NUTRITIONAL ANTHROPOMETRIC SURVEYS FINAL REPORT. NORTHERN and WESTERN AREAS OF MANDERA DISTRICT NORTH KENYA

Transcription

1 KENYA MISSION NUTRITIONAL ANTHROPOMETRIC SURVEYS FINAL REPORT NORTHERN and WESTERN AREAS OF MANDERA DISTRICT NORTH KENYA 22 ND FEBRUARY - 20 TH MARCH, 2007 Onesmus Muinde, Assistant CMN Kenya and South Sudan Mission James Batende, Senior Nutrition Programme Manager

2 2 ACKNOWLEDGMENTS AAH would like to express its deep gratitude to the Ministry of Health in Mandera district, for releasing their two staff to participate in the survey. We would like to thanks AAH staff, particularly the management team for the preparation of the survey, logistics, personnel and administrative issues, fieldwork without which this survey would not have been possible. We appreciate the team members (Measures, Data recorders and Supervisors) who were involved in ensuring the survey obtained good quality data. Thanks also to all the drivers who ensured timely movement of field staff. We finally wish to say many thanks to the mothers and the fathers who pleasantly allowed the team to measure their children and patiently sat through the interviews and shared with the team valuable information without which the survey would not have been possible. AAH would like to thank the following people for their support and assistance without which the survey would not have been possible. Special thanks are due to the Chief of all the divisions and the elders of Mandera Central, Khalalio, Rhamu Dimtu, Malkamari, Banisa, Takaba and Dandu, for their support during the survey, and to the elders and some home visitors for their support during the survey

3 3 Table of content TABLE OF CONTENT...3 I EXECUTIVE SUMMARY...4 II INTRODUCTION...10 III METHODOLOGY...11 III.1 Type of Survey and Sample Size...11 III.2 Data Collection...12 III.3 Indicators, Guidelines, and Formula s Used...13 III.3.1 Acute Malnutrition...13 III.3.2 Mortality...13 III.4 Field Work...14 III.5 Data Analysis...14 IV RESULTS OF THE ANTHROPOMETRIC SURVEY...14 V IV.1 ANTHROPOMETRIC RESULTS IN BANISA, MALAKAMARI AND RHAMU DIMTU DIVISIONS...14 IV.1.1 Distribution by Age and Sex...14 IV.1.2 Anthropometrics Analysis...15 IV.2 ANTHROPOMETRIC RESULT IN MANDERA CENTRAL AND KHALALIO DIVISIONS...17 IV.2.1 Distribution by Age and Sex...17 IV.2.2 Anthropometrics Analysis...18 IV.3 ANTHROPOMETRIC RESULTS IN TAKABA AND DANDU DIVISIONS...20 IV.3.1 Distribution by Age and Sex...20 IV.3.2 Anthropometrics Analysis...21 IV.4 Measles Vaccination Coverage...23 IV.5 Household Status...23 IV.6 Composition of the households...24 RESULTS OF THE RETROSPECTIVE MORTALITY SURVEY...24 VI DISCUSSION AND CONCLUSION...25 APPENDIX...27 I A: Sample Size and Cluster Determination Banisa, Malkamari and Rhamu Dimtu Survey...27 I B: Sample Size and Cluster Determination Mandera Central and Khalalio Survey...27 I C: Sample Size and Cluster Determination Takaba and Dandu...28 II Anthropometric survey questionnaire...29 III Household enumeration data collection form for a death rate calculation survey (one sheet/household)...30 IV Enumeration data collection form for a death rate calculation survey (one sheet/cluster)...31 V: Calendar of events in Mandera district (Months and Seasons in both Somali and Gare languages)...32

4 4 I Executive summary Mandera District is one of the four districts in North-Eastern province, located at the North-Eastern corner of Kenya. The district covers an area of 26,474 km 2, and counts 18 divisions, 86 locations and 116 sub-locations. It shares international boundaries with Ethiopia to the north and Somalia to the east. It borders Wajir to the south and southwest. The district is characterized by low-lying rocky hills. The plains rise gradually from the south at Elwak towards Malkamari area in the north. The altitude of the plains rises between 400m and 970m above sea level. There are no perennial rivers except the seasonal river Daua that passes over half of the district s boundary with Ethiopia. The source of the rivers is from the south Ethiopian highlands flowing eastwards through Malkamari, Rhamu Dimtu, Rhamu, Hareri, Khalalio and Central Divisions into Somalia at Border Point One (BP1) 1. There are many dry riverbeds (Laga), which get filled by run-off water during the rain season but dry up as soon as the rain ceases. These make road construction and maintenance difficult. Rainfall is scanty and erratic with an annual average of 255 mm. The long rains fall in the months of April and May while the short rains fall in October and November. There is high rate of evaporation, which causes withering to most vegetation before maturity. Mandera District is one of the hottest districts in the country with a mean annual temperature of 30 o C. The highest temperatures are experienced in the months of February to April and September to December. The district generally has a sparse population density, which fall below 35 persons per square kilometre except the Central Division, which has 436 persons/ km 2,. The population gathers in areas where water and pasture are available. Areas like Banisa Division, which has more permanent settlements and water sources have high population concentrations especially around boreholes and earth pans. In urban and rural market centres the density is high due to availability of social facilities and security 1. Mandera district is facing perennial food insecurity as a result of extreme climates, characterized by a succession of drought and floods in the past years. Agricultural outcomes are extremely poor, leading to a lack of market for livestock and unemployment. Since the drought experienced in 2005 and 2006 WFP, UNICEF and other nutrition NGOS have being providing relief food distribution to the community in order to prevent the community vulnerability to malnutrition and rehabilitate already malnourished populace. Most people, in pastoral and marginal agricultural areas in particular rely heavily on relief food (maize rations and water) 2. From October 2006, the heavy rainfalls caused floods that had major consequences: damages on the cultivating the land along rivers, and lost of crops, destruction of irrigation schemes, pumping sets and other farm implements. ACF-USA runs nutrition programs in Mandera Central, Khalalio, Hareri, Malkamari, Rhamu Dimtu, Banisa, Takaba and Dandu Divisions from Each year ACF-USA conducts a nutrition survey in these districts to monitor the nutrition situation. OBJECTIVES OF THE SURVEY Three anthropometric nutrition surveys were implemented in the district from 22 nd February to 20th March The geographic areas surveyed were similar to the ones considered in the 2006 set of surveys, namely: Banisa, Malkamari and Rhamu Dimtu divisions Takaba and Dandu divisions Mandera Central, Khalalio and Hareri divisions The objectives for each survey are: 1 Mandera District Development Plan Kenya Food Security Update October 9, 2006

5 5 To evaluate the nutritional status of children aged 6 to 59 months. To estimate the measles immunisation coverage of children aged 9 to 59 months. To estimate the crude mortality rate through a retrospective survey. METHODOLOGY The SMART methodology was applied. The sample size defined according to the population figures are: 31 cluster of 14 households in Mandera central and Khalalio Divisions, 36 clusters by 18 households in Malkamari, Banisa and Rhamu Dimtu Divisions 37 clusters of 18 households in Takaba and Dandu divisions were surveyed. The sampling frame covered all accessible villages in the divisions selected. In each cluster, households were randomly selected and surveyed using the EPI method. All the children aged between 6 and 59 months of the same family, defined as a woman and her children living the same household, were included in the survey if there are. A retrospective mortality survey over the past three months was undertaken alongside the anthropometric survey, using SMART methodology. Two clusters in Mandera Central Division in Kumor village were replaced as the community were unwilling to let there children measured. The community gave the following reasons for their refusal; they are comfortable about the survey; they did not require any assistance hence they did not see the value of the assessment; they estimate their children are healthy and that taking measurements would make them sick or retard their growth. The team tried to address the community s concerns, but even with the intervention of chief and village elder they would not back off from their stance. Nutrition and mortality data were analyzed using Nutrisurvey version December 2006 software. SUMMARY OF FINDINGS The population is, similarly to Somalia, divided into clans. The four main clans are the Garre (who speak Borana), Degodia, Murule and Corner tribe (who speak Somali), each principally occupying a geographically distinct area within the district. There are community elders and locally elected chiefs and sub chiefs who interact between the communities and government officials. The populace of the district are mainly pastoralist with the some of the community members living along the river practicing small scale crop farming. Mandera district faces perennial food insecurity, water scarcity and inadequate health care services. The region receives sporadic rainfalls in some years which have made the community to develop coping mechanism of migration to seek for source of water and pasture, for both human and animal survival. The community keep a lot of cattle as they can survive the harsh climatic conditions in the region, cows, goats, camels and donkeys are the main animals kept in Mandera district. The sale of these animals is the main source of livelihood. But the number of livestock s was drastically reduced as a result of famine which was experienced in 2005 resulted to ban of sale of livestock s from north eastern districts confining the community to dependence on relief to meet their food demands. Water shortage is rife to most part of the district. Only few divisions in the district are endowed with potable water, while the other ones depend on earth pans, water tanks and water tracking system for there water needs. The quality of water in earth pans is questionable, as both animals and human share this valuable resource in the district. In general, hygiene and sanitation practices are inadequate, leading to contamination of water collection points. Outbreaks of diarrhoea diseases are frequently reported during the wet seasons. Accessibility to health services is poor in Mandera West divisions. Only one dispensary is present in each of the following divisions; Malkamari, Rhamu Dimtu, Banisa, Takaba and Dandu. The huge surface of the divisions and the lack of public transport make it extremely hard for the most of the populace to access health services. The following humanitarian NGOs are present in the district to address the population needs: AAH (Action Against Hunger) runs nutrition, water and sanitation and health education programs, in Mandera Central, Malkamari, Banisa, Rhamu Dimtu, Takaba and Dandu divisions. World Food Program (WFP): food distributions through COCOP Mandera Educational Development Society (MEDS): water distribution. Northern Region Development Agency (NORDA): water and food distribution Rural Community Integrated Development Agency (RACIDA): water and food distribution Emergency Pastoral Assistance Group (EPAG): water and food distribution

6 6 Kenyan Red Cross: herds destocking and food logistics of the Kenya government. CARE: water and sanitation activities for the current emergency. Islamic relief : Health and nutrition activities in Mandera Central and West RESULTS OF THE NUTRITION SURVEY Table 1: Results for Mandera Central and Khalalio Divisions Index INDICATOR RESULTS (n =561) NCHS WHO Z-score % Median Z-score % Median Global Acute Malnutrition W/H< -2 z and/or Oedemas Severe Acute Malnutrition W/H < -3 z and/or Oedemas Global Acute Malnutrition W/H < 80% and/or Oedemas Severe Acute Malnutrition W/H < 70% and/or Oedemas Global Acute Malnutrition W/H< -2 z and/or Oedemas Severe Acute Malnutrition W/H < -3 z and/or Oedemas Global Acute Malnutrition W/H < 80% and/or Oedemas Severe Acute Malnutrition W/H < 70% and/or Oedemas Total crude retrospective mortality (last 3 months) /10,000/day Under five crude retrospective mortality /10,000/day Measles immunization coverage on children >=9 months old (n= 548) By card According to caretaker 3 Not immunized 20.9% [17.6%-24.1%] 1.2% [0.4%-2.1%] 10.2% [8.3%-12.1%] 0.0% [0.0%-0.2%] 21.0 % [17.4%-24.7%] 3.0% [1.9%-4.1%] 5.5% [4.1%-7.0%] 0.0% [0.0%-0.2%] 0.18[ ] 0.76[ ] 8.4% 83.8% 7.8% 3 When no EPI card was available for the child at the household, measles vaccination information was collected according to the caretaker.

7 7 Table 2: Banisa, Malkamari and Rhamu Dimtu Divisions Index NCHS WHO INDICATOR Z-score % Median Z-score % Median Global Acute Malnutrition W/H< -2 z and/or Oedemas Severe Acute Malnutrition W/H < -3 z and/or Oedemas Global Acute Malnutrition W/H < 80% and/or Oedemas Severe Acute Malnutrition W/H < 70% and/or Oedemas Global Acute Malnutrition W/H< -2 z and/or Oedemas Severe Acute Malnutrition W/H < -3 z and/or Oedemas Global Acute Malnutrition W/H < 80% and/or Oedemas Severe Acute Malnutrition W/H < 70% and/or Oedemas Total crude retrospective mortality (last 3 months) /10,000/day Under five crude retrospective mortality /10,000/day Measles immunization coverage on children >=9 months old (n=717) By card According to caretaker 3 Not immunized RESULTS(n =758) 18.7% [14.6%-22.9%] 1.7% [0.8%-2.7%] 8.2% [5.9%-10.5%] 0.4% [0.0%-0.9%] 18.3% [14.6%-22.1%] 3.8% [2.2%-5.4%] 5.3 % [3.5%-7.1%] 0.2% [0.1%-0.3%] 0.33 [ ] 1.39 [ ] 10.3% 50.5% 39.2% Table 3: Takaba and Dandu Divisions Nutrition Survey. Index INDICATOR RESULTS (n=825) NCHS WHO Z-score % Median Z-score % Median Global Acute Malnutrition W/H< -2 z and/or Oedemas Severe Acute Malnutrition W/H < -3 z and/or Oedemas Global Acute Malnutrition W/H < 80% and/or Oedemas Severe Acute Malnutrition W/H < 70% and/or Oedemas Global Acute Malnutrition W/H< -2 z and/or Oedemas Severe Acute Malnutrition W/H < -3 z and/or Oedemas Global Acute Malnutrition W/H < 80% and/or Oedemas Severe Acute Malnutrition W/H < 70% and/or Oedemas Total crude retrospective mortality (last 3 months) /10,000/day Under five crude retrospective mortality /10,000/day Measles immunization coverage on children >=9 months old (n=793) By card According to caretaker 3 Not immunized 7.5%[4.9%-10.2%] 0.1%[0.0%-0.4%] 18.1% [14.9%-21.3%] 3.6% [1.5%-5.8%] 5.6 % [3.4%-7.8%] 0.0% [0.0% - 0.2%] 0.18 [ ] 0.26 [ ] 6.1% 58.4% 35.6%

8 8 The results of the 3 surveys show a general slight improvement in the prevalence of Global Acute Malnutrition, as compared to the rates found in the previous years: DIVISIONS % 21.0% 20.9% GAM ( ) ( ) ( ) Mandera, Khalalio and Libehia 3.5% 2.1% 1.2% SAM ( ) ( ) ( ) 23.6%* 18.7% GAM Rhamu, Rhamu Dimtu, Hareri and ( ) ( ) Malkamari 2.4% 1.7% SAM ( ) ( ) 27.0% 17.5% GAM Banisa, Dandu, Takaba and ( ) ( ) Ashabito 3.0% 2.3% SAM ( ) ( ) * the geographical area surveyed in the 2006 survey is not the same than the one in 2007: comparison cannot be done as such, but the rates of 2006 are given here as indictor. The rates of moderate malnutrition are nevertheless still very high. The retrospective mortality rates are below alarm level, and are therefore acceptable. The immunization rates are extremely low, which is a problem for the prevention of epidemics, and also reveals a poor health access. The malnutrition in the surveyed areas is of a high magnitude but low intensity, which makes the population very vulnerable to potential shocks. The current state of nutrition status can be explained by the following factors. Health Access. Mandera district is affected by high prevalence of water borne diseases and malaria. The district is vast, and the low number of facilities (with the exception of Mandera central division), prevent a good access of the health services by the population. In addition to poor coverage, the existing Health Centres are facing a lack of man power (only one nurse present in most of the health facilities). Water and Sanitation. Water in the district is a very valuable and scare resource. Climatic conditions are characterized by scanty rains and hot temperatures most months of the year. The sanitary practices also contribute a lot to the problem, as quality of the water is often not adequate. Human waste is left on open field, animals share the same source of water, etc. Food Security. The community being pastoralist have adopted animal keeping as the major source of livelihood and minimal crop growing (only along the river). Moreover, the scanty rainfall and floods observed for the several past years led to poor agricultural production, which exposes the community to perennial food shortage. In early 2006, the district experienced drought and famine that resulted to death of many cattle and high malnutrition in the district. The government of Kenya then declared famine. The International community reacted quickly, and two more nutrition NGOS (Islamic Relief and MSF-B) started nutrition activities in the district with the support of WFP, UNICEF and other Donors. Relief food distribution has been in the community for many years but distribution increased in 2006 as a result of the nutrition emergency in the district. Nutrition and Health Education. Poor nutrition and health education has been observed among the mothers, regarding topics such as proper breastfeeding, weaning, balanced diets and food safety. The food proposed to the children is therefore of a poor quality, predisposing the children to malnutrition as they lack essential nutrients required for their growth.

9 9 In order to improve the nutrition status of the surveyed communities, ACF recommends the following: Health and nutrition Integration of Nutrition Treatment activities in the existing health facilities to ensure sustainability Capacity building the MOH in the district on treatment of malnourished children. Institute EPI campaigns occasionally to ensure that all the children are vaccinated against childhood diseases especially Mandera West Divisions Increase the number of health facilities in the Mandera West divisions. Increase the number of medical staff in the dispensaries. Water and Sanitation Increase the accessibility of water by constructing/rehabilitating earth pans and water storage tanks in the Mandera west districts. Improve the water quality in the earth pans by introducing cheap methods to filter water that are affordable and sustainable by the community. Continue with sanitation programs such as water protection, education and safe human waste disposal. Nutrition and health education Initiate an elaborate nutrition education activity in the district, focusing on improving the quality of food prepared from locally available foods as well as doing cooking demonstrations. Continue with health education programs in the community, schools and other institutions to improve hygienic practices. Food Security Establish food for work programs as only the vulnerable people in the community will receive food distribution resulting to proper targeting. Device ways of enhancing food security of the pastoralist community especially improving grazing lands, establishing market for the livestock s and improving crop cultivation especially along the rivers.

10 II INTRODUCTION Mandera District is one of the four districts in North-Eastern province located at the North-Eastern corner of Kenya. The district covers an area of 26,474 km2. It shares international boundaries with Ethiopia to the north and Somalia to the east. It borders Wajir to the south and southwest. The district has 18 divisions, 86 locations and 116 sub-locations. The district is characterized by low-lying rocky hills. The plains rise gradually from the south at Elwak towards Malkamari area in the north. The altitude of the plains rises between 400m and 970m above sea level. There are no perennial rivers except the seasonal river Daua that passes over half of the district s boundary with Ethiopia. The source of the rivers is from the south Ethiopian highlands flowing eastwards through Malkamari, Rhamu Dimtu, Rhamu, Hareri, Khalalio and Central Divisions into Somalia at Border Point One (BP1) 4. M Map1. Mandera District Map The district generally has a sparse population density, which fall below 35 persons per square kilometre except the Central Division, which has 436 persons / km 2. In the district, water and pasture availability determines population distribution and density. Areas like Banisa Division, which has more permanent settlements and water sources have high population concentrations especially around boreholes and earth pans. In urban and rural market centres the density is high due to availability of social facilities and security 1. Due to constant drought lack of market for livestock and unemployment most people are poor and depend entirely on relief food (maize rations and water). While the severity of the humanitarian and livelihood crisis has eased since the height of the drought in March 2006, food insecurity remains pervasive. Increasingly, the food security problems in pastoral and marginal agricultural areas in particular, are chronic and an outcome of successive poor seasons coupled with inadequate livelihood support interventions prior to and during droughts. 5 Mandera district has been a key area of operation for ACF-USA since October 2004, when the first nutrition program was started in the district. In the beginning of 2006, drought and famine hit Mandera district that prompted Kenya government to declare famine a national disaster in several districts Mandera included. There was an overwhelming response to the declaration as different agencies pulled resources to intervene in the district. Since 2004 ACF has being the sole nutrition agency in the district, but this changed after the declaration as Islamic Relief and MSF-H started nutrition programs also in the district. 4 Mandera District Development Plan Kenya Food Security Update October 9, 2006

11 11 Last year ACF-USA did three nutrition surveys in Mandera Central and West divisions. The surveys results are as shown in the table below. Table 4: Results for 2006 nutrition surveys done, results in Z-scores, reference NCHS DIVISIONS GAM SAM Mandera, Khalalio and Libehia 21.0% 2.1% [17.5% %] [1.0% - 4.0%] Rhamu, Rhamu Dimtu, Hareri and Malkamari 23.6% 2.4% [19.9% %] [1.3% - 4.4%] Banisa, Dandu, Takaba and Ashabito 27.0% 3.0% [23.0% %] [1.7% - 5.2%] As a result of other nutrition partners operating in the same region ACF-USA was not able to implement nutrition surveys in Liberia, Hareri, Rhamu and Ashabito divisions, Islamic relief did a survey in those divisions in February-March In order to continue with monitoring the nutrition situation for the divisions ACF-USA has nutrition programs anthropometric surveys were done in following divisions Mandera Central and Khalalio -Survey 1 Banisa, Malkamari and Rhamu Dimtu- Survey 2 Takaba and Dandu- Survey 3 III METHODOLOGY III.1 Type of Survey and Sample Size A two-stage cluster sampling method was used. The anthropometric surveys target children aged between 6 and 59 months utilizing SMART methodology, which ensures accuracy and precision of data collected. Selection of accessible villages was done using a map of the area indicating administrative boundaries of the divisions and villages. Information on population figures for the divisions where AAH has programs activities was collected. The geographical units and their respective population were then inputted into the Nutrisurvey for SMART software December 2006 for planning the survey. The total population for all accessible villages in the different surveys is estimated as follows: 65,294 persons in Mandera central and Khalalio divisions; 72,848 persons in Malkamari, Banisa and Rhamu Dimtu divisions 30,138 persons in Takaba and Dandu Divisions. At the first stage, the sample size was determined by inputting necessary information into the Nutrisurvey software for both anthropometric and mortality surveys. The information included estimated population sizes, estimated prevalence rates of mortality and malnutrition, the desired precision and design effect. Mandera central and Khalalio Division Sample size calculation. Utilizing malnutrition prevalence of 25% based on previous surveys, precision of 4% and design effect of 2, a sample size of 870 children was obtained. In the mortality session with estimated prevalence of 0.28, desired precision of 0.3 with a design effect of 2 resulted to a sample size The number of households in the anthropometric session is (870/2) 435 assuming each household has 2 children while in the mortality session will have 371 households assuming each household has 7 people. Hence the higher number of household i.e. 435 was picked. The number of clusters was calculated by dividing the total households by the number of households covered in a day by one team (435/14) resulting to 31 clusters. See appendix I (B)

12 12 Malkamari, Banisa and Rhamu Dimtu Divisions Sample size calculation Using malnutrition prevalence of 32% based on previous surveys, precision of 4% and design effect of 2, a sample size of 1009 children was obtained. In the mortality session with estimated prevalence of 0.49, desired precision of 0.3 with a design effect of 2 resulted to a sample size The number of households in the anthropometric session is (1009) 505 assuming each household has 2 children while in the mortality session will have 641 households assuming each household has 7 people. Hence the higher number of household i.e. 641 was picked. The number of clusters was calculated by dividing the total households by the number of households covered in a day by one team (641/18) resulting to 36 clusters. See appendix I (A) Takaba and Dandu Divisions Sample calculation Utilizing malnutrition prevalence of 36% based on previous surveys, precision of 4% and design effect of 2, a sample size of 1014 children was obtained. In the mortality session with estimated prevalence of 0.54, desired precision of 0.3 with a design effect of 2 resulted to a sample size The number of households in the anthropometric session is (1014/2) 507 assuming each household has 2 children while in the mortality session will have 672 households assuming each household has 7 people. Hence the higher number of household i.e. 672 was picked. The number of clusters was calculated by dividing the total households by the number of households covered in a day by one team (672/18) resulting to 37 clusters. See Appendix I (C) At the second stage, selection of households to be visited within each cluster was done. The EPI methodology was used whereby a pen was spun from the centre of the village to randomly choose a direction. The team then walked in the direction indicated, to the edge of the village. At the edge of the village the pen was spun again, until it pointed into the body of the village. The team then walked along this second line counting each house on the way. Using simple balloting, the first house to be visited was selected at random by drawing a number between one and the number of households counted when walking. In the selected household, all children aged 6-59 months in each household were included in the nutritional survey. If there was more than one wife (care taker) in the household 6, each wife was considered separately regardless of whether they were cooking together. If there were no children in a household, the house remained a part of the sample that contributed zero children to the nutritional part of the survey. The household was recorded on the nutritional data sheet as having no eligible children. The mortality questionnaire was only administered in households that were included in the anthropometric questionnaire and numbered correspondingly. Once the questionnaires were completed in the household, the next selected house to be visited is the one the closest on the right. III.2 Data Collection Five data recorders were subjected to a standardization test to ascertain their capability in taking accurate and precise measurements, so as to minimize errors during data collection. For each selected child, information was collected during the anthropometric survey using an anthropometric questionnaire. The information included (See appendix II) Age: recorded with the help of a local calendar of events (See appendix v). Gender: male or female Weight: children were weighed without clothes, with a SALTER balance of 25kg (precision of 100g). Height: children were measured on a measuring board (precision of 0.1cm). Children less than 85cm were measured lying down, while those greater than or equal to 85cm were measured standing up. Mid-Upper Arm Circumference: MUAC was measured at mid-point of left upper arm for measured children (precision of 0.1cm). 6 A household refers to a mother and her children

13 13 Bilateral Oedemas: assessed by the application of normal thumb pressure for at least 3 seconds to both feet. Measles vaccination: assessed by checking for measles vaccination on EPI cards and asking caretakers. Household status: for the surveyed children, households were asked if they were permanent residents, temporarily in the area, displaced or returnee. III.3 Indicators, Guidelines, and Formula s Used III.3.1 Acute Malnutrition Weight for Height Index Acute malnutrition rates are estimated from the weight for height (WFH) index values combined with the presence of Oedemas. The WFH indices are expressed in both Z-scores and percentage of the median, according to both NCHS 7 and WHO references 8. The complete analysis is done with the NCHS reference. The expression in Z-scores has mainly statistical meaning, and allows inter-study comparison. The percentage of the median, on the other hand, is used for the identification criteria of acute malnutrition in nutrition programs. Guidelines for the results expressed in Z-score: Severe malnutrition is defined by WFH < -3 SD and/or existing bilateral Oedemas on the lower limbs of the child. Moderate malnutrition is defined by WFH < -2 SD and -3 SD and no Oedemas. Global acute malnutrition is defined by WFH < -2 SD and/or existing bilateral Oedemas. Guidelines for the results expressed in percentage of median: Severe malnutrition is defined by WFH < 70 % and/or existing bilateral Oedemas on the lower limbs Moderate malnutrition is defined by WFH < 80 % and 70 % and no Oedemas. Global acute malnutrition is defined by WFH <80% and/or existing bilateral Oedemas Children s Mid-Upper Arm Circumference (MUAC) The weight for height index is the most appropriate index to quantify wasting in a population in emergency situations where acute forms of malnutrition are the predominant pattern. However the mid-upper arm circumference (MUAC) is a useful tool for rapid screening of children at a higher risk of mortality. MUAC measurements are significant for children with a height of 65 cm or one year and above. The guidelines are as follows: MUAC < 110 mm MUAC 110 mm and <120 mm MUAC 120 mm and <125 mm MUAC 125 mm and <135 mm MUAC 135 mm severe malnutrition and high risk of mortality moderate malnutrition and moderate risk of mortality high risk of malnutrition moderate risk of malnutrition adequate nutritional status III.3.2 Mortality Mortality data was collected using Standardized Monitoring and Assessment of Relief. The crude mortality rate (CMR) is determined for the entire population surveyed for a given period. The CMR is calculated using Nutrisurvey for SMART software for Emergency Nutrition Assessment. The formula below is applied: Crude Mortality Rate (CMR) = 10,000/a*f/ (b+f/2-e/2+d/2-c/2), Where: a = Number of recall days (90) b = Number of current household residents c = Number of people who joined household 7 NCHS: National Center for Health Statistics (1977) NCHS growth curves for children birth-18 years. United States. Vital Health Statistics. 165, WHO reference, 2005

14 14 d = Number of people who left household e = Number of births during recall f = Number of deaths during recall period The result is expressed per 10,000-people / day. The thresholds are defined as follows 9 : Total CMR: Alert level: Emergency level: Under five CMR: Alert level: Emergency level: 1/10,000 people/day 2/10,000 people/day 2/10,000 people/day 4/10,000 people/day III.4 Field Work Five teams composed of two measurers and one data recorder each executed the fieldwork. They were recruited within the local communities. All the data recorders participating in the survey underwent 4-day training while the measurers were trained for 1 day, which included standardization exercise (for the data recorders) and a pilot survey. ACF-USA staff and MOH staff supervised all the teams in the villages. The survey (including training, and data collection and travelling) lasted for a period of 27 days. III.5 Data Analysis Data processing and analysis for both anthropometric and mortality were carried out using Nutrisurvey for SMART software, December 2006 version using both NCHS and WHO references. Excel was used to carry out analyses on MUAC, measles immunization coverage, household status and composition. IV RESULTS OF THE ANTHROPOMETRIC SURVEY IV.1 ANTHROPOMETRIC RESULTS IN BANISA, MALAKAMARI AND RHAMU DIMTU DIVISIONS 763 children between 6 and 59 months were measured during the survey. The data of 5 of them were excluded from the analysis, due to incoherence. IV.1.1 Distribution by Age and Sex Table 5: Distribution by age and Sex in Banisa, Malkamari and Rhamu Dimtu divisions Age groups Boys Girls Total Sex (months) n % n % n % ratio Total The above table 2 shows the proportion of boys to girls gives a sex ratio (B/G) of 1.1 this is acceptable. Figure 1: Distribution by Age and Sex 9 Health and nutrition information systems among refugees and displaced persons, Workshop report on refugee s nutrition, ACC / SCN, Nov 95.

15 15 Distribution of Age by Sex in Banisa, Malkamari and Rhamu Dimtu Divisions Age groups in months Boys Girls % -40% -20% 0% 20% 40% 60% Percentage IV.1.2 Anthropometrics Analysis Distribution of Acute Malnutrition in Z-Scores Table 6: Weight for Height distribution by age in Z-scores Banisa, Malkamari and Rhamu Dimtu (NCHS Reference) Moderate Severe wasting wasting No wasting Age groups Oedemas N (<-3 z-scores) [>= -3 and <-2 z- (> = -2 z scores) (months) scores] n % n % n % n % Total Table 7: Weight for height vs. Oedemas in Banisa, Malkamari and Rhamu Dimtu Divisions (NCHS Reference) <-2 z-score >=-2 z-scores Oedemas Marasmic kwashiorkor Kwashiorkor present 0 (0.0 %) 0 (0.0 %) Oedemas Marasmic Normal absent 142 (18.7 %) 616 (81.3 %)

16 16 Figure2: Z-scores distribution Weight-for-Height, Banisa, Malkamari and Rhamu Divisions Feb and March The displacement of the sample curve to the left side of the reference curve indicates a critical nutritional situation in the surveyed population. The mean Z-Scores of the sample is-1.25 and the Standard Deviation is The SD is within the interval , which shows that the sample is representative of the population. Table 8: Global and Severe Acute Malnutrition by Age group in Z-scores NCHS Reference WHO Reference Global acute malnutrition Severe acute malnutrition 18.7% [ ] 1.7% [ ] 18.3% [ ] 3.8% [ ]. Distribution of Malnutrition in Percentage of the Median Table 9: Distribution of Weight/Height by age in percentage of the median in Banisa Malkamari and Rhamu Dimtu Divisions (NCHS Reference) Moderate Severe wasting wasting No wasting Age groups Oedemas N (< 70%) (>= 70% and (> = 80%) (months) <80%) n % n % n % n % Total

17 17 Table 10: Global and Severe Acute Malnutrition by Age group in % of the median NCHS Reference WHO Reference Global acute malnutrition Severe acute malnutrition 8.2% [ ] 0.4% [ ] 5.3% [ ] 0.2% [ ] Risk of Mortality: Children s MUAC All children measured were included in the analysis Table 11: MUAC Distribution in Banisa, Malkamari and Dandu Divisions MUAC (mm) < 75 cm height >=75 < 90 CM >=90 CM Total < % 0 0.0% 0 0.0% 0 0.0% 110<= MUAC< % 6 2.1% 0 0.0% % 120<= MUAC< % % 8 2.3% % 125<=MUAC < % % % % MUAC>= % % % % TOTAL % % % % The MUAC analysis reveals that 2.4% of the children surveyed are moderately malnourished. IV.2 ANTHROPOMETRIC RESULT IN MANDERA CENTRAL AND KHALALIO DIVISIONS 568 children between 6 and 59 months were measured during the survey. The data of 7 of them were excluded from the analysis, due to incoherence. IV.2.1 Distribution by Age and Sex Table 12: Distribution by age and sex in Mandera Central and Khalalio divisions Age groups Boys Girls Total Sex (months) n % n % n % ratio Total The sex ratio is 1.0, which shows that there was no bias of selection of children during the survey.

18 18 Figure 3: Distribution by Age and Sex Distribution by Age and Sex in Mandera central and Khalalio Divisions Age Boys Girls % -40% -20% 0% 20% 40% 60% 80% Percentage IV.2.2 Anthropometrics Analysis Distribution of Acute Malnutrition in Z-Scores Table 13: Weight for Height distribution by age in Z-score in Mandera central and Khalalio Divisions (NCHS Reference) Moderate Severe wasting wasting No wasting Age groups Oedemas N (<-3 z-scores) [>= -3 and <-2 z- (> = -2 z scores) (months) scores] n % n % n % n % Total Table 13: Weight for height vs. Oedemas Mandera central and Khalalio Divisions (NCHS Reference) <-2 z-scores >=-2 z-scores Oedemas Marasmic kwashiorkor Kwashiorkor present 0 (0.0 %) 0 (0.0 %) Oedemas Marasmic Normal absent 117 (20.9 %) 444 (79.1 %)

19 19 Figure 1. Weight for height in Z-scores Mandera central and Khalalio Divisions The displacement of the sample curve to the left side of the reference curve indicates a critical nutritional situation in the surveyed population. The mean Z-Scores of the sample is 1.25, and the Standard Deviation is The SD is within the interval , which shows that the sample is representative of the population. Table 15 : Global and Severe Acute Malnutrition by Age group in Z-scores NCHS Reference WHO Reference Global acute malnutrition Severe acute malnutrition 20.9% [ ] 1.2% [ ] 21.0% [ ] 3.2% [ ]. Distribution of Malnutrition in Percentage of the Median Table 161: Distribution of Weight/Height by age in percentage of the median Mandera central and Khalalio divisions Moderate Severe wasting wasting No wasting Age groups Oedemas N (< 70%) (>= 70% and (> = 80%) (months) <80%) n % n % n % n % Total

20 20 Table 17: Global and Severe Acute Malnutrition by Age group in % of the median NCHS Reference WHO Reference Global acute malnutrition Severe acute malnutrition 10.2% [ ] 0.0% [ ] 5.5% [ ] 0.0% [ ] Risk of Mortality: Children s MUAC All children measured were included in the analysis Table 18: MUAC Distribution in Mandera Central and Khalalio Divisions MUAC (mm) < 75 cm height >=75 < 90 CM >=90 CM Total < % 0 0.0% 0 0.0% 0 0.0% 110<= MUAC< % 8 3.8% 0 0.0% % 120<= MUAC< % % 2 0.7% % 125<=MUAC < % % % % MUAC>= % % % % TOTAL % % % % According to the MUAC criteria, 2.0% of the children surveyed are moderately malnourished. IV.3 ANTHROPOMETRIC RESULTS IN TAKABA AND DANDU DIVISIONS 837 children between 6 and 59 months were measured during the survey. The data of 12 of them were excluded from the analysis, due to incoherence. IV.3.1 Distribution by Age and Sex Table 19: Distribution by age and Sex in Takaba and Dandu Divisions Age groups Boys Girls Total Sex (months) n % n % n % ratio Total There was no bias of selection of children between male and female as sex ratio (B/G) is 0.9.

21 21 Figure 5: Distribution by age and sex in Takaba and Dandu divisions Distribution by Age and Sex in Takaba and Dandu Divisions Age groups (months) Boys Girls % -40% -20% 0% 20% 40% 60% Percentage IV.3.2 Anthropometrics Analysis Distribution of Acute Malnutrition in Z-Scores Table 20: Weight for Height distribution by age in Z-scores in Takaba and Dandu Divisions (NCHS Reference) Moderate Severe wasting wasting No wasting Age groups Oedemas N (<-3 z-scores) [>= -3 and <-2 z- (> = -2 z scores) (months) scores] n % n % n % n % Total Table 21: Weight for height vs. Oedemas in Takaba and Dandu Divisions (NCHS Reference) <-2 z-score >=-2 z-score Oedemas Marasmic kwashiorkor Kwashiorkor present 0 (0.0 %) 0 (0.0 %) Oedemas Marasmic Normal absent 145 (17.6 %) 680 (82.4 %) No case of Oedemas was found, during the survey in all the divisions surveyed in Takaba and Dandu division.

22 22 Figure 6: Z-scores distribution Weight-for-Height, Takaba and Dandu Divisions. The displacement of the sample curve to the left side of the reference curve indicates a critical nutritional situation in the surveyed population. The mean Z-Scores of the sample is 1.19, and the Standard Deviation is The SD is within the interval , which shows that the sample is representative of the population. Table 22 : Global and Severe Acute Malnutrition by Age group in Z-scores NCHS Reference WHO Reference Global acute malnutrition Severe acute malnutrition 17.5% [ ] 2.3% [ ] 18.1% [ ] 3.6% [ ] Distribution of Malnutrition in Percentage of the Median Table 23: Distribution of Weight/Height by age in percentage of the median in Takaba and Dandu divisions (NCHS Reference) Moderate Severe wasting wasting No wasting Age groups Oedemas N (< 70%) (>= 70% and (> = 80%) (months) <80%) n % n % n % n % Total

23 23 Table 24 : Global and Severe Acute Malnutrition by Age group in % of the median NCHS Reference WHO Reference Global acute malnutrition Severe acute malnutrition 7.5% [ ] 0.1% [ ] 5.6% [ ] 0.0% [ ] Risk of Mortality: Children s MUAC All children measured were included in the analysis. Table 25: MUAC Distribution in Takaba and Dandu Divisions MUAC (mm) < 75 cm height >=75 < 90 CM >=90 CM Total < % 0 0.0% 1 0.2% 1 0.1% 110<= MUAC< % 7 2.4% 2 0.5% % 120<= MUAC< % % 6 1.5% % 125<=MUAC < % % % % MUAC>= % % % % TOTAL % % % % According to the MUAC criteria, 2.3% of the children surveyed are moderately malnourished, and 0.1% is severely malnourished. IV.4 Measles Vaccination Coverage The source of information on immunization was either the child s health card or the mother s recall. A child was considered fully vaccinated if he had received the last dose of the EPI programme (from 9 months of age, according to the national protocol). It is important to mention however, that these results should be interpreted with caution since they are based on the caretaker s recall, when no health card is available. Table 262: Measles Vaccination Coverage in all the divisions surveyed Banisa, Malkamari and Rhamu Dimtu Divisions Mandera central and Khalalio Divisions Takaba and Dandu Divisions Population >= 9 months Immunized with card 10.3% 8.4% 6.1% Immunized without card 50.5% 83.8% 58.4% Not immunized 39.2% 7.8 % 35.6% IV.5 Household Status The table below gives an outline of households visited. Table 27: Household Status Banisa, Malkamari and Rhamu Dimtu Mandera central and Khalalio Takaba and Dandu N % N % N % House holds with children< Households without children< Empty houses Households who refused to be surveyed Residents status Total Household Visited

24 24 The households without children under five were mainly the elderly and new wed homesteads. The empty houses were as a result of the community migratory patterns, they had moved to graze their cattle in the other locations within Mandera district. Some households were empty in Banisa, Malkamari and Rhamu survey, some household s refused their children to be measured and also to give mortality information. 100% of the households surveyed during anthropometry data collection were residents. IV.6 Composition of the households Table 28: Age group proportion Banisa, Malkamari Age groups and Rhamu Dimtu Mandera central and Khalalio Takaba and Dandu N % N % N % Under 5 years Adults Total The average composition of the households is described below: Table 29: Household Composition Average number of people per household Average number of <5 per household Banisa, Malkamari and Rhamu Dimtu Mandera Central and Khalalio Takaba and Dandu V RESULTS OF THE RETROSPECTIVE MORTALITY SURVEY The crude mortality rate was calculated from the figures collected from families with or without children under 5 years, over the past 3 months. Table 30: Demographic information Demographic data Banisa, Malkamari and Rhamu Dimtu Mandera central and Khalalio Takaba and Dandu Current resident HH Current resident < 5 years old People who joined HH < 5 years old who joined HH People who left HH < 5 years old who left HH Birth Death Death < 5 years old CMR (deaths /10,000 people/day) U5MR (deaths in children<5/ / day ) 0.33 [ ] 1.39 [ ] 0.18 [ ] 0.76 [ ] 0.18 [ ] 0.26 [ ] Both the crude and under-5 mortality rates were below the alert levels of 1/10,000 and 2/10,000 per day respectively.

25 25 VI Discussion and conclusion The results of the 3 surveys show a general slight improvement in the prevalence of Global Acute Malnutrition, as compared to the rates found in the previous years: DIVISIONS % 21.0% 20.9% GAM ( ) ( ) ( ) Mandera, Khalalio and Libehia 3.5% 2.1% 1.2% SAM ( ) ( ) ( ) 23.6%* 18.7% GAM Rhamu, Rhamu Dimtu, Hareri and ( ) ( ) Malkamari 2.4% 1.7% SAM ( ) ( ) 27.0% 17.5% GAM Banisa, Dandu, Takaba and ( ) ( ) Ashabito 3.0% 2.3% SAM ( ) ( ) * the geographical area surveyed in the 2006 survey is not the same than the one in 2007: comparison cannot be done as such, but the rates of 2006 are given here as indictor. The rates of moderate malnutrition are nevertheless still very high. The retrospective mortality rates are below alarm level, and are therefore acceptable. The immunization rates are extremely low, which is a problem for the prevention of epidemics, and also reveals a poor health access. The malnutrition in the surveyed areas is of a high magnitude but low intensity, which makes the population very vulnerable to potential shocks. The current state of nutrition status can be explained by the following factors. Health Access. Mandera district is affected by high prevalence of water borne diseases and malaria. The district is vast, and the low number of facilities (with the exception of Mandera central division), prevent a good access of the health services by the population. In addition to poor coverage, the existing Health Centres are facing a lack of man power (only one nurse present in most of the health facilities). Water and Sanitation. Water in the district is a very valuable and scare resource. Climatic conditions are characterized by scanty rains and hot temperatures most months of the year. The sanitary practices also contribute a lot to the problem, as quality of the water is often not adequate. Human waste is left on open field, animals share the same source of water, etc. Food Security. The community being pastoralist have adopted animal keeping as the major source of livelihood and minimal crop growing (only along the river). Moreover, the scanty rainfall and floods observed for the several past years led to poor agricultural production, which exposes the community to perennial food shortage. In early 2006, the district experienced drought and famine that resulted to death of many cattle and high malnutrition in the district. The government of Kenya then declared famine. The International community reacted quickly, and two more nutrition NGOS (Islamic Relief and MSF-B) started nutrition activities in the district with the support of WFP, UNICEF and other Donors. Relief food distribution has been in the community for many years but distribution increased in 2006 as a result of the nutrition emergency in the district. Nutrition and Health Education. Poor nutrition and health education has been observed among the mothers, regarding topics such as proper breastfeeding, weaning, balanced diets and food safety. The food proposed to the children is therefore of a poor quality, predisposing the children to malnutrition as they lack essential nutrients required for their growth.