33.2,42.3] [36.9,43.7] [63.1,70.6] State Adamawa (519) 47.2 (566) 51.4 (687) 62.6 4.57 1101 [39.7,54.9] [44.0,58.8] [54.4,70.2] Borno (887) 34.1 (935) 36.4 (1941) 67.7 4.07 2839 [29.2,39.3] [32.2,40.7] [62.4,72.5] Yobe (432) 29.1 (603) 40.5 (1045) 65.8 3.98 1583 [22.9,36.2] [33.6,47.8] [58.0,72.9] Domain S. Adamawa (271) 50.4 (337) 63.4 (365) 67.7 4.54 545 [40.8,60.0] [53.4,72.3] [56.7,77.0] N. Adamawa (248) 44.0 (229) 39.0 (322) 57.4 4.60 556 [32.5,56.0] [28.7,50.5] [44.8,69.2] Northern Borno (110) 24.1 (120) 25.0 (368) 74.1 3.70 500 [16.0,34.7] [17.5,34.4] [61.5,83.7] Southern Borno (255) 53.9 (202) 43.4 (314) 63.3 4.63 494 [42.2,65.2] [32.8,54.7] [49.9,75.0] East Borno (142) 21.0 (189) 28.4 (409) 62.2 3.65 662 [13.4,31.4] [19.9,38.6] [50.6,72.7] Central Borno (131) 25.1 (131) 25.2 (395) 73.8 3.67 530 [16.5,36.2] [17.0,35.7] [61.8,83.1] MMC & Jere (249) 39.3 (293) 47.3 (455) 68.8 4.36 653 [28.7,51.0] [39.8,55.0] [58.5,77.5] Central Yobe (155) 31.2 (246) 48.3 (357) 66.4 4.06 536 [20.0,45.0] [35.4,61.4] [52.8,77.7] Southern Yobe (149) 30.3 (164) 33.1 (341) 66.0 4.07 516 [20.2,42.8] [22.9,45.1] [51.4,78.0] Northern Yobe (128) 25.4 (193) 39.1 (347) 65.1 3.79 531 [17.2,35.8] [28.2,51.2] [51.7,76.5]
3.7 Public Health Interventions that Prevents against Malnutrition
3.7.1 Deworming, Vitamin A and Micronutrient Powder (MNP) Helminths are a group of parasites including schistosomiases and soil-transmitted helminths. They can impair nutritional status by causing internal bleeding which can lead to loss of iron and anaemia; malabsorption of nutrients; diarrhoea and loss of appetite. The nutritional impairment caused by schistosome and soil-transmitted helminth infections during childhood has been shown to have a significant impact on growth and development of children. Periodic deworming of children can reduce the transmission of schistosome and soil-transmitted helminth infections.
UNICEF recommends a minimum coverage threshold of 70 percent at which countries can expect to observe reductions in child mortality from this intervention. Deworming medications are distributed as part of the MNHCW campaigns (conducted twice a year in Borno State) as well as part of routine health care at facilities.
Surveyed mothers or caregivers were asked whether their children aged 12-59 months had received any deworming medication in the six months preceding the survey. A child was recorded as having received treatment if the caregiver reported receipt of anthelminthic drug. No distinction was made between receipt of anthelminthic drugs as part of the MNHCW campaign and other distribution methods.
MNP coverage was reported well below the recommended threshold at 11.0% in Adamawa, 15.2% in Borno, and 11.1% in Yobe. Coverage gradually increased with age, with the highest among children aged 48-59 months (15.9%) but lowest among children aged 12-23 months (11.5%). Coverage was slightly higher among boys (14.8%) than girls (12.4%). MNP coverage was extremely low in the three states: Adamawa – 5.4%, Borno – 6.9% and Yobe – 5.3%. Vitamin A coverage amongst children 6-59 of age is also low with only one of every three children receiving supplementation: 30.6% in Adamawa, 28.4% in Borno and 30.5% in Yobe. (Table 29).
Table 29: Percentage of Children Receiving Vitamin A, Anthelminthic Drug, And MNP In the Past 6 Months by Sex, Age and Location Children age 6-59 Children age 12-59 Children age 6-23 months months given months given an given micronutrient Vitamin A anthelminthic drug powders (MNP) % [CI] N % [CI] N % [CI] N Sex Male (868) 31.0 2939 (382) 14.8 2619 (44) 5.0 931 [26.4,36.0] [11.7,18.5] [3.2,7.6] Female (820) 29.2 2830 (318) 12.4 2504 (67) 8.5 909 [24.6,34.3] [9.6,15.9] [5.8,12.1] Age in months 6-11 (127) 18.3 646 - - (44) 7.7 646 [14.6,22.7] [5.1,11.6] 12-23 (343) 28.4 1195 (146) 11.5 1195 (67) 6.1 1195 [23.7,33.6] [8.8,14.8] [4.1,8.9] 24-35 (429) 30.5 1425 (208) 14.4 1425 - - [25.7,35.8] [11.2,18.5] 36-47 (384) 30.9 1271 (158) 12.5 1271 - - [26.0,36.3] [9.5,16.3] 48-59 (435) 36.3 1235 (189) 15.9 1235 - - [30.6,42.4] [12.1,20.6] State Adamawa (299) 30.6 1053 (103) 11.0 954 (18) 5.4 308 [22.4,40.2] [7.1,16.5] [2.5,11.4] Borno (862) 28.4 2872 (414) 15.2 2543 (64) 6.9 925 [22.4,35.2] [11.0,20.5] [4.4,10.7] Yobe (557) 30.5 1847 (184) 11.1 1629 (29) 5.3 608 [22.3,40.3] [6.8,17.6] [2.8,9.6] Domain S. Adamawa (70) 13.1 535 (46) 9.6 477 (14) 8.7 161 [6.1,25.8] [4.4,19.8] [3.5,20.0] N. Adamawa (229) 44.2 518 (57) 11.9 477 (4) 2.7 147 [31.2,58.0] [7.2,19.1] [0.6,12.0] Northern Borno (122) 27.9 437 (39) 10.2 383 (5) 5 139 [16.3,43.5] [4.1,23.2] [1.7,13.8] Southern Borno (189) 35.5 532 (60) 12.5 480 (21) 14.5 145 [21.6,52.4] [5.0,27.9] [5.8,31.9] East Borno (237) 33.4 709 (150) 24.5 611 (10) 4.1 245 [20.8,48.9] [13.9,39.7] [2.0,8.1] Central Borno (132) 24 549 (58) 11.9 488 (16) 8.5 189 [13.8,38.5] [5.6,23.4] [3.7,18.4] MMC & Jere (182) 28.2 645 (107) 18.4 581 (10) 4.8 207 [17.9,41.4] [11.1,28.9] [1.9,11.7] Central Yobe (164) 26.5 620 (59) 11 536 (15) 6.8 219 [15.7,41.0] [4.9,23.0] [2.4,18.2] Southern Yobe (195) 31.4 622 (60) 10.8 554 (12) 6.2 195 [19.1,47.0] [5.2,21.3] [2.7,13.4] Northern Yobe (198) 32.7 605 (65) 12.1 539 (2) 1 194 [20.7,47.5] [4.9,26.8] [0.3,4.0]
3.7.2 Specialised Nutritious Foods Specialised nutritious foods such as fortified blended foods (FBFs) are made from cereals, a protein-rich food, and a vitamin and mineral premix that are formulated to provide specific amounts of energy, micronutrients and macronutrients needed to prevent and treat malnutrition. In Northeast Nigeria, Super Cereal and Super Cereal Plus are the two FBFs provided by the World Food Programme (WFP). A daily ration of Super Cereal for a pregnant and lactating woman has the equivalent calories of almost four cups of cooked rice, the protein of five eggs, and contains essential vitamins and minerals that are only found in a combination of foods. As part of the humanitarian response, Super Cereal is provided to food insecure households in a monthly food basket, and to pregnant and lactating women as a supplement to prevent malnutrition. Super Cereal Plus is provided to children 6 to 59 months for both prevention and treatment.
Survey respondents were shown example packaging of Super Cereal and asked whether they had received any of the product in the three months preceding the survey. Reported coverage was less than 10% in all three states. However, while all HHs regardless of status were sampled in the three states, only HHs receiving humanitarian assistance would be eligible for Super Cereal or a cash-based transfer to address identified food insecurity needs. In October 2019, out of 2.9 million individuals targeted for humanitarian assistance 1.2 million (63%) were assisted with food, including Super Cereal (583,652 individuals) or cash (600,366). By NFSS domain, reported receipt of Super Cereal ranged from 0.6% of HHs in Southern Adamawa to 19.1% of HHs in East Borno (Table 30).
Table 30: Percentage of households receiving Super Cereal in the last three months, by state and domain16 Households who received Super Cereal % [CI] N
State Adamawa (9) 0.7 1381 [0.2,2.0] Borno (340) 7.6 3661 [5.4,10.4] Yobe (28) 1.2 2059 [0.6,2.3] Domain S. Adamawa (4) 0.6 698 [0.1,2.7] N. Adamawa (5) 0.7 683 [0.1,3.6] Northern Borno (44) 6.3 702 [3.0,12.6] Southern Borno (6) 1.0 606 [0.3,3.2] East Borno (166) 19.1 869 [11.3,30.4] Central Borno (76) 11.1 686 [5.7,20.6] MMC & Jere (48) 6.0 798
16 The data should be integrated with caution as not all population groups are targeted, but only those receiving humanitarian assistances.
[2.7,12.7] Central Yobe (10) 1.5 685 [0.5,4.2] Southern Yobe (6) 0.9 673 [0.3,2.9] Northern Yobe (12) 1.7 701 [0.6,4.8]
3.8 Water, Sanitation and Hygiene (WASH) Safe treatment of drinking water and proper hygiene and sanitation are important cornerstones of public health, and lack of is a key contributor to undernutrition. In the context of an emergency with mass displacement, people may become resettled in locations without adequate water, access to means to treat water, sufficient latrines, and handwashing stations. Unsafe drinking water can be a carrier of many diseases such as cholera, schistosomiasis, and typhoid.
Households were asked whether they treat the water used for drinking. Among HHs that reported treating water, all methods used were recorded. Drinking water is considered appropriately treated if one of the following methods are used: boiling; adding bleach or chlorine; using a water filter; or using solar disinfection. Use of solar disinfection was assessed but is not presented here as no household in the survey reported this method. Sanitation was assessed through a series of observations. Survey teams observed whether there was a location in the house where household members could wash their hands. If yes, the presence of water and soap were each verified, and the type of soap was recorded.
In Adamawa, 2.0% of HHs reported treating their drinking water with 3.8% in Borno and 2.1% in Yobe. However, of those that reported treating their water, only one in 20 used a safe and appropriate water treatment method in Yobe (4.1%) while more than fifty percent used safe and appropriate water treatment in Adamawa (64.3%) and Borno (52.8%). The most common methods used - letting it stand, settle, and straining through a cloth - are not as effective. By domain, the proportion of HHs using an appropriate treatment method was highest in East Borno (85.7%). Worryingly, zero HHs in Southern Borno used any treatment method, and zero households in Northern Borno, and Northern and Southern Yobe zero HHs reported using safe and appropriate water treatment methods. The percentage of HHs treating their drinking water, and the methods used are presented in Table 31.
Of all HHs in the three states, approximately one in six HHs had a facility for handwashing with both water and soap. The proportion of HHs with a facility for handwashing was highest in Yobe (34.5%), although Yobe HHs had the lowest proportion with both soap and water (4.3%). In Borno the proportion of HHs with a facility for handwashing was low (31.4%), but a higher proportion had soap and water (15.6%). In Adamawa 32.5% of HHs had a facility for hand washing, but only 22.1% had soap and water present, which was the highest for all the 3 states. By domain, both the proportion of HHs with a facility for handwashing (22.2% to 42.5%) and the proportion with soap and water observed among them (1.7% to 58.7%) was highly variable. The percent of HHs where a place for handwashing was observed is shown Table 32.
These results suggest that in all domains, the majority of HHs did not have the ability to properly wash their hands at home. Washing hands with water and soap is an important and cost-effective health intervention to reduce the incidence of conditions observed to be prevalent in the surveyed areas (e.g., diarrhoea and pneumonia).
Table 31: Percentage of Households Treating Their Drinking Water by Treatment Method, By State and Domain Number of households Proportion Water treatment method used among households treating their water: treating their of HHs drinking water, treating No. of any method their HHs Any drinking Add Strain Appropriate water, any Use water Let it stand Boil bleach/ through a Solar Alum Water method filter and settle chlorine cloth Treatment Method
State Adamawa (28) 2.0 1381 (8) 25.0 (7) 21.9 (0) 0.0 (4) 12.5 (1) 3.1 (8) 25.0 (4) 12.5 (18) 64.3 28 [0.7,5.6] [8.7,41.4] [6.3,37.5] [0.0,25.0] [0.0,9.7] [8.7,41.4] [0.0,25.0] [46.5,82.1] Borno (125) 3.8 3661 (14) 9.7 (38) 26.4 (19) 13.2 (2) 1.4 (13) 9.0 (44) 30.6 (9) 6.3 (66) 52.8 125 [2.2,6.5] [0.0,27.2] [0.3,52.5] [0.0,33.2] [0.0,8.3] [0.0,26.0] [3.3,57.8] [0.0,20.6] [44.0,61.6] Yobe (49) 2.1 2059 (1) 1.9 (0) 0.0 (9) 17.0 (1) 1.9 (0) 0.0 (37) 69.8 (2) 3.8 (2) 4.1 49 [1.0,4.3] [0.0,9.6] [0.0,38.2] [0.0,9.6] [43.8,95.8] [0.0,14.6] [0.0,9.6] Domain S. Adamawa (23) 3.3 698 (8) 32.0 (7) 28.0 (0) 0.0 (4) 16.0 (0) 0.0 (4) 16.0 (2) 8.0 (17) 73.9 23 [0.9,11.0] [13.7,50.3] [10.4,45.6] [1.6.30.4] [1.6.30.4] [0.0,18.6] [55.9,91.9] N. Adamawa (5) 0.7 683 (0) 0.0 (0) 0.0 (0) 0.0 (0) 0.0 (1) 14.3 (4) 57.1 (2) 28.6 (1) 20.0 5 [0.1,3.6] [[0.0,40.2] [20.4,93.8] [0.0,62.1] [0.0,55.1] Northern Borno (2) 0.3 702 (0) 0.0 (0) 0.0 (0) 0.0 (0) 0.0 (0) 0.0 (2) 100.0 (0) 0.0 (0) 0.0 2 [0.0,2.0] Southern Borno (0) 0 606 (0) 0.0 (0) 0.0 (0) 0.0 (0) 0.0 (0) 0.0 (0) 0.0 (0) 0.0 (0) 0.0 0 [0.3,2.2] East Borno (21) 2.4 869 (2) 9.5 (3) 14.3 (0) 0.0 (0) 0.0 (13) 61.9 (2) 9.5 (0) 0.0 (18) 85.7 21 [0.7,8.3] [0.0,22.1] [0.0,29.3] [41.1,82.7] [0.0,22.1] [70.7,100.0] Central Borno (58) 8.5 686 (3) 4.1 (20) 27.4 (12) 16.4 (1) 1.4 (0) 0.0 (30) 41.1 (4) 5.5 (23) 39.7 58 [3.4,19.5] [0.0,8.7] [17.2,37.6] [7.9,24.9] [0.0,4.0] [29.8,52.4] [0.3,10.7] [27.1,52.3] MMC & Jere (44) 5.5 798 (9) 17.6 (15) 29.4 (7) 13.7 (1) 2.0 (0) 0.0 (10) 19.6 (5) 9.8 (25) 56.8 44 [2.5,11.8] [7.2,28.1] [16.9,41.9] [4.3,23.2] [0.0,5.8] [8.7,30.5] [1.6,18.0] [42.2,71.5] Central Yobe (26) 3.8 685 (1) 3.7 (0) 0.0 (8) 29.6 (1) 3.7 (0) 0.0 (16) 59.3 (1) 3.7 (2) 7.7 26 [1.4,9.6] [0.0,10.8] [12.4,46.9] [0.0,10.8] [40.7,77.8] [0.0,10.8] [0.0,17.9] Southern Yobe (11) 1.6 673 (0) 0.0 (0) 0.0 (0) 0.0 (0) 0.0 (0) 0.0 (10) 90.9 (1) 9.1 (0) 0.0 11 [0.4,5.9] [73.9,100.0] [0.0,26.1] Northern Yobe (12) 1.7 701 (0) 0.0 (0) 0.0 (1) 8.3 (0) 0.0 (0) 0.0 (11) 91.7 (0) 0.0 (0) 0.0 12
[0.5,5.4] [0.0,24.0] [76.0,100.0]
Table 32: Percentage of Households Where A Place for Handwashing Was Observed and Availability of Soap and/or Water, By State and Domain Place for handwashing observed Percentage of Water is available and: Water is not available and: households Number of where place Number of No soap: No soap: households for households No other Soap Ash, mud, No other Soap where a place handwashing Ash, mud, or cleansing present or sand cleansing agent present for handwashing was observed sand present agent present present was observed present State Adamawa (445) 32.5 1381 (102) 22.1 (1) 0.2 (253) 57.2 (79) 18.1 (0) 0 (9) 2.0 445 [23.3,43.4] [14.7,32.0] [0.0,1.5] [41.9,71.3] [7.6,37.5] [0.8,4.9] Borno (1199) 31.4 3661 (177) 15.6 (2) 0.1 (738) 59 (245) 22 (0) 0 (37) 3.3 1199 [25.0,38.6] [9.7,24.2] [0.0,0.4] [46.9,70.2] [12.5,35.7] [1.0,10.4] Yobe (717) 34.5 2059 (37) 4.3 (1) 0.2 (465) 64.8 (137) 21.5 (0) 0 (67) 9.1 717 [25.5,44.7] [2.1,8.3] [0.0,1.7] [47.9,78.7] [9.6,41.4] [3.5,21.7] Domain S. Adamawa (155) 22.2 698 (91) 58.7 (1) 0.6 (61) 39.4 (0) 0 (0) 0 1.3 155 [11.2,39.1] [43.7,72.3] [0.1,4.1] [25.8,54.8] [0.3,6.3] N. Adamawa (290) 42.5 683 (11) 3.8 (0) 0 (192) 66.2 (79) 27.2 (0) 0 (7) 2.4 290 [28.7,57.5] [1.7,8.4] [43.2,83.5] [11.2,52.5] [0.9,6.5] Northern Borno (249) 35.5 702 (10) 4 (2) 0.8 (163) 65.5 (56) 22.5 (0) 0 (18) 7.2 249 [22.4,51.2] [1.0,14.7] [0.2,3.0] [43.4,82.4] [7.8,49.9] [3.0,16.4] Southern Borno (177) 29.2 606 (3) 1.7 (0) 0 ((103) 58.2 (55) 31.1 (0) 0 (16) 9 177 [17.1,45.3] [0.4,7.6] [28.5,82.9] [10.1,64.3] [1.3,43.0] East Borno (331) 38.1 869 (59) 17.8 (0) 0 (227) 68.6 (45) 13.6 (0) 0 (0) 0 331 [25.5,52.5] [9.1,31.9] [49.7,82.8] [3.8,38.3] Central Borno (204) 29.7 686 (35) 17.2 (0) 0 (129) 63.2 (39) 19.1 (0) 0 (1) 0.5 204 [17.3,46.1] [8.9,30.4] [40.3,81.4] [4.5,54.0] [0.1,3.4] MMC & Jere (238) 29.8 798 (70) 29.4 (0) 0 (116) 48.7 (50) 21 (0) 0 (2) 0.8 238 [17.6,45.8] [12.2,55.4] [24.5,73.6] [5.7,53.9] [0.1,5.5] Central Yobe (247) 36.1 685 (15) 6.1 (0) 0 (169) 68.4 (39) 15.8 (0) 0 (24) 9.7 247 [22.7,52.0] [2.3,15.2] [43.2,86.1] [3.8,47.2] [1.9,37.6] Southern Yobe (228) 33.9 673 (6) 2.6 (1) 0.4 (142) 62.3 (59) 25.9 (0) 0 (20) 8.8 228 [20.8,50.0] [0.6,10.4] [0.1,3.0] [36.1,82.8] [8.3,57.4] [2.0,31.0] Northern Yobe (242) 34.5 701 (16) 6.6 (0) 0 (164) 67.8 (39) 16.1 (0) 0 (23) 9.5 242 [21.5,50.3] [2.1,18.7] [41.6,86.1] [3.9,47.5] [1.7,39.7]
4. Discussion:
4.1 Nutrition Situation:
The nutritional status of children under five and pregnant and lactating women are important indicators for the overall health and nutritional wellbeing of a population.
The prevalence of global acute malnutrition was 11.5% in Yobe State, with Central Yobe showing the highest GAM rate (13.8%). In all three domains of Yobe State, the GAM17 rates exceeded 10%, which is considered to be of high public health concern18. The main causes of the high GAM levels in Yobe are mostly attributed to developmental issues including poor health services, high illiteracy rates, food insecurity and overall high levels of poverty and less on the impact of the conflict. The GAM rates in Borno and Adamawa states were 8.1% and 7.2%, respectively, which are considered a medium severity.
The GAM rates in Yobe State have remained persistently high since the establishment of the surveillance system in 2016. In Borno State, the GAM rates have fluctuated probably due to seasonality, and the scale-up of the nutrition responses (Figure 2). The GAM rates in Adamawa have remained relatively stable, but with a slight increase in October 2019 from 6.1% to 7.2%.
When analyzing the prevalence of acute malnutrition by both MUAC and WHZ score, a poor correlation between both results was found. The prevalence of acute malnutrition by MUAC is significantly lower compared to WHZ score. For example, in Yobe State, the GAM as measured by WHZ was 11.5% but 2.6% by MUAC. Surveys conducted in some countries in Africa19 have shown that the two measures are not detecting the same children, and they can correlate poorly. Grellety and Golden concluded in their 2016 study20 that “the perceived need for humanitarian intervention can be affected by the measure chosen to assess the prevalence of malnutrition which will vary from region to region. MUAC measurement is recommended to be included in all anthropometric surveys and the two criteria are not to be seen as alternative measures of the loss of body tissue leading to an increased risk of death, but complementary variables that should both be used independently to guide admission for treatment of malnourished children”.
It is important to note that “in a protracted crisis” like in most areas of Borno State, the drivers of persistent GAM are often unclear, in part because the three underlying causes — food, care, and health — all potentially play a role, so there may be no single reason accounting for persistent GAM. Addressing persistent GAM presents particular challenges for operational agencies, in part because of structural issues within the humanitarian system which focusses on treatment of severe acute malnutrition, “siloed” sectors, short-term funding cycles that do not include nutrition causal analysis (NCA) or prioritize prevalence data”.
17 There is currently no formal SAM threshold issued by any UN agency.. 18 World Health Organization (WHO). Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. 1995. Available at: http://www.who.int/childgrowth/publications/physical_status/en/
19https://www.researchgate.net/publication/281204067_Inconsistent_diagnosis_of_acute_malnutrition_by_weight-for- height_and_mid-upper_arm_circumference_Contributors_in_16_cross- sectional_surveys_from_South_Sudan_the_Philippines_Chad_and_Bangladesh 20 https://bmcnutr.biomedcentral.com/track/pdf/10.1186/s40795-016-0049-7
Figure 2: GAM Trends from 2016 to 2019
16 13.3 14 12.7 13 12.0 12.2 11.5 12 11.3 11.4 11.6 10.6 10 11.4 8.9 9.9 8.0 8 8.1 6.7 8.2 6 6.4 7.2 GAM Rate (%) Rate GAM 6.5 6.1 5.6 4 Adamawa Borno 2 Yobe 0 Oct-16 Mar-17 Aug-17 Nov-17 Apr-18 Oct-18 Apr-19 Oct-19
Underweight and Stunting: The prevalence of underweight was highest in Yobe at 16%, Borno at 14.5% and Adamawa at 9.4%. The prevalence of underweight has significantly reduced since 2016 to below the Nigeria average of 21% and to within the global average of 15%, while Adamawa is significantly lower. The prevalence of stunting in all three states was below serious based on the WHO classification21 of below 30% and below the Nigeria average of 36.8%. (2013 DHS). Both underweight and stunting are higher in boys than girls in all three states.
The prevalence of acute malnutrition, underweight and stunting were higher among boys than girls in all domains with the exception of MMC/Jere and Central Borno. Speculation on the observed sex differences can be mainly centered on behavioral patterns. For instance, in an extensive analysis of gender bias for undernutrition in sub-Saharan Africa, Svedberg22 proposed that the slight anthropometric advantage shown by girls in many countries can suggest a historical pattern of preferential treatment to females due to the high value placed on women's agricultural labor. The anthropological explanation can be applied to the result of this survey not only for the role gender related for females but also for a perception of considering women/girls as vulnerable causing a disadvantage in boys.
4.2 Mortality:
The U5MR is often used as a more sensitive indicator of the effect of emergency conditions on mortality since; young children are more susceptible to health and nutrition challenges. The U5MR often changes faster and to a greater extent than the CMR in a crisis situation. Under- five mortality rates did not exceed the emergency thresholds of 2 deaths in children under five /10,000 children under five / day in all domains. Both crude and under five mortality rates were below the emergency threshold of 1death/10,000 population/day and 2 deaths/10,000 population/day, respectively.
21 World Health Organization (WHO). Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. 1995. Available at: http://www.who.int/childgrowth/publications/physical_status/en/
22 Cronk L: Low socioeconomic status and female-biased parental investment: the Mukogobo example. Am Anthropol 1989,91:414-429.
4.3 Vaccination Coverage:
Immunization is one of the most essential public health interventions and cost-effective strategy to reduce childhood morbidity and mortality. The initiation of immunity through application of vaccine is considered to be vital for improving chances of child survival. Failure to vaccinate children against measles puts them at risk of severe health complications such as acute malnutrition, pneumonia, diarrhoea, encephalitis, and blindness.
The overall measles coverage among children 12-59 months as determined by observation of vaccination card and maternal recall was Adamawa (87.3%), Borno (86%) and Yobe (75.9%). The current measles coverage is below the recommended 90-95% to achieve herd immunity. This means that to achieve 95% immunity in the population for measles, vaccination coverage needs to be higher than 95%. The suboptimal coverage rates maybe cause of the frequency measles outbreak in certain parts of Borno States.
Measles vaccination campaigns have been organized in the 3 emergency states. However, data suggest that coverage of measles vaccination is below 95% coverage rate required to give herd immunity in all the 9 domains. A vaccination campaign should therefore be ramped up given insufficient coverage in the context of an ongoing outbreak. Additionally, despite ongoing distributions of deworming medication as part of routine activities and through campaigns, coverage remains low in all domains (below 15% in all domains and as low as 1% in Northern Yobe).
As presented in Table 29, the coverage of Vitamin A is low with only one-third of children having received supplementation in the past 6 months. Vitamin A deficiency is a recognized risk factor for severe measles. To ensure a comprehensive prevention and fight against measles, both measles vaccination and Vitamin A supplementation should be integrated.
4.4 Infant and Young Child Feeding:
Breast milk provides all the nutrients, vitamins, and minerals an infant need for growth during their first six month of life. Breastfeeding also protects children from infection. As a result, early and exclusive breastfeeding are among the most economical and safe public health interventions. However, many mothers stop breastfeeding early. This is particularly true in the context of an emergency where factors such as stress, displacement and distributions of infant formula may contribute to early interruption. Emergency interventions in Northeast Nigeria have therefore included counselling on Infant and Young Child Feeding (IYCF) aimed at encouraging proper breastfeeding and complementary feeding practices.
Despite the importance of breast milk, both the percent of exclusively breastfeeding low with Borno (45.6%), Adamawa (52.2%) and Yobe (35.1%). Nonetheless, the exclusive breastfeeding rates have significantly improved in the 3 states since 2016, from a low of 20%.
The overall predominant breastfeeding (PBF) was 95% across the 3 states. Predominant breastfeeding means that the infant's predominant source of nourishment has been breast milk.
The issue of the studying predominant breastfeeding needs further clarification. Although awareness and knowledge of exclusive breastfeeding might be relatively high among mothers, this might not translate into practice of exclusive breastfeeding. It is important to note that predominant breastfeeding, just like exclusive breastfeeding, is associated with substantially lower risk of child mortality than partial or no breastfeeding at all. Therefore, much greater attention should be given to this finding. The current high rates of predominantly breastfeeding
is very encouraging, a clear indication that the IYCF programming outcome and possibly a reason of the relatively low levels of acute malnutrition despite other aggravating factors such as very low rates of minimum dietary, frequency and acceptable diet and general food insecurity.
4.5 Child Minimum Dietary Diversity and Minimum Acceptable Diet.
The minimum dietary diversity and minimum acceptable diets are extremely low across the 3 states. The minimum acceptable diet across the 3 states is extremely low, with Adamawa (3.8%), Borno (0.5%) and Yobe (3.0%). Low dietary diversity and meal frequency practices are determinant for health and growth in children 6 to 23 months. They increase the risk of undernutrition, illness, and mortality in infants and young children. Even with optimum breastfeeding, stunting will occur if children do not receive sufficient dietary diversity and frequency over 6 months of age. Supplementing breastfeeding with nutritious complementary foods can reduce stunting among children of this age by 20%. 23
Both individual and community level factors are significantly associated with a minimum acceptable diet of 6–23 months age children in Nigeria, suggesting that nutritional interventions designed to improve child health should not only be implemented at the individual level but tailored to community context as well. The individual factors include high levels of illiteracy, low incomes, gender disparities (intrahousehold food allocation) and low awareness on appropriate IYCF practices. Community factors includes the impact of the ongoing insecurity (displacements), lack of access for farming land and markets, poor health and nutrition services, and general poor infrastructure.
4.6 Maternal Nutrition:
The nutritional status of women of reproductive age (15-49 years) is concerning with approximately 1 out of 10 women acutely malnourished in Borno and Adamawa states and 2 out of 10 women in Yobe State. Moreover, the prevalence of acute malnutrition was found to be five times higher for adolescent girls (15 to 19 years) at 29.5% than for adult women (20 to 49 years) at 5.9%. (Table 28). Early child bearing carries significant risks for young girls, particularly in rural areas where women do not complete their growth before the age of 20 years. This finding is particularly significant since nutritional status before and during pregnancy is essential for healthy maternal and neonatal outcomes. More effort is needed to improve adolescent nutrition, and to support positive birth outcome and prevent the vicious cycle of inter-generational growth failure. Further investigation is warranted to understand the causes of low MUAC among adolescent girls, particularly in Yobe State.
The proportion of women of reproductive age who met minimum dietary diversity was below half in all three states, a clear indication that macro and micronutrient intakes are inadequate, and that diets lack diversity. The poor diet diversity could be attributed to low agricultural activity in the surveyed areas24 and low agrobiodiversity, low education levels, and/or large household/family size among other factors. Nutrition interventions focusing on malnutrition prevention and improving dietary quality should be linked to nutrition sensitive interventions, especially agricultural, that promote locally-available micronutrient dense foods such vegetables, fruits, dairy and animal proteins.
4.7 Deworming, Vitamin A and Micronutrient Powder Supplementation.
23 Food and Agricultural Organization (FAO) and FHI 360. 2016. Minimum Dietary Diversity for Women: A Guide for Measurement. Rome: FAO. Available at: http://www.fao.org/3/a-i5486e.pdf
24 Famine Early Warning Systems Network (FEWSNET). Nigeria Livelihood Zones. 2014. Available at: http://www.fews.net/west-africa/nigeria/livelihood-zone-map/may-2014
The nutritional impairment caused by schistosome and soil-transmitted helminth infections during childhood has been shown to have a significant impact on growth and development of children25. Across the 3 states, approximately only 13% of children had received deworming drugs in the past 6 months. Periodic deworming of children can reduce the transmission of schistosome and soil-transmitted helminth infections. However, drug therapy alone is only a short-term measure of reducing worm infection and re-infection is frequent. Thus, control measures with improvement of water and sanitation, and health education are needed to prevent infection and re-infection.
In Africa, Vitamin A deficiency (VAD) alone is responsible for almost 6% of child deaths under the age of 5 years. According to the survey results, only about 30% of the children aged between 6 to 59 months received Vitamin A supplement in the 6 months prior to the survey26. This implies that two-thirds of the children in the 3 states that did not receive the supplement, may be growing up with VAD. The low Vitamin A coverage is despite bi-annual mass supplementation during the MNCH week.
To improve the Vitamin A coverage, to above 90%27 or higher (recommendation for areas with low minimum acceptable diet), supplementation must be integrated into the EPI, better coverage of MNCH week and promotion of appropriate infant and young child feeding practices that promote the consumption of vitamin A rich foods.
Micronutrient deficiency is a major contributor to childhood morbidity and mortality. Children can receive micronutrients from foods, food fortification, and home (direct) supplementation. Micronutrient powders are one strategy of addressing micronutrient deficiencies especially in areas with high food insecurity, and minimum acceptable diets. The overall uptake of MNPs is very low at Adamawa (5.4%), Borno (6.9%) and Yobe (5.3%) due geographically incomplete distribution programmes. Analysis of the MNP coverage in Borno State has shown am improved in the uptake and utilization of MNPs increases when combined with IYCF programmes28.
4.8 Diarrhoea, Oral Rehydration Therapy and Zinc Supplementation Coverage:
Diarrhoea is the second leading cause of death after pneumonia in children worldwide29. The risk factors of diarrhea include: consumption of contaminated water and unhygienic practices in food preparation and disposal of stools can increase in the context of a humanitarian emergency, prevalence of diarrhoea is often observed to increase.
On average, 10% of children surveyed had diarrhea episode in the last two weeks preceding the survey. Humanitarian updates suggest that during the period of the survey diarrhoea, along with suspected malaria and suspected pneumonia, remained a major cause of consultations at primary health centers in the northeast30. Given concerns about increased risk of diarrhoeal disease, and in particular potential for outbreaks of diarrhoeal diseases such as cholera or Shigella dysentery, humanitarian partners have prepositioned Interagency Diarrhoeal Disease
25 https://www.ncbi.nlm.nih.gov/pubmed/16634028?dopt=Abstract 26 https://www.ncbi.nlm.nih.gov/pubmed/16634028?dopt=Abstract 27 https://www.ncbi.nlm.nih.gov/pubmed/16634028?dopt=Abstract 28 Nutrition Sector, NE Nigeria. 5W (2017-2019). 29 World Health Organization (WHO). 2013. WHO Fact sheet N°330: Diarrhoeal disease. Available at: http://www.who.int/mediacentre/factsheets/fs330/en/
30 United Nations Children’s Fund (UNICEF). 2016. Nigeria Humanitarian Situation Report #16. Available at: http://reliefweb.int/report/nigeria/nigeria-weekly-humanitarian-situation-report-no-16-15-21-december-2016.
Kits (IDDKs) at the Ministry of Health in Borno. Along with other supplies, kits contain ORS and Zinc31.
WHO and UNICEF recommend Zinc with ORS in the treatment for diarrhoea. Diarrhoea is treated with low-osmolarity oral rehydration salt (ORS) to replenish water and electrolytes lost in loose stools. Zinc deficiency is associated with immune system dysfunctions, growth retardation, and a high risk of morbidities, including diarrhoea. Studies show that supplemental Zinc, when combined oral rehydration solutions (ORS), provides therapeutic benefits, reducing the duration and the severity of the diarrhoea episodes.
Survey results indicate that in the emergency states, appropriate medications, and preventive services for common childhood illnesses remain below national benchmarks. The prevalence of diarrhoea was above 8% all domains except Northern Borno and Northern Adamawa which were slightly above 6.0%. However, access to proper treatment remains very low thereby leaving room for improvement in the management of diarrhoea cases (recommended treatment with Lo-ORS zinc combination as low as 2% in Southern Adamawa with the highest being 25.5% in MMC/Jere). Where the conflict has resulted in considerable destruction to health infrastructure, use of community health volunteers can be prioritized to improve coverage.
4.9 Acute Respiratory Infection (ARI) and treatment.
Acute respiratory infections (ARI) are a heterogeneous and complex group of diseases that constitute the major causes of mortality and morbidity among under-five children in Nigeria, and globally. Most of these deaths are caused by pneumonia and bronchiolitis. According to a study conducted in Nigeria, the overall incidence of ARI is 6-8 episodes during the first 5 years of life.32 As with diarrhoea, prevalence of ARI varies seasonally. Previous research from Nigeria suggests that the peak of infection corresponded to the rainy season (July-November). WHO guidelines recommend that all children with fast breathing are classified as having “pneumonia” and treated with oral amoxicillin.33
In the survey, the prevalence of ARI has been estimated by asking mothers (or caretakers) whether the child had had a cough accompanied by short, rapid breathing in the two weeks prior to the survey. The estimate is based on mothers' perception and not on a diagnosis by a health professional, therefore this finding needs to be interpreted with caution.
4.10 Fever, Prevention of Malaria, and Antimalarial Treatment.
These survey results show that the clinical management of malaria with first line treatment remains below the national target (80%) as specified in the National Malaria Strategic Plan.34
Fever is a major manifestation of many acute infections in children, including malaria. Malaria is endemic in Nigeria, with year-round transmission. Plasmodium falciparum is the predominant
31 Butta ZA, Bird SM, Black RE, et al. Therapeutic effects of oral zinc in acute and persistent diarrhea in children in developing countries: pooled analysis of randomized controlled trials. Am J Clin Nutr. 2000 Dec;72(6):1516-22.
32 Fagbule D, Parakoyi DB, Spiegel R. Acute respiratory infections in Nigerian children: prospective cohort study of incidence and case management. J Trop Pediatr. 1994 Oct;40(5):279-84.
33 17 World Health Organization (WHO). 2014. Revised WHO classification and treatment of childhood pneumonia at health facilities: Evidence summaries. Available at: http://apps.who.int/iris/bitstream/10665/137319/1/9789241507813_eng.pdf
34 Federal Ministry of Health. 2011. National Policy on Malaria Diagnosis and Treatment.
parasite species. Children in Nigeria have an estimated average of 2-4 episodes annually. Malaria is most prevalent after the end of the rainy season (July – November). Previous national surveys found prevalence of fever to be lowest in the North East region.
In 2010, the World Health Organization started recommending universal use of diagnostic testing to confirm malaria infection and apply appropriate treatment based on the results. According to the new guidelines, treatment solely on the basis of clinical suspicion should only be considered when a parasitological diagnosis is not accessible. Children with severe malaria symptoms, such as fever or convulsions, should be taken to a health facility and subjected to diagnostic testing.
The proportion of children under five with reported symptoms of fever is provided in Table 24, along with measures of clinical management including proportions tested for malaria and receiving anti-malarial drugs. Prevalence was highest in Yobe (12.0%) followed by Adamawa (11.6%) and Borno (11.4%). By domain, prevalence ranged from 7.0% (East Borno) to 14.0% (Central Borno). No significant differences were observed by sex. Despite WHO recommendations, less than 13 percent of children with fever in the last two weeks were tested for malaria with only 7.4% in Adamawa, 12.1% in Borno, and 9.2% in Yobe. In all domains with the exception of MMC & Jere, Southern Borno and Central Yobe, less than 10% of children with symptoms of fever in the preceding two weeks received malaria diagnostic tests. None of the 3 domains have up to 20% of children with symptoms of fever in the preceding two weeks received malaria diagnostic tests.
less than half of the households have the recommended number of bed nets, one net per two persons with only 24.7% in Borno, 47.0% in Yobe, and 39.1% in Adamawa. Among children residing in households with bed nets, about three in four slept under a bed net during the night preceding the survey with 73.8% in Yobe, and 63.5% in Adamawa. Utilization did not vary notably by age cohort or by gender. However, there remains a need for both improved coverage of bed nets as well as education on utilization given evidence of households where bed nets are not currently in use by children.
4.11 Specialised Nutritious Foods:
Emergency affected populations often face limited access to diversified diets, or livelihood opportunities, and are frequently reliant upon food assistance. A household general food distribution (GFD) is not able to support the unique nutritional requirements of young children, pregnant and lactating women, and other vulnerable groups. Selective feeding programmes may be implemented to help bridge the nutrient gap.
4.12 Water, Sanitation and Hygiene:
The survey results are limited to the water treatment and handwashing practices. The proportion of households treating water was Adamawa (2.0%), Borno (3.8%) and Yobe (2.1%). Data was not collected on the main source of water, and therefore the results should be interpreted with caution. It is assumed that the low rate of water treatment is that the main source of water is protected, treated and safe e.g. boreholes. It is worthy to note that water that is safe at the point of delivery can nevertheless present a significant health risk due to re- contamination during collection, storage, and drawing. Steps must be taken to minimize such risk include improved collection and storage practices, distributions of clean and appropriate collection and storage containers and treatment with a residual disinfectant, or treatment at the point of use. However, on those that reported treating their water, only 1 in 20 employed safe and appropriated water treatment methods, putting at risk 95% of the population to drinking contaminated water.
The importance of hand washing after defecation and before eating and preparing food, to prevent the spread of disease, cannot be over-estimated. The proportion of households that had both soap and water observed at a handwashing facility below 30% in all the 3 States.
Agencies implementing WASH facilities should go beyond providing adequate water supply and also focus on basic hygiene messaged including handwashing and household level appropriate water treatment and storage.
5. Conclusion and Recommendations The results presented represent the only population-representative estimates for all accessible areas of the emergency states for October 2019. The findings provide evidence that prevalence of GAM remains at serious levels35 all of Yobe state since 2016 when the surveillance was established. Prevalence of acute malnutrition is generally comparable with estimates of GAM from the round 1 through round 7 (2016-2019) with slight seasonal variability observed in Borno and to a lesser extent Adamawa.
Under five mortality rates did not exceed the emergency threshold in all domains. However, the upper confidence intervals for U5MR in Northern Yobe exceeded 2 deaths in children under five / 10,000 children under five / day, suggesting it is possible that U5MR exceeded emergency thresholds in that domain.
There remain critical gaps in both preventive and curative nutrition services, and clinical management of common childhood morbidities. Inadequate coverage of measles vaccination (less than 100% required to confer herd immunity in all three states) is particularly concerning given the ongoing measles outbreak in Borno and Yobe states.
Acute malnutrition prevalence, mortality rates, and other indicators are likely poorer in newly liberated and inaccessible areas. Large areas of the assessed domains remain inaccessible, particularly in Borno. Additionally, this assessment was conducted during the end of hunger season and following a surge in emergency response programs, factors that might also contribute to the end of hunger season and following a surge in emergency response programs, factors that might also contribute to the lower estimated prevalence of acute malnutrition in these surveys relative to estimates from other small-scale surveys.
Based on these results the following are recommended:
A) Prevention:
1. UNICEF and WHO to continue support for SPHCDA to strengthen the routine provision of vitamin A and deworming through the EPI at health facilities, and in regular campaigns. UNICEF to assist in developing communication strategies to improve the uptake of vitamin A and deworming both in routine programming, and campaigns. 2. Health Sector to ensure 100% coverage of measles vaccination to ensure 100% herd immunity is achieved. 3. WHO, UNICEF and health sector partners to strengthen management of common childhood illnesses, such as diarrhoea, at accessible at the household level and primary health centers. 4. WFP to continue strengthening its ongoing humanitarian response (nutrition and food or
35 World Health Organization (WHO). Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. 1995. Available at: http://www.who.int/childgrowth/publications/physical_status/en/
cash assistance), which may be attributable in contributing to the documented decrease in acute malnutrition.
B) Response: 5. WFP to continue strengthening its ongoing humanitarian response (nutrition and food or cash assistance) which may be attributable in contributing to the documented decrease in acute malnutrition. 6. Donors to support Nutrition Sector partners to scale-up malnutrition prevention and treatment responses in areas with persistent high levels of GAM including Central Yobe, Southern Yobe, Northern Yobe, and East Borno. 7. Nutrition Sector partners to adopt innovative methods to improve the coverage and quality of infant and young child feeding (IYCF) and Micro-Nutrient Powder (MNP) including establishing Father-to-Father Groups, MtMSG, Care Models and use of the CNMs to distribute MNPs. 8. Improve coverage of effective nutrition intervention e.g. targeting them in Mother to Mother Support groups, aimed at improving the nutritional status of adolescent girls. 9. Nutrition Sector partners to adopt tested and innovative methods to improve the coverage and quality of infant and young child feeding (IYCF), and use of micronutrient powder (MNP), including establishing Father-to-Father Groups, Mother-to-Mother Support Groups, Care Models, and engagement of Community Nutrition Mobilisers to distribute MNPs.
C) Funding 10. Donors to support Nutrition Sector partners to scale-up nutrition prevention and treatment response in areas with persistent high levels of GAM including Central, Northern and Southern Yobe, and East Borno.
D) Monitoring and Evaluation: 11. Nutrition Sector to plan and carry out systematic SMART methodology nutrition surveys in LGAs, and to seek donor funding for regularization of these surveys.
E) Coordination: 12. OCHA to support the Nutrition Sector to involve the ISWG and specifically the WASH and Food Security in the planning, implementation, analysis, and dissemination of results. This is to ensure the SMART results are relevant to the other sectors. 13. OCHA to support the adoption of GAM results as a cross cutting outcome for all sectors.
6. References 1. Famine Early Warning Systems Network (FEWSNET). Nigeria Livelihood Zones. 2014. Available at: http://www.fews.net/west-africa/nigeria/livelihood-zone-map/may- 2014
2. Nigeria - DTM Round 28 Report (August 2019). Available at; https://displacement.iom.int/system/tdf/reports/Nigeria_DTM_Round_28_Report_Aug ust%202019.pdf?file=1&type=node&id=6616
3. United States Agency for International Development (USAID), United Nations Children’s Fund (UNICEF), United Kingdom Agency for International Development (UKAID). 2015. National Nutrition and Health Survey: Report on the Nutrition and Health Situation in Nigeria (NNHS). Available at: http://somlpforr.org.ng/pdfs/SMARTResults%202015.pdf.
4. World Health Organization (WHO). Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. 1995. Available at: http://www.who.int/childgrowth/publications/physical_status/en/
5. World Health Organization (WHO). 2006. Child Growth Standards. Available at: http://www.who.int/childgrowth/en/
6. World Health Organization (WHO). 2007. WHO Fact sheet N°286: Measles. Available at: http://www.who.int/mediacentre/factsheets/fs286/en/
7. NCDC 2019 Measles Outbreak in Nigeria, May 18, 2019 Available: https://reliefweb.int/sites/reliefweb.int/files/resources/An%20Update%20of%20Measl es%20Outbreak%20in%20Nigeria_100519_19.pdf
8. World Health Organization (WHO), Government of Nigeria. 2016. Northeast Nigeria Response: Borno State Health Sector Bulletin #08. Avalable : http://reliefweb.int/report/nigeria/northeast-nigeria-response-borno-state-health- sector-bulletin-08
9. Measles Eradication: Recommendations from a Meeting Cosponsored by the World Health Organization, the Pan American Health Organization, and CDC. MMWR. 1997:46(RR11);1- 20.
10. World Health Organization (WHO). 2013. WHO Fact sheet N°330: Diarrhoeal disease. Available at: http://www.who.int/mediacentre/factsheets/fs330/en/
11. United Nations Children’s Fund (UNICEF). 2016. Nigeria Humanitarian Situation Report #16. Available at: http://reliefweb.int/report/nigeria/nigeria-weekly-humanitarian- situation-report-no-16-15-21-december-2016.
12. United Nations Children’s Fund (UNICEF). 2016. Nigeria Humanitarian Situation Report #12. Available at: http://reliefweb.int/report/nigeria/nigeria-weekly-humanitarian- situation-report-no-12-17-23-november-2016.
13. Borno State Government. Health Sector Nigeria. 2016. Northeast Nigeria Response. Borno State Health Sector Bulletin #04. Available at: http://www.who.int/health- cluster/news-and-events/news/Borno-Health-Sector-Bulletin-Issue4.pdf?ua=1.
14. Butta ZA, Bird SM, Black RE, et al. Therapeutic effects of oral zinc in acute and persistent diarrhea in children in developing countries: pooled analysis of randomized controlled trials. Am J Clin Nutr. 2000 Dec;72(6):1516-22.
15. Oyejide CO, Osinusi K. Incidence of acute lower respiratory infections in a low socioeconomic community. Niger J Paediatr. 1991:8–21.
16. Fagbule D, Parakoyi DB, Spiegel R. Acute respiratory infections in Nigerian children: prospective cohort study of incidence and case management. J Trop Pediatric. 1994 Oct;40(5):279-84.
17. World Health Organization (WHO). 2014. Revised WHO classification and treatment of childhood pneumonia at health facilities: Evidence summaries. Available at: http://apps.who.int/iris/bitstream/10665/137319/1/9789241507813_eng.pdf
18. Federal Ministry of Health. 2011. National Policy on Malaria Diagnosis and Treatment.
19. National Primary Health Care Development Agency. 2012. National Guidelines for the Development of Primary Health Care System in Nigeria. Available at: http://www.nphcda.gov.ng/index.php/publication
20. World Food Program (WFP). 2016. Number of People in Need of Food Assistance Grows in North East Nigeria. Available at: https://www.wfp.org/news/news-release/number- people-need-food-assistance-grows-north-eastern-nigeria
21. World Food Program (WFP). 2016. WFP Nigeria Situation Report #3. http://reliefweb.int/report/nigeria/wfp-nigeria-situation-report-03-october-2016
22. Martin-Prevel, Y, Allemand, P, Wiesmann, D, et al. 20015. Moving Forward: On choosing a standard operational indicator for women’s dietary diversity. Available at: http://www.fao.org/3/a-i4942e.pdf
23. Food and Agricultural Organization (FAO) and FHI 360. 2016. Minimum Dietary Diversity for Women: A Guide for Measurement. Rome: FAO. Available at: http://www.fao.org/3/a-i5486e.pdf
7. Annexes
Annex 1: Local Government Areas and Estimated Accessible Population, by Survey Domain State Domain LGA Population
Gombi 194,055 Hong 206,123 Madagali 125,971 Maiha 80,723 Michika 162,931 Mubi North 175,467 Mubi South 153,835 Northern Adamawa Northern Song 245,537 Demsa 143,706 Fufore 246,120 Adamawa Ganye 173,784 Girei 186,947 Guyuk 204,118 Jada 199,430 Lamurde 80,349 Mayo-Belwa 162,520 Numan 81,664
Southern Adamawa Southern Shelleng 151,842 Teungo 48,367 Yola North 208,609 Yola South 365,030
Damboa 151,616
Gubio 187,849 Kaga 132,650 Konduga 188,117 Mafa 128,654
Central Borno Central Magumeri 256,733
Monguno 208,815
Bama 182,947 Dikwa 114,802 Kala/Balge 68,944 Borno
East Borno East Ngala 142,322
Jere 607,063 Jere
MMC & MMC Maiduguri 1,030,217
Mobbar 153,834 North
Borno Nganzai 101,679
Askira/Uba 256,301
Bayo 155,884 n Borno n Souther Biu 272,089
Chibok 112,815 Gwoza 199,702 Hawul 243,893 Kwaya/Kusar 129,637 Shani 219,859
Bade 204,246
Bursari 177,746
Yobe Geidam 316,411 Central Central Jakusko 190,243
Karasuwa 107,950 Machina 107,784 Nguru 207,627 Yunusari 216,066
Yobe North Yobe Yusufari 201,177 Damaturu 259,977
Fika 230,190 Fune 329,072 Gujba 229,301 Gulani 214,885 Nangere 183,440
Southern Yobe Southern Potiskum 749,099 Tarmua 141,202 Total 3 States 12,909,967
Annex 3. Maps of Local Government Areas, by Survey Domain
Figure. Map of Lower Government Areas by Survey Domain
1. Southern Adamawa 2. Northern Adamawa 3. Northern Borno 4. Southern Borno 5. East Borno 6. Central Borno 7. MCC/Jere 8. Central Yobe 9. Southern Yobe 10. Northern Yobe
Annex 4. List of nutrition indicators and definitions
S.N Indicators Numerator Denominator 1. Child Nutrition 1.1 Underweight
Number of children under age 5 who fall below Underweight Total number of children 1.1.1 minus two standard deviations from the median prevalence age 0-59 months weight for age of the WHO standard
Number of children under age 5 who fall between Moderate below minus two to greater than or equal to minus Total number of children 1.1.2 underweight three standard deviations from the median weight age 0-59 months prevalence for age of the WHO standard
Severe Total number of children 1.1.3 underweight Number of children under age 5 who fall below age 0-59 months prevalence minus three standard deviations from the median weight for age of the WHO standard 1.2 Stunting
Number of children under age 5 who fall below Stunting Total number of children 1.2.1 minus two standard deviations from the median prevalence age 0-59 months height for age of the WHO standard
Number of children under age 5 who fall between Moderate below minus two to greater than or equal to minus Total number of children 1.2.2 Stunting three standard deviations from the median height age 0-59 months prevalence for age of the WHO standard
Severe Number of children under age 5 who fall below Total number of children 1.2.3 Stunting minus three standard deviations from the median age 0-59 months prevalence height for age of the WHO standard 1.3 Wasting (Z-Score)
Number of children age 0-59 months who fall Wasting Total number of children 1.3.1 below minus two standard deviations from the prevalence age 0-59 months median weight for height of the WHO standard
Number of children age 0-59 months who fall Moderate between below minus two to greater than or equal Total number of children 1.3.2 Wasting to minus three standard deviations from the median age 0-59 months prevalence weight for height of the WHO standard
Severe Number of children age 0-59 months who fall Total number of children 1.3.3 Wasting below minus three standard deviations from the age 0-59 months prevalence median weight for height of the WHO standard
1.4 Acute malnutrition (MUAC &/or bilateral oedema) Wasting Number of children age 6-59 months who fall below Total number of children 1.4.1 prevalence MUAC 125 mm age 6-59 months Moderate Number of children age 6-59 months fall between Total number of children 1.4.2 Wasting below MUAC 125 mm and greater or equal to 115 age 6-59 months prevalence mm Severe Number of children age 6-59 months who fall below Total number of children 1.4.3 Wasting MUAC 115 mm age 6-59 months prevalence 1.5 Acute Malnutrition (WHZ &/ or bilateral oedema )
Acute Number of children age 6-59 months who fall Total number of children 1.5.1 malnutrition below minus two standard deviations from the age 6-59 months
prevalence median weight for height of the WHO standard
Moderate Number of children age 6-59 months who fall acute between below minus two to greater than or equal Total number of children 1.5.2 malnutrition to minus three standard deviations from the median age 6-59 months prevalence weight for height of the WHO standard Severe acute Number of children age 6-59 months who fall below Total number of children 1.5.3 malnutrition minus three standard deviations from the median age 6-59 months prevalence weight for height of the WHO standard
2. Mortality
Crude Total number of deaths of any cause occurring during Total number of persons per 2.1 Mortality the recall period (January 1, 2016 and the date of the 10,000 per day Rate survey)
Under 5 Total number of deaths among children under five of Total number of children 2.2 Mortality any cause occurring during the recall period (January under five per 10,000 per Rate 1, 2016 and the date of the survey) day
Child Health Number of children age 9 to 59 months Measles immunization Total number of children 9 to 3.1 who received measles vaccine before coverage 59 months the survey Prevalence of Number of children under age 5 years diarrhoea among Total number of children 3.2 who had diarrhoea in the last two children under age 5 under age 5 years weeks years Total number of children Diarrhoea treatment Number of children under age 5 years under age 5 years with 3.3 with oral rehydration with diarrhoea in the previous 2 weeks diarrhoea in the previous 2 salts (ORS) and zinc who received ORS and Zinc weeks Prevalence of fever Number of children under age 5 years Total number of children 3.4 among children under who had fever in the last two weeks under age 5 years age 5 years Number of children under age 5 years Total number of children Treatment of Malaria 3.5 who had fever in the last two weeks under age 5 years with fever with ACT who were treated with ACT in the previous 2 weeks
Number of households with Household availability (a) at least one mosquito nets Total number of households 3.6 of mosquito nets (b) at least one mosquito nets for surveyed every two people Total number of children Children under age 5 Number of children under age 5 years under age 5 who spent the 3.7 who slept under a who slept under a mosquito net the previous night in the mosquito net previous night interviewed households Intermittent Number of children under age 0 - 59 preventive treatment Total number of children 3.8 months who received iintermittent for of children under from age 0 - 59 months preventive treatment age 5 Prevalence of ARI Number of children under age 5 years Total number of children 3.9 among children under who had cough and rapid breathing in under age 5 years age 5 years the last two weeks Number of children under age 5 years Total number of children Treatment of ARI with who had cough and rapid breathing in under age 5 years with cough 3.10 antibiotics the last two weeks who were treated and rapid breathing in the with antibiotics previous 2 weeks
4. Public Health Campaigns
Number of households that lived in an area where MNCHW Geographic Total number of 4.1 Maternal Newborn and Child Health Week Coverage households activities were accessible
Number of households who received services Total number of 4.2 MNCHW Coverage during the Maternal Newborn and Child Health households Week Number of children age 12-59 months who given Total number of Deworming among 4.3 an anthelmintic drug in the 6 months preceding children age 12-59 children under age 5 the survey months Number of households reporting receipt of corn Fortified Blended Total number of 4.4 soy blend (CSB) in the three months preceding the Food Coverage households survey
5. Women Nutrition
Acute Malnutrition Number of women age 15 - 49 years with a MUAC Total number of 5.1 prevalence value less than or equal to 221 mm women age 15 to 49
Moderate Acute Number of women age 15 - 49 years with a MUAC Total number of 5.2 Malnutrition value that falls between below MUAC 221 mm and women age 15 to 49 prevalence is greater than or equal to 214 mm Severe Acute Number of women age 15 - 49 years who fall Total number of 5.3 Malnutrition below MUAC 214 mm women age 15 to 49 prevalence Minimum Dietary Number of women age 15 - 49 years consuming Number of randomly 5.4 Diversity for foods from less than 5 of 10 dietary groups during selected women age Women the day before the survey 15 to 49
6. Water and Sanitation Household water Number of households reported treating drinking Total number of 6.1 treatment water (any method) households Number of households treating drinking water using Total number of Household water at least one appropriate method defined as: boiling; households reporting 6.2 treatment adding bleach or chlorine; using a water filter; or treating drinking method using solar disinfection water Use of Number of households with handwashing location / Total number of 6.3 handwashing facility households location
7. Infant & Young Child Feeding 7.1 Children ever Number of children 0-23 (born in the last 24) months Total number of breastfed who were ever breastfed children aged 0-23 months 7.2 Early initiation of Number of children 0-23 months who were put to the Total number of breastfeeding breast within the first hour of birth children aged 0-23 months 7.3 Bottle feeding Number of children 0–23 months of age who were fed Total number of with a bottle during the previous day children aged 0-23 months 7.4 Exclusive Number of infants 0-5 months who received breast milk Total number of breastfeeding the previous day (in the past 24 hours) and did not infants aged 0-5 receive any other foods or liquids during the previous months day
7.5 Predominant Number of Infants 0–5 months of age who received Total number of breastfeeding breast milk as the predominant source of nourishment infants aged 0-5 under 6 months during the previous day months
7.6 Continued Number of children 12–15 months of age who received Total number of breastfeeding (at breast milk during the previous day children aged 12- 1 year) 15 months 7.7 Continued Number of children 20–23 months of age who received Total number of breastfeeding at breast milk during the previous day children aged 20- 2 years 23 months 7.8 Age appropriate Number of Infants 0–5 months of age who received only Total number of Breastfeeding breast milk during the previous day and Children 6–23 children aged 0-23 months of age who received breast milk, as well as months solid, semi-solid or soft foods, during the previous day
7.9 Introduction of Number of infants 6–8 months of age who breastfed and Total number of solid, semi-solid also received solid, semi-solid or soft foods during the children aged 6-8 or soft foods previous day months
7.10 Minimum Dietary Number of children 6–23 months of age who received Total number of Diversity foods from ≥4 food groups36 during the previous day children aged 6-23 months
7.11 Minimum Meal Number of breastfed and non-breastfed children 6–23 Total number of Frequency months of age who received solid, semi-solid or soft breastfed children foods the minimum number of times37 or more during aged 6-23 months the previous day
7.12 Minimum Number of breastfed and non-breastfed children 6–23 Total number of Acceptable Diet months of age who had at least the minimum dietary breastfed children diversity and the minimum meal frequency during the aged 6-23 months previous day
36 Dietary diversity is computed based on 7 food groups as recommended by WHO (2008b) which comprise of: grains, roots and tubers; legumes and nuts; dairy products; flesh foods (meat, fish, poultry and organ meats); eggs; vitamin-A rich fruits and vegetables other fruits and vegetables. Consumption of any amount of food from each food group is sufficient to count except if a food item was only used as a condiment. 37 Minimum dietary diversity is defined as: 2 times for breastfed infants 6–8 months old; 3 times for breastfed children 9–23 months old and 4 times for non-breastfed children 6–23 months old (WHO, 2008a). “Meals” include both meals and snacks (other than trivial amounts) as reported by the respondents.
Annex 5: Calendar of Local Events Month Seasons/ Holidays 2014 2015 2016 2017 2018 2019 57 45 33 21 9 Explosion at General Hosp. Rann New Years Missing Aircraft in Rann January Beginning of National ID The Governor and UN Buhari's visit to Borno and Harmattan Gamboru Mosque Bomb (Janairu) Maloud (3 Jan) card Registration in Secretary's visit to Bama' Yobe States for campaign Armed Forces Day Blast Damaturu Gamari Attack rally 1st attack on Rann Attack and Snatching of food items by insurgents in Banki 56 44 32 20 8 Flooding from cameroon Valentine Day to Rann Adaption of Dapchi School End of Harmattan Fulani Attack (Kolu), Bomb Blast in Ajiri Ward February Change of Damaturu Girls, Explosion behind MSF Attacked of Governors convoy Land Preparation General Election Dikwa (Fabreru) market day site Rann in Ngala and Presidential Argungu Fishing (Postponed) Arrival of the state Eid-ul maulud First Issuance Of ID for Food Election & National Assembly festival Jimeta bomb blast Governor to Kukawa Reg. by IOM in Bama Red Cross 1st GFD in Mobbar 55 43 31 19 7 Beginning of Hot Release of Dapchi School Ambush on troops along Season Presidential Election & Muharam Girls from captivity, March (Maris) Ajiri - Dikwa Road Governorship Election & State Land Preparation National Assembly Gogaram fishing festival Abduction of 3 UN Aid Mass arrival of IDPS House of Assembly Fishing Festival Muharram in Bade Yobe Workers in Rann From Cameroon to Banki Return of Host Community 54 42 30 18 6 Abduction of Chibok Bush Clearing in Rann Gubernatorial & State Fire Outbreak In Rann Hot Season (Rani) Girls, Nyanya Bomb IOM Biometric reg, for April (Afirilu) Elections, Easter, Bomblast In Gwoza Land Preparation Blast food distribution in Ngala Oviia Osese Festival, Massive Returnees to Dikwa Bring Back Our Attack by Insurgents On Sacking Of IGP Camp Girls Protest Pulka 53 41 29 17 5 Democracy Day Yobe Millitary Base Beginning of Ramadan Hot Season (Rani) Attack, Car Bomb In Beginning of return of Registration of World Bank May (Mayu) Swearing in of President Worker's Day Jos, Attack of IDP's to their homes in Planting of crops in Bama Beginning of Ramadan Buhari Children's Day Gamborun, Watan Yobe Seizing of Fish by Military in Sha'Aban Kukawa 52 40 28 16 4 Nupe Day Celebration (Bida Oro festival (Kabba, kogi), Niger state), Beginning of Ramadan, June (Uni) Beginning of rains Election of Senate Beginning of Ramadan Eid-el-fitri Sallah, Karamar Eid-el-fitri Sallah, Karamar Beginning of Return of IDP's to Gala, President, Beginning of Sallah Ramadan, Banex Koh attack in Adamawa Sallah Ramadan (28 June) Plaza bomb blast (Abuja) 63 51 39 27 15 3 End of Ramadan ( karamar sallah) New Arrival from Tumbun Beginning of Raining October-19 Kare Okun Land Yam Eid-el-fitri Sallah, Season Rainy season Attack on Military Patrol in July (Uli) Festival (Kogi) Zaria Bomb Blast Karamin Sallah, Death of Arabic Village IDP Camp Closing of school Banki End of Ramadan (Kaduna), Karaman Sallah Dr Ali Mongunu, was Opened in Ngala Failed Migration to Ebola Out Break Adamawa election Oubreak of Heps. E In Cameroon (Minimawo Ngala Camp) by IDPS IOM Biometric Card Reg. in Pulka 62 50 38 26 14 2 Blocking of road and network Rann Dibit Cultural Eid El Kabir, Opening of August Abduction of health Festival Kano horse riding Death of Borno state Damaturu/Biu road, IDP (Aginasta) personnel on Dikwa- Eid El Kabir, Babbar Sallah Eid El Kabir, Babbar Sallah Heavy rains (Durbar) festival Deputy Governor camp bomb blast in Maiduguri Road Adamawa Shelter Destruction by Heavy Wind in Pulka 61 49 37 25 13 1 Cholera Outbreak and Bomb Blast Borno State Govt House in Dikwa September School resumes Beginning of Hajj, to Bama, Death of Amna Babbar Sallah Disappearance of General (Satumba) Beginning of harvest attack of FCE Eid-el Kabir day (24-25) Sheveng in Adamawa, Attack on ISS Camp Ngala by Alkali and Political Partys Kabuga (Kano) Distribution of National Insurgence Primary Elections ID (Yobe) Insurgence Attack in Banki Month of Thunderstorm in Pulka 60 48 36 24 12 0
Eid El Kabir, Bomb Flooding from cameroon to Blast in Emir of Rann October Independence day Death of Borno Bomb Blast in Ajiri Ward kano Mosque, EIKA Political Partys Primary (Okkutoba) End of Rains Harvest Hijira day (14-15) Commissioner for Dikwa Featival in Ebira Elections enviroment (Waziri Imam) Arrival of the state Governor Land (Kogi); Tafiya to Kukawa Achazai Ambush on Military In Banki 59 47 35 23 11
End of Hajj, Bird Attack on Farm Product Rann Attack on military and Civilian Dawowan November convoy en route Adamawa Attack of Soja's in Metele Alhazai,Muharam Gashua students riot in Gajibo Attack (Nuwamiba) Harvest and Alh. Atiku's Turban as (Wata Daya) or Cika- Yobe Sabon Ruwan Chaadi in Kukawa Waziri of Adamawa Ciki, Kano central Release of 15 Female Police Officers in Banki mosque bomb blast Red Cross Last GFD in Mobbar Christmas 58 46 34 22 10 Harmattan Introduction of new Attack in neighbouring December Murama Festival in Borno, Attack of Kukareta, Katarko, Uhola Cultural 100 Naira, APC town of Cameroon (Dusamba) Muharam, Marriage of Buni Gari, Buni Yadi and Festival Presidental Election Bomb Blast in Pulka Gen. Tukur Burate's son Baga Boxing day Primaries Firgi Farming in Pulka
Month Seasons/ Holidays 2014 2015 2016 2017 2018 2019 56 44 32 20 8 Explosion at General Hosp. Rann New Years Missing Aircraft in Rann January Beginning of National ID The Governor and UN Buhari's visit to Borno and Harmattan Gamboru Mosque Bomb (Janairu) Maloud (3 Jan) card Registration in Secretary's visit to Bama' Yobe States for campaign Armed Forces Day Blast Damaturu Gamari Attack rally 1st attack on Rann Attack and Snatching of food items by insurgents in Banki 55 43 31 19 7 Valentine Day Flooding from cameroon Adaption of Dapchi School End of Harmattan Fulani Attack (Kolu), to Rann February Change of Damaturu Girls, Explosion behind MSF Attacked of Governors convoy Land Preparation General Election Bomb Blast in Ajiri Ward (Fabreru) market day site Rann in Ngala and Presidential Argungu Fishing (Postponed) Dikwa Eid-ul maulud First Issuance Of ID for Food Election & National Assembly festival Jimeta bomb blast Arrival of the state Reg. by IOM in Bama Governor to Kukawa 54 42 30 18 6 Beginning of Hot Release of Dapchi School Ambush on troops along Season Presidential Election & Muharam Girls from captivity, March (Maris) Ajiri - Dikwa Road Governorship Election & State Land Preparation National Assembly Gogaram fishing festival Abduction of 3 UN Aid Mass arrival of IDPS House of Assembly Fishing Festival Muharram in Bade Yobe Workers in Rann From Cameroon to Banki Return of Host Community 53 41 29 17 5
Abduction of Chibok Bush Clearing in Rann Gubernatorial & State Fire Outbreak In Rann Hot Season (Rani) Girls, Nyanya Bomb IOM Biometric reg, for April (Afirilu) Elections, Easter, Bomblast In Gwoza Land Preparation Blast food distribution in Ngala Oviia Osese Festival, Massive Returnees to Dikwa Bring Back Our Attack by Insurgents On Sacking Of IGP Camp Girls Protest Pulka
52 40 28 16 4 Democracy Day Yobe Millitary Base Beginning of Ramadan Hot Season (Rani) Attack, Car Bomb In Beginning of return of Registration of World Bank May (Mayu) Swearing in of President Worker's Day Jos, Attack of IDP's to their homes in Planting of crops in Bama Beginning of Ramadan Buhari Children's Day Gamborun, Watan Yobe Seizing of Fish by Military in Sha'Aban Kukawa 51 39 27 15 3 Nupe Day Celebration (Bida Oro festival (Kabba, kogi), Niger state), Beginning of Ramadan, June (Uni) Beginning of rains Election of Senate Beginning of Ramadan Eid-el-fitri Sallah, Karamar Eid-el-fitri Sallah, Karamar Beginning of Return of IDP's to Gala, President, Beginning of Sallah Ramadan, Banex Koh attack in Adamawa Sallah Ramadan (28 June) Plaza bomb blast (Abuja) 50 38 26 14 2 End of Ramadan ( karamar New Arrival from Tumbun sallah) Kare
September-19 Okun Land Yam Eid-el-fitri Sallah, Rainy season Beginning of Raining Attack on Military Patrol in July (Uli) Festival (Kogi) Zaria Bomb Blast Karamin Sallah, Death of Closing of school Season Banki End of Ramadan (Kaduna), Karaman Sallah Dr Ali Mongunu, Arabic Village IDP Camp Failed Migration to Ebola Out Break Adamawa election was Opened in Ngala Cameroon (Minimawo Oubreak of Heps. E In Camp) by IDPS 61 49 37 25 13 1 Blocking of road and network Rann Dibit Cultural Eid El Kabir, Opening of August Abduction of health Festival Kano horse riding Death of Borno state Damaturu/Biu road, IDP (Aginasta) personnel on Dikwa- Eid El Kabir, Babbar Sallah Eid El Kabir, Babbar Sallah Heavy rains (Durbar) festival Deputy Governor camp bomb blast in Maiduguri Road Adamawa Shelter Destruction by Heavy Wind in Pulka 60 48 36 24 12 0 Cholera Outbreak and Bomb Blast Borno State Govt House in Dikwa September School resumes Beginning of Hajj, to Bama, Death of Amna Babbar Sallah Disappearance of General (Satumba) Beginning of harvest attack of FCE Eid-el Kabir day (24-25) Sheveng in Adamawa, Attack on ISS Camp Ngala by Alkali and Political Partys Kabuga (Kano) Distribution of National Insurgence Primary Elections Insurgence Attack in Banki ID (Yobe) Month of Thunderstorm in Pulka 59 47 35 23 11 Eid El Kabir, Bomb Flooding from cameroon to Blast in Emir of Rann October Independence day Death of Borno Bomb Blast in Ajiri Ward kano Mosque, EIKA Political Partys Primary (Okkutoba) End of Rains Harvest Hijira day (14-15) Commissioner for Dikwa Featival in Ebira Elections enviroment (Waziri Imam) Arrival of the state Governor Land (Kogi); Tafiya to Kukawa Achazai Ambush on Military In Banki 58 46 34 22 10 End of Hajj, Bird Attack on Farm Product Rann Attack on military and Civilian Dawowan November convoy en route Adamawa Attack of Soja's in Metele Harvest Alhazai,Muharam Gashua students riot in Gajibo Attack (Nuwamiba) and Alh. Atiku's Turban as (Wata Daya) or Cika- Yobe Sabon Ruwan Chaadi in Kukawa Waziri of Adamawa Ciki, Kano central Release of 15 Female Police Officers in Banki mosque bomb blast Red Cross Last GFD in Mobbar 57 45 33 21 9 Christmas Harmattan Introduction of new Attack in neighbouring December Murama Festival in Borno, Attack of Kukareta, Katarko, Uhola Cultural 100 Naira, APC town of Cameroon (Dusamba) Muharam, Marriage of Buni Gari, Buni Yadi and Festival Presidental Election Bomb Blast in Pulka Gen. Tukur Burate's son Baga Boxing day Primaries Firgi Farming in Pulka
Annex 6: Selected Clusters State Domain LGA Ward/Locality Name Cluster Name Cluster Rem No ark Yobe C Yobe Bade Gashua Moh'd Mai Turare 801 Yobe C Yobe Bade Gashua Alh. Manager 802 Yobe C Yobe Bade Gashua Gstc Staff Quarters 803 Yobe C Yobe Bade Gashua Mallam Mai Mata 804 Yobe C Yobe Bade Gashua Sarkin Ruwa 805 Yobe C Yobe Bade Asbak Alh. Mai Dumma 806 Yobe C Yobe Bade Dalah Sule Inuwa 807 Yobe C Yobe Bade Gwio Alhaji Idi 808 Yobe C Yobe Bursari Garin Bulama Dogo Bulama Dogo 809 Yobe C Yobe Bursari Nangere Bulama Buhari 810 Yobe C Yobe Bursari Garin Aduwa Mallam Marghi Ali 811 Yobe C Yobe Bursari Musari Baruma Haruna 812 Yobe C Yobe Bursari Zurkaya Zurkaya Pr. Sch. 813 Yobe C Yobe Bursari Dumukai Mallam Musa 814 Yobe C Yobe Bursari Machidori Bulama Idi 815 Yobe C Yobe Geidam Kusur Goni Ali Kindilla 816 Yobe C Yobe Geidam Buramdi Bulama Buramdi 817 Yobe C Yobe Geidam Ali Fantamiri Bulama Abba Kur 818 Yobe C Yobe Geidam Goni Bukar Kaudimiri Goni Bukar Kawudimi 819 Yobe C Yobe Geidam Mauwa Umarti Bulama Fugu 820 Yobe C Yobe Geidam Geidam Goni Aji 821 Yobe C Yobe Geidam Geidam Baba Goni Usman 822 Yobe C Yobe Geidam Shuwwari Alhaji Garba 823 Yobe C Yobe Jakusko Jakusko Alh. Mamman Mai Jaki 824 Yobe C Yobe Jakusko Kaluluwa Alhaji Audu 825 Yobe C Yobe Jakusko Ngajaje Ardo Isah 826 Yobe C Yobe Jakusko Muguram Tsoho Mai Ganga 827 Yobe C Yobe Jakusko Nasari Isa Wakil 828 Yobe C Yobe Jakusko Dantakune Ahmadu Janari 829 Yobe C Yobe Jakusko Garin Goje Mai Gari Haruna 830 Yobe C Yobe Jakusko Amshi Alh. Musa 831 Yobe C Yobe Jakusko Gogaram Mallam Biri 832 Yobe C Yobe Jakusko Guju - Guju Maina Hassan 833 Yobe C Yobe Jakusko Maleka Ibrahim M. Yusubu 834 Yobe C Yobe Jakusko Kagamu Kara Bade 835 Yobe C Yobe Jakusko Gaya Motor Galadima Ilu 836 Yobe C Yobe Bade Gashua Alh. Moh's Mai Shayi 837 Rese rve Yobe C Yobe Bursari Gana Wajiri A Mamman Alhaji 838 Rese rve Yobe C Yobe Geidam Barko Bulama Duna Bulama Duna 839 Rese rve Yobe C Yobe Jakusko Nasari Kanga Manu 840 Rese rve Adam N Demsa Nassarawo-Demsa Mutari Yamusa 201 awa Adamawa
Adam N Demsa Mbula Sunday Dinki 202 awa Adamawa Adam N Demsa Ngangsari Pastor Robert L 203 awa Adamawa Adam N Fufore Wuro Bayo Wuro Bayo 204 awa Adamawa Adam N Fufore Yolde Njoro Yolde Jauro 205 awa Adamawa Adam N Fufore Bantahi Ardo Bello Jalo 206 awa Adamawa Adam N Ganye Samben Samben 207 awa Adamawa Adam N Ganye Tim Tubi/Yapassi Yapasi 208 awa Adamawa Adam N Ganye Sugu Palace 209 awa Adamawa Adam N Gombi Gombi Moh'd Gada 210 awa Adamawa Adam N Gombi Sheno Danjuma Bitrus 211 awa Adamawa Adam N Guyuk Lokoro Calvin Amakula 212 awa Adamawa Adam N Guyuk Kola Anguwan Fulani 213 awa Adamawa Adam N Guyuk Gwalura Garba Buhari 214 awa Adamawa Adam N Jada Mayo Ine Gari ,Gumbiri Mayo Ine Gari 215 awa Adamawa ,Allam Wat Adam N Jada Tappare ,Yaken Jebeni Tappare 216 awa Adamawa Adam N Lamurd Bulkutu Gabriel Yakubu 217 awa Adamawa e Adam N Lamurd Ngbakowo Primary School 218 awa Adamawa e Adam N Mayo- Kwanan Kumbai Polituna 219 awa Adamawa Belwa Adam N Mayo- Wakka Vakka 220 awa Adamawa Belwa Adam N Numan Hodikakai L.C.C.N 221 awa Adamawa Adam N Numan Ngbalang Umaru Garba 222 awa Adamawa Adam N Shelleng Babrah Jauro Haniel 223 awa Adamawa Adam N Shelleng Gwagwarap Oliver Bware 224 awa Adamawa Adam N Toungo Toungo Abdul-Kadiri Yerima 225 awa Adamawa Adam N Yola Fombare P.D.P Secretariat 226 awa Adamawa North Adam N Yola Jimeta Dawa'u Clinic 227 awa Adamawa North Adam N Yola Jalingoyel Pink And Violet House 228 awa Adamawa North Adam N Yola Ngurore C.A Yakubu 229 awa Adamawa South Adam N Yola Yola Aliyu Musdafa Clinic 230 awa Adamawa South Adam N Yola Wuro Hausa Hajiya Atiku 231
awa Adamawa South Adam N Demsa Gurin Kasuwa Tartius Dabansi 232 Rese awa Adamawa rve Adam N Gombi Ngalga Ngalga 233 Rese awa Adamawa rve Adam N Mayo- Yaruyi Yaruyi 234 Rese awa Adamawa Belwa rve Adam N Yola Madagalire Usman Chollo Filling 235 Rese awa Adamawa North Station rve YOBE N Yobe Karasuw Rugar Zannari B Adamu Lamido 1001 a YOBE N Yobe Karasuw Gawu Zaribe Mallam Mohammadu 1002 a YOBE N Yobe Karasuw Jajimaji Alhaji Diyeh 1003 a YOBE N Yobe Karasuw Kilbuwa Alhaji Duna 1004 a YOBE N Yobe Karasuw Madu Gawari Mai Gari Barma M. 1005 a YOBE N Yobe Karasuw Isari Usaini Mahauchi 1006 a YOBE N Yobe Karasuw Garin Jadi Moh'd Suleiman 1007 a YOBE N Yobe Machina Kunshini Mallam Umar 1008 YOBE N Yobe Machina Burdu Maram Isheu Dan Marke 1009 YOBE N Yobe Machina Shehuri Bulliti Abdu Alh. Haru 1010 YOBE N Yobe Machina Kaisuwa Ba Shettima 1011 YOBE N Yobe Nguru Kakuri Baba Alh. 1012 YOBE N Yobe Nguru Garbi Mai Anguwa Ya'u 1013 YOBE N Yobe Nguru Gajamu Shagari Nyako 1014 YOBE N Yobe Nguru Nguru Mallam Mahiru 1015 YOBE N Yobe Nguru Nguru Gani Kime 1016 YOBE N Yobe Nguru Nguru Alhaji Hamza 1017 YOBE N Yobe Nguru Nguru Primary Health Care 1018 YOBE N Yobe Nguru Gorgole Maigari Haru 1019 YOBE N Yobe Nguru Bulanguwa Alhaji Boka 1020 YOBE N Yobe Nguru Karambari Alhaji Abdu 1021 YOBE N Yobe Nguru Rugar M. J. Ali Maigari Wanzam 1022 YOBE N Yobe Yunusari Alhaji Tahiruri Bulama Bukar 1023 YOBE N Yobe Yunusari Shehuri Fulatari Dangil Bulama M. Kolomi 1024 YOBE N Yobe Yunusari Kumamiram Ba Dumba Barma 1025 YOBE N Yobe Yunusari Zai Ahmadu Lawan 1026 YOBE N Yobe Yunusari Saleri Mallam Umara 1027 YOBE N Yobe Yunusari Fulatari Haruna Haruna Gidado 1028 YOBE N Yobe Yunusari Kawiya Mohammed Kaniya 1029 YOBE N Yobe Yunusari Njirabo Bulama Ibrahim 1030 YOBE N Yobe Yusufari Bula Kuloye Mallam Budu 1031 YOBE N Yobe Yusufari Abanderi Bah Jajimi 1032 YOBE N Yobe Yusufari Dusare Mai Gari Audu 1033 YOBE N Yobe Yusufari Bula Kulo Mai Gari Ari 1034 YOBE N Yobe Yusufari Rugar Lamido Timi Mai Gari Mallam 1035 Kuwara
YOBE N Yobe Yusufari Gurdari Mallam Gajere 1036 YOBE N Yobe Yusufari Kirewa Mai Gari Ahmadu 1037 Yobe N Yobe Karasuw Kilbuwa Mallam Ishiyaka 1038 Rese a rve Yobe N Yobe Nguru Garbi Bashir Sheriff 1039 Rese rve Yobe N Yobe Yunusari Birnin Gazargamu Abubakar Jali 1040 Rese rve Yobe N Yobe Yusufari Jindigi Mai Gari Umar 1041 Rese rve Adam S Girei Jabbi Lamba Mal. Abubakar H/Jam 101 awa Adamawa Adam S Girei Langerei Langire 'B' 102 awa Adamawa Adam S Girei Sangere Jauro Yahaya Lavi Restaurant 103 awa Adamawa Adam S Girei Viniklang Bakari Liman 104 awa Adamawa Adam S Hong Gaya Gartsanu Adanaya Talman 105 awa Adamawa Adam S Hong Uba Adamawa Arewa Bread 106 awa Adamawa Adam S Hong Njairi Ekelisia Baptist Njayiri 107 awa Adamawa Adam S Hong Gashaka Gashaka Chanyi 108 awa Adamawa Adam S Hong Puba Puba 109 awa Adamawa Adam S Madagal Kirchinga Fulani Kirchinga Fulani 110 awa Adamawa i Adam S Madagal Madagali Baba Ardo 111 awa Adamawa i Adam S Madagal Tur Thoma Ngawa 112 awa Adamawa i Adam S Madagal Kwafur Kwafur Pri. Sch./ Giwa 113 awa Adamawa i Izigu Adam S Madagal Kuda (Wuro Nga) Lawan Watham 114 awa Adamawa i Adam S Maiha Suwari Suwari B 115 awa Adamawa Adam S Maiha Lefen Jauro Ahmadu 116 awa Adamawa Adam S Maiha Belel Jauro Julde Yerima 117 awa Adamawa Adam S Michika Dzuruk Joshua Bitrus 118 awa Adamawa Adam S Michika Margwa Titi Kwaji/Wagedin 119 awa Adamawa Chita Adam S Michika Michika Vagalsi Kwada 120 awa Adamawa Adam S Michika Kankila Adamu Koji Kalla 121 awa Adamawa Adam S Michika Tilli Tari Masighu 122 awa Adamawa Adam S Mubi Betso Manga Betso Manga 123 awa Adamawa North Adam S Mubi Maskoka Ibrahim Manegla 124 awa Adamawa North Adam S Mubi Vimtim Jauro Ezra Ndibo 125
awa Adamawa North Adam S Mubi Mubi Alh. Sani Maimashin 126 awa Adamawa North Adam S Mubi Mubi Alh. Dan'iya Mai Yadi 127 awa Adamawa North Adam S Mubi Mubi Union Bank Mubi 128 awa Adamawa South Adam S Mubi Mubi Ali. O.P.P 129 awa Adamawa South Adam S Mubi Gipalema Gipalema 130 awa Adamawa South Adam S Mubi Gella Aminu Sa'ad 131 awa Adamawa South Adam S Song Prambe Elkanah Maratobi 132 awa Adamawa Adam S Song Sangra Fulani Sangra Fulani 133 awa Adamawa Adam S Song Gakta Gakta 134 awa Adamawa Adam S Song Jimeta Paul Maigari Yuguda 135 awa Adamawa Adam S Song Dakkai Dakkai 136 awa Adamawa Adam S Song Song Alh. Sa’Adu Ibrahim 137 awa Adamawa Adam S Song Barikin Sajo Primary Scholl Barikin 138 awa Adamawa Sajo Adam S Girei Sabon Gari Sabon Gari 139 Rese awa Adamawa rve Adam S Madagal Madagali Girls Hostel 140 Rese awa Adamawa i rve Adam S Michika Michika Jauro Helwa 141 Rese awa Adamawa rve Adam S Mubi Madanya Ndotti Ali 142 Rese awa Adamawa South rve YOBE S Yobe Damatu Damaturu Police Barrack Gjb Rd 901 ru YOBE S Yobe Damatu Damaturu Oasis Hotel 902 ru YOBE S Yobe Damatu Goni Tujari Bulama Ngari 903 ru YOBE S Yobe Fika Shenbirem Madaki Shengile 904 YOBE S Yobe Fika Koyaya Mai Anguwa Haruna 905 YOBE S Yobe Fika Buba Damo Jauro Buba Damo 906 YOBE S Yobe Fika Turmi Kare-Kare Umaru Makeri 907 YOBE S Yobe Fune Hardo Isa Hardo Isa 908 YOBE S Yobe Fune Dankara Bulama Suleiman 909 YOBE S Yobe Fune Ngelmandoro Jauro Julde 910 YOBE S Yobe Fune Ngelzarma Maiunguwa Ado 911 YOBE S Yobe Fune Maltumba Jauro Hamma 912 YOBE S Yobe Fune G.W. Siminti G.W. Siminti 913 YOBE S Yobe Fune Jajere Ada Mai Lifati 914 YOBE S Yobe Fune Mainari Lamido Sale 915 YOBE S Yobe Fune Kotire Jauro Damana 916 YOBE S Yobe Fune Koli Baba Gari 917
YOBE S Yobe Gujba Goniri Bulama Tijani 918 YOBE S Yobe Gujba Katarko Mai Anguwa M. Mohd. 919 YOBE S Yobe Gujba Ambiya Tasha Police Station 920 YOBE S Yobe Gujba Buni Yadi Mohammed Sheriff 921 Gulani YOBE S Yobe Gulani Ruhu Mai Masara Taiyabu 922 YOBE S Yobe Gulani Njibulwa Shugaba Gidado 923 YOBE S Yobe Gulani Zango Mamman Rilwanu 924 YOBE S Yobe Nangere Shira Shira 925 YOBE S Yobe Nangere Gelodori Jauro Ahmadu 926 YOBE S Yobe Nangere Kukuri Kukuri Worutelli 927 YOBE S Yobe Potisku Potiskum Haruna Babayo 928 m YOBE S Yobe Potisku Potiskum Mal. Saidu Ningim 929 m YOBE S Yobe Potisku Potiskum Mallam Yahuza 930 m YOBE S Yobe Potisku Potiskum Chiroma House Gstc 931 m YOBE S Yobe Potisku Potiskum Alhaji Lamara 932 m YOBE S Yobe Potisku Gishuwa Dabuwa Gareji Alh. Hassan 933 m YOBE S Yobe Potisku Mamudo Alhaji Abba 934 m YOBE S Yobe Tarmua Mandoli Burem Gambomi 935 YOBE S Yobe Tarmua Chirokusko Mai Anguwa Yale 936 Yobe S Yobe Damatu Dumbulwa I Sale Audu Liman 937 Rese ru rve Yobe S Yobe Fune Sabon Garin Idi Barde Maiunguwa Shuaibu 938 Rese rve Yobe S Yobe Gujba Buni Yadi Madu Goniri 939 Rese rve Yobe S Yobe Potisku Potiskum Ba Daine 940 Rese m rve Borno Southern Askira/ Hausari Tampul Tampul 401 Borno Uba Borno Southern Askira/ Lassa Shishiwa 402 Borno Uba Borno Southern Askira/ Ngulde Whala 403 Borno Uba Borno Southern Bayo Balbaya Zona Gabas 404 Borno Borno Southern Bayo Gamdadi Gamadadi Anguwan 405 Borno Galadima Borno Southern Bayo Jaragol Jaragol 406 Borno Borno Southern Bayo Telii Gedaba Fulani 407 Borno Borno Southern Bayo Wuyo Wuyo Town 408 Borno Borno Southern Biu Dugja Diza 409 Borno Borno Southern Biu Dugja Tabra Tsahuyam 410 Borno Borno Southern Biu Galdimari Nasarawa 411 Borno
Borno Southern Biu Gunda Buba Shandu Sarkin 412 Borno Aska Borno Southern Biu Gur Zira Gudugu 413 Borno Borno Southern Biu Miringa Dashu 414 Borno Borno Southern Biu Yawi Yalwa Barki 415 Borno Borno Southern Biu Zarawuyaki Zarawuyaku 416 Borno Borno Southern Chibok Kurbumbulla Kuburmbula Kwikanda 417 Borno Borno Southern Chibok Pemi Bila Musa 418 Borno Borno Southern Hawul Bilingwi Ghumma 419 Borno Borno Southern Hawul Gwanzang Bulama Tuakari 420 Borno Borno Southern Hawul Hizhi Bwala Kwaguninim 421 Borno Borno Southern Hawul Kwajaffa Debiro 422 Borno Borno Southern Hawul Kwaya Bura Yaulari 423 Borno Borno Southern Hawul Puba Vidau HA_50 424 Borno Borno Southern Hawul Shaffa Shinduffu Sikta Side 425 Borno Borno Southern Kwaya Guwal Madi Mallam 426 Borno Kusar Borno Southern Kwaya Peta Anguwan Audu 427 Borno Kusar Borno Southern Shani Bargu Kirkatha Umoru 428 Borno Borno Southern Shani Gasi Jauro Ruwace 429 Borno Borno Southern Shani Kubo Dandang Hardo 430 Borno Borno Southern Shani Shani Bakaina Dera 431 Borno Borno Southern Shani Walama SSA_2 432 Rese Borno rve Borno Southern Askira/ Uba Kidisa 433 Rese Borno Uba rve Borno Southern Askira/ Uba Thlikwaji 434 Rese Borno Uba rve Borno Southern Kwaya Kwaya Kusar Guba 435 Rese Borno Kusar rve Borno Southern Shani Gwalasho Jauro Hamma 436 Rese Borno rve Borno Central Damboa Azir Multe Sabon Gari Gana 601 Borno Borno Central Damboa Damboa Camp-CENTRAL PRI 602 Borno SCH DAMBOA Borno Central Damboa Damboa Camp - SSS QUARTERS 603 Borno Borno Central Damboa Nzuba Wayaram Kauji Kura 604 Borno Borno Central Gubio Ardimini SSA_8 605
Borno Borno Central Gubio Gubio I Lawanti 606 Borno Borno Central Gubio Kingowa Kadauri 607 Borno Borno Central Gubio Ngetra Kasacha 608 Borno Borno Central Gubio Zowo Karari 609 Borno Borno Central Kaga Benisheikh Bulama Bukar Kolo 610 Borno Borno Central Kaga Karagawaru HA_3 611 Borno Borno Central Kaga Mainok HA_5 612 Borno Borno Central Kaga Ngamdu Goni Umarti 613 Borno Borno Central Kaga Wajiro HA_3 614 Borno Borno Central Konduga Auno 1000 Eatate 615 Borno Borno Central Konduga Auno HA_38 617 Borno Borno Central Konduga Dalori Camp - 250 HOUSING 618 Borno ESTATE Borno Central Konduga Dalori Camp - FED TRAINING 619 Borno CENTER Borno Central Konduga Dalori Dalorima House 620 Borno Borno Central Konduga Jakana Kontori Fasham 621 Borno Borno Central Konduga Konduga Camp - KALARI ABULE 622 Borno Borno Central Mafa Mafa Aji Sambori 623 Borno Borno Central Mafa Tamsum Gamdua Fulatari Gida 100 624 Borno Borno Central Mafa Tamsum Gamdua Goni Kachallari 625 Borno Borno Central Mafa Tamsum Gamdua Gwazari 626 Borno Borno Central Magume Furram Furram Lawanti 627 Borno ri Borno Central Magume Hoyo Chingua HA_29 628 Borno ri Borno Central Magume Kareram Gasauwamari 629 Borno ri Borno Central Magume Titiwa HA_29 630 Borno ri BORN Central Mongun Monguno Camp - Gana Ali 631 O Borno o BORN Central Mongun Monguno Camp-Govt Girls Sec 632 O Borno o Sch (Ggss) BORN Central Mongun Monguno Camp - Gssss Monguno 633 O Borno o BORN Central Mongun Monguno Camp - Kuya Primary 634 O Borno o School BORN Central Mongun Monguno Camp - Vertinary 635 O Borno o
Borno Central Magume Gajiganna Kori 639 Rese Borno ri rve Borno Central Magume Ngamma HA_21 640 Rese Borno ri rve Borno Central Konduga Auno Auno 616, 641 1 Borno Rese rve Borno Central Mongun Monguno Monguno 636, 1 Borno o 637, 638 Rese rve Borno East Bama Bama Dina Bama Dina 501 Borno Borno East Bama Shehuri Bama Dina - Bukar 505 Borno Kawuri Borno East Bama Shehuri Bayan Tasha 506 Borno Borno East Bama Shehuri Gaji Masar 507 Borno Borno East Dikwa Dikwa Agric Store 511 Borno Borno East Dikwa Dikwa Camp - AGRIC IDP 512 Borno CAMP Borno East Dikwa Dikwa Camp - FULATARI CAMP 513 Borno Borno East Dikwa Dikwa Camp - MINISTRY OF 514 Borno WORKS CAMP Borno East Dikwa Dikwa Camp - SANGAYA 515 Borno Borno East Dikwa Dikwa Camp - SHEWARI CAMP 516 Borno Borno East Dikwa Dikwa Kulagoru 517 Borno Borno East Gwoza Bita Izge Biwa 518 Borno Borno East Gwoza Bulabulin Gwoza Wakani Dalhatu 519 Borno Borno East Gwoza GWOZA TOWN Camp - 20 HOUSING 520 Borno GADAMAYO UNIT Borno East Gwoza Hambagda Limankara Hudughum 521 Borno Jaje Borno East Gwoza Hausari Anguwan Dogo Huya 522 Borno Borno East Gwoza Pulka Bokko Bala Daga Whiza 523 Borno Borno East Gwoza Pulka Bokko Bulama Manya Tada 524 Borno Borno East Gwoza Pulka Bokko Majuwane 525 Borno Borno East Gwoza PULKA/BOKKO Camp - UMBAZAH ROCK 526 Borno SIDE CAMP Borno East Kala Rann "A" Camp - Boarding 527 Borno Balge Primary School Borno East Kala Rann "A" Camp - General 528 Borno Balge Hospital Rann Borno East Ngala Ndufu Meleri Limanti 535 Borno Borno East Bama Banki Banki 541 Rese Borno rve Borno East Bama SHEHURI / HAUSARI / GSSSS Bama IDP Camp 510, 542 1
Borno MAIRI Rese rve Borno East Bama KUMSHE / NDUGUNO Camp - BANKI CAMP 502, Borno 503, 504 Borno East Bama Shehuri Mairi 508, 509 Borno Borno East Kala Rann "A" Camp - Kilagaru Camp 529, Borno Balge 530, 531 Borno East Ngala Gamboru A Abuja Galadima Road 532, 533 Borno Borno East Ngala Gamboru B Shehuri 534, 539 1 Borno Rese rve Borno East Ngala Ngala Camp - 536, 1 Borno INTERNATIONAL SCH 537, Rese CAMP 538, 540 rve Borno MMC&Jere Jere Dusuman Camp - FARM CENTRE 701 Borno MMC&Jere Jere Dusuman Camp-MUNA GARAGE 702 EL BADAWE Borno MMC&Jere Jere Dusuman Muna Dalti 703 Borno MMC&Jere Jere Galtimari Fori Lawanti 704 Borno MMC&Jere Jere Galtimari Galtimari 705 Borno MMC&Jere Jere Gomari Bulama Jidda Ndollori 706 Borno MMC&Jere Jere Gomari Kasula 707 Borno MMC&Jere Jere Gongulong Gongolong Aliri 708 Borno MMC&Jere Jere Maimusari Maimusari 709 Borno MMC&Jere Jere Mairi Dalori Quarters 710 Borno MMC&Jere Jere NGUDA/ADDAMARI Camp - KHADDAMARI 713 QTRS Borno MMC&Jere Jere Old Maiduguri El Miskin Idps 714 Borno MMC&Jere Jere Old Maiduguri Lari Kari 715 Borno MMC&Jere Maidugu Bolori I Camp - TEACHERS 716 ri VILLAGE Borno MMC&Jere Maidugu Gamboru Gamboru 724 ri Borno MMC&Jere Maidugu Gwange I Gwange 1 725 ri Borno MMC&Jere Maidugu Gwange III Sabon Layi 726 ri Borno MMC&Jere Maidugu Lamisula Lamisula 727 ri Borno MMC&Jere Maidugu Limanti Limanti Tamsuwa 728 ri Borno MMC&Jere Maidugu Maisandari Camp - BAKASI CAMP 729 ri Borno MMC&Jere Maidugu Maisandari Goni Kyariri 730 ri Borno MMC&Jere Maidugu Maisandari Moduganari Tudu 735 ri Borno MMC&Jere Jere Dala Sandari Bulama Bukar 736 Rese Abdullahi rve Borno MMC&Jere Maidugu Gwange II Sabon Gari Tsakiya 737 Rese ri rve Borno MMC&Jere Maidugu Shehuri South Talbari 738 Rese ri rve Borno MMC&Jere Jere Mashamari Mara Mari 711, 712
Borno MMC&Jere Maidugu Bolori I Shuwari 717, ri 718, 719 Borno MMC&Jere Maidugu Bolori II Bolori Gana 720, ri 721, 722, 723 Borno MMC&Jere Maidugu Maisandari Kaigama 731, 739 1 ri Rese rve Borno MMC&Jere Maidugu Maisandari Kasula 732, ri 733, 734 Borno Northern Mobbar Damasak Gss Damasak Street 301 Borno Borno Northern Mobbar Kareto Fulatari 304 Borno Borno Northern Mobbar Kareto HA_113 305 Borno Borno Northern Mobbar Kareto HA_26 306 Borno Borno Northern Mobbar Kareto HA_64 307 Borno Borno Northern Mobbar Kareto Mad Kavri 308 Borno Borno Northern Mobbar Kareto Masho M Kura 309 Borno Borno Northern Mobbar Kareto SSA_5 310 Borno Borno Northern Mobbar Zanna Umarti Bulakurti 314 Borno Borno Northern Mobbar Zanna Umarti HA_1 315 Borno Borno Northern Mobbar Zanna Umarti Tsuyuri 316 Borno Borno Northern Nganzai Badu Dalkime 317 Borno Borno Northern Nganzai Badu HA_60 318 Borno Borno Northern Nganzai Badu Malaimari 319 Borno Borno Northern Nganzai Damaram Balumiri 320 Borno Borno Northern Nganzai Damaram Hassanti 321 Borno Borno Northern Nganzai Damaram Usmanti 322 Borno Borno Northern Nganzai Gadai Doya Abba Bidiri 323 Borno Borno Northern Nganzai Gadai HA_33 324 Borno Borno Northern Nganzai Gadai Kuriya 325 Borno Borno Northern Nganzai Gadai Sudagu 326 Borno Borno Northern Nganzai Gajiram Borberi 329 Borno Borno Northern Nganzai Gajiram Kotte 330 Borno Borno Northern Nganzai Gajiram Zairam Gana 331 Borno Borno Northern Nganzai Kuda Goni Shettiri 332
Borno Borno Northern Nganzai Kuda Kangartilo 333 Borno Borno Northern Nganzai Sabsabuwa Bulama Kyari 334 Borno Borno Northern Nganzai Sabsabuwa HA_39 335 Borno Borno Northern Nganzai Sabsabuwa Mallum Kari 336 Borno Borno Northern Mobbar Kareto Kairi Bulama Modu 339 Rese Borno rve Borno Northern Nganzai Kuda Mata Faltami 340 Rese Borno rve Borno Northern Mobbar Damasak Mallam Hudu 302, 1 Borno 303, 337 Rese rve Borno Northern Mobbar Zanna Umarti Alhaji Buremti 311, Borno 312, 313 Borno Northern Nganzai Gajiram Balamari 327, 1 Borno 328, 338 Rese rve
Annex 7: Plausibility Checks
Available as a separate file.